Sports Med 2010; 40 (9): 715-727 0112-1642/10/0009-0715/$49.95/0
LEADING ARTICLE
ª 2010 Adis Data Information BV. All rights reserved.
Neuromotor Control of the Lower Limb in Achilles Tendinopathy Implications for Foot Orthotic Therapy Narelle Wyndow,1 Sallie M. Cowan,2 Tim V. Wrigley1 and Kay M. Crossley 2,3 1 Centre for Health, Exercise and Sports Medicine, Melbourne Physiotherapy School, University of Melbourne, Melbourne, Victoria, Australia 2 Melbourne Physiotherapy School, University of Melbourne, Melbourne, Victoria, Australia 3 Department of Mechanical Engineering, Melbourne School of Engineering, University of Melbourne, Melbourne, Victoria, Australia
Abstract
Achilles tendinopathy (AT) is a common injury in running sports. While the exact aetiology of Achilles injury is still unclear, foot orthoses are often effectively employed in the conservative management of the condition. Foot orthoses have traditionally been provided for people with AT on the basis that they may reduce the rearfoot eversion associated with excessive foot pronation. This increased rearfoot motion is thought to produce excessive Achilles tendon loads. To date, the available literature indicates that foot orthoses have small and unsystematic effects on rearfoot kinematics. However, limitations of foot kinematic measurement currently restrict the ability to conduct truly valid investigations into kinematic responses to foot orthoses. Therefore, the roles of alternate mechanisms, for which orthoses may provide clinical success in pathology such as AT, are now being investigated. One alternative theory is that foot orthoses alter neuromotor recruitment patterns and thus lower limb loads in response to the additional sensory input provided by the device. In AT, altered neuromotor recruitment patterns of the triceps surae have been hypothesized to create differential intratendinous loads. This may lead to pathological changes within the tendon. Furthermore, it is possible that foot orthoses may aid to normalize intratendinous loads via altering neuromotor activity in the triceps surae in AT. This review examines the literature with regard to changes in neuromotor recruitment as an associated aetiological factor in AT and the role foot orthoses may play in the management of this condition.
1. Introduction Achilles tendinopathy (AT) is commonly experienced by people involved in sporting activities involving running. Abnormal load is considered
to be integral to the development of AT; however, the exact aetiology of AT is still unclear. Biomechanical ‘faults’, particularly excessive foot pronation, have been considered to contribute to the pathogenesis of AT.[1-3] However, only a few
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studies have investigated this relationship with mostly consistent results observed.[2,4,5] For example, one recent study found increased rearfoot eversion in subjects with AT when running barefoot,[2] while another study only found increased rearfoot eversion during shod running.[4] Centre of pressure (CoP) measures from the plantar surface of the foot are not more medially deviated in subjects with AT than in healthy controls.[5] Therefore, while excessive pronation may be associated with AT symptomatology, it is possible that there are alternate contributions to the mechanical pathogenesis of AT. Various investigations, from cadaver studies to in vivo cine magnetic resonance imaging (MRI), coupled with optic fibre technology, have suggested that non-homogenous stress within the Achilles tendon may be associated with tendon pathology.[6-9] An altered neuromotor activation strategy of the triceps surae has been proposed as one potential source of nonhomogenous Achilles tendon stress.[6,10] As indicated above, foot orthoses are considered an effective component in the conservative treatment of AT.[1,11-14] However, the exact mechanisms by which foot orthoses provide clinical benefit in the management of this condition are not understood. Currently, there is only one randomized controlled trial on the use of foot orthoses in AT. This study demonstrated that the use of foot orthoses for 4 weeks was sufficient to produce significant improvements in pain and eccentric calf strength in the absence of a formal strength training programme.[11] A similar improvement in pain and eccentric calf strength was found following conservative physical therapy consisting of sensorimotor and eccentric training in combination with deep frictions and ultrasound. The exact mechanism via which foot orthoses produced this response was not able to be determined from this study. However, the authors hypothesized that the orthoses may have modified sensory input to provide ‘optimization of muscular-regulated joint stability’. Recent electromyography (EMG) and MRI investigations into the response to foot orthoses in pronated but uninjured populations indicate that the devices modified the neuromotor activation patterns in a running task[15] and a seated foot adduction task.[16] While the ª 2010 Adis Data Information BV. All rights reserved.
neuromotor responses differed between the two studies, this is likely related to the specificity of neuromotor responses to both the task and the type of foot orthoses used. Developing a better understanding of whether altered neuromotor activation is associated with AT may enable the development and implementation of targeted treatment of the functional deficits associated with the pathology. Specifically, the efficacy of foot orthoses as an intervention may be increased by improving our understanding of the effect of foot orthoses on the neuromotor control of the triceps surae. Additionally, if altered neuromotor control precedes the development of AT, it may be possible to screen those at risk prior to the development of pathology. 2. Purpose and Methodology This article reviews the literature pertaining to neuromotor activity in the triceps surae in subjects with AT and uninjured runners. In addition, literature relating to the neuromotor effects of foot orthoses in the lower limb will be reviewed to provide a possible mechanism for the clinical response to foot orthoses in Achilles injuries. Searches in MEDLINE (PubMed) and Web of Knowledge databases were performed using the search terms ‘Achilles tendinosis’, ‘Achilles tendinopathy’, ‘Achilles tendonitis’, ‘shoe inserts’, ‘foot orthoses’, ‘heel lifts’, ‘running biomechanics’, ‘muscle activity’ and ‘EMG’. The reference lists of the articles obtained were also hand searched for relevant articles. 3. Achilles Tendinopathy (AT) 3.1 Incidence and Morbidity
Achilles tendon injuries are commonly experienced by individuals participating in activities involving running and/or jumping. A recent systematic review of running injuries in long-distance runners found that lower leg injuries account for 9–32.2% of all injuries sustained by runners.[17] The frequency of Achilles injury, specifically, has been reported to be between 7% and 9% of all running injuries.[1,18,19] It appears to be more common in men than women, usually presenting Sports Med 2010; 40 (9)
Neuromotor Control of the Lower Limb in Achilles Tendinopathy
in the 35–45 years of age group.[20] In a surgical cohort of 58 patients with Achilles tendon pain, 31% were classified as having low activity levels. Thus, the authors proposed that the loads associated with physical activity may not be the primary cause of the condition in this patient population.[21] While most cases of AT are managed non-operatively, there is limited evidence on which to base the conservative treatment of Achilles tendon disorders.[22,23] In a review article of AT in athletic populations, Kvist[3] commented that approximately 25% of this population required surgical intervention, and the frequency of surgery increased with patient age and duration of symptoms, as well as the presence of pathological change in the tendon. Furthermore, approximately 3–5% of patients had to abandon their sporting activities because of Achilles injuries. 3.2 Achilles Tendon Anatomy and Function
The Achilles tendon is comprised of the combined tendons of the medial and lateral heads of the gastrocnemius and the soleus muscles (triceps surae). It inserts into the posterior surface of the calcaneus. At around the level that the soleus muscle begins to contribute fibres to the Achilles tendon, the tendon spirals with the medial fibres rotating posteriorly and the posterior fibres rotating laterally.[24] The degree of rotation varies from 11 to 68.[25] Each of the triceps surae muscle bellies forms a fascicle of the tendon. A recent cadaver study found that the posterior and lateral portions of the tendon are comprised of fibres from the medial head of the gastrocnemius. The fibres from the lateral head of the gastrocnemius muscle constitute the anterior tendon layer and fibres from the soleus muscle are located in the anteromedial part of the Achilles tendon.[26] Biomechanically, the tendon transmits forces from the gastrocnemius and soleus muscles to the calcaneus during gait. Soleus is the primary plantarflexor of the ankle joint during walking (i.e. activating concentrically late in stance). In addition, it serves an eccentric postural role to control dorsiflexion and prevent excessive anterior translation of the body over the foot during static stance and during the stance phase of ª 2010 Adis Data Information BV. All rights reserved.
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walking and running.[27] As the gastrocnemius originates on the posterior surface of the femoral condyles, it is capable of flexing the knee joint as well as plantarflexing the ankle joint. Additionally, the triceps surae has a role in the control of pronation and supination of the subtalar joint. Eversion moments at the calcaneus have been demonstrated by the tensioning of the lateral gastrocnemius in cadaver specimens, while calcaneal inversion moments are observed with all other combinations of soleus and gastrocnemius tensioning.[8] Measurement of tendon force in vivo is extremely difficult due to ethical and feasibility constraints. However, one group used a buckle-type force transducer to measure tendon force in a healthy participant.[28] They recorded force up to 9 kN during running (corresponding to 12.5 times bodyweight), 2.6 kN during walking and <1 kN during cycling.[28] This same procedure was used to demonstrate that during walking and running, force increases within the tendon prior to heel strike where it is rapidly released.[29] Forces then peak again in the propulsive phase of gait and are slightly higher than in the braking phase for both modes of gait. Physical activity and ageing have been associated with greater cross-sectional area (CSA) in healthy tendons.[30,31] Increased CSA in a healthy tendon may act to reduce tendon stress (force/ CSA) for a given force and thus minimize the risk of injury in these populations.[30] Muscle CSA of the triceps surae is, as expected, higher in healthy individuals who participate in high-load activity and is related to a larger tendon CSA.[31] However, the relationship between CSA and tendon pathology is unclear. In AT, CSA has been found to be increased,[32] while in Achilles rupture patients CSA was not different to controls.[33] Significant variations in soleus muscle anatomy and mode of insertion of soleus into the Achilles tendon have also been shown using MRI. For example, insertion of the muscle fibres of soleus into the Achilles tendon varies from a mid-anterior attachment to insertion of the soleus muscle to only the medial tip of the tendon.[6] Furthermore, the median septum does not always separate from the posterior aponeurosis, thus dividing the muscle into a medial and lateral compartment in some individuals.[34] Sports Med 2010; 40 (9)
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3.3 Pathophysiology
Current evidence indicates that chronic Achilles injuries result from an inadequate healing response, which is degenerative rather than inflammatory in nature.[35] Structurally, the pathological tendon displays substantial tissue degeneration (tendinosis) and in a review of histopathological changes in chronic tendon disorders, it has been proposed that different stimuli may be responsible for different forms of degeneration.[36] This hypothesis has recently been supported by research into the effects of different loading levels on tendon stemcell response. Using an in vitro system, small stretches promoted differentiation of tendon stem cells into tenocytes whereas larger stretches induced differentiation of some tendon stem cells into adipocytes, chondrocytes and osteocytes.[37] Thus, this response may explain the mucoid, hyaline, and calcific forms of tendon degeneration often seen. Hypoxic, hyaline and mucoid degeneration are examples of these different forms.[36] In tendinopathy, the simultaneous loss or separation of collagen fibres results in disorganized collagen structure[22] and the pathological tendon is then assumed to be less able to tolerate load and to be vulnerable to further injury.[38] The pain in this condition may originate from a combination of mechanical and biochemical factors.[39] In AT, tissue samples have demonstrated neurovascular ingrowth of the tendon. This may be due to the angiogenic effects of locally produced signalling substances such as substance P and neuropeptide Y, which have been identified in pathological tendon.[40,41] There are several other signalling substances found in AT, some of which are produced by the tenocytes themselves.[42] Glutamate, acetylcholine, catecholamines and vascular endothelial growth factor-A have been identified and appear to be involved in producing tendon tissue changes, altered vascular regulation and/or pain and swelling.[40-43] There are two common locations of Achilles tendon injury, insertional tendinopathy and the more common mid-portion tendinopathy. While the histological characteristics of tendinopathy in different tendons appear to be similar,[44] the two common sites of AT vary in their prognosis and ª 2010 Adis Data Information BV. All rights reserved.
response to treatment. Generally, insertional tendinopathy is less common and more resistant to treatment, and a larger percentage of patients with this type of tendinopathy require surgical intervention.[45] Ultrasonographic studies have identified that the deep surface of the tendon is primarily involved in insertional tendinopathy.[46] In midportion tendinopathy, the medial portion of the tendon is involved in approximately 80% of cases while diffuse tendon changes are seen in the remaining 20%. Lateral tendon involvement was never seen in isolation in a cohort of 118 tendons.[46] 3.4 Aetiology and Risk Factors
The aetiology of Achilles tendon degeneration is still unclear. There are currently several biomechanical theories attempting to explain the initiation of the degenerative changes in AT, the traditional overload model and two more recent theories of stress-shielded regions of tendon and hyperthermic tendon injury. The traditional biomechanical theory is that of excessive and repetitive tendon stress. Training or biomechanical errors may load the tendon beyond its inherent mechanical capabilities. The tendon may then be unable to repair the micro-injury and progressive pain and pathology develops.[1] Ker[47] proposed that increased tendon loads produce tendon damage due to fatigue of the tendon matrix rather than collagen fibres. The stress-shielding theory proposes that focal regions of tendon are not exposed to normal loading.[48] Abnormal regional unloading may occur due to reduced muscle activity, or isolated collagen fibril damage. The decreased mechanobiological stimulation of tendon cells may cause an upregulation of collagenase and a weakening of the tendon structure to develop.[49] This weakening of the tendon may cause sufficient tendon atrophy to allow injury to occur more easily. Finally, the theory of hyperthermic damage suggests that rapid changes in joint angles create repetitive internal shear forces within the tendon generating sufficient heat so as to induce thermal damage.[48] All of these theoretical biomechanical models of tendon pathology share the common theory of altered tendon loads creating non-homogenous Sports Med 2010; 40 (9)
Neuromotor Control of the Lower Limb in Achilles Tendinopathy
stress within the tendon, thus, leading to degenerative changes and pain. 3.4.1 Intrinsic and Extrinsic Risk Factors
Extrinsic factors associated with the development of AT in active individuals have been identified from surveys of long-distance runners. These factors relate to training variables such as a change in training pattern (increased mileage or intensity), poor technique and a reduced frequency of stretching.[50] Seasoned runners appear more likely to be injured.[50,51] A history of previous injury generally increases the risk for further injury[17] as does running on soft, rather than hard, surfaces.[51] In the clinical setting, inappropriate footwear is often regarded as a contributing extrinsic factor to the development of AT. Footwear with soft heel cups may allow excessive rearfoot movement, as would footwear with poor medio-lateral stability in the rear and midfoot region, thus reducing pronation control. However, currently there is little evidence supporting these observations. As mentioned in section 3.1, AT is also present in sedentary individuals. Thus, it has been suggested that physical activity may be more important in provoking symptoms rather than being the cause of all pathology and pain. Factors other than activity levels must therefore underlie the failed healing response, which results in the degenerative cascade and pain. Genetics and dyslipidaemia are two intrinisic factors that, together with other known intrinsic and extrinsic factors, have been suggested to increase the likelihood for some individuals to develop tendinopathy.[52,53] Furthermore, there are a number of other intrinsic risk factors that have been proposed to be related to the development and persistence of AT. These factors include lower limb biomechanics, specifically foot pronation and muscular factors such as tightness or eccentric weakness of the triceps surae. These factors will be described in sections 4.2 and 4.3. 4. Neuromotor Control and AT Neuromotor control can be defined as the unconscious muscular or motor response to an afferent signal concerning dynamic joint stability.[54] This motor response may entail both ª 2010 Adis Data Information BV. All rights reserved.
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feedback and feed-forward components.[55] The function of the neuromotor control system is to transmit mechanical loads including bodyweight in an efficient manner and has been proposed to be a major component of joint and postural stability.[56] In the musculoskeletal system, pain in the lumbar spine, knee and ankle is associated with disrupted neuromotor control, specifically changes in muscle activation patterns.[57-62] Effective rehabilitation is often aimed at re-establishing normal neuromotor control in these conditions. 4.1 Normal Neuromotor Control during Running
The task requirements of running differ from walking with regard to the speed and loads imposed upon the body and, hence, the neuromotor control varies between the two modes of gait. Similar activation profiles have been observed for most muscles of the lower limb during walking and running with the most notable exceptions in the triceps surae and quadriceps.[27,63] The averaged EMG profiles of these muscle groups indicate earlier and prolonged activation during stance in jogging and running, compared with walking.[27] Forward dynamical simulations have suggested that the most significant change occurs in the activation of soleus during running.[63] During walking, soleus has a weak eccentric component in early stance and a more significant concentric component in late stance. However, during running, soleus displays stronger activation in early stance compared to late stance. It was thus hypothesized that the role of soleus in walking appears to be to help generate forward propulsion, while in running the force generated by soleus is delivered primarily in the vertical direction thus contributing more to support of the body rather than forward progression.[63] During running, gastrocnemius appears to have increased and prolonged activation compared with soleus. 4.2 Altered Neuromotor Control of the Triceps Surae and Achilles Injuries
Altered neuromotor control of the triceps surae has been hypothesized to play a role in the Sports Med 2010; 40 (9)
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genesis of AT[6-10] or arise as a result of the tendon pain and pathology. However, presently, there is little research that has directly evaluated this. A number of studies have examined various aspects of plantarflexor function in people with and without AT. Reduced isokinetic plantarflexion strength has been reported in subjects with AT,[50,64] as has decreased EMG amplitude of the triceps surae just after heel strike.[65,66] These deficits of triceps surae function may underpin the reduced functional capabilities of the lower limb demonstrated in AT using a test battery consisting of jumping and strength tests.[67] Currently, one study has examined the temporal aspect of triceps surae recruitment during running. In a small sample of 8 AT and 14 control subjects, no differences in onset time, time to maximum activation and total time of activation were found.[65] Further investigations addressing the temporal characteristics of neuromotor control of the triceps surae utilizing larger sample sizes are warranted. Thus, based on the limited evidence available, it appears that altered neuromotor control is associated with AT, and further research is required to confirm these findings and establish the temporal relationship between tendon pathology, pain and altered neuromotor control. 4.3 Altered Foot Kinematics and Kinetics in AT
It has long been considered by clinicians that excessive subtalar joint pronation is a feature of, and risk factor for, AT. Pronation is a triplanar motion involving a combination of rearfoot eversion, dorsiflexion and abduction of the foot and is coupled with internal tibial rotation.[68,69] It has been suggested that excessive foot pronation creates a whipping or torsional action upon the Achilles tendon as the foot rotates rapidly from an inverted position at heel strike to an excessively everted position in midstance. Vascular blanching of the tendon is thought to result from this purported torsional effect on the relatively avascular mid-portion of the tendon,[1,12] where most of the pain and degeneration is found. This theory of torsional stress of the tendon from ª 2010 Adis Data Information BV. All rights reserved.
rearfoot motion was based on clinical observations, case series and anatomical studies that identified the role of the plantar flexors in resupination during stance phase and propulsion.[1,12] As a result of the difficulties in measuring pronation during dynamic activities, this association between pronation and AT has not been frequently measured. Only two studies have investigated this theory. Ryan et al.[2] found that during barefoot running, subjects with AT demonstrated greater rearfoot eversion during midstance than controls, with a trend towards greater overall range of rearfoot motion. However, Donoghue et al.[4] only found greater rearfoot eversion and rearfoot range of motion during shod running but not barefoot running when compared to controls. Thus, dynamic measures suggest that increased eversion is often present in AT but may only become excessive and thus pathological in some individuals when footwear is worn. Correct footwear selection may therefore be important in some individuals in the prevention and management of AT. Other studies have utilized measures of static posture, such as a forefoot varus deformity or increased rearfoot inversion, as an indicator of increased pronation during dynamic activities. A forefoot varus deformity may lead to increased pronation of the foot, especially during late stance when the Achilles tendon is exposed to high loads. Foot types with increased rearfoot inversion range and position at heel strike may exhibit greater pronation from heel strike into midstance during gait. These studies utilizing static measures have generally found features consistent with increased pronation. For example, greater pronation was implied by a retrospective study of patient records at a sports medicine centre that found a correlation between AT and forefoot varus.[70] Furthermore, a prospective study of 449 naval recruits found an increased static rearfoot inversion range to be associated with AT.[71] This corroborates findings from a cross-sectional study of runners with AT that combined both dynamic (two-dimensional video gait analysis) and static measures.[50] This study found increased rearfoot inversion at heel strike during treadmill running in AT subjects. Sports Med 2010; 40 (9)
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Thus, both dynamic and static studies suggest that pronation is associated with the pathogenesis of AT. However, further studies are required to evaluate the relationship of the triplanar motion of pronation with AT. Rearfoot eversion is only one aspect of pronation. Therefore, structure or function that alters dorsiflexion or abduction of the rearfoot may also contribute to pathological AT loads. A common clinical perception is that AT is associated with a reduced range of ankle joint dorsiflexion motion. A restricted range of ankle dorsiflexion excursion may limit the capacity of the triceps surae to absorb eccentric loads and result in greater loading rates.[38] Alternatively, an increased range of ankle dorsiflexion may result in prolonged load on the musculotendinous unit over a larger range. Thus, increased or decreased ankle joint dorsiflexion ranges may generate abnormal AT loads and may also explain how AT may present in foot types that do not display excessive pronation. Reflecting the competing theories, the evidence for a relationship between ankle dorsiflexion and AT is inconsistent. Ankle joint ranges in AT have been found to be increased in both passive assessment[64] and during stance phase when running.[13] These findings are contrary to the results of McCrory et al.[50] who found no difference in passive ankle joint dorsiflexion range and Kvist[70] and Kaufman et al.[71] who found a decreased passive dorsiflexion range. Further studies are required to establish a relationship between passive and active ankle dorsiflexion range and Achilles tendon load and, also, to confirm the relationship between ankle dorsiflexion and the presence or development of AT symptoms. Because of the inherent coupling between the foot and lower leg, altered foot motions and forces may be linked to tibial and knee motions. Knee flexion range of motion appears to be reduced in AT during running.[72,73] Furthermore, there is some suggestion that lower peak internal knee rotation and a lower peak tibial external rotation moment[74] may be associated with AT. Further studies are required to confirm these observations as the interaction between knee motion and rearfoot inversion/eversion has imª 2010 Adis Data Information BV. All rights reserved.
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portant implications with regard to abnormal Achilles tendon loads. Further evidence for altered foot kinetics was observed in a single study that examined plantar pressure distribution patterns in novice runners who developed AT. During barefoot running, CoP measures revealed a decreased forward transfer of the CoP at propulsion.[5] The CoP was more laterally directed at the forefoot just prior to propulsion and more medially directed during propulsion in the ten subjects who developed AT. Sixty-three participants did not develop any injury. The decreased forward transfer of the CoP may represent inefficient propulsion possibly attributable to the reduced plantarflexor strength often observed in AT. The increased lateral to medial CoP measures would clinically correlate to the CoP patterns often seen in forefoot varus deformities. These inconsistent results obtained from kinematic gait analyses may stem from the known problems that can affect these measurements. Variability of marker placement and movement of skin markers over the underlying skeletal segments are well known issues.[75,76] Furthermore, there are specific difficulties in the measurement of foot motion when wearing shoes[77,78] and only recently have the intrinsic articulations of the foot been more accurately represented in multisegmental foot models rather than as one rigid segment.[75,76] 4.4 A Hypothetical Basis for the Role of Neuromotor Control in AT
The triceps surae consists of the bi-articular medial and lateral heads of the gastrocnemius and the uni-articular soleus, which generally act as one functional unit during gait. There is increasing evidence, however, that the triceps surae muscles work independently within the plantarflexor synergy. Evidence for differential activation of the components of the triceps surae comes from studies of healthy individuals. These studies have highlighted that the three muscular components exhibit varying responses to fatigue.[79,80] The variable fatigue responses may reflect the fibre type distribution, with a much higher proportion (88%) of slow Sports Med 2010; 40 (9)
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type I fibres reported in the soleus, compared with approximately 50% in the medial and lateral gastrocnemius.[81] However, this distribution may vary amongst subjects, thus resulting in a variety of neuromotor synergies for the execution of the same task.[82] Further evidence that the triceps surae do not have the same muscular coordination has also been observed at the level of the muscle fascicle. Using ultrasonography, medial gastrocnemius fascicles were observed to remain at the same length or tended to shorten while the fascicles of soleus lengthened during the early push phase of stance.[83] Furthermore, the structural and functional anatomy of the soleus is more complex than previously thought (see Hodgson et al.[34] for a review). It has been proposed that regions of motor units within the soleus may be more active or passive than others, thus contributing to variable stress within the aponeurosis of this muscle.[6] The same study also observed significant variation in the mode of insertion of the soleus onto the distal tendon as mentioned in section 3.2.[6] Some subjects presented with a small medial attachment site of the soleus, which the authors suggest may be a potential source of non-uniform stress on the tendon. Therefore, in healthy individuals there is evidence from cadaver, EMG and imaging studies that the triceps surae muscles work together as a functional unit, but with different activation patterns with regard to magnitude and timing. It is feasible that altered activation patterns of the different components of the triceps surae could result in differential loads within the aponeuroses of the triceps surae, as could changes in knee flexion angles.[6,10] However, could this differential stress translate into the tendon? Routine direct measurement of the Achilles tendon stress in vivo is not feasible, since current methods for measuring tendon stress are extremely invasive. However, anatomical studies provide indirect evidence for the transfer of stress from the aponeurosis to the tendon. Distally, the fascia of the triceps surae muscles appear tightly interwoven, potentially indicating more homogenous stress and strain distribution within the tendon.[84] However, it has been demonstrated, in human cadaver specimens, that the tendon fascicles of ª 2010 Adis Data Information BV. All rights reserved.
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each of the triceps surae can be clearly separated by simple dissection[26] and in animal specimens, the collagen fibrils of mature tendon appear to be continuous and independent.[85] Furthermore, tendon fascicle samples obtained from surgery on Achilles rupture patients, imply minimal lateral force transmission between the tendon fascicles of the Achilles tendon.[86] This raises the possibility for differential focal stresses transferred from the aponeurosis into the tendon to remain differentially distributed within the tendon. Variations in stress may be due to the relatively independent structure and function of the soleus and gastrocnemius components of the tendon and collagen fibrils. The effect of spiralling of the tendon on the distribution of load is unclear from the current literature. 5. The Use of Foot Orthoses in AT In the clinical setting, foot orthoses are used in the treatment of AT, with success rates reported in case series and retrospective surveys of runners to be as high as 75%.[1,12,87] However, high-quality evidence supporting the use of foot orthoses in AT is limited. In the one randomized controlled study of 31 male runners experiencing AT, the use of foot orthoses for 4 weeks resulted in a pain reduction of 50%[11] compared with a no-treatment control. Despite this limited evidence supporting the use of foot orthoses for AT, many authors have advocated their use in the management of AT based on their potential effect on biomechanical malalignment.[1,11,12,50,88,89] As highlighted in section 3.3, there is conflicting evidence regarding the presence of biomechanical malalignments. Thus, there is little biomechanical evidence to guide orthotic prescriptions. Therefore, until further research is available, orthotic prescription in AT is based on clinical reasoning. 5.1 Biomechanical Effects of Foot Orthoses in AT
It was traditionally considered that foot orthoses could reduce some of the shear forces on the Achilles tendon purported to result from the torsional effect of pronation. Foot orthoses have Sports Med 2010; 40 (9)
Neuromotor Control of the Lower Limb in Achilles Tendinopathy
been shown to produce small reductions in rearfoot eversion velocity and the maximum rearfoot eversion angle.[90] Cadaver studies have demonstrated that the soleus and gastrocnemius muscles have a role in controlling pronation and supination of the rearfoot as well as their primary role of plantarflexing the ankle.[8] Thus, reduced rearfoot excursions and moments from the use of foot orthoses could modify musculotendinous loads in the triceps surae. However, as highlighted in section 3.3, people with Achilles pathology do not necessarily display excessive pronation. Furthermore, in an AT case series of people with excessive pronation, the considerable (~92%) reduction in symptoms in response to foot orthoses was associated with increased rearfoot eversion but reduced ankle joint dorsiflexion during running.[13,14] Considering that pronation is a multiplanar motion, the results may reflect the capacity for a foot orthosis to influence different aspects of pronation in opposing directions. Kinematic responses to foot orthoses have also been found to be inconsistent in healthy subjects.[69] These conflicting kinematic responses may be explained in part by the many methodological issues related to studies involving foot orthoses (see section 5.2 for further discussion). Contemporary opinions have thus recently suggested that the positive clinical responses to foot orthoses in a variety of lower limb pathologies may relate to a change in the activation patterns of muscles in the lower extremity rather than changes in kinematics.[11,15,16,91] 5.2 Neuromotor Control Changes in Response to Foot Orthoses
In recent years, numerous studies have looked at various aspects of changes in neuromotor control in response to foot orthoses or simple foot wedging. Some studies have looked at changes in muscle activation during running or walking,[15,92-95] while other studies have looked at specific tasks such as postural sway,[96,97] single leg squats[98] or reaction times to perturbations of the lower limb.[99,100] A recent systematic review of neuromotor responses to foot orthoses concluded that the most consistent responses generª 2010 Adis Data Information BV. All rights reserved.
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ated by foot orthoses are an increase in peroneus longus, tibialis anterior and biceps femoris EMG amplitude, and that the duration of tibialis anterior activation is longer.[101] While this review provides valuable information regarding the response of the lower limb musculature to the use of orthoses, none of the reviewed papers addressed the relative activation of the individual muscles of the triceps surae nor did any of them address neuromotor responses to orthoses in AT. Only one article has assessed the neuromotor responses within the triceps surae in response to foot orthoses in healthy people.[16] In this study, the use of foot orthoses resulted in significant reductions in abnormal medial gastrocnemius and soleus co-activation (estimated by MRI signal intensity) during seated, closed chain, resisted foot adduction in people with pes planus.[16] It is not known whether a similar finding would be observed in people with AT or during functional activities such as running. If such findings were observed in future studies, then foot orthoses have potential to positively influence tendon loads in AT via this pathway. The neuromotor and biomechanical response to foot orthoses may be influenced by many factors. These include the structural features of orthoses design, the duration of use, the foot type of the subject and the type of device used (e.g. rigid or flexible, custom made or pre-made). In addition, the type of footwear in which the orthoses are used also impacts significantly on the function of the device thus making comparisons between studies into the neuromotor response to orthoses difficult. 6. Directions for Future Research Further cross-sectional studies are required to confirm whether neuromotor control is altered in people with AT. If measures of neuromotor control, such as timing or magnitude of muscle activity are confirmed, then prospective studies are required to determine if altered neuromotor control precedes AT or results from AT pathology and/or pain. Measures of neuromotor control should be combined with detailed kinematic and kinetic measures of the lower limb to fully Sports Med 2010; 40 (9)
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understand the relationships between neuromotor control and joint motions, ideally utilizing multisegmental foot models. Imaging studies of the tendon may indicate the presence of regional pathological changes in AT and the relationship of such changes to alterations in neuromotor control. Finally, the relationship between changes in pain, physical function and neuromotor control with an intervention such as an in-shoe foot orthosis could be evaluated utilizing a randomized controlled trial. 7. Conclusions Based on the presented evidence, it is plausible that people with AT may have altered neuromotor control of the triceps surae. Such alterations may be associated with an increase in the vulnerability of the tendon to further injury or persistent pain. Intrinsic factors, such as structural foot deformities (e.g. forefoot varus), plantarflexion strength deficits or pain, may necessitate compensatory neuromotor behaviour in the triceps surae. Similarly, extrinsic factors such as fatigue induced by poor training techniques or poor footwear could also alter triceps surae neuromotor control. There has been little investigation into the specific kinematic, kinetic or neuromotor mechanisms by which foot orthoses may be associated with a positive influence on pain in AT. Thus, the purported positive effect of foot orthoses in this condition is largely unsubstantiated. To further our understanding of the neuromotor presentation of the pathology may provide insight in to the aetiology of the condition. Further, the information obtained may enable the development of better treatment protocols with regard to orthotic design.
References 1. Clement D, Taunton J, Smart G. Achilles tendinitis and peritendinitis: etiology and treatment. Am J Sports Med 1984; 12 (3): 179-84 2. Ryan M, Grau S, Krauss I, et al. Kinematic analysis of runners with Achilles mid-portion tendinopathy. Foot Ankle Int 2009; 30 (12): 1190-5 3. Kvist M. Achilles-tendon injuries in athletes. Sports Med 1994; 18 (3): 173-201
ª 2010 Adis Data Information BV. All rights reserved.
4. Donoghue OA, Harrison AJ, Laxton P, et al. Lower limb kinematics of subjects with chronic Achilles tendon injury during running. Res Sports Med 2008; 16: 23-8 5. Van Ginckel A, Thijs Y, Ghani Zadeh Hesar N, et al. Intrinsic gait-related risk factors for Achilles tendinopathy in novice runners: a prospective study. Gait Posture 2009; 29 (3): 387-91 6. Finni T, Hodgson JA, Lai AM, et al. Nonuniform strain of human soleus aponeurosis-tendon complex during submaximal voluntary contractions in vivo. J Appl Phys 2003; 95 (2): 829-37 7. Arndt AN, Komi PV, Bruggemann GP, et al. Individual muscle contributions to the in vivo Achilles tendon force. Clin Biomech 1998; 13 (7): 532-41 8. Arndt A, Bruggemann GP, Koebke J, et al. Asymmetrical loading of the human triceps surae: II. Differences in calcaneal moments. Foot Ankle Int 1999; 20 (7): 450-5 9. Arndt A, Bruggemann GP, Koebke J, et al. Asymmetrical loading of the human triceps surae: I. Mediolateral force differences in the Achilles tendon. Foot Ankle Int 1999; 20 (7): 444-9 10. Bojsen-Moller J, Hansen P, Aagaard P, et al. Differential displacement of the human soleus and medial gastrocnemius aponeuroses during isometric plantar flexor contractions in vivo. J Appl Phys 2004; 97 (5): 1908-14 11. Mayer F, Hirschmueller A, Muller S, et al. Effects of short term treatment strategies over 4 weeks in Achilles tendinopathy. Br J Sports Med 2007; 41: e6 12. Mohr R. Achilles tendonitis. Foot Ankle Clin 1997; 2 (3): 439-56 13. Donoghue OA, Harrison AJ, Coffey N, et al. Functional data analysis of running kinematics in chronic Achilles tendon injury. Med Sci Sports Exerc 2008; 40 (7): 1323-35 14. Donoghue OA, Harrison AJ, Laxton P, et al. Orthotic control of rear foot and lower limb motion during running in participants with chronic Achilles tendon injury. Sports Biomech 2008; 7 (2): 194-205 15. Mundermann A, Wakeling J, Nigg B, et al. Foot orthoses affect frequency components of muscle activity in the lower extremity. Gait Posture 2006; 23 (3): 295-302 16. Kulig K, Burnfield JM, Reischl S, et al. Effect of foot orthoses on tibialis posterior activation in persons with pes planus. Med Sci Sports Exerc 2005; 37 (1): 24-9 17. van Gent RN, Siem D, van Middelkoop M, et al. Incidence and determinants of lower extremity running injuries in long distance runners: a systematic review. Br J Sports Med 2007; 41 (8): 469-80 18. Johansson C. Injuries in elite orienteers. Am J Sports Med 1986; 14: 410-5 19. Lysholm J, Wiklander J. Injuries in runners. Am J Sports Med 1987; 15: 168-71 20. Taunton JE, Ryan MB, Clement DB, et al. A retrospective case-control analysis of 2002 running injuries. Br J Sports Med 2002; 36 (2): 95-101 21. Rolf C, Movin T. Etiology, histopathology, and outcomes of surgery in achillodynia. Foot Ankle Int 1997; 18: 565-9 22. Paavola M, Kannus P, Jarvinen TAH, et al. Current concepts review Achilles tendinopathy. J Bone Joint Surg 2002; 84A (11): 2062-76
Sports Med 2010; 40 (9)
Neuromotor Control of the Lower Limb in Achilles Tendinopathy
23. Alfredson H, Lorentzon R. Chronic Achilles tendinosis: recommendations for treatment and prevention. Sports Med 2000; 29 (2): 135-46 24. Cummins EJ, Anson BJ, Carr BW, et al. The structure of the calcaneal tendon (of Achilles) in relation to orthopedic surgery. Surg Gynecol Obstet 1946; 83: 107-16 25. van Gils CC, Steed RH, Page JC. Torsion of the human Achilles tendon. Foot Ankle Surg 1996; 35 (1): 41-8 26. Szaro P, Witkowski G, Smigielski R, et al. Fascicles of the adult human Achilles tendon: an anatomical study. Ann Anat 2009; 191 (6): 586-93 27. Gazendam MGJ, Hof AL. Averaged EMG profiles in jogging and running at different speeds. Gait Posture 2007; 25 (4): 604-14 28. Komi PV, Fukashiro S, Jarvinen M. Biomechanical loading of the Achilles tendon during normal locomotion. Clin Sports Med 1992; 11 (3): 521-31 29. Kyrolainen H, Finni T, Avela J, et al. Neuromuscular behaviour of the triceps surae muscle-tendon complex during running and jumping. Int J Sports Med 2003; 24 (3): 153-5 30. Magnusson SP, Beyer N, Abrahamsen H, et al. Increased cross-sectional area and reduced tensile stress of the Achilles tendon in elderly compared with young women. J Gerontol 2003; 58A (2): 123-7 31. Magnusson SP, Kjaer M. Region-specific differences in Achilles tendon cross-sectional area in runners and nonrunners. Eur J Appl Phys 2003; 90: 549-53 32. Leung J, Griffith J. Sonography of chronic Achilles tendinopathy: a case-control study. J Clin Ultrasound 2008; 36 (1): 27-32 33. Kongsgaard M, Aagaard P, Kjaer M, et al. Structural Achilles tendon properties in athletes subjected to different exercise modes and in Achilles rupture patients. J Appl Phys 2005; 99: 1965-71 34. Hodgson JA, Finni T, Lai AM, et al. Influence of structure on the tissue dynamics of the human soleus muscle observed in MRI studies during isometric contractions. J Morph 2006; 267: 584-601 35. Sharma P, Maffulli N. Tendon injury and tendinopathy: healing and repair. J Bone Joint Surg 2005; 87: 187-202 36. Ja¨rvinen M, Jo´zsa L, Kannus P, et al. Histopathological findings in chronic tendon disorders. Scand J Med Sci Sports 1997; 7 (2): 86-95 37. Zhang J, Wang JH-C. Mechanobiological response of tendon stem cells: implications of tendon homeostasis and pathogenesis of tendinopathy. J Orthop Res 2010; 28 (5): 639-43 38. Cook JL, Khan KM, Purdam C. Achilles tendinopathy. Man Ther 2002; 7 (3): 121-30 39. Maffulli N, Sharma P, Luscombe KL. Achilles tendinopathy: aetiology and management. J Roy Soc Med 2004; 97 (10): 472-6 40. Andersson G, Danielson P, Alfredson H, et al. Presence of substance P and the neurokin-1 receptor in tenocytes of the human Achilles tendon. Regul Pept 2008; 150: 81-7 41. Bjur D, Alfredson H, Forsgren S. Presence of the neuropeptide Y 1 receptor in tenocytes and blood vessel walls in the human Achilles tendon. Br J Sports Med 2009; 43 (14): 1136-42
ª 2010 Adis Data Information BV. All rights reserved.
725
42. Danielson P. Reviving the ‘‘biochemical’’ hypothesis for tendinopathy: new findings suggest the involvement of locally produced signalling substances. Br J Sports Med 2009; 43: 265-8 43. Bjur D, Danielson P, Alfredson H, et al. Immunohistochemical and in situ hybridization observations favor a local catecholamine production in the human Achilles tendon. Histol Histopathol 2008; 23 (2): 197-208 44. Maffulli N, Testa V, Capasso G, et al. Similar histopathological picture in males with Achilles and patellar tendinopathy. Med Sci Sports Exerc 2004; 36: 1470-5 45. Alfredson H, Cook JL. Pain in the Achilles region. In: Brukner P, Khan K, editors. Clinical sports medicine. 3rd ed. Sydney (NSW): McGraw-Hill, 2006: 590-611 46. Gibbon WW, Cooper R, Radcliffe GS. Distribution of sonographically detected tendon abnormalities in patients with a clinical diagnosis of chronic Achilles tendinosis. J Clin Ultrasound 2000; 28: 61-6 47. Ker R. The implications of the adaptable fatigue quality of tendons for their construction, repair and function. Comp Biochem Physiol 2002; Part A 133: 987-1000 48. Maganaris CN, Narici MV, Almekinders LC, et al. Biomechanics and pathophysiology of overuse tendon injuries: ideas on insertional tendinopathy. Sports Med 2004; 34 (14): 1005-17 49. Arnoczky SP, Lavagnino M, Egerbacher M. The mechanobiological aetiopathogenesis of tendinopathy: is it the over-stimulation or the under-stimulation of tendon cells? Int J Exp Pathol 2007; 88 (4): 217-26 50. McCrory JL, Martin DF, Lowery RB, et al. Etiologic factors associated with Achilles tendinitis in runners. Med Sci Sports Exerc 1999; 31 (10): 1374-81 51. Knobloch K, Yoon U, Vogt PM. Acute and overuse injuries correlated to hours of training in master running athletes. Foot Ankle Int 2008; 29 (7): 671-6 52. Magra M, Maffulli N. Genetic aspects of tendinopathy. J Sci Med Sport 2008; 11: 243-7 53. Gaida JE, Alfredson L, Kiss ZS, et al. Dyslipidemia in Achilles tendinopathy is characteristic of insulin resistance. Med Sci Sports Exerc 2009; 41 (6): 1194-7 54. Lephart SM, Fu FH. Proprioception and neuromuscular control in joint stability. Champaign (IL): Human Kinetics, 2000 55. Lam T, Anderschitz M, Dietz V. Contributions of feedback and feedforward strategies to locomotor adaptations. J Neurophysiol 2006; 95: 766-73 56. Granata KP, Wilson SE, Massimini AK, et al. Active stiffness of the ankle in response to inertial and elastic loads. J Electromyogr Kinesiol 2004; 14 (5): 599-609 57. Richardson C, Hodges P, Hides J. Therapeutic exercise for lumbopelvic stabilization: a motor control approach for the treatment and prevention of low back pain. Sydney (NSW): Churchill Livingstone, 2004 58. Delahunt E, Monaghan K, Caulfield B. Altered neuromuscular control and ankle joint kinematics during walking in subjects with functional instability of the ankle joint. Am J Sports Med 2006; 34 (12): 1970-6 59. Delahunt E. Neuromuscular contributions to functional instability of the ankle joint. J Body Mov Ther 2007; 11: 203-13
Sports Med 2010; 40 (9)
Wyndow et al.
726
60. Delahunt E. Peroneal reflex contribution to the development of functional instability of the ankle joint. Phys Ther Sport 2007; 8 (2): 98-104 61. Cowan S, Bennell K, Hodges P, et al. Simultaneous feedforward recruitment of the vastii in untrained postural tasks can be restored by physical therapy. J Orthop Res 2003; 21: 553-8 62. Cowan S, Bennell K, Hodges P, et al. Delayed onset of electromyographic activity of the vastus lateralis compared to vastus medialis obliquus in subjects with patellofemoral pain syndrome. Arch Phys Med Rehabil 2001; 82: 183-9 63. Sasaki K, Neptune RR. Differences in muscle function during walking and running at the same speed. J Biomech 2006; 39 (11): 2005-13 64. Mahieu NN, Witvrouw E, Stevens V, et al. Intrinsic risk factors for the development of Achilles tendon overuse injury: a prospective study. Am J Sports Med 2006; 34 (2): 226-35 65. Baur H, Divert C, Hirschmuller A, et al. Analysis of gait differences in healthy runners and runners with chronic Achilles tendon complaints. Isokinet Exerc Sci 2004; 12 (2): 111-6 66. Mayer F, Grau S, Baeurle W, et al. Differences and influences of EMG-time quantities in healthy subjects and patients with Achilles tendinitis [abstract]. Med Sci Sports Exerc 2001; 33 (5): S89 67. Silbernagel KG, Gustavsson A, Thomee R, et al. Evaluation of lower limb function in patients with achilles tendinopathy. Knee Surg Sports Traumatol Athrosc 2006; 14 (11): 1207-17 68. Nawoczenski DA, Saltzman CL, Cook TM. The effect of foot structure on the three-dimensional kinematic coupling behaviour of the leg and rear foot. Phys Ther 1998; 78 (4): 404-16 69. Stacoff A, Reinschmidt C, Nigg B, et al. Effects of foot orthoses on skeletal motion during running. Clin Biomech 2000; 15 (1): 54-64 70. Kvist M. Achilles tendon injuries in athletes. Ann Chir Gynaecol 1991; 80 (2): 188-201 71. Kaufman KR, Brodine SK, Shaffer RA, et al. The effect of foot structure and range of motion on musculoskeletal injuries. Am J Sports Med 1999; 27 (5): 585-93 72. Azevedo L, Lambert M, Vaughan C, et al. Lower limb biomechanics and EMG activity during painful running in runners with Achilles tendinopathy [abstract]. Med Sci Sports Exerc 2006; 38 (5): S123 73. Azevedo L, Lambert M, Vaughan C, et al. Biomechanical variables associated with Achilles tendinopathy in runners. Br J Sports Med 2009; 43 (4): 288-92 74. Williams DS, Zambardino J, Banning V. Transverse-plane mechanics at the knee and tibia in runners with and without a history of Achilles tendinopathy. J Orthop Sports Phys Ther 2008; 38 (12): 761-7 75. Arndt A, Wolf P, Liu A, et al. Intrinsic foot kinematics measures in vivo during the stance phase of slow running. J Biomech 2007; 40: 2672-8 76. Carson MC, Harrington ME, Thompson N, et al. Kinematic analysis of a multisegmental foot model for research
ª 2010 Adis Data Information BV. All rights reserved.
77. 78.
79.
80.
81.
82.
83.
84.
85.
86.
87.
88.
89.
90.
91. 92.
93.
94.
and clinical applications: a repeatability analysis. J Biomech 2001; 34: 1277-307 Reinschmidt C, Stacoff A, Stussi E. Heel movement within a court shoe. Med Sci Sports Exerc 1992; 24 (12): 1390-5 Stacoff A, Reinschmidt C, Stussi E. The movement of the heel within a running shoe. Med Sci Sports Exerc 1992; 24 (6): 695-701 McLean L, Goudy N. Neuromuscular response to sustained low-level muscle activation: within- and between-synergist substitution in the triceps surae muscles. Eur J Appl Physiol 2004; 91: 204-16 Wakeling J, Uehli K, Rozitis AI. Muscle fibre recruitment can respond to the mechanics of the muscle contraction. J R Soc Interface 2006; 3: 533-44 Johnson MA, Polgar J, Weightman D, et al. Data on the distribution of fibre types in thirty-six human muscles: an autopsy study. J Neurol Sci 1973; 18: 111-29 Nardone A, Schieppati M. Shift of activity from slow to fast muscle during voluntary lengthening contractions of the triceps surae muscles in humans. J Physiol 1988; 395 (1): 363-81 Ishikawa M, Komi PV, Grey MJ, et al. Muscle-tendon interaction and elastic usage in human walking. J Appl Physiol 2005; 99: 603-8 Bruggemann GP, Potthast W, Lersch C, et al. Achilles tendon strain distribution is related to foot and ankle shank kinematics and muscle forces [abstract]. J Biomech 1997; 40 (S2): S139 Provenzano PP, Vanderby Jr R. Collagen fibril morphology and organization: implications for force transmission in ligament and tendon. Mat Biol 2006; 25: 71-84 Haraldsson BT, Aagaard P, Qvortrup K, et al. Lateral force transmission between human tendon fascicles. Mat Biol 2008; 27: 86-95 Gross M, Davlin L, Evanski P. Effectiveness of orthotic shoe inserts in the long distance runner. Am J Sports Med 1991; 19 (4): 409-12 Melegati G, Volpi P, Tomese D, et al. Rehabilitation in tendinopathies. J Sports Traumatol Rel Res 1999; 21 (1): 66-83 Kader D, Saxena A, Movin T, et al. Achilles tendinopathy: some aspects of basic science and clinical management. Br J Sports Med 2002; 36 (4): 239-49 MacLean C, Davis I, Hamill J. Influence of a custom foot orthotic intervention on lower extremity dynamics in healthy runners. Clin Biomech 2006; 21 (6): 623-30 Nigg B. The role of impact forces and foot pronation: a new paradigm. Clin J Sports Med 2001; 11: 2-9 Tomaro J, Burdett RG. The effect of foot orthotics on the EMG activity of selected leg muscle during gait. J Orthop Sports Phys Ther 1993; 18 (4): 532-6 Nawoczenski DA, Ludewig PM. Electromyographic effects of foot orthotics on selected lower extremity muscles during running. Arch Phys Med Rehab 1999; 80: 540-4 Murley GS, Bird AR. The effect of three levels of foot orthotic wedging on the surface electromyographic activity of selected lower limb muscles during gait. Clin Biomech 2006; 21 (10): 1074-80
Sports Med 2010; 40 (9)
Neuromotor Control of the Lower Limb in Achilles Tendinopathy
95. Bird AR, Bendrups AP, Payne CB. The effect of foot wedging on electromyographic activity in the erector spinae and gluteus medius muscles during walking. Gait Posture 2003; 18: 81-91 96. Mattacola CG, Dwyer MK, Miller AK, et al. Effect of orthoses on postural stability in asymptomatic subjects with rearfoot malalignment during a six week acclimation period. Arch Phys Med Rehab 2007 May; 88: 653-60 97. Cobb SC, Tis LL, Johnson JT. The effect of 6 weeks of custom-moulded foot orthosis intervention on postural stability in participants with >7 degrees of forefoot varus. Clin J Sports Med 2006; 16 (4): 316-22 98. Vanicek N, Kingman J, Hencken C. The effects of foot orthotics on myoelectric fatigue in the vastus lateralis during a simulated skier’s squat. J Electromyogr Kinesiol 2004; 14: 693-8
ª 2010 Adis Data Information BV. All rights reserved.
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99. Waddington G, Adams R. Football boot insoles and sensitivity to extent of ankle inversion movement. Br J Sports Med 2003; 37 (2): 170-5 100. Rose HM, Schultz SJ, Arnold BL, et al. Acute orthotic intervention does not affect muscular response times and activation patterns at the knee. J Athl Train 2002; 37 (2): 133-40 101. Murley GS, Landorf KB, Menz HB, et al. Effect of foot posture, foot orthoses and footwear on lower limb muscle activity during walking and running: a systematic review. Gait Posture 2009; 29 (2): 172-87
Correspondence: Dr Kay M. Crossley, Department of Physiotherapy, Melbourne School of Health Sciences, University of Melbourne, 200 Berkeley St, Carlton, VIC, 3010, Australia. E-mail:
[email protected]
Sports Med 2010; 40 (9)
Sports Med 2010; 40 (9): 729-746 0112-1642/10/0009-0729/$49.95/0
REVIEW ARTICLE
ª 2010 Adis Data Information BV. All rights reserved.
A ‘Plane’ Explanation of Anterior Cruciate Ligament Injury Mechanisms A Systematic Review Carmen E. Quatman,1,2 Catherine C. Quatman-Yates1,3 and Timothy E. Hewett1,4,5,6 1 Cincinnati Children’s Hospital Research Foundation, Sports Medicine Biodynamics Center and Human Performance Laboratory, Cincinnati, Ohio, USA 2 University of Toledo, Engineering Center for Orthopaedic Research Excellence, College of Engineering, University of Toledo, Toledo, Ohio, USA 3 Cincinnati Children’s Hospital, Division of Occupational Therapy and Physical Therapy, Cincinnati, Ohio, USA 4 Cincinnati Children’s Hospital Research Foundation, Division of Molecular Cardiovascular Biology, Cincinnati, Ohio, USA 5 University of Cincinnati College of Medicine, Departments of Pediatrics, Orthopaedic Surgery and College of Allied Health Sciences, Department of Rehabilitation Sciences, Cincinnati, Ohio, USA 6 The Ohio State University, Sports Medicine Center, Departments of Physiology and Cell Biology, Orthopaedic Surgery, Family Medicine and Biomedical Engineering, Columbus, Ohio, USA
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Search Strategy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.1 Electronic Database Literature Search . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.2 Inclusionary and Exclusionary Criteria . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2.3 Independent Review and Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3. Results . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4. Discussion. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.1 Planar Biomechanics Surrounding the Inciting Anterior Cruciate Ligament Injury Event . . . . . . . 4.2 Evidence that Supports a Sagittal Plane Mechanism Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.3 Evidence Against a Sole Sagittal Plane Mechanism Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.4 Evidence that Supports a Frontal Plane Mechanism Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.5 Evidence Against a Sole Frontal Plane Mechanism Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.6 Evidence in Support of a Transverse Plane Mechanism Theory . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.7 Evidence Against of a Sole Transverse Plane Mechanism Theory . . . . . . . . . . . . . . . . . . . . . . . . . . 4.8 Multi-Planar Mechanism . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4.9 Kinetic Chain Involvement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
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Although intrinsic and extrinsic risk factors for anterior cruciate ligament (ACL) injury have been explored extensively, the factors surrounding the inciting event and the biomechanical mechanisms underlying ACL injury remain elusive. This systematic review summarizes all the relevant data and
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clarifies the strengths and weaknesses of the literature regarding ACL injury mechanisms. The hypothesis is that most ACL injuries do not occur via solely sagittal, frontal or transverse plane mechanisms. Electronic database literature searches of PubMed MEDLINE (1966–2008), CINAHL (1982–2008) and SportDiscus (1985–2008) were used for the systematic review to identify any studies in the literature that examined ACL injury mechanisms. Methodological approaches that describe and evaluate ACL injury mechanisms included athlete interviews, arthroscopic studies, clinical imaging and physical exam tests, video analysis, cadaveric studies, laboratory tests (motion analysis, electromyography) and mathematical modelling studies. One hundred and ninety-eight studies associated with ACL injury mechanisms were identified and provided evidence regarding plane of injury, with evidence supporting sagittal, frontal and/or transverse plane mechanisms of injury. Collectively, the studies indicate that it is highly probable that ACL injuries are more likely to occur during multi-planar rather than single-planar mechanisms of injury.
1. Introduction The anterior cruciate ligament (ACL) is one of the most commonly injured ligaments of the knee.[1] An estimated 200 000 injuries occur annually in the US and epidemiological studies demonstrate that female athletes have a 2- to 8-fold greater ACL injury rate compared with male athletes.[2,3] ACL injuries can be devastating to an athlete, with the potential loss of a year or more of sports participation, possible loss of scholarship funding and a significantly greater risk of developing knee osteoarthritis in the long term, regardless of the treatment.[4] Prevention of ACL injury would allow many athletes to receive the health benefits of sports participation and avoid the long-term sequelae of disability associated with knee osteoarthritis. It is widely recognized that tibiofemoral knee joint motions occur in three planes (sagittal, frontal and transverse) with six degrees of freedom (three rotations, three translations) between the femoral condyles and tibial plateaus.[5] The knee joint can rotate in the sagittal plane by flexion and extension, in the frontal plane by abduction and adduction, and in the transverse plane by internal and external rotation. The knee joint can also translate in the sagittal plane anteriorly and posteriorly, in the frontal plane medially and laterally, and in the transverse plane by compression and distraction (figure 1). ª 2010 Adis Data Information BV. All rights reserved.
While the knee can move in all 12 of these potential directions, most of these motions take place in a relatively limited range with the exception of flexion and extension (tables I and II). The end range of motion (joint laxity) is highly variable in the general population and may vary by age, pubertal status, sex and race.[10-12] Excessive knee joint loading that leads to motion beyond the normal physiological range in the sagittal, frontal or transverse planes could potentially damage the internal knee joint structures. Several studies indicate that individuals with greater knee or general joint laxity have an increased risk for ACL injury.[13] The planar contributions to the mechanisms of ACL injury is a current debate in recent journal articles, which has led to many letters to the editor, commentaries and symposia at sports medicine conferences.[14-17] Many current ACL prevention programmes only target single plane landing and movement mechanics (hops/jumps in one direction) rather than complex multi-planar movements that incorporate rotational and translational directions.[18-20] Such programmes may minimize risk of injury in the targeted plane but may be ineffective at ameliorating important multi-planar contributions. Likewise, post-injury interventions that neglect to address the multi-planar contributions to ACL injury could seriously hamper ACL injury prevention efforts in athletes returning to sport after a previous ACL injury. This ongoing controversy was the primary motivation Sports Med 2010; 40 (9)
Rotations
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Internal/external
Lateral/medial
Flexion/extension
Posterior/anterior
Translations
Distraction/ compression
Adduction/abduction
Fig. 1. Rotation and translation motions of the knee joint.
for examining the multi-planar contributions of ACL injury supported in the literature via a thorough systematic review. This review summarizes all the relevant data and identifies the strengths and weaknesses in the literature regarding ACL injury mechanisms. The primary research goal attempts to identify and consider any biomechanical and mechanistic knee studies that evaluated the ACL in the literature to determine the most likely underlying mechanisms of ACL injuries. The hypothesis is that ACL injuries do not occur via solely sagittal, frontal or transverse plane mechanisms. 2. Search Strategy 2.1 Electronic Database Literature Search
Electronic database literature searches, including PubMed MEDLINE (1966–2008), CINAHL (1982–2008) and SportDiscus (1985–2008) with ª 2010 Adis Data Information BV. All rights reserved.
the subject term ‘anterior cruciate ligament’ were used for the review. The search was supplemented by a review of the bibliographies of retrieved articles, personal correspondence with authors of the retrieved articles and hand searching of pertinent journals to identify any additional studies addressing this topic of interest. These relatively liberal search criteria were used to identify all published relevant studies and to maximize the generalizability of this review. 2.2 Inclusionary and Exclusionary Criteria
Since the quality of a systematic review depends on the quality of studies appraised, reviewing Level I or II studies would provide the best evidence for answering our important clinical question about ACL injury mechanisms. However, it is unethical to attempt to incite ACL injury events in subjects in the laboratory and it is currently not feasible to design randomized Sports Med 2010; 40 (9)
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controlled trials that examine ACL injury mechanisms. Hence, this specific research question necessitated the inclusion of lower level evidence and a comprehensive evaluation of both basic and applied research examining probable mechanisms of ACL injury. Assimilation and integration of the results of such studies may provide important preliminary data and may identify areas of concentration for future research on ACL injury mechanisms and prevention methods. Thus, for this review, all levels of evidence for both basic and applied research were included if the studies met the required inclusionary and exclusionary criteria. Investigations were included in the review if the report identified ACL injury mechanisms, risk factors for ACL injury (prospectively or retrospectively) or knee biomechanics associated with ACL loading. However, only studies that were associated with ACL injury and provided evidence regarding a plane of injury were included in the final analysis. A study that directly observed or induced an ACL injury mechanism was defined as a direct ACL injury mechanism study. A study that evaluated the differences between in-
tact and ACL deficient conditions, described lesions or identified risk factors associated with ACL injury was defined as an indirect ACL injury mechanism study. Abstracts, unpublished data and published reports not written in English were excluded. Studies were also excluded from the analysis if the experiment was not conducted in humans or human specimens, did not examine planar loading or motion, did not contain original (i.e. review article) or empirical data, or contained only one specimen or subject (case report). In addition, studies that included subjects that had pathologies that may significantly alter knee biomechanics relative to the native (or deficient) conditions or that examined variables unrelated to ACL injury mechanisms were excluded from the analyses. For example, studies that examined reconstruction techniques, effects of bracing, effects of menstrual cycle or hormones, long-term outcomes of ACL injury, partial ACL tears or injuries resulting from vehicle accidents were excluded. Finally, studies with subject (or specimen) reported knee osteoarthritis or ACL deficiency without intact comparisons were excluded from the analyses.
Table I. Range of motion for all knee translations Translationa
Direction
Knee flexion ()
Applied force (N)
Sagittal plane
Anterior and posterior
0 20 45 90
100
Anterior Posterior
25 25
133 133
~6.9 ~5.2
Living subjects (20)
Used KT2000 to measure anterior-posterior translation and distinguishing between
7
Anterior
0 20 90 0 20 90
Manual maximum
~1.8 ~3.2 ~2.0 ~1.8 ~3.0 ~1.8
Cadaver (35); living subjects (49)
Manual maximum was not a specified force. The cadaveric and live subjects did not have a large difference in measurements
6
0 30 0 30
660–690 510–690 510–650 470–630
~4.5 ~5.0 ~4.5 ~5.0
Cadaver (2)
Small subject number and high forces that would not necessarily occur physiologically without some type of rotational component
8
Posterior
Frontal plane
Medial Lateral
a
Tibial displacement (mm) [mean] 2.0 [– 0.5] 4.8 [– 2.0] 3.9 [– 2.5] 2.9 [– 1.7]
Study type (n)
Comment
Reference
Cadaver (35)
6
Transverse plane: no data available.
mm = millimetre; n = no. of subjects; N = Newton; ~ indicates approximate; indicates degrees.
ª 2010 Adis Data Information BV. All rights reserved.
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2.3 Independent Review and Analysis
Two independent reviewers performed firststage screening of titles and abstracts based on the study design and research question to identify all relevant articles. Any study identified by either reviewer was included in the first-stage screen. After the initial screening, a second-stage review was performed to identify which studies met the study criteria and for data extraction and analysis. If there was disagreement regarding study criteria or data extraction, a third reviewer was available to reconcile any differences of opinion. A quality appraisal of the literature was used to determine the strengths and weaknesses of the methodologies used to examine ACL injury mechanisms. Data analysis and results consisted of descriptive evaluations of each study, including the methodology, outcomes and the planar direction (if available) supported by the results for each study. 3. Results The initial literature search yielded 9861 total references; 639 articles met the minimum inclusion criteria. The articles retrieved varied by level of evidence, methodology, study population and outcomes. As expected, no randomized controlled trials were identified. Common methodological approaches used to study ACL injury mechanisms included athlete interviews or questionnaires, arthroscopic studies, clinical imaging and physical
exam testing, video analysis, in vivo laboratory tests (such as motion analysis or EMG) or mathematical modelling studies. The studies utilized either in vivo (human subjects) or in vitro (human cadaver) techniques. However, because of the unique differences between in vivo and in vitro techniques, we categorized cadaveric investigations as using a separate methodology, even though cadaveric studies often utilized similar methods such as imaging, motion analysis or arthroscopy to evaluate knee biomechanics. While 639 studies met the a priori established criteria, only 34 studies were associated with ‘direct’ ACL injury mechanisms and provided evidence regarding the planar mechanism of injury. The breakdown of studies addressing planar mechanisms of injury consisted of 16 interview/ questionnaire studies,[21-36] six video analysis studies[21,37-41] that reported a planar mechanism of injury, six modelling studies[42-47] and six cadaveric studies.[48-53] Twenty-eight of these 34 studies (82%) supported multi-planar mechanisms (table III). In addition to the studies related to direct ACL injury mechanisms, 164 studies were identified that looked at ACL injury mechanism ‘indirectly’ and provided evidence regarding possible planar injury mechanisms. A total of 80 of these 164 studies (49%) supported multi-planar mechanisms (table IV). Sixty-two of 132 (47%) diagnostic studies using imaging, arthroscopy, physical exam or instrumented laxity provided evidence to support multi-planar mechanisms (table IV). While 50 of
Table II. Range of motion for knee rotations in the frontal and transverse planes Rotation
Direction
Knee flexion ()
Applied force (Nm)
Laxity () [mean]
Study type (n)
Comment
Reference
Frontal plane
Adduction and abduction
0 10 20 45 90 135
~8
1.9 [– 1.7] 4.5 [– 1.9] 5.4 [– 2.1] 6.0 [– 2.4] 7.5 [– 2.8] 8.4 [– 3.1]
Cadaver (35)
Manual application of force to determine laxity
9
Transverse plane
Internal and external
0 10 20 45 90 135
~8
10.1 [– 4.0] 19.5 [– 4.9] 24.5 [– 4.9] 26.7 [– 5.8] 24.3 [– 4.7] 26.2 [– 7.2]
Cadaver (35)
Manual application of force to determine laxity
9
n = no. of subjects; Nm = Newton metres; ~ indicates approximate; indicates degrees.
ª 2010 Adis Data Information BV. All rights reserved.
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Table III. Planar evidence for studies directly associated with anterior cruciate ligament injury Study type
No. of studies with planar mechanism evidence
No. of studies that support multi-planar mechanisms
Other support
Cadaver
6
4
Sagittal = 1; frontal = 1
Modelling
6
3
Sagittal = 2; frontal = 1
Video
6
6
Interview/questionnaire
16
15
Sagittal = 1
Total
34
28
Sagittal = 4; frontal = 2
the 132 (38%) diagnostic studies provided evidence to support a sole sagittal plane mechanism, it is important to consider that most of these studies only evaluated anterior tibial translation and did not consider other planes in the diagnostic evaluation. Four of eight (50%) modelling studies and 13 of 23 (57%) cadaveric studies supported multiplanar mechanisms for ACL injury (table IV). Although many in vivo laboratory studies evaluated the effects of ACL deficiency on dynamic knee biomechanics, the complex neuromuscular compensation patterns that may occur as a result of injury made it difficult to interpret the planar conseqences of ACL deficiency. However, one prospective in vivo biomechanical/epidemiological laboratory study supported a multi-planar mechanism, as abnormal mechanics in all three planes during landing predicted ACL injury risk (table IV). 4. Discussion 4.1 Planar Biomechanics Surrounding the Inciting Anterior Cruciate Ligament Injury Event
The various methods used to study ACL injury mechanisms indicate that the ACL may be subject to high forces when under varying loading conditions. Based on this systematic analysis, we
accepted the hypothesis that ACL injuries do not occur via solely a sagittal, frontal or transverse plane mechanism. Table V summarizes the types, advantages and limitations of research methods used to study ACL injury mechanisms found in the studies identified through this review.[54] It is important to note that since it is well established that females have increased rates of ACL injury in similar sports compared with males, the ACL injury studies identified often focused on the determination of differences between the sexes that may increase the risk for injury in females. Sections 4.2–4.8 highlight some of the support and limitations for solely sagittal, frontal and transverse mechanisms of ACL injury compared with a multi-planar mechanistic view of ACL injury. 4.2 Evidence that Supports a Sagittal Plane Mechanism Theory
Many conventional and current theories support a sagittal plane mechanism of injury. A total of 32% of the studies identified supported a sole sagittal plane mechanism of injury. The knee has the largest range of motion in the sagittal plane compared with the frontal or transverse planes and more erect knee postures during landing are theorized to increase risk for ACL injury. Females have been reported to have less knee flexion during landing, jumping
Table IV. Planar evidence for studies indirectly associated with anterior cruciate ligament injury Study type
No. of studies with planar mechanism evidence
No. of studies that support multi-planar mechanisms
Other support Sagittal = 6; frontal = 4
Cadaver
23
13
Modelling
8
4
132
62
1
1
164
80
Diagnostic In vivo laboratory Total
ª 2010 Adis Data Information BV. All rights reserved.
Sagittal = 4 Sagittal = 50; frontal = 11; transverse = 9 Sagittal = 60; frontal = 17; transverse = 9
Sports Med 2010; 40 (9)
Examples
Advantages
Limitations
Applications in ACL research
References
In vivo
Observational: questionnaires, videos, interviews
Direct observation or description of injury mechanism
Cannot determine internal structure stresses/strains Questionnaire/interview: subjective and dependent on athletes ability to recall event Video: limited by quality of video, camera angles available and observer’s ability to describe event
Description of inciting event (contact or non-contact, type of sporting activity), gross position of knee, trunk, lower extremity during injury
2,21,25,27,55,56
Clinical: arthroscopic, imaging, physical exam
Identify lesions associated with injury, strain gauges on internal joint structures, analyse anatomic restraints Functional-dynamic imaging such as MRI or roentgen stereogrammetric analysis techniques offer enhanced ability to visualize internal structures during dynamic weight-bearing activities Accuracy, precision, reliability of data acquisition continues to improve
Do not directly analyse injury mechanism Post-injury pathology and associated biomechanical effects may not be reliable indicators of actual injury mechanisms Arthroscopic: not ethical for healthy subjects, may affect proprioception or cause joint impingement, expensive Imaging: possible radiation exposure, expensive Physical exam: often subjective and highly variable differences between subjects
Strain gauges placed on ACL during arthroscopy provide information about ACL strains during external loads Bone bruise locations may provide evidence for injury mechanisms Posterior tibial slope calculated from images may be associated with ACL injury Lachman’s, pivot shift, knee arthrometer data provide evidence of biomechanical effects of ACL deficiency Functional dynamic images help identify osteokinematics and ACL changes that occur during weight-bearing tasks
57,58
Laboratory: motion analysis, electromyography
Mimic specific movements that occur during injury Estimate both kinematics and net kinetics at joint during high risk movements Coupled
Do not replicate actual injury, rather estimate total joint biomechanics during high risk movements Difficult to reproduce or even approximate the strains and stresses that occur in internal joint structures
Identify sex differences in landing/cutting mechanics that may be associated with ACL injury Identify biomechanical/ neuromuscular variables
9,59-68
Continued next page
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Data collection method
ACL Injury Mechanisms
ª 2010 Adis Data Information BV. All rights reserved.
Table V. Summary of research methods used to study anterior cruciate ligament (ACL) injury mechanisms (reproduced from Quatman et al.,[54] with permission from BMJ publishing group)
Data collection method
Examples
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ª 2010 Adis Data Information BV. All rights reserved.
Table V. Contd Advantages
Limitations
Applications in ACL research
biomechanical/epidemiological studies provide predictive tools about injury risk factors (allows for both correlation and prediction of musculoskeletal injury)
(ligaments, cartilage, bones) Unethical to try to produce injury in laboratory
associated with ACL injury
References
Robotic, quasi-static, dynamic
Identify passive biomechanical characteristics of joint motions Direct injury studies possible Quantify multiple degree of freedom kinematics of joints Measure ligament and joint articulation contact forces
Age of specimens (may differ significantly from the population of interest) Difficult to reproduce dynamic joint motions and neuromuscular contributions to motion during injury conditions Expensive and injury studies often require a large number of specimens to reproduce injury mechanisms Orientation of loading, rate of loading and age of specimen may have significant effects on musculoskeletal failure loads
ACL strains and biomechanical parameters during different external loading parameters provide evidence of how ACL injuries may occur Cadaveric ACL injury may occur during anterior tibial shear, abduction, knee hyperextension and many combined loads Biomechanical consequences of ACL deficiency
48-53,69-76
In silico
Phenomenological, anatomic, rigid, finite element, quasi-static, dynamic, stochastic, inverse simulation, forward simulation
Estimate internal joint biomechanics In vivo biomechanical data can be used as input for geometric models to analyse movements Can be used to extend motion analysis data to relate ground reaction forces and kinematics to ligament, cartilage and bone forces Can be used to simulate injury mechanisms Parametric/sensitivity studies possible Relatively inexpensive if equipment is readily available Accuracy, precision, reliability of data acquisition continues to improve
Due to complexity of joints, models are simplified Certain assumptions are necessary about material properties, boundary conditions and anatomy Models must be validated (ideally by in vivo and in vitro data), which can be difficult without adequate material property characteristics available for the population of interest Not currently possible to validate high loading rate/injury simulations
ACL injury simulations for various tasks Identification of possible strategies to lower ACL injury risk Extension of coupled biomechanical/epidemiological motion analysis data to relate ground reaction forces and external loading conditions to ACL strains
44,45,77-85
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In vitro
ACL Injury Mechanisms
and cutting tasks compared with males. In addition, interview and video observational studies indicate that the knee is at low (0–30) knee flexion angles during injury events.[21,25,29,37,39,41] Sagittal plane translation movements are also important to consider, since the ACL is a major stabilizing ligament of the knee that provides approximately 85% of the total restraint in the knee joint to the anterior tibial translation.[6,86] Many cadaveric, imaging and physical exam studies demonstrate that ACL-deficient knees have significantly more anterior tibial translation compared with ACL-intact conditions.[9,59] Both in vivo and in vitro studies demonstrate that the total range for anterior/posterior tibial displacement is greater at 30 than 90 of knee flexion, which indicates that the knee joint has the potential to translate further anteriorly at shallow knee flexion angles.[59,87] During sagittal plane movements at the knee joint, the quadriceps muscle contractions produce anterior shear force at the proximal end of the tibia through the patellar tendon.[48,88] Proximal tibia anterior shear is the most direct ACL loading mechanism and decreasing knee flexion angles increases the anterior shear force at the tibia.[89,90] Since video studies indicate that ACL injuries usually occur at low flexion angles, it is theorized that a powerful quadriceps force at low knee flexion angles could produce enough anterior shear force at the tibia to cause ACL rupture.[88,90-92] Correspondingly, several studies support anterior tibial shear as a mechanism for ACL injury. MRI studies after ACL injury demonstrate that tibial bone bruises are located more posteriorly than femoral condylar bone bruises and it has been speculated that this is a result of the tibia shifting anteriorly relative to the femur during the injury.[93,94] In vivo arthroscopic studies demonstrate that the ACL is a primary restraint to anterior shear loading and abnormal anterior tibial translation relative to the femur is a clinical measure used to determine ACL deficiency.[60,95] The relationships between high ACL strains, low knee flexion angles and quadriceps muscle forces have been extensively examined.[69,92,96-98] The landing phase of many sports movements are associated with large quadriceps forces at relaª 2010 Adis Data Information BV. All rights reserved.
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tively small knee flexion angles, which induce anterior force on the tibia.[98] Cadaveric investigations have demonstrated that isolated quadriceps contractions increase ACL strain and force during low knee flexion angles.[69,98] Studies by DeMorat et al. and Pandy and Shelburne indicated that aggressive quadriceps loading in slight knee flexion produce significant anterior tibial translation sufficiently large enough to injure the ACL.[48,88] Withrow et al. showed that during a high impact load, ACL strain is proportional to increased quadriceps forces.[70] In an arthroscopic study, Fleming et al. found that quadriceps contractions produced ACL strains between 0 and 30 of knee flexion.[95] At the same time, several motion analysis and EMG studies showed that females have more knee extension during landing compared with males, and that females have significant neuromuscular imbalances between quadriceps and hamstrings recruitment levels, making it more difficult to decelerate from a landing and control anterior tibial translation.[99-103] 4.3 Evidence Against a Sole Sagittal Plane Mechanism Theory
Although, theoretically, many of the studies identified support a sagittal plane mechanism, several limitations to these studies should be considered. In combination, these limitations provide a strong argument against single plane mechanisms of injury and subsequently underscore the likelihood of a more multi-planar mechanism of injury. For example, theoretically, if the mechanism was solely an anterior shear, the bone bruise patterns on MRI after ACL injury would most likely be located along the medial tibial plateau as well as the tibial plateau. Since the bone bruises are usually located laterally, lateral compression or internal/external tibial rotation of the joint also likely occurred during these injuries. Moreover, while some motion analysis studies suggest that females show greater knee extension during landing, other studies show no sex difference or even greater knee flexion in females during athletic tasks.[104-106] Video analyses of ACL injuries indicate that females may actually have a higher knee flexion angle compared with males during the Sports Med 2010; 40 (9)
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injury event.[39] Furthermore, knee flexion angle does not appear to predict ACL injury risk.[107] Cadaveric studies also indicate that hamstrings co-contraction with quadriceps contraction is effective in reducing excessive forces in the ACL, specifically between 15 and 60 of knee flexion.[92] At the same time, during landing, ACL strains are higher under multi-planar loading conditions compared with isolated anterior tibial loading situations, making it easier to damage the ACL under combined planar situations.[90] DeMorat et al. found that a quadriceps contraction appeared to affect ACL loading in more than one plane of motion, as knee internal rotation and valgus moments to the tibia occurred coincident with anterior tibial translation.[48] Mathematical models indicate that large ground reaction forces posteriorly directed with respect to the proximal tibia help protect the ACL during landing and posterior deceleration forces and reduce ACL strain during a run-to-stop simulation.[108] Moreover, hamstrings co-contraction can lead to joint compression and decreased anterior tibial translation.[109,110] Several mathematical models have demonstrated that sagittal plane mechanisms alone cannot account for ACL forces high enough to rupture the ACL.[45,111,112] Therefore, it is highly unlikely that ACL injuries result exclusively from a sagittal plane mechanism. 4.4 Evidence that Supports a Frontal Plane Mechanism Theory
The frontal plane theory mechanism has become a recent topic of debate as a contributing factor to ACL injuries. Approximately 10% of the studies identified supported a sole frontal plane mechanism and over 80% of the studies identified supported frontal plane mechanisms (specifically abduction motions) as a contributor to a multiplanar mechanism of injury. Based upon the studies identified, frontal plane motions are often associated with ACL injuries and excessive movements in the frontal plane outside normal ranges may be catastrophic to the knee joint. Ligament restraints and knee joint articulation limit the passive range of knee motion in the frontal plane, which results in a smaller range of moª 2010 Adis Data Information BV. All rights reserved.
tion in the frontal plane compared with the sagittal plane. It is difficult to accurately measure mediallateral translations of the knee since the translations that can occur in a healthy knee are limited. Cadaveric studies and in vivo studies have demonstrated that the frontal plane rotational range of motion is also relatively limited.[6] Shultz et al. demonstrated in vivo that a 10 Newton (N) metres (abduction/ adduction) load at 20 of knee flexion produced approximately 10 total knee rotation in the frontal plane (abduction ~5.5; adduction ~4.5).[7] Markolf et al. and Miyaska et al. demonstrated that cadaveric specimens subjected to adduction torque show increases in ACL tension throughout a range of knee flexion angles (0–90) with the highest between 0 and 30 of knee flexion.[71,90] Similarly, Wascher et al. and Markolf et al. demonstrated that adduction moments lead to high ACL forces particularly near full knee extension.[72,113] Arthroscopic studies indicate that the ACL strain increases under adduction moments during weight-bearing conditions.[95] While adduction motions of the knee do appear to increase the tension and strain in the ACL, few observational studies attribute this type of motion to ACL injuries.[21,39] Video analyses of ACL injuries during sports indicate a common body posture during injury in which the knee is near full extension (between 0 and 30), the tibia is externally rotated, the foot is planted and a deceleration followed by an abduction collapse of the knee joint occurs.[21,39] Olsen et al. found that dynamic abduction collapse was the most common mechanism for ACL injury in handball.[41] Similarly, Krosshaug et al. found that dynamic abduction collapse was a common ACL injury mechanism with female basketball players demonstrating a 5.3-fold higher relative risk of abduction collapse during ACL injury compared with male basketball players.[39] At the same time, motion analysis studies indicate that high knee abduction motion and torque are both common sex differences during athletic movements and predictors of future ACL injury risk.[64,65,67,68,101,104,107,114] Clinical imaging and arthroscopic studies also indicate that frontal plane mechanisms play a role in ACL injury. Bone bruises of the lateral Sports Med 2010; 40 (9)
ACL Injury Mechanisms
femoral condyle or posterolateral portions of the tibial plateau are found to occur 80% of the time in MRI studies after acute ACL injury.[93,94,115,116] It is theorized that these bone bruise locations indicate that ACL injury occurs from an abduction mechanism, because bone bruising on the lateral part of the knee joint indicates that compression occurs laterally while the medial aspect of the joint opens up. In addition, arthroscopic studies indicate that abduction knee moments applied during weight-bearing conditions significantly increase relative ACL strain.[95] Several cadaveric studies have demonstrated that the ACL may have increased force during abduction loads.[72,90,113] Markolf et al. demonstrated that a quadriceps force (200 N) applied in combination with an abduction load increased the ACL force up to 100% compared with abduction loads without a quadriceps force.[90] Withrow et al. demonstrated that cadavers subjected to impulsive compression loads with the knee joint in an abduction alignment led to 30% higher ACL strains compared with knees in neutral alignment.[73] Modelling studies have also shown support for an abduction injury mechanism. McLean et al. utilized motion analysis and mathematical modelling to simulate injury and showed that external abduction loads reach values high enough to rupture the ACL during cutting manoeuvres and these abduction loads occurred more frequently in females than males.[45] Another forward dynamics model that was used to simulate ACL injuries during an abduction mechanism demonstrated that perturbations to the lower extremity during a side-step cutting manoeuvre can lead to external abduction loads that are capable of rupturing the ACL.[44] 4.5 Evidence Against a Sole Frontal Plane Mechanism Theory
Although increased lower extremity abduction loads and movements in the frontal plane may be associated with increased ACL strain and risk of injury, controversy surrounds this theory. The ACL is considered the primary restraint to anterior tibial translation during passive physical ª 2010 Adis Data Information BV. All rights reserved.
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exam testing, while the medial collateral ligament (MCL) is considered the primary restraint against abduction stress in the knee joint. Therefore, the abduction motion and torque at the knee joint associated with increased ACL injury risk is surprising to clinicians, since it is estimated that combined ACL/MCL injuries make up only 4–27% of all ACL injuries.[1,117] If ACL injuries occur due to movements solely in the frontal plane, higher combined ACL/MCL injury patterns would be expected. Cadaveric studies indicate that the ACL and MCL may both provide restraint to external abduction, albeit via different mechanisms. The ACL appears to prevent knee abduction by limitation of axial tibial rotation, while the MCL restrains knee abduction by limiting medial joint space opening. Thus, both the MCL and ACL are important structures for restraint of abduction loads and either one may potentially be injured during high knee abduction loading.[74] Cadaveric ACL failure loads are reported to range from approximately 640–2100 N, depending upon the age of the specimen, rate and orientation of loading.[75] Cadaveric MCL failure loads have been reported to be around 2300 N for complete MCL disruption.[118] While higher reported MCL failure loads compared with the ACL may help explain how and why the ACL may fail earlier than the MCL during external abduction loading, there are currently no reported studies to support or refute this theory. Few studies have examined ACL and MCL loading simultaneously during an abduction load. Because of the variability in laxity between specimens and different testing conditions and setups, cross referencing of studies to determine how the ACL and MCL simultaneously behave during abduction is difficult. Another limitation to the frontal plane theory is the non-descript term of ‘valgus’ used in previous studies to describe what occurs during an ACL injury. The medical definition of valgus refers to the outward angulation of the distal segment of a bone or joint. However, at the knee joint, valgus may occur from a direct abduction motion of the knee joint or from transverse-plane knee rotation motions (femoral/tibial internal Sports Med 2010; 40 (9)
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and external rotations). Thus, describing an injury mechanism as a valgus collapse does not necessarily indicate that the injury occurred solely in the frontal plane. 4.6 Evidence in Support of a Transverse Plane Mechanism Theory
Although only 5% of the studies supported a sole transverse plane mechanism, many of the studies neglected to assess the transverse rotations during experimental procedures. Thus, the transverse plane contributions to ACL injury mechanisms may be significantly underestimated. Similar to the frontal plane, transverse plane ranges of motion (rotational and translational) are not as large as sagittal plane motions and difficult to assess experimentally. Compression is the most common translation that occurs during cutting and landing activities, and could be a direct result of impact (ground reaction) forces, an indirect result from muscular stabilization or, most likely, a combination of both effects. As evidenced by the common association of bone bruises accompanying ACL injuries, compression is a likely component of the ACL injury event. The total passive range of rotation (internal and external) in the transverse plane is approximately 25, depending on the knee flexion angle.[6] Numerous studies have reported that the ACL experiences higher strains during internal tibial rotation, while only minimal increases in strains during external rotation have been noted.[71,90,113] Cadaveric studies by Meyer et al. demonstrated that high compressive or internal torsional tibial loads can cause ACL damage with limited damage to other knee ligaments.[50] Similarly, Markolf et al. demonstrated that an internal tibial torque generates significantly higher ACL forces than application of a 100 N anterior tibial force during shallow knee flexion angles.[90] In contrast, external tibial torques applied to cadaveric knees demonstrated little differences in ACL strain and tension over a wide range of flexion angles.[90] Snow skiing results in a high rate of ACL injury. A common mechanism described during snow skiing ACL injuries is internal tibial rotation or a combination of high axial loading with ª 2010 Adis Data Information BV. All rights reserved.
transverse plane rotations.[27] However, comparisons between ACL injuries that result from snow skiing and ACL injuries that occur during sports that involve cutting, jumping and landing activities are questionable. Skiers have different movement mechanics, since their feet are fixed in ski bindings and they have the added extensions of the skis, which may increase the surface area for applying external multi-planar loads to the distal end of the lower extremity. A recent imaging study by Stijak et al. found that ACL-injured patients have greater posterior lateral tibial plateau slopes compared with controls.[61] In addition, the lateral femoral condyle has greater translation on the tibia compared with the medial condyle as the flexion angle increases.[119] As the knee goes into deeper flexion, the lateral femoral condyle internally rotates relative to the tibial plateau, while the medial femoral condyle remains relatively stable.[119] Therefore, a greater posterior tibial slope may lead to greater external rotation of the femur or internal rotation of the tibia during activities and may increase an individual’s risk for ACL injury. 4.7 Evidence Against of a Sole Transverse Plane Mechanism Theory
Theoretically, the cushioning provided by the menisci and articular cartilage aids in reduction of the compressive forces and minimization of the compression that occurs during landing and cutting activities. Moreover, it is unlikely that compression without movements in other degrees of freedom could cause injury to the ACL, since ligaments are minimally stressed in compression. It is possible to rupture the ACL in vitro in distraction.[75] However, the intra-articular orientation of the ACL and its variable fibre lengths makes uniform loading of the ACL during tension difficult. Thus, the likelihood of a complete midsubstance ACL rupture is low with pure distractive loads applied along the axis of the tibia.[75] In addition, the compressive knee joint forces resulting from muscle activation during weightbearing activities would counter any distractive forces that may occur during landing and cutting activities. Sports Med 2010; 40 (9)
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In addition, given the strong support for internal tibial rotations being more likely to injure the ACL than external rotations, observational studies that described an external tibial rotation during injury seem counterintuitive and contradictory.[39] Arthroscopic data indicate that during non-weight-bearing conditions, internal tibial torque significantly increases ACL strain while external tibial torques produce minimal strain in the ACL.[95] However, arthroscopic data show that weight-bearing conditions can significantly increase the ACL strain during both internal and external torques. In particular, external torques (0–10 nm) increased the ACL strain during weight-bearing conditions by 2–4% compared with non-weight-bearing conditions.[95] Since most ACL injuries occur during weightbearing conditions, it may be feasible that an external rotation torque could potentially damage the ACL. However, an alternative combined multi-planar loading mechanism may include an externally rotated foot or ski, coupled with foot hyper-pronation and tibial internal rotation and knee abduction, which would lead to high loads on the ligament. 4.8 Multi-Planar Mechanism
Many studies indicate that the knee may experience high loading conditions in any plane. In particular, high loading conditions can occur in sporting manoeuvres, such as landing, jumping and cutting, all of which require movements in multiple planes. Thus, it is unlikely that an ACL injury occurs in a single isolated plane. In support of this concept, 82% of the direct ACL injury mechanism studies identified supported a multi-planar mechanism of injury. This is in corroboration with Shimokochi and Shultz, who systematically reviewed the retrospective and observational studies available in the literature that assessed ACL injury mechanisms and found that the primary mechanism of ACL injury appears to be a result of multi-planar knee loading conditions.[120] Physical examination techniques are forensic in that they may reproduce the increased luxations that occurred during the inciting injury. The pivot shift test is one such clinical exam, which is ª 2010 Adis Data Information BV. All rights reserved.
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performed by a valgus (knee abduction) stress coupled with flexion and tibial rotation. As such, it is likely reproducing the original mechanism of injury. The pivot shift is a highly sensitive test for ACL insufficiency. Benjaminse and Gokeler reported the pivot shift exam to be the most specific clinical test for ACL rupture, demonstrating a 98% specificity (95% CI 96, 99).[121] It is also a sensitive predictor of future poor conservative outcomes following injury.[122] Cumulatively, these data demonstrate that knee abduction motion may be an important component of the ACL injury mechanism. In retrospective interview studies, individuals often reported that their knee moved in multiple planes during the injury event. Specifically, a ‘valgus’ rotation combined with either an internal or external tibial rotation at low knee flexion angles was reported by injured individuals. Similarly, video studies indicate that ACL injuries occur with minimal knee flexion and are often combined with knee ‘valgus’ or transverse knee rotation movements.[21,39,41] This is supported by the bone bruise patterns associated with ACL injuries on imaging studies, with the bone bruises located on the lateral femoral condyles and posterolateral tibial plateaus of patients with acute ACL injured knees. This bruise pattern indicates that internal tibial rotation, femoral external rotation, abduction and/or anterior tibial translation would lead to these specific bone bruise locations. While few in vivo arthroscopic studies have examined combined planar loading, Fleming et al. noted that weight bearing, which resulted in compressive forces across the joint, altered the strain results in the ACL for various loading conditions.[95] ACL strains were higher when an anterior shear force was applied to the tibia during weight-bearing conditions compared with non-weight bearing, and the weight-bearing effect was shear-load dependent. Strains in the ACL were torque dependent for internal and external rotation torques, with weight bearing leading to significantly higher strains than non-weightbearing conditions. Similarly, weight bearing led to significantly higher strains in the ACL during abduction/adduction loading compared with non-weight-bearing conditions.[95] While all of Sports Med 2010; 40 (9)
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these outcomes indicate the ACL can be subjected to high loading strains in all planes in weight bearing, combined loading of anterior shear, abduction/adduction and internal/external torques were not examined. Consequently, it is difficult to surmise the combined effects of multiplanar loading on ACL strain from the study. Cadaveric investigations show that valgus or varus moments, combined with a quadriceps contraction or anterior shear force, increases ACL strain. Markolf et al. and Berns et al. demonstrated that coupled loading of an abduction moment to an anterior tibial force (at a knee flexion greater than 10) or coupled loading of an anterior tibial force with an internal tibial torque (at knee flexion less than 20) leads to additive generation of ACL force and strain compared with an isolated anterior tibial force.[76,90] In contrast, coupled external tibial torque and anterior tibial force appears to lower the ACL tensile force after 20 of knee flexion. As such, the ACL may be less vulnerable to injury, since the MCL could be shielding the ACL from stress in this knee position.[90] Motion analysis studies have indicated that various multi-planar motions may increase risk for ACL injury in female athletes. Hewett et al. showed that subjects who subsequently went on to ACL injury after biomechanical testing had larger abduction angles at initial contact and at peak abduction in the frontal plane and significantly lower knee flexion at peak contact in the sagittal plane.[107] In addition, various sex differences in landing mechanics have been identified in multiple planes and have been speculated as possible risk factors for ACL injury. Modelling studies have provided some unique perspectives on the effects of multi-planar loading. Fung and Zhang developed 3-dimensional models of knees to examine factors that could lead to ACL impingement on the intercondylar notch of the femur.[123] Simulation of the physical interaction between the ACL and the notch during six-degrees of freedom tibiofemoral motions showed that abduction and external tibial rotation can lead to ACL impingement. McLean et al. reported that neuromuscular control perturbation produced peak stance phase knee abduction loads large enough to cause ACL injury, and ª 2010 Adis Data Information BV. All rights reserved.
landing in a more extended knee flexion angle increased this risk for injury.[44] Although the current literature is limited for the evaluation of multi-planar loading effects on knee biomechanics and, specifically, ACL stresses and strains, future modelling work may provide the opportunity to extend motion analysis data to predict stresses and strains in the internal joint structures, simulate injury scenarios, and conduct parametric studies evaluating the effects of isolated and multi-planar loading scenarios without inter-subject variability that occurs during cadaveric and in vivo investigations. 4.9 Kinetic Chain Involvement
Finally, while the ACL injury is a direct result of what occurs at the knee joint, it is important to consider the contribution of the entire kinetic chain to knee joint loading. Motion and forces at any segment of the kinetic chain (foot, ankle, hip, trunk and upper extremities) may influence knee joint mechanics. There is increasing evidence that poor or abnormal neuromuscular control of the lower limb during athletic movements, especially at the knee joint, contributes to ACL injury risk. Future work should establish the effects of proximal and distal structures on knee joint biomechanics and how they relate to ACL injury. 5. Conclusions The methodological approaches that have been utilized to investigate ACL injury mechanisms include athlete interviews, arthroscopic studies, clinical visits, video analysis, cadaveric studies, in vivo laboratory studies and mathematical modelling studies. Although none of these methodologies alone can provide strong answers to the question of what the underlying mechanisms are for ACL injuries, all of these data considered together provide important clues to ACL injury mechanisms. When the data from the published literature that relates to mechanisms of ACL injury are summarized and considered in toto, ACL injuries are more likely to occur during multiplanar rather than single-planar mechanisms of injury. Therefore, based on this systematic analysis, Sports Med 2010; 40 (9)
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we accepted the hypothesis that ACL injuries likely do not occur solely via a sagittal, frontal or transverse plane mechanism. One important clinical implication for the acceptance of this hypothesis is that ACL prevention programmes that neglect multi-planar mechanisms, such as combined frontal, sagittal and transverse plane mechanisms, could seriously hamper ACL injury prevention efforts in healthy athletes and athletes returning to sport after a previous ACL injury. Future studies should focus on the examination of the precise mechanisms of combined knee joint loading scenarios to determine at-risk knee postures that may be addressed with neuromuscular training programmes targeted for ACL injury prevention. Acknowledgements The authors acknowledge funding support from the University of Toledo, College of Medicine Pre-Doctoral Fellowship, the American College of Sports Medicine Foundation, Plus One Active Research Grant on Wellness Using Internet Technology, and the National Institutes of Health Grants R01-AR049735, RO1-AR05563 and R01-AR056259. The authors thank Vijay Goel, Dean Demetropoulos, Kevin Ford, Keith Kenter and Greg Myer for their discussions about the topic covered in this review. The authors have no conflicts of interest that are directly relevant to the content of this review.
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References 1. Miyasaka K, Daniel DM, Stone ML, et al. The incidence of knee ligament injuries in the general population. Am J Knee Surg 1991; 4: 3-8 2. Agel J, Arendt EA, Bershadsky B. Anterior cruciate ligament injury in national collegiate athletic association basketball and soccer: a 13-year review. Am J Sports Med 2005; 33 (4): 524-30 3. Hewett TE, Shultz SJS, Griffen LY, editors. Understanding and preventing noncontact ACL injuries. Champaign (IL): AOSSM, 2007 4. Myklebust G, Bahr R. Return to play guidelines after anterior cruciate ligament surgery. Br J Sports Med 2005; 39 (3): 127-31 5. Woo SL, Abramowitch SD, Kilger R, et al. Biomechanics of knee ligaments: injury, healing, and repair. J Biomech 2006; 39 (1): 1-20 6. Markolf KL, Mensch JS, Amstutz HC. Stiffness and laxity of the knee: the contributions of the supporting structures. A quantitative in vitro study. J Bone Joint Surg Am 1976; 58 (5): 583-94 7. Shultz SJ, Shimokochi Y, Nguyen AD, et al. Measurement of varus-valgus and internal-external rotational knee
ª 2010 Adis Data Information BV. All rights reserved.
18.
19.
20.
21. 22.
23.
laxities in vivo. Part I: assessment of measurement reliability and bilateral asymmetry. J Orthop Res 2007; 25 (8): 981-8 Piziali RL, Seering WP, Nagel DA, et al. The function of the primary ligaments of the knee in anterior-posterior and medial-lateral motions. J Biomech 1980; 13 (9): 777-84 Logan MC, Williams A, Lavelle J, et al. What really happens during the Lachman test? A dynamic MRI analysis of tibiofemoral motion [published erratum appears in Am J Sports Med 2004; 32 (3): 824]. Am J Sports Med 2004; 32 (2): 369-75 Larsson LG, Baum J, Mudholkar GS, et al. Hypermobility: prevalence and features in a Swedish population. Br J Rheumatol 1993; 32 (2): 116-9 Jansson A, Saartok T, Werner S, et al. General joint laxity in 1845 Swedish school children of different ages: age- and gender-specific distributions. Acta Paediatr 2004; 93 (9): 1202-6 Quatman CE, Ford KR, Myer GD, et al. The effects of gender and pubertal status on generalized joint laxity in young athletes. J Sci Med Sport 2008; 11 (3): 257-63 Myer GD, Ford KR, Paterno MV, et al. The effects of generalized joint laxity on risk of anterior cruciate ligament injury in young female athletes. Am J Sports Med 2008; 36 (6): 1073-80 Yu B, Garrett WE. Mechanisms of non-contact ACL injuries. Br J Sports Med 2007; 41 Suppl. 1: i47-51 Quatman CE, Hewett TE. The anterior cruciate ligament injury controversy: is ‘‘valgus collapse’’ a sex-specific mechanism? Br J Sports Med 2009; 43 (5): 328-35 Lin CF, Gross M, Ji C, et al. A stochastic biomechanical model for risk and risk factors of non-contact anterior cruciate ligament injuries. J Biomech 2009; 42 (4): 418-23 van den Bogert AJ, McLean SG. Comment on ‘‘A stochastic biomechanical model for risk and risk factors of non-contact anterior cruciate ligament injuries’’. J Biomech 2009; 42 (11): 1778-9; author reply 1780-2 Mandelbaum BR, Silvers HJ, Watanabe D, et al. Effectiveness of a neuromuscular and proprioceptive training program in preventing the incidence of ACL injuries in female athletes: two-year follow up. Am J Sport Med 2005; 33 (6): 1003-10 Gilchrist J, Mandelbaum BR, Melancon H, et al. A randomized controlled trial to prevent noncontact anterior cruciate ligament injury in female collegiate soccer players. Am J Sports Med 2008; 36 (8): 1476-83 DiStefano LJ, Padua DA, DiStefano MJ, et al. Influence of age, sex, technique, and exercise program on movement patterns after an anterior cruciate ligament injury prevention program in youth soccer players. Am J Sports Med 2009; 37 (3): 495-505 Boden BP, Dean GS, et al. Mechanisms of anterior cruciate ligament injury. Orthopedics 2000; 23 (6): 573-8 Dallalana RJ, Brooks JH, Kemp SP, et al. The epidemiology of knee injuries in English professional rugby union. Am J Sports Med 2007; 35 (5): 818-30 Faude O, Junge A, Kindermann W et al. Injuries in female soccer players: a prospective study in the German national league. Am J Sports Med 2005; 33 (11): 1694-700
Sports Med 2010; 40 (9)
744
24. Faunø P, Wulff Jakobsen B. Mechanism of anterior cruciate ligament injuries in soccer. Int J Sports Med 2006; 27 (1): 75-9 25. Ferretti A, Papandrea P, Conteduca F, et al. Knee ligament injuries in volleyball players. Am J Sports Med 1992; 20 (2): 203-7 26. Fride´n T, Erlandsson T, Za¨tterstro¨m R, et al. Compression or distraction of the anterior cruciate injured knee: variations in injury pattern in contact sports and downhill skiing. Knee Surg Sports Traumatol Arthrosc 1995; 3 (3): 144-7 27. Jarvinen M, Natri A, Laurila S et al. Mechanisms of anterior cruciate ligament ruptures in skiing. Knee Surg Sports Traumatol Arthrosc 1994; 2 (4): 224-8 28. McConkey JP. Anterior cruciate ligament rupture in skiing: a new mechanism of injury. Am J Sports Med 14 (2): 160-4 29. McNair PJ, Marshall RN, Matheson JA, et al. Important features associated with acute anterior cruciate ligament injury. N Z Med J 1990; 103 (901): 537-9 30. Meuffels DE, Verhaar JA. Anterior cruciate ligament injury in professional dancers. Acta Orthop 2008; 79 (4): 515-8 31. Myklebust G, Maehlum S, Holm I, et al. A prospective cohort study of anterior cruciate ligament injuries in elite Norwegian team handball. Scand J Med Sci Sports 1998; 8 (3): 149-53 32. Nakajima H, Kondo M, Kurosawa H, et al. Insufficiency of the anterior cruciate ligament: review of our 118 cases. Arch Orthop Trauma Surg 1979; 95 (4): 233-40 33. Noyes FR, Bassett RW, et al. Arthroscopy in acute traumatic hermarthrosis of the knee: incidence of anterior cruciate tears and other injuries. J Bone Joint Surg 1980; 62 (5): 687-95, 757 34. Olsen OE, Myklebust G, Engebretsen L, et al. Relationship between floor type and risk of ACL injury in team handball. Scand J Med Sci Sports 2003; 13 (5): 299-304 35. Pope RP. Injury surveillance and systematic investigation identify a rubber matting hazard for anterior cruciate ligament rupture on an obstacle course. Mil Med 2002; 167 (4): 359-62 36. Scriber K, Matheny M. Knee injuries in college football: an 18 year report. Athl Train 1990; 25 (3): 233-36 37. Cochrane J, Lloyd D, Buttfield A, et al. Characteristics of anterior cruciate ligament injuries in Australian football. J Sci Med Sport 2007; 10 (2): 96-104 38. Ebstrup JF, Bojsen-Møller F. Anterior cruciate ligament injury in indoor ball games. Scand J Med Sci Sports 2000; 10 (2): 114-6 39. Krosshaug T, Nakamae A, Boden BP, et al. Mechanisms of anterior cruciate ligament injury in basketball: video analysis of 39 cases. Am J Sports Med 2007; 35 (3): 359-67 40. Lightfoot AJ, McKinley T, Doyle M, et al. ACL tears in collegiate wrestlers: report of six cases in one season. Iowa Orthop J 2005; 25: 145-8 41. Olsen O, Myklebust G, Engebretsen L, et al. Injury mechanisms for anterior cruciate ligament injuries in team handball: a systematic video analysis. Am J Sports Med Olsen 2004; 32 (4): 1002-12 42. Chaudhari AM, Andriacchi TP. The mechanical consequences of dynamic frontal plane limb alignment for non-contact ACL injury. J Biomech 2006; 39 (2): 330-8
ª 2010 Adis Data Information BV. All rights reserved.
Quatman et al.
43. Gerritsen KG, Nachbauer W, van den Bogert AJ. Computer simulation of landing movement in downhill skiing: anterior cruciate ligament injuries. J Biomech 1996; 29 (7): 845-54 44. McLean SG, Huang X, van den Bogert AJ. Investigating isolated neuromuscular control contributions to noncontact anterior cruciate ligament injury risk via computer simulation methods. Clin Biomech (Bristol, Avon) 2008; 23 (7): 926-36 45. McLean SG, Huang X, Su A, et al. Sagittal plane biomechanics cannot injure the ACL during sidestep cutting. Clin Biomech (Bristol, Avon) 2004; 19 (8): 828-38 46. McLean SG, Su A, van den Bogert AJ. Development and validation of a 3-D model to predict knee joint loading during dynamic movement. J Biomech Eng 2003; 125 (6): 864-74 47. Zavatsky AB, Wright HJ. Injury initiation and progression in the anterior cruciate ligament. Clin Biomech (Bristol, Avon) 2001; 16 (1): 47-53 48. DeMorat G, Weinhold P, Blackburn T, et al. Aggressive quadriceps loading can induce noncontact anterior cruciate ligament injury. Am J Sports Med 2004; 32 (2): 477-83 49. Mazzocca AD, Nissen CW, Geary M, et al. Valgus medial collateral ligament rupture causes concomitant loading and damage of the anterior cruciate ligament. J Knee Surg 2003; 16 (3): 148-51 50. Meyer EG, Baumer TG, Slade JM, et al. Tibiofemoral contact pressures and osteochondral microtrauma during anterior cruciate ligament rupture due to excessive compressive loading and internal torque of the human knee. Am J Sports Med 2008; 36 (10): 1966-77 51. Meyer EG, Haut RC. Excessive compression of the human tibio-femoral joint causes ACL rupture. J Biomech 2005; 38 (11): 2311-6 52. Meyer EG, Haut RC. Anterior cruciate ligament injury induced by internal tibial torsion or tibiofemoral compression. J Biomech 2008; 41 (16): 3377-83 53. Schenck Jr RC, Kovach IS, Argarwal A, et al. Cruciate injury patterns in knee hyperextension: a cadaveric model. Arthroscopy 1999; 15 (5): 489-95 54. Quatman CE, Quatman CC, Hewett TE. Prediction and prevention of musculoskeletal injuries: a paradigm shift in methodology. Br J Sports Med 2009; 43 (14): 1100-7 55. Orchard J, Seward H, McGivern J, et al. Intrinsic and extrinsic risk factors for anterior cruciate ligament injury in Australian footballers. Am J Sports Med 2001; 29 (2): 196-200 56. Gray J, Taunton JE, McKenzie DC, et al. A survey of injuries to the anterior cruciate ligament of the knee in female basketball players. Int J Sports Med 1985; 6 (6): 314-6 57. Binfield PM, Maffulli N, King JB. Patterns of meniscal tears associated with anterior cruciate ligament lesions in athletes. Injury 1993; 24 (8): 557-61 58. Cerabona F, Sherman MF, Bonamo JR, et al. Patterns of meniscal injury with acute anterior cruciate ligament tears. Am J Sports Med 1988; 16 (6): 603-9 59. Daniel DM, Malcom LL, Losse G, et al. Instrumented measurement of anterior laxity of the knee. J Bone Joint Surg 1985; 67A (5): 720-6
Sports Med 2010; 40 (9)
ACL Injury Mechanisms
60. Benvenuti JF, Vallotton JA, Leyvraz PF. Objective assessment of the anterior tibial translation in Lachman test position: comparison between three types of measurement. Knee Surg Sports Traumatol Arthrosc 1998; 6 (4): 215-9 61. Stijak L, Herzog RF, Schai P. Is there an influence of the tibial slope of the lateral condyle on the ACL lesion? A case-control study. Knee Surg Sports Traumatol Arthrosc 2008; 16 (2): 112-7 62. Bach Jr BR, Warren RF, Flynn WM, et al. Arthrometric evaluation of knees that have a torn anterior cruciate ligament. J Bone Joint Surg Am 1990; 72 (9): 1299-306 63. Uhorchak JM, Scoville CR, Williams GN, et al. Risk factors associated with noncontact injury of the anterior cruciate ligament: a prospective four-year evaluation of 859 West Point cadets. Am J Sports Med 2003; 31 (6): 831-42 64. Ford KR, Myer GD, Hewett TE. Valgus knee motion during landing in high school female and male basketball players. Med Sci Sports Exerc 2003; 35 (10): 1745-50 65. Ford KR, Myer GD, Smith RL, et al. A comparison of dynamic coronal plane excursion between matched male and female athletes when performing single leg landings. Clin Biomech 2006; 21 (1): 33-40 66. Padua DA, Marshall SW, Beutler AI, et al. Predictors of knee valgus angle during a jump-landing task [abstract]. Med Sci Sports Exerc 2005; 37 (5): S398 67. McLean SG, Huang X, van den Bogert AJ. Association between lower extremity posture at contact and peak knee valgus moment during sidestepping: implications for ACL injury. Clin Biomech (Bristol, Avon) 2005; 20 (8): 863-70 68. McLean SG, Neal RJ, Myers PT, et al. Knee joint kinematics during the sidestep cutting maneuver: potential for injury in women. Med Sci Sports Exerc 1999; 31 (7): 959-68 69. Draganich LF, Vahey JW. An in vitro study of anterior cruciate ligament strain induced by quadriceps and hamstrings forces. J Orthop Res 1990; 8 (1): 57-63 70. Withrow TJ, Huston LJ, Wojtys EM, et al. The relationship between quadriceps muscle force, knee flexion, and anterior cruciate ligament strain in an in vitro simulated jump landing. Am J Sports Med 2006; 34 (2): 269-74 71. Miyasaka T, Matsumoto H, Suda Y, et al. Coordination of the anterior and posterior cruciate ligaments in constraining the varus-valgus and internal-external rotatory instability of the knee. J Orthop Sci 2002; 7 (3): 348-53 72. Markolf KL, Gorek JF, Kabo JM, et al. Direct measurement of resultant forces in the anterior cruciate ligament. An in vitro study performed with a new experimental technique. J Bone Joint Surg Am 1990 Apr; 72 (4): 557-67 73. Withrow TJ, Huston LJ, Wojtys EM, et al. The effect of an impulsive knee valgus moment on in vitro relative ACL strain during a simulated jump landing. Clin Biomech (Bristol, Avon) 2006; 21 (9): 977-83 74. Matsumoto H, Suda Y, Otani T, et al. Roles of the anterior cruciate ligament and the medial collateral ligament in preventing valgus instability. J Orthop Sci 2001; 6 (1): 28-32 75. Woo SL, Hollis JM, Adams DJ, et al. Tensile properties of the human femur-anterior cruciate ligament-tibia complex: the effects of specimen age and orientation. Am J Sport Med 1991; 19 (3): 217-27
ª 2010 Adis Data Information BV. All rights reserved.
745
76. Berns GS, Hull ML, Patterson HA. Strain in the anteromedial bundle of the anterior cruciate ligament under combination loading. J Orthop Res 1992; 10 (2): 167-76 77. Gardiner JC, Weiss JA. Subject-specific finite element analysis of the human medical collateral ligament during valgus knee loading. J Orthop Res 2003; 21 (6): 1098-106 78. Moglo KE, Shirazi-Adl A. On the coupling between anterior and posterior cruciate ligaments, and knee joint response under anterior femoral drawer in flexion: a finite element study. Clin Biomech (Bristol, Avon) 2003; 18 (8): 751-9 79. Pena E, Calvo B, Martinez MA, et al. A three-dimensional finite element analysis of the combined behavior of ligaments and menisci in the healthy human knee joint. J Biomech 2006; 39 (9): 1686-701 80. Beillas P, Papaioannou G, Tashman S, et al. A new method to investigate in vivo knee behavior using a finite element model of the lower limb. J Biomech 2004; 37 (7): 1019-30 81. Blankevoort L, Huiskes R, de Lange A. Recruitment of knee joint ligaments. J Biomech Eng 1991; 113 (1): 94-103 82. Li G, Gil J, Kanamori A, et al. A validated three-dimensional computational model of a human knee joint. J Biomech Eng 1999; 121 (6): 657-62 83. Donahue TL, Hull ML, Rashid MM, et al. A finite element model of the human knee joint for the study of tibiofemoral contact. J Biomech Eng 2002; 124 (3): 273-80 84. Hirokawa S, Tsuruno R. Three-dimensional deformation and stress distribution in an analytical/computational model of the anterior cruciate ligament. J Biomech 2000; 33 (9): 1069-77 85. Gardiner JC, Weiss JA, Rosenberg TD. Strain in the human medial collateral ligament during valgus loading of the knee. Clin Orthop Relat Res 2001; (391): 266-74 86. Butler DL, Noyes FR, Grood ES. Ligamentous restraints to anterior-posterior drawer in the human knee: a biomechanical study. J Bone Joint Surg Am 1980; 62 (2): 259-70 87. Fukubayashi T, Torzilli PA, Sherman MF, et al. An in vitro biomechanical evaluation of anterior-posterior motion of the knee: tibial displacement, rotation, and torque. J Bone Joint Surg Am 1982; 64 (2): 258-64 88. Pandy MG, Shelburne KB. Dependence of cruciate-ligament loading on muscle forces and external load. J Biomech 1997; 30 (10): 1015-24 89. Sell TC, Ferris CM, Abt JP, et al. Predictors of proximal tibia anterior shear force during a vertical stop-jump. J Orthop Res 2007; 25 (12): 1589-97 90. Markolf KL, Burchfield DM, Shapiro MM, et al. Combined knee loading states that generate high anterior cruciate ligament forces. J Orthop Res 1995; 13 (6): 930-5 91. Yu B, Lin CF, Garrett WE. Lower extremity biomechanics during the landing of a stop-jump task. Clin Biomech (Bristol, Avon) 2006; 21 (3): 297-305 92. Li G, Rudy TW, Sakane M, et al. The importance of quadriceps and hamstring muscle loading on knee kinematics and in-situ forces in the ACL. J Biomech 1999; 32 (4): 395-400 93. Speer KP, Spritzer CE, Bassett 3rd FH, et al. Osseous injury associated with acute tears of the anterior cruciate ligament. Am J Sports Med 1992; 20 (4): 382-9
Sports Med 2010; 40 (9)
746
94. Mink JH, Deutsch AL. Occult cartilage and bone injuries of the knee: detection, classification, and assessment with MR imaging. Radiology 1989; 170 (3 Pt 1): 823-9 95. Fleming BC, Renstrom PA, Beynnon BD, et al. The effect of weightbearing and external loading on anterior cruicate ligament strain. J Biomech 2001; 34: 163-70 96. Beynnon BD, Fleming BC, Johnson RJ, et al. Anterior cruciate ligament strain behavior during rehabilitation exercises in vivo. Am J Sports Med 1995; 23 (1): 24-34 97. Beynnon BD, Johnson RJ, Fleming BC, et al. The strain behavior of the anterior cruciate ligament during squatting and active flexion-extension: a comparison of an open and a closed kinetic chain exercise. Am J Sports Med 1997; 25 (6): 823-9 98. Durselen L, Claes L, Kiefer H. The influence of muscle forces and external loads on cruciate ligament strain. Am J Sports Med 1995; 23 (1): 129-36 99. Chappell JD, Yu B, Kirkendall DT, et al. A comparison of knee kinetics between male and female recreational athletes in stop-jump tasks. Am J Sports Med 2002; 30 (2): 261-7 100. Chappell JD, Creighton RA, Giuliani C, et al. Kinematics and electromyography of landing preparation in vertical stop-jump: risks for noncontact anterior cruciate ligament injury. Am J Sports Med 2007; 35 (2): 235-41 101. Malinzak RA, Colby SM, Kirkendall DT, et al. A comparison of knee joint motion patterns between men and women in selected athletic tasks. Clin Biomech 2001; 16 (5): 438-45 102. Hewett TE, Stroupe AL, Nance TA, et al. Plyometric training in female athletes: decreased impact forces and increased hamstring torques. Am J Sports Med 1996; 24 (6): 765-73 103. White KK, Lee SS, Cutuk A, et al. EMG power spectra of intercollegiate athletes and anterior cruciate ligament injury risk in females. Med Sci Sports Exerc 2003; 35 (3): 371-6 104. Ford KR, Myer GD, Toms HE, et al. Gender differences in the kinematics of unanticipated cutting in young athletes. Med Sci Sports 2005; 37 (1): 124-9 105. Fagenbaum R, Darling WG. Jump landing strategies in male and female college athletes and the implications of such strategies for anterior cruciate ligament injury. Am J Sports Med 2003; 31 (2): 233-40 106. Pollard CD, Davis IM, Hamill J. Influence of gender on hip and knee mechanics during a randomly cued cutting maneuver. Clin Biomech 2004; 19 (10): 1022-31 107. Hewett TE, Myer GD, Ford KR, et al. Biomechanical measures of neuromuscular control and valgus loading of the knee predict anterior cruciate ligament injury risk in female athletes: a prospective study. Am J Sports Med 2005; 33 (4): 492-501 108. Shin CS, Chaudhari AM, Andriacchi TP. The influence of deceleration forces on ACL strain during single-leg landing: a simulation study. J Biomech 2007; 40 (5): 1145-52 109. Imran A, O’Connor JJ. Theoretical estimates of cruciate ligament forces: effects of tibial surface geometry and ligament orientations. Proc Inst Mech Eng [H] 1997; 211 (6): 425-39
ª 2010 Adis Data Information BV. All rights reserved.
Quatman et al.
110. Mesfar W, Shirazi-Adl A. Knee joint mechanics under quadriceps–hamstrings muscle forces are influenced by tibial restraint. Clin Biomech (Bristol, Avon) 2006; 21 (8): 841-8 111. Aune AK, Cawley PW, Ekeland A. Quadriceps muscle contraction protects the anterior cruciate ligament during anterior tibial translation. Am J Sports Med 1997; 25 (2): 187-90 112. Pflum MA, Shelburne KB, Torry MR, et al. Model prediction of anterior cruciate ligament force during droplandings. Med Sci Sports Exerc 2004; 36 (11): 1949-58 113. Wascher DC, Markolf KL, Shapiro MS, et al. Direct in vitro measurement of forces in the cruciate ligaments. Part I: The effect of multiplane loading in the intact knee. J Bone Joint Surg Am 1993; 75 (3): 377-86 114. Hewett TE, Myer GD, Ford KR. Decrease in neuromuscular control about the knee with maturation in female athletes. J Bone Joint Surg Am 2004; 86-A (8): 1601-8 115. Kaplan PA, Walker CW, Kilcoyne RF, et al. Occult fracture patterns of the knee associated with anterior cruciate ligament tears: assessment with MR imaging. Radiology 1992; 183 (3): 835-8 116. Viskontas DG, Giuffre BM, Duggal N, et al. Bone bruises associated with ACL rupture: correlation with injury mechanism. Am J Sports Med 2008; 36 (5): 927-33 117. LaPrade RF, Wentorf FA, Fritts H, et al. A prospective magnetic resonance imaging study of the incidence of posterolateral and multiple ligament injuries in acute knee injuries presenting with a hemarthrosis. Arthroscopy 2007; 23 (12): 1341-7 118. Paulos LE, France EP, Rosenberg TD, et al. The biomechanics of lateral knee bracing. Part I: response of the valgus restraints to loading. Am J Sports Med 1987; 15 (5): 419-29 119. Mahfouz MR, Komistek RD, Dennis DA, et al. In vivo assessment of the kinematics in normal and anterior cruciate ligament-deficient knees. J Bone Joint Surg Am 2004; 86-A Suppl. 2: 56-61 120. Shimokochi Y, Shultz SJ. Mechanisms of noncontact anterior cruciate ligament injury. J Athl Train 2008; 43 (4): 396-408 121. Benjaminse A, Gokeler A, van der Schans CP. Clinical diagnosis of an anterior cruciate ligament rupture: a metaanalysis. J Orthop Sports Phys Ther 2006; 36 (5): 267-88 122. Kostogiannis I, Ageberg E, Neuman P, et al. Clinically assessed knee joint laxity as a predictor for reconstruction after an anterior cruciate ligament injury: a prospective study of 100 patients treated with activity modification and rehabilitation. Am J Sports Med 2008; 36 (8): 1528-33 123. Fung DT, Zhang LQ. Modeling of ACL impingement against the intercondylar notch. Clin Biomech (Bristol, Avon) 2003; 18 (10): 933-41
Correspondence: Dr Timothy E. Hewett, PhD, Cincinnati Children’s Hospital, 3333 Burnet Avenue, MLC 10001, Cincinnati, OH 45229, USA. E-mail:
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Sports Med 2010; 40 (9)
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REVIEW ARTICLE
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Carbohydrate Administration and Exercise Performance What Are the Potential Mechanisms Involved? Antony D. Karelis,1 JohnEric W. Smith,2 Dennis H. Passe3 and Francois Pe´ronnet4 1 2 3 4
Department of Kinesiology, Universite´ du Que´bec a` Montre´al, Montreal, Quebec, Canada Gatorade Sports Science Institute, Barrington, Illinois, USA Scout Consulting, LLC, Hebron, Illinois, USA Department of Kinesiology, Universite´ de Montre´al, Montreal, Quebec, Canada
Contents Abstract. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1. Carbohydrate (CHO) Administration and Central Fatigue during Exercise . . . . . . . . . . . . . . . . . . . . . . 1.1 Central Fatigue and Tryptophan . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.2 Hypoglycaemia and Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.3 Cognition and Performance. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1.4 Mouth Rinsing with CHO and Performance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2. Blood Glucose Oxidation and CHO Administration during Exercise: Effect on Performance . . . . . . . 3. Effects of CHO Administration on Muscle Glycogen Metabolism during Exercise. . . . . . . . . . . . . . . . . 4. Effects of CHO Administration on Muscle Metabolite Levels during Exercise. . . . . . . . . . . . . . . . . . . . . 5. Exercise-Induced Strain: Effect of CHO Ingestion . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6. CHO Administration and Excitation-Contraction Coupling during Exercise. . . . . . . . . . . . . . . . . . . . . . 7. Conclusions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Abstract
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It is well established that carbohydrate (CHO) administration increases performance during prolonged exercise in humans and animals. The mechanism(s), which could mediate the improvement in exercise performance associated with CHO administration, however, remain(s) unclear. This review focuses on possible underlying mechanisms that could explain the increase in exercise performance observed with the administration of CHO during prolonged muscle contractions in humans and animals. The beneficial effect of CHO ingestion on performance during prolonged exercise could be due to several factors including (i) an attenuation in central fatigue; (ii) a better maintenance of CHO oxidation rates; (iii) muscle glycogen sparing; (iv) changes in muscle metabolite levels; (v) reduced exercise-induced strain; and (vi) a better maintenance of excitation-contraction coupling. In general, the literature indicates that CHO ingestion during exercise does not reduce the utilization of muscle glycogen. In addition, data from a meta-analysis suggest that a dose-dependent relationship was not shown between CHO ingestion during exercise and an increase in performance. This could support the idea that providing enough CHO to maintain CHO oxidation during exercise may
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not always be associated with an increase in performance. Emerging evidence from the literature shows that increasing neural drive and attenuating central fatigue may play an important role in increasing performance during exercise with CHO supplementation. In addition, CHO administration during exercise appears to provide protection from disrupted cell homeostasis/integrity, which could translate into better muscle function and an increase in performance. Finally, it appears that during prolonged exercise when the ability of metabolism to match energy demand is exceeded, adjustments seem to be made in the activity of the Na+/K+ pump. Therefore, muscle fatigue could be acting as a protective mechanism during prolonged contractions. This could be alleviated when CHO is administered resulting in the better maintenance of the electrical properties of the muscle fibre membrane. The mechanism(s) by which CHO administration increases performance during prolonged exercise is(are) complex, likely involving multiple factors acting at numerous cellular sites. In addition, due to the large variation in types of exercise, durations, intensities, feeding schedules and CHO types it is difficult to assess if the mechanism(s) that could explain the increase in performance with CHO administration during exercise is(are) similar in different situations. Experiments concerning the identification of potential mechanism(s) by which performance is increased with CHO administration during exercise will add to our understanding of the mechanism(s) of muscle/central fatigue. This knowledge could have significant implications for improving exercise performance.
It is well established that carbohydrate (CHO) administration increases performance during prolonged exercise in humans[1-4] and animals.[5-7] For example, Coyle et al.[8] showed that the ingestion of a glucose polymer (1.8 g/min) increased exercise time from 3.02 to 4.02 hours during cycling . ). Exat 71% maximum oxygen uptake ( VO 2max . ercise time at 69% VO2max was shown by McConell et al.[9] to increase from 152 to 199 minutes with the ingestion of 285 g of CHO. Furthermore, Mitchell et al.[10] observed that the ingestion of CHO significantly increased the amount of work performed (1.98 – 0.09 vs 1.83 – 0.11 Nm · 105) in four trials of. intermittent (7 · 12 min bout) cycling at 70% VO2max. In addition to these improvements in endurance performance, the ability to perform resistance exercise has also been shown to increase when CHO is administered.[11] Lambert[12] showed that the total number of sets and repetitions tended to increase when subjects ingested 125 g of CHO while performing leg extensions at 80% of the previously determined ten repetition maximums, with 3 minutes of rest between sets. In another study by Haff et al.,[13] ª 2010 Adis Data Information BV. All rights reserved.
subjects were required to perform 16 sets of ten repetitions of leg extension/flexions at 120/s on a Cybex isokinetic dynamometer, with 3 minutes of rest between sets with and without CHO ingestion. Results show that total work performed significantly increased from 38.1 to 41.1 kJ when subjects ingested 240 g of CHO. However, two other studies reported that CHO supplementation does not improve the performance of resistance exercise.[14,15] We performed a meta-analysis of the literature that assessed the effect of CHO administration on endurance performance and capacity. For the purpose of this review, we define endurance performance as a sub-maximal exercise lasting 30 minutes or more requiring the completion of a given amount of work, task or a given distance as fast as possible or continued to exhaustion. A PubMed database search was initially conducted using the terms: carbohydrate and performance OR carbohydrate and cycling OR carbohydrate and running. Examination of reference lists from articles and review papers identified through the database further refined the search. Inclusion Sports Med 2010; 40 (9)
Carbohydrate Administration and Performance
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Fig. 1. Performance effect of carbohydrate administration by category in the 72 compiled studies. Means of moderator variables that are not overlapped by their respective 95% confidence intervals are significantly different from each other at the 95% level. The number above each point represents the number of individual comparisons that are included into each category.
criteria requirements were that the study had to have a placebo or water control, there had to be a CHO treatment and CHO had to be consumed during exercise. As a result, a total of 72 studies[8,10,16-85] involving 1117 subjects and 112 comparisons were identified for inclusion in this analysis. Dependent measures included percentage change in the Loughborough Soccer Passing Test (LSPT) score, percentage change in the Loughborough Soccer Shooting Test (LSST) score, distance covered in time, time of performance rides, time to complete revolutions, time to complete work, time to exhaustion, power output decrement, Wingate results and work completed in time. Effect sizes (performance effect) were calculated as standardized mean differences relative to their pooled standard deviations, weighted as a function of the inverse within-group variation, and were adjusted for the correlation between pre- and post-ingestion measurements.[86] A randomized model was chosen and a correction for small-sample bias (Hedges’s g) was implemented. Effect size direction was deemed positive if performance improved from the control to the CHO condition and was deemed negative if performance decreased from the control to the CHO condition. Calculations were made using the Comprehensive Meta-Analysis V. 2.2.048 software package (Biostat, Englewood, ª 2010 Adis Data Information BV. All rights reserved.
NJ, USA). Results are presented with 95% confidence intervals (CI). The effects of various moderator variables on the change in performance with CHO administration are presented in figure 1. Means of moderator variables that are not overlapped by their respective 95% CI are significantly different from each other at the 95% level. The scale proposed by Cohen[87] (small [0.2], medium [0.5] or large [0.8]) may be used as a starting point for interpreting the results. We confirmed that a significant performance effect was observed in the total data set when CHO are ingested during exercise. Interestingly, the mean performance effect in studies with a more than 2-hour exercise duration was significantly greater than in studies with a less than 2-hour exercise duration. No other significant differences in performance effect were observed between moderator variables. Most of the performance effects in figure 1 approach the medium level in Cohen’s nomenclature, which corresponds to effect sizes ‘‘visible to the naked eye.’’[87] Moreover, based on the examination of studies with exercise time ranging between about 30 and 60 minutes, it seems that the beneficial effect of CHO administration on performance may occur when exercise lasts for at least 40–50 minutes.[18,22,63,88,89] In the study of Bonen Sports Med 2010; 40 (9)
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et al.,[88] which was the shortest exercise period we found in the literature, ingestion of glucose (1.5 g/kg) immediately before or during exercise did not . increase cycling time to exhaustion at 80% VO2max (26.6 and 26.1 minutes, respectively, vs 29.9 minutes with the placebo). Similarly, Mitchell et al.[89] did not observe any change in the time required to run 10 km with ingestion of water (41.9 minutes), 0.9 g/min of glucose (41.7 minutes) or a glucose-sucrose mixture (41.8 minutes), and 1.2 g/min of a high-fructose corn syrup (41.7 minutes). In contrast, Anantaraman et al.[18] showed that during a 60-minute exercise period to exhaustion, when compared with the placebo (138 W), the power output sustained between minutes 40 and 60 was significantly higher with ingestion of glucose immediately before exercise (30 g) and with ingestion of glucose both before and during exercise (120 g) [~164 W in both situations]. In the study by Neufer et al.,[63] subjects . performed 45 minutes of exercise at 77% VO2max on a cycle ergometer, followed by a 15-minute exercise period in which they were requested to produce the maximal amount of work. When compared with the placebo (159 kJ), performance significantly increased with ingestion of 45 g of CHO 5 minutes before exercise (175 kJ). Finally, Ball et al.[22] showed that the performance on a Wingate anaerobic test following cycling at 80% . VO2max for 50 minutes with ingestion of CHO (0.9 g/min) was significantly higher than with ingestion of a placebo (i.e. mean power output = 700 vs 655 W). The increase in performance with CHO ingestion during exercise has been extensively reviewed and will not be further summarized or discussed in this review.[1-4] The mechanism(s), which could mediate improvements in exercise performance associated with CHO administration however, remain(s) unclear. This review of the literature focuses on possible underlying mechanisms that could explain the increase in performance observed with the administration of CHO during prolonged exercise or muscle contractions in humans and animals. The beneficial effect of CHO ingestion on performance during prolonged exercise could be due to several factors including (i) an attenuation in central fatigue; ª 2010 Adis Data Information BV. All rights reserved.
(ii) a better maintenance in CHO oxidation rates; (iii) muscle glycogen sparing; (iv) changes in muscle metabolite levels; (v) reduced exercise-induced strain; and (vi) a better maintenance of excitationcontraction coupling (table I). There is evidence to suggest that these six factors may be associated with fatigue.[90-92] In addition, these six factors may be related and involved in proper muscle function in order to produce muscle force and perform prolonged exercise.[90-92] Therefore, positive changes in one or several of these factors could lead to an increase in performance during prolonged exercise. It should be noted that other possible factors may also be involved that have yet to be identified or more fully described. For example, on a whole body level, the better muscle functioning during exercise with CHO administration may be associated with a better gross efficiency, which could translate into an increase in performance.[93] 1. Carbohydrate (CHO) Administration and Central Fatigue during Exercise 1.1 Central Fatigue and Tryptophan
Newsholme et al.[94] proposed the hypothesis that higher serotonin levels could potentially influence the development of central fatigue by affecting arousal and mood linked to altered Table I. Potential mechanisms that could explain the increase in performance with carbohydrate (CHO) administration during exercise Potential mechanisms
Effect of CHO administration during exercise
Glucose oxidation rates
›
Blood glucose levels
›
Utilization of muscle glycogen
fl2
Na+/K+ pump activity
›
Ca2+ cycling
2
Central fatigue
fl
Cognitive function
›
Heat shock proteins
fl
Immune system
fl
5-Adenosine monophosphateactivated protein kinase
fl2
Oxidative stress
fl2
2 indicates no change; fl indicates decreases; › indicates increases.
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Carbohydrate Administration and Performance
perceptions of effort and muscle fatigue. In support of this hypothesis, it has been shown that serotonin levels in the brain are increased during prolonged exercise in rats.[95] Since tryptophan is the precursor for the synthesis of serotonin, increased plasma levels of free tryptophan could increase cerebral tryptophan uptake and enhance serotonin production in the brain.[96] During prolonged exercise low levels of plasma insulin are observed, which favours the release of free fatty acids (FFA) from adipose tissue. This results in an increased plasma level of both FFA and free tryptophan, as FFA binds to albumin and displaces some of the albumin-bound tryptophan.[97] Glucose ingestion stimulates the secretion of insulin and blunts the exercise-induced rise in both plasma FFA and free tryptophan.[96] Therefore, this could counteract the development of central fatigue by attenuating the rise in brain serotonin. This hypothesis was tested in the study of Davis et al.[98] Their research showed that in the control situation, plasma free tryptophan increased by ~7-fold, when subjects performed . prolonged exercise for 200 minutes at 68% VO2max. This was associated with an increase in plasma FFA levels and reduced blood glucose levels from 5 to 4 mmol/L. When subjects ingested ~1 g/min of CHO, the blood glucose level was maintained at 5.5 mmol/L, and plasma free tryptophan as well as FFA was significantly attenuated and fatigue was delayed by ~1 hour. 1.2 Hypoglycaemia and Performance
Circulating glucose and lactate seem to be the two main energy sources for the central nervous system during exercise and a continuous supply may be essential for optimal function in activating skeletal muscle.[99,100] Accordingly, the findings of Koslowski et al.[101] support the idea that CHO availability for the brain may be important in maintaining an adequate neural drive to the muscles. Their study demonstrated that the infusion of glucose directly into the carotid artery (increasing central blood glucose level from 4 to 10 mmol/L and maintaining peripheral blood glucose level at 4.5 mmol/L) delayed fatigue in dogs exercising until exhaustion on a treadmill ª 2010 Adis Data Information BV. All rights reserved.
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with a slope of 12% and a speed ranging from 1.2 to 1.8 m/sec. Nybo[102] showed that the average force production during a sustained maximal muscle contraction .was decreased after 3 hours of exercise at 60% VO2max in endurance-trained subjects, in which blood glucose levels significantly decreased from 4.5 to 3 mmol/L after exercise. The reduced force development in this study was associated with a diminished activation drive from the CNS. This central fatigue was reversed when euglycaemia (4.5 mmol/L) was maintained with the ingestion of 200 g of CHO. In addition, it was easier for the subjects to retain power output at the end of prolonged exercise when hypoglycaemia was prevented. However, Felig et al.[38] showed that hypoglycaemia may not affect performance during prolonged exercise, and that a better maintenance of glucose levels appears not to consistently improve performance. They demonstrated a progressive decline in blood glucose levels and hypoglycaemia (blood glucose <2.5 mmol/L) when . water was ingested during exercise at 60–65% VO2max in 7 of 19 healthy men. The exhaustion time in the hypoglycaemic subjects (142 – 15 minutes) was not significantly different compared with those in the 12 subjects whose blood glucose levels remained above 2.5 mmol/L (165 – 11 minutes), despite blood glucose levels of 1.4–2.7 mmol/L. Furthermore, perceived exertion during exercise was not significantly greater in subjects who became hypoglycaemic. Finally, when subjects ingested 114 g of CHO during exercise, blood glucose levels at the end of exercise remained unchanged from values during the resting state (~4.5 mmol/L) and exhaustion time (171 – 14 minutes) was not significantly different from that observed with water ingestion (164 – 8 minutes). The authors concluded that glucose ingestion does not consistently delay exhaustion or alter the subjective sensation of exertion during exercise. These results are in line with those from other studies that also showed that a decline in blood glucose levels may not be associated with a decrease in exercise performance. Horowitz and Coyle[103] reported that the glycaemic index of a meal does not affect the sensation of fatigue or the ability to complete a 1-hour cycling trial at Sports Med 2010; 40 (9)
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. 50–70% VO2max despite having blood glucose levels as low as 2.2 mmol/L. Another study observed that hypoglycaemia in subjects with diabetes mellitus affected well-being and susceptibility to fatigue; however, it had no effect on exercise performance.[104] Finally, the study of Claassen et al.[105] showed that hypoglycaemia might not consistently decrease exercise performance in all trained subjects that.performed up to 150 minutes of cycling at 70% VO2max, after 48 hours on a low-CHO diet. These results suggest that hypoglycaemia may not necessarily be a mechanism of fatigue and that the better maintenance of blood glucose levels with the ingestion of glucose may not be a potential mechanism for improved performance during prolonged exercise. 1.3 Cognition and Performance
Several studies have examined the effect of prolonged exercise on cognitive performance with and without CHO administration.[82,106,107] For example, in the study of Collardeau et al.,[106] cognitive tasks were performed before and after a . 100-minute run at 64% VO2max. Blood glucose levels significantly increased from 5.2 to 5.6 mmol/L when subjects ingested 118 g of glucose during exercise, whereas when subjects ingested a placebo, blood glucose level decreased from 5.1 to 4.7 mmol/L. Immediately after exercise several cognitive tasks were performed. Results show a significant decrease of choice reaction time from 689 to 654 ms in the CHO group, whereas in the control group choice reaction time remained unchanged (688 ms vs 676 ms). Additionally, no significant differences in the rating of perceived exertion were observed in the CHO group, while the rating of perceived exertion significantly increased from 11 to 16 in the control group. These results suggest that glucose ingestion during exercise could increase cognitive function, but further research is needed to investigate if improvements in cognitive function could lead to an increase in exercise performance. 1.4 Mouth Rinsing with CHO and Performance
Three interesting studies have shown that rinsing the mouth with a CHO solution increased ª 2010 Adis Data Information BV. All rights reserved.
performance compared with water during a 1-hour time trial.[108-110] Carter et al.[108] observed that rinsing the mouth with a CHO solution during a 1-hour cycle time trial significantly improved performance time compared with the control (59.57 – 1.50 vs 61.37 – 1.56 minutes, respectively). The authors suggested that this increase in performance may be due to CHO receptors in the oral cavity that could increase the central neural drive associated with motivation. Similarly, using functional MRI, Chambers et al.[109] concluded that the increase in performance during a 1-hour cycle time trial with rinsing of the mouth with CHO may be due to the activation of certain brain regions believed to be involved in reward and motor control. Based on the present evidence, maintaining an adequate central neural drive to the muscles appears to be an important mechanism that could explain the better muscle function and an increase in performance with CHO supplementation during prolonged exercise. 2. Blood Glucose Oxidation and CHO Administration during Exercise: Effect on Performance Coyle and Coggan[8,30,111] hypothesized that a better maintenance of CHO oxidation rates during prolonged exercise may explain the increase in performance with CHO administration. Therefore, in the 1980s, a series of studies was performed examining the importance of maintaining blood glucose oxidation during exercise. In these studies, CHO ingestion delayed fatigue by 30–60 minutes and this was associated with a better maintenance of a high rate of CHO oxidation at a time when muscle glycogen levels were low. These experiments consisted of performing . bicycle exercise between 70% and 74% VO2max with and without CHO administration. In one of these studies, Coyle et al.[8] showed that in the control group the rate of total CHO oxidation (2.0 g/min at the start of exercise) was significantly reduced at fatigue (1.2 g/min). In contrast, when large amounts of CHO were ingested (432 g) over 4 hours, the rate of total CHO oxidation was maintained (2.0 g/min). It should be Sports Med 2010; 40 (9)
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noted that in these studies it is not clear what induced fatigue in the CHO group, since plasma glucose and CHO oxidation rates remained unchanged throughout exercise. This could suggest that a better maintenance of plasma glucose levels and/or oxidation rates may not be responsible for delaying fatigue and that other mechanisms could be involved. Several studies have reported that the increase in exercise performance with CHO administration was not associated with a higher rate of CHO oxidation.[36,47,112] For example, a recent study[112] showed that the ingestion of glucose plus fructose (1.8 g/min) significantly increased power output by 8% compared with glucose alone (1.8 g/min) during a time trial exercise. In that study, no significant differences in CHO oxidation rates (glucose plus fructose 2.54 vs glucose 2.50 g/min) between the two groups were observed. The authors suggested that the increase in performance could not be due to a better maintenance of CHO oxidation rates. In addition to these observations, several studies have failed to report a dose-dependent relationship between the amounts of CHO ingested and exercise performance.[60-62] For example, Murray et al.[61] showed that exercise performance was not significantly different between CHO groups when glucose was provided at different doses of 26, 52 and 78 g/h during 2 hours of cycling. The compilation of data from 72 studies[8,10,16-85] that examined the effect of CHO ingestion on performance during prolonged exercise (figure 2) shows no significant correlation between the amount of 6.0
Performance effect
5.0 4.0 3.0 2.0 1.0 0 −1.0
0
50
100
150
200
250
300
−2.0 CHO intake (g/h) Fig. 2. Relationship between carbohydrate (CHO) intake and performance (r2 = 3 · 10-7; p = not significant) in the 72 compiled studies.
ª 2010 Adis Data Information BV. All rights reserved.
CHO ingested and the change in performance. This could further suggest that a dose-dependent relationship may not necessarily exist between CHO ingestion during exercise and an increase in performance; however, caution needs to be taken because of the fact that many different types of CHO and feeding regimens were included in the analysis. 3. Effects of CHO Administration on Muscle Glycogen Metabolism during Exercise Fatigue during prolonged exercise often coincides with low muscle glycogen content, and endurance performance could be improved by increasing initial muscle glycogen stores (see review by Conlee[113]). Therefore, it has been hypothesized that the administration of CHO during exercise could slow the rate of muscle glycogenolysis.[114] This possibility was first raised by the experiments of Bergstrom and Hultman[115] who reported that the intravenous infusion of glucose at up to 3.5 g/min ([glucose] = 21 mmol/L) decreased net muscle glycogen degradation by ~20% while performing stationary cycling exercise at a workload of 950 kpm/min for 60 minutes. In addition, muscle glycogen sparing has also been observed in exercising rats when glucose was infused during prolonged running at a moderate intensity.[6] In that study, rats were infused intravenously with either saline or glucose (1.6 g kg-1 h-1) [(glucose) = 7.8 mmol/L] during exercise on a treadmill at 21 m/min with a 10% grade. Time to exhaustion was significantly increased in rats infused with glucose compared with control (225 vs 164 minutes, respectively). These studies support the hypothesis that CHO ingestion during exercise improves performance by slowing the rate of muscle glycogen degradation. However, in general, the literature indicates that CHO ingestion during continuous moderate-intensity exercise does not reduce the utilization of muscle glycogen.[8,39,58,116-123] Coyle et al.[8] reported no significant differences in glycogen utilization in the vastus lateralis. before and after 105 minutes of cycling at 71% VO2max with and without CHO ingestion. The authors in that study obtained Sports Med 2010; 40 (9)
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muscle biopsies . at rest, after 120 minutes of exercise at 71% VO2max and at fatigue from another group of cyclists who either ingested CHO or did not. Results showed that exercise performance was significantly increased in the CHO group compared with the control group (241 – 20 vs 181 – 11 minutes, respectively). However, muscle glycogen utilization during exercise was similar in both groups. Chryssanthopoulos et al.[117] showed that ingesting a CHO. meal 3 hours before treadmill running at 70% VO2max does not influence muscle glycogen degradation. Arkinstall et al.[116] also reported that the ingestion of CHO (63.6 g) did not attenuate muscle glycogen utilization during 60 minutes of continuous submaximal running or cycling. Finally, few authors have observed no change in muscle glycogen degradation with CHO administration during exercise in rats.[7,124] Nevertheless, several authors have reported reductions in muscle glycogen utilization ranging from 20% to 28% with CHO administration during exercise.[75,125-128] Hargreaves et al.[125] observed that muscle glycogen utilization was ~26% lower in subjects who ingested 172 g of sucrose during 4 hours of moderate prolonged exercise. Similar results were reported by Bjorkman et al.[24] when subjects ingested 212 g of glucose during prolonged exercise. In another study, Tsintzas et al.[127] investigated the effect of CHO ingestion on muscle. glycogen utilization during running at 70% VO2max. In that study, preexercise glycogen levels (350 mmol/kg dm) and the duration of exercise (60 minutes) were kept the same. As a result of ingesting 50 g of CHO in a 5.5% solution, a 28% sparing of glycogen in the vastus lateralis muscle was observed. This glycogen sparing was accompanied by an increase in blood glucose levels. Glycogen determination in type I and type II muscle fibres revealed that the ingestion of the CHO solution resulted in a 42% sparing of glycogen in type I fibres only, whereas in type II fibres no significant differences were observed. It is widely accepted that muscle glycogen sparing as well as the better maintenance of blood glucose levels and the increase in CHO oxidation rates during exercise with CHO ingestion are ª 2010 Adis Data Information BV. All rights reserved.
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associated with an increase in performance. However, it should be recognized that muscle glycogen sparing as well as the better maintenance of blood glucose levels and the increase in CHO oxidation rates during exercise with CHO ingestion are not mechanisms per se that could explain how the muscle can either sustain or develop more force during exercise and thus increase performance. They are merely corresponding observations. A possible mechanism linking muscle glycogen availability and exercise performance could be Ca2+ handling. Several studies have shown that glycogen depletion is closely associated with a decrease in muscle force and Ca2+ release during prolonged contractions in isolated muscle fibres.[129,130] However, since several studies have observed no differences in glycogen utilization during exercise with or without CHO administration, a better maintenance of Ca2+ release may not be an explanation for the increase in muscle performance with CHO administration during exercise. Moreover, studies using skinned muscle fibres reported that the failure in Ca2+ release with glycogen depletion appears not to be due to changes in the membrane potential or adenosine triphosphate (ATP) or phosphocreatine (PCr) levels.[131,132] 4. Effects of CHO Administration on Muscle Metabolite Levels during Exercise It has been suggested that impairments of metabolite at the cellular level could be implicated in the development of muscle fatigue.[133] This hypothesis was supported by the findings that muscle contraction and fatigue could be associated with changes in metabolite levels in the muscle such as ATP, inosine monophosphate (IMP), inorganic phosphate (Pi) and PCr.[133] It should also be noted that Pi, which increases during exercise due to breakdown of PCr, appears to play a major role in the development of muscle fatigue.[134] There is evidence to suggest that Ca2+ release from the sarcoplasmic reticulum (SR) may be decreased if Pi enters the SR and precipitates with Ca2+ leading to lower muscle force production.[135] The beneficial effect of CHO administration on muscle performance during exercise could, Sports Med 2010; 40 (9)
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Table II. Differences in adenosine triphosphate (ATP), phosphocreatine (PCr), inosine monophosphate (IMP) and inorganic phosphate (Pi) content during exercise with or without the ingestion of carbohydrate (CHO) Study (year)
ATP
PCr
IMP
Pi
Tsintzas et al.[75] (1996)
No difference between groups
No difference between groups
Data not available
Data not available
Tsintzas et al.[128] (2001)
No difference between groups
Significantly higher in CHO group
Data not available
Data not available
Duhamel et al.[139] (2007)
No difference between groups
No difference between groups
No difference between groups
No difference between groups
Snow et al.[137] (2000)
No difference between groups
Significantly higher in CHO group at min 30 only
No difference between groups
Data not available
Spencer et al.[138] (1991)
No difference between groups
No difference between groups
Significantly lower in CHO group
Data not available
McConnel et al.[9] (1999)
No difference between groups
No difference between groups
Significantly lower in CHO group
Data not available
Lewis and Haller[136] (1986)
No difference between groups
Significantly higher in CHO group
Data not available
Significantly lower in CHO group
thus, be associated with changes in metabolite levels in the muscle fibre.[9,75,128,136-139] Table II shows seven studies that examined the effect of CHO ingestion on muscle metabolites during prolonged exercise. In all seven studies, ATP levels were not significantly modified during exercise and no significant difference in ATP levels were observed between the control and CHO groups. However, all seven studies showed significant reductions in PCr levels after exercise and three of the studies reported that PCr levels were higher when CHO are ingested during exercise.[128,136,137] For example, Tsintzas et al.[128] reported an increase in running performance with CHO ingestion and this was associated with a smaller decline of PCr levels by 46 – 17% in type I fibres and by 36 – 9% in type II fibres. Four[9,137-139] of the seven studies measured IMP levels, in which significant increases were observed during exercise. Two studies showed no significant difference between the control and CHO group,[137,139] whereas two studies reported that IMP levels were lower when CHO are ingested during exercise.[9,138] McConell et al.[9] showed that the muscle IMP level at the point of fatigue was lower when CHO were ingested, despite the subjects exercising 30% longer during cycling at 69% . VO2max. Furthermore, Snow et al.[137] reported that CHO ingestion during exercise attenuated muscle ammonia accumulation. It appears that only one study examined the effect of CHO adª 2010 Adis Data Information BV. All rights reserved.
ministration on Pi levels during exercise, which was performed in subjects with McArdle’s disease.[136] In that study, lower levels of Pi were observed when glucose was infused during exercise. Additionally, Phillips et al.[140] examined different metabolic fuels (pyruvate, glucose, lactate) on force production in isolated mouse soleus and extensor digitorum longus (EDL) muscles during isometric tetanic contractions at 50 Hz (soleus) and 150 Hz (EDL). Results show that pyruvate administration (20 mmol/L) increased muscle performance in the soleus during isometric contractions, whereas glucose (11 mmol/L) or lactate (20 mmol/L) showed no significant effects. EDL muscles produced the same isometric force whether the metabolic fuel was glucose, pyruvate or lactate. The authors indicated that the increase in muscle performance in the soleus with pyruvate administration was due to a lowering of Pi by 17%. It has also been suggested that the cause of muscle fatigue could be due to an insufficient energy supply mediated either through a limited supply of substrate (acetyl-CoA) to the tricarboxylic acid cycle (TCA) or limitations in TCA activity due to reduced TCA intermediates (TCAI).[141,142] Based on this hypothesis, Spencer et al.[138] investigated the effect of CHO ingestion on . TCAI during prolonged exercise at 70% VO2max. Results from that study show that performance was increased with CHO ingestion Sports Med 2010; 40 (9)
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during prolonged exercise and this was associated with a higher content of TCAI. It should be noted that other studies have shown a decrease in TCAI during prolonged exercise; however, the authors in these studies indicated that this was not associated with a deterioration in aerobic energy provision or a mechanism of muscle fatigue.[143-145] In addition, modifying muscle glycogen levels did not affect TCAI pool expansion and the total adenine nucleotide pool (ATP plus adenosine diphosphate plus adenosine monophosphate [AMP]) nor PCr and IMP levels during prolonged exercise to fatigue.[143] Several studies have suggested that CHO ingestion during exercise could increase muscle performance, at least in part, by better maintaining oxidative ATP re-synthesis.[9,128,146] However, in all of these studies, no significant differences in oxygen consumption were observed during exercise between the CHO and control group.[9,128,146] Thus, the production of oxidative ATP during prolonged muscle contractions appears to be the same with or without CHO ingestion. 5. Exercise-Induced Strain: Effect of CHO Ingestion We cannot rule out other possible mechanisms that may also be involved in the beneficial effect of CHO administration on performance during exercise, such as a reduction in exercise-induced strain. Evidence in the literature suggests that CHO administration may be effective in reducing exercise-induced immune suppression,[147,148] decreasing oxidative stress[149,150] and heat shock proteins (Hsp)[151] as well as attenuating 5-AMPactivated protein kinase (AMPK).[152] The production of cytokines could be induced by specific stimuli such as physical exercise. It has been suggested that skeletal muscle during exercise increases the production/activity of several cytokines and this may be associated with an increase in central fatigue, which could affect the production of muscle force during exercise.[91] Recent studies have shown that CHO ingestion during exercise could reduce stress hormones and inflammatory cytokine response as well as diminished oxidative burst activity. For example, ª 2010 Adis Data Information BV. All rights reserved.
the study of Scharhag et al.[153] observed that CHO administration during prolonged exercise attenuated the exercise-induced immune and stress response as evidenced by lower levels of C-reactive protein, interleukin-6 and cortisol. Two studies showed that. CHO supplementation during exercise at 75% VO2max attenuated oxidative stress.[149,150] However, three other studies observed that CHO ingestion during exercise did not have an effect on the accumulation of oxidative stress.[154-156] Febbraio et al.[151] reported that glucose ingestion during exercise at 65% . VO2max attenuated the increase in circulating Hsp (i.e. Hsp72 and Hsp60). Glucose ingestion during exercise has also been shown to attenuate the exercise-induced response of AMPK activity in human skeletal muscle.[152] In contrast, another study indicated that CHO ingestion during exercise was not associated with any changes in AMPK activity in human skeletal muscle.[157] Collectively, CHO administration appears to provide protection from disrupted cell homeostasis/integrity, which could translate into better muscle function and an increase in performance during exercise. 6. CHO Administration and ExcitationContraction Coupling during Exercise An impairment of action potential propagation along the sarcolemma, and/or a possible failure of generating action potentials in some fibres as well as disturbances in the Na+/K+ pump and Ca2+ cycling properties may be possible mechanisms of muscle fatigue during exercise.[90,92] The electrical properties of the membrane largely depend on proper gradients of Na+ and K+, which are maintained by the activity of ATP-dependent Na+/K+ pumps.[158,159] CHO administration and the associated increase in plasma glucose levels could increase the activity of Na+/K+-adenosine triphosphatase (ATPase) and Na+/K+ pumps by providing glycolytic ATP, which appears to preferentially fuel membrane ion pumps in skeletal muscle.[160,161] Karelis et al.[162,163] showed that glucose infusion attenuates fatigue in rat plantaris and soleus muscle stimulated indirectly for 60 minutes in situ. A comparison between maximal Sports Med 2010; 40 (9)
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isometric force developed with indirect and massive direct muscle stimulation showed that the attenuation of fatigue with glucose infusion was not due to a better maintenance of the function of the neuromuscular junction. However, the attenuation of muscle fatigue was associated with a better maintenance of the electrical properties of the membrane of the muscle fibre as shown by the characteristics of M-wave (peak-to-peak amplitude, duration and total area).[162] This in turn could be due to the effect of glucose per se on ATP production in the vicinity of the Na+/K+ pump, and/or to the effect of insulin on the Na+/K+ pump since data from Clausen et al.[164] indicated that insulin could have a beneficial effect on muscle force by increasing the activity of Na+/K+-ATPase in the membrane of the muscle fibre. However, additional research by Karelis et al.[165] showed that the increase in insulin level was not responsible for the increase in muscle performance observed following the elevation of circulating glucose levels. In line with the previous observations, a recent study by Stewart et al.[166] showed that . glucose administration during exercise at 60% VO2max in untrained subjects protected muscle membrane excitability. The increase in muscle performance was associated with a better maintenance in membrane excitability as measured by M-wave characteristics (peak-to-peak amplitude and total area). In addition, Green et al.[167] reported that glucose supplementation during exercise at 57% . VO2max in untrained individuals increased maximal Na+/K+-ATPase activity, which could explain the better maintenance of the electrical properties of the muscle membrane fibre and increase performance. However, further studies are needed to examine the effect of CHO administration on Na+/K+-ATPase activity at various levels of exercise intensities. It has been shown that deterioration in action potential generation and/or propagation or in muscle excitability could be associated with a reduction in M-wave peak-to-peak amplitude,[168] which, in turn could be related to a decrease in resting membrane potential (RMP).[169,170] CHO administration and the associated increase in plasma glucose levels could attenuate the decrease ª 2010 Adis Data Information BV. All rights reserved.
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in RMP. Karelis et al.[171] reported that RMP was significantly decreased by ~8 mV in the control group immediately after a 60-minute period of stimulation in the rat plantaris muscle, whereas when glucose was infused, RMP was not significantly reduced at the end of the stimulation period. An alternate or complementary explanation for the increase in muscle performance with CHO administration during exercise could be a better maintenance of the Ca2+ pump in the SR, which may help attenuate muscle fatigue related to changes in Ca2+ handling since disturbances in Ca2+ cycling properties develop under prolonged exercise.[172] Xu et al.[173] showed that glycolytic ATP from infused glucose could also preferentially fuel the Ca2+ pump, which could lead to an increase in performance. However, a recent study from Duhamel et al.[139] showed that . glucose ingestion during exercise at 60% VO2max in untrained subjects did not affect SR Ca2+ handling compared with the control group. It should be noted that substantial changes in the action potentials or the M-wave characteristics could occur without affecting Ca2+ cycling properties,[90,92] which may explain the results of Duhamel et al.[139] Taken together, it appears that during prolonged exercise when the ability of metabolism to match energy demand is exceeded, adjustments seem to be made in the activity of the Na+/K+ pump. Therefore, muscle fatigue could be acting as a protective mechanism during prolonged contractions by reducing the activity of the Na+/K+ pump when energy demand is increased. This increased demand could be alleviated when CHO is administered, resulting in the better maintenance of the electrical properties of the muscle fibre membrane. It is apparent that muscle fatigue takes on the role of a ‘circuit breaker’ that may be essential for maintaining muscle viability. The data of Ortenblad and Stephenson[174] support this hypothesis by showing that a decrease in mitochondrial ATP-producing function with three different mitochondrial function antagonists, under conditions in which the cytosolic ATP was maintained high and constant, consistently decreased the excitability of rat fibres. The authors suggested that mitochondria may regulate muscle Sports Med 2010; 40 (9)
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cell function and have important implications for further understanding the differences between ATP utilization and ATP production during muscle contractions. This phenomenon seems to be involved, in particular, at the cellular level of skeletal muscle fibres. However, no data appear to be currently available on the effect of CHO administration on a possible change in mitochondrial ATP-producing function. 7. Conclusions There is only a rudimentary understanding as to the constellation of factors or mechanisms underlying fatigue. It should be clear that the mechanism by which CHO administration increases performance during prolonged exercise is complex, likely involving multiple factors acting at numerous cellular sites. In addition, due to the large variation in types of exercise, durations, intensities, feeding schedules and CHO types it is difficult to assess if the mechanism(s) that could explain the increase in performance with CHO administration during exercise is(are) similar in different protocols. Experiments concerning the identification of potential mechanism(s) by which performance is increased with CHO administration during exercise will add to our understanding of how muscle functions during exercise. Once it is possible to identify the cause(s) of this phenomenon, we may be able to broaden our understanding of the mechanism(s) of muscle/central fatigue. This knowledge could have significant implications for improving exercise performance. Acknowledgements JohnEric W. Smith is a research scientist for the Gatorade Company, a subsidiary of PepsiCo Inc. The authors have no conflicts of interest that are directly relevant to the content of this review.
References 1. Coggan AR, Coyle EF. Carbohydrate ingestion during prolonged exercise: effects on metabolism and performance. Exerc Sport Sci Rev 1991; 19: 1-40 2. Coombes JS, Hamilton KL. The effectiveness of commercially available sports drinks. Sports Med 2000 Mar; 29 (3): 181-209
ª 2010 Adis Data Information BV. All rights reserved.
3. el-Sayed MS, MacLaren D, Rattu AJ. Exogenous carbohydrate utilisation: effects on metabolism and exercise performance. Comp Biochem Physiol A Physiol 1997; 118 (3): 789-803 4. Jeukendrup AE. Carbohydrate intake during exercise and performance. Nutrition 2004 Jul-Aug; 20 (7-8): 669-77 5. Dill DB. Studies in muscular activity: factors limiting the capacity for work. J Physiol 1932; 77: 49-62 6. Bagby GJ, Green HJ, Katsuta S, et al. Glycogen depletion in exercising rats infused with glucose, lactate, or pyruvate. J Appl Physiol 1978; 45 (3): 425-9 7. Slentz CA, Davis JM, Settles DL, et al. Glucose feedings and exercise in rats: glycogen use, hormone responses, and performance. J Appl Physiol 1990; 69 (3): 989-94 8. Coyle EF, Coggan AR, Hemmert MK, et al. Muscle glycogen utilization during prolonged strenuous exercise when fed carbohydrate. J Appl Physiol 1986; 61 (1): 165-72 9. McConell G, Snow RJ, Proietto J, et al. Muscle metabolism during prolonged exercise in humans: influence of carbohydrate availability. J Appl Physiol 1999; 87 (3): 1083-6 10. Mitchell JB, Costill DL, Houmard JA, et al. Effects of carbohydrate ingestion on gastric emptying and exercise performance. Med Sci Sports Exerc 1988; 20 (2): 110-5 11. Haff GG, Lehmkuhl MJ, McCoy LB, et al. Carbohydrate supplementation and resistance training. J Strength Cond Res 2003; 17 (1): 187-96 12. Lambert C. Effects of carbohydrates feeding on multiplebout resistance exercise. J Appl Sport Science Res 1991; 5 (4): 192-7 13. Haff GG, Schroeder CA, Koch AJ, et al. The effects of supplemental carbohydrate ingestion on intermittent isokinetic leg exercise. J Sports Med Phys Fitness 2001; 41 (2): 216-22 14. Haff GG, Koch AJ, Potteiger JA, et al. Carbohydrate supplementation attenuates muscle glycogen loss during acute bouts of resistance exercise. Int J Sport Nutr Exerc Metab 2000 Sep; 10 (3): 326-39 15. Kulik JR, Touchberry CD, Kawamori N, et al. Supplemental carbohydrate ingestion does not improve performance of high-intensity resistance exercise. J Strength Cond Res 2008 Jul; 22 (4): 1101-7 16. Abbiss CR, Peiffer JJ, Peake JM, et al. Effect of carbohydrate ingestion and ambient temperature on muscle fatigue development in endurance-trained male cyclists. J Appl Physiol 2008 Apr; 104 (4): 1021-8 17. Ali A, Williams C, Nicholas CW, et al. The influence of carbohydrate-electrolyte ingestion on soccer skill performance. Med Sci Sports Exerc 2007 Nov; 39 (11): 1969-76 18. Anantaraman R, Carmines AA, Gaesser GA, et al. Effects of carbohydrate supplementation on performance during 1 hour of high-intensity exercise. Int J Sports Med 1995; 16 (7): 461-5 19. Andrews JL, Sedlock DA, Flynn MG, et al. Carbohydrate loading and supplementation in endurance-trained women runners. J Appl Physiol 2003 Aug; 95 (2): 584-90 20. Angus DJ, Hargreaves M, Dancey J, et al. Effect of carbohydrate or carbohydrate plus medium-chain triglyceride ingestion on cycling time trial performance. J Appl Physiol 2000; 88 (1): 113-9
Sports Med 2010; 40 (9)
Carbohydrate Administration and Performance
21. Bacharach DW, von Duvillard SP, Rundell KW, et al. Carbohydrate drinks and cycling performance. J Sports Med Phys Fitness 1994; 34 (2): 161-8 22. Ball TC, Headley SA, Vanderburgh PM, et al. Periodic carbohydrate replacement during 50 min of high-intensity cycling improves subsequent sprint performance. Int J Sport Nutr 1995; 5 (2): 151-8 23. Below PR, Mora-Rodriguez R, Gonzalez-Alonso J, et al. Fluid and carbohydrate ingestion independently improve performance during 1 h of intense exercise. Med Sci Sports Exerc 1995; 27 (2): 200-10 24. Bjorkman O, Sahlin K, Hagenfeldt L, et al. Influence of glucose and fructose ingestion on the capacity for longterm exercise in well-trained men. Clin Physiol 1984; 4 (6): 483-94 25. Brooke JD, Davies GJ, Green LF. The effects of normal and glucose syrup work diets on the performance of racing cyclists. J Sports Med Phys Fitness 1975; 15 (3): 257-65 26. Burgess WA, Davis JM, Bartoli WP, et al. Failure of low dose carbohydrate feeding to attenuate glucoregulatory hormone responses and improve endurance performance. Int J Sport Nutr 1991; 1 (4): 338-52 27. Carter J, Jeukendrup AE, Jones DA. The effect of sweetness on the efficacy of carbohydrate supplementation during exercise in the heat. Can J Appl Physiol 2005 Aug; 30 (4): 379-91 28. Coggan AR, Coyle EF. Effect of carbohydrate feedings during high-intensity exercise. J Appl Physiol 1988; 65 (4): 1703-9 29. Cole KJ, Grandjean PW, Sobszak RJ, et al. Effect of carbohydrate composition on fluid balance, gastric emptying, and exercise performance. Int J Sport Nutr 1993; 3 (4): 408-17 30. Coyle EF, Hagberg JM, Hurley BF, et al. Carbohydrate feeding during prolonged strenuous exercise can delay fatigue. J Appl Physiol 1983; 55 (1 Pt 1): 230-5 31. Davis JM, Burgess WA, Slentz CA, et al. Effects of ingesting 6% and 12% glucose/electrolyte beverages during prolonged intermittent cycling in the heat. Eur J Appl Physiol Occup Physiol 1988; 57 (5): 563-9 32. Davis JM, Jackson DA, Broadwell MS, et al. Carbohydrate drinks delay fatigue during intermittent, high-intensity cycling in active men and women. Int J Sport Nutr 1997; 7 (4): 261-73 33. Davis JM, Lamb DR, Pate RR, et al. Carbohydrate-electrolyte drinks: effects on endurance cycling in the heat. Am J Clin Nutr 1988; 48 (4): 1023-30 34. el-Sayed MS, Balmer J, Rattu AJ. Carbohydrate ingestion improves endurance performance during a 1 h simulated cycling time trial. J Sports Sci 1997; 15 (2): 223-30 35. el-Sayed MS, Rattu AJ, Roberts I. Effects of carbohydrate feeding before and during prolonged exercise on subsequent maximal exercise performance capacity. Int J Sport Nutr 1995; 5 (3): 215-24 36. Febbraio MA, Chiu A, Angus DJ, et al. Effects of carbohydrate ingestion before and during exercise on glucose kinetics and performance. J Appl Physiol 2000; 89 (6): 2220-6 37. Febbraio MA, Murton P, Selig SE, et al. Effect of CHO ingestion on exercise metabolism and performance in
ª 2010 Adis Data Information BV. All rights reserved.
759
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
48.
49.
50.
51.
52.
53.
54.
different ambient temperatures. Med Sci Sports Exerc 1996; 28 (11): 1380-7 Felig P, Cherif A, Minagawa A, et al. Hypoglycemia during prolonged exercise in normal men. N Engl J Med 1982; 306 (15): 895-900 Flynn MG, Costill DL, Hawley JA, et al. Influence of selected carbohydrate drinks on cycling performance and glycogen use. Med Sci Sports Exerc 1987; 19 (1): 37-40 Foskett A, Williams C, Boobis L, et al. Carbohydrate availability and muscle energy metabolism during intermittent running. Med Sci Sports Exerc 2008 Jan; 40 (1): 96-103 Fritzsche RG, Switzer TW, Hodgkinson BJ, et al. Water and carbohydrate ingestion during prolonged exercise increase maximal neuromuscular power. J Appl Physiol 2000; 88 (2): 730-7 Fulco CS, Zupan M, Muza SR, et al. Carbohydrate supplementation and endurance performance of moderate altitude residents at 4300 m. Int J Sports Med 2007 May; 28 (5): 437-43 Hargreaves M, Costill DL, Coggan A, et al. Effect of carbohydrate feedings on muscle glycogen utilization and exercise performance. Med Sci Sports Exerc 1984; 16 (3): 219-22 Hulston CJ, Jeukendrup AE. Substrate metabolism and exercise performance with caffeine and carbohydrate intake. Med Sci Sports Exerc 2008 Dec; 40 (12): 2096-104 Ivy JL, Costill DL, Fink WJ, et al. Influence of caffeine and carbohydrate feedings on endurance performance. Med Sci Sports 1979; 11 (1): 6-11 Ivy JL, Miller W, Dover V, et al. Endurance improved by ingestion of a glucose polymer supplement. Med Sci Sports Exerc 1983; 15 (6): 466-71 Jeukendrup A, Brouns F, Wagenmakers AJ, et al. Carbohydrate-electrolyte feedings improve 1 h time trial cycling performance. Int J Sports Med 1997; 18 (2): 125-9 Johnson HL, Nelson RA, Consolazio CF. Effects of electrolyte and nutrient solutions on performance and metabolic balance. Med Sci Sports Exerc 1988; 20 (1): 26-33 Kang J, Robertson RJ, Denys BG, et al. Effect of carbohydrate ingestion subsequent to carbohydrate supercompensation on endurance performance. Int J Sport Nutr 1995; 5 (4): 329-43 Kingwell B, McKenna MJ, Sandstrom ER, et al. Effect of glucose polymer ingestion on energy and fluid balance during exercise. J Sports Sci 1989; 7 (1): 3-8 Langenfeld ME, Seifert JG, Rudge SR, et al. Effect of carbohydrate ingestion on performance of non-fasted cyclists during a simulated 80-mile time trial. J Sports Med Phys Fitness 1994; 34 (3): 263-70 Madsen K, MacLean DA, Kiens B, et al. Effects of glucose, glucose plus branched-chain amino acids, or placebo on bike performance over 100 km. J Appl Physiol 1996; 81 (6): 2644-50 Maughan RJ, Bethell LR, Leiper JB. Effects of ingested fluids on exercise capacity and on cardiovascular and metabolic responses to prolonged exercise in man. Exp Physiol 1996; 81 (5): 847-59 Maughan RJ, Fenn CE, Leiper JB. Effects of fluid, electrolyte and substrate ingestion on endurance capacity. Eur J Appl Physiol Occup Physiol 1989; 58 (5): 481-6
Sports Med 2010; 40 (9)
Karelis et al.
760
55. Meyer F, Bar-Or O, MacDougall D, et al. Drink composition and the electrolyte balance of children exercising in the heat. Med Sci Sports Exerc 1995 Jun; 27 (6): 882-7 56. Millard-Stafford M, Sparling PB, Rosskopf LB, et al. Carbohydrate-electrolyte replacement during a simulated triathlon in the heat. Med Sci Sports Exerc 1990; 22 (5): 621-8 57. Millard-Stafford ML, Sparling PB, Rosskopf LB, et al. Carbohydrate-electrolyte replacement improves distance running performance in the heat. Med Sci Sports Exerc 1992; 24 (8): 934-40 58. Mitchell JB, Costill DL, Houmard JA, et al. Influence of carbohydrate dosage on exercise performance and glycogen metabolism. J Appl Physiol 1989; 67 (5): 1843-9 59. Murray R, Bartoli WP, Eddy DE, et al. Physiological and performance responses to nicotinic-acid ingestion during exercise. Med Sci Sports Exerc 1995; 27 (7): 1057-62 60. Murray R, Eddy DE, Murray TW, et al. The effect of fluid and carbohydrate feedings during intermittent cycling exercise. Med Sci Sports Exerc 1987; 19 (6): 597-604 61. Murray R, Paul GL, Seifert JG, et al. Responses to varying rates of carbohydrate ingestion during exercise. Med Sci Sports Exerc 1991; 23 (6): 713-8 62. Murray R, Seifert JG, Eddy DE, et al. Carbohydrate feeding and exercise: effect of beverage carbohydrate content. Eur J Appl Physiol Occup Physiol 1989; 59 (1-2): 152-8 63. Neufer PD, Costill DL, Flynn MG, et al. Improvements in exercise performance: effects of carbohydrate feedings and diet. J Appl Physiol 1987; 62 (3): 983-8 64. Nicholas CW, Tsintzas K, Boobis L, et al. Carbohydrateelectrolyte ingestion during intermittent high-intensity running. Med Sci Sports Exerc 1999 Sep; 31 (9): 1280-6 65. Nicholas CW, Williams C, Lakomy HK, et al. Influence of ingesting a carbohydrate-electrolyte solution on endurance capacity during intermittent, high-intensity shuttle running. J Sports Sci 1995; 13 (4): 283-90 66. Nishibata I, Sadamoto T, Mutoh Y, et al. Glucose ingestion before and during exercise does not enhance performance of daily repeated endurance exercise. Eur J Appl Physiol Occup Physiol 1993; 66 (1): 65-9 67. Osterberg KL, Zachwieja JJ, Smith JW. Carbohydrate and carbohydrate + protein for cycling time-trial performance. J Sports Sci 2008 Feb 1; 26 (3): 227-33 68. Powers SK, Lawler J, Dodd S, et al. Fluid replacement drinks during high intensity exercise: effects on minimizing exercise-induced disturbances in homeostasis. Eur J Appl Physiol Occup Physiol 1990; 60 (1): 54-60 69. Riley ML, Israel RG, Holbert D, et al. Effect of carbohydrate ingestion on exercise endurance and metabolism after a 1-day fast. Int J Sports Med 1988; 9 (5): 320-4 70. Rogers J, Summers RW, Lambert GP. Gastric emptying and intestinal absorption of a low-carbohydrate sport drink during exercise. Int J Sport Nutr Exerc Metab 2005 Jun; 15 (3): 220-35 71. Sasaki H, Maeda J, Usui S, et al. Effect of sucrose and caffeine ingestion on performance of prolonged strenuous running. Int J Sports Med 1987; 8 (4): 261-5 72. Sasaki H, Takaoka I, Ishiko T. Effects of sucrose or caffeine ingestion on running performance and biochemical
ª 2010 Adis Data Information BV. All rights reserved.
73.
74.
75.
76.
77.
78.
79.
80.
81.
82.
83.
84.
85.
86. 87.
88.
89.
responses to endurance running. Int J Sports Med 1987; 8 (3): 203-7 Sugiura K, Kobayashi K. Effect of carbohydrate ingestion on sprint performance following continuous and intermittent exercise. Med Sci Sports Exerc 1998; 30 (11): 1624-30 Tsintzas K, Liu R, Williams C, et al. The effect of carbohydrate ingestion on performance during a 30-km race. Int J Sport Nutr 1993; 3 (2): 127-39 Tsintzas OK, Williams C, Boobis L, et al. Carbohydrate ingestion and single muscle fiber glycogen metabolism during prolonged running in men. J Appl Physiol 1996; 81 (2): 801-9 Tsintzas OK, Williams C, Wilson W, et al. Influence of carbohydrate supplementation early in exercise on endurance running capacity. Med Sci Sports Exerc 1996; 28 (11): 1373-9 van Essen M, Gibala MJ. Failure of protein to improve time trial performance when added to a sports drink. Med Sci Sports Exerc 2006 Aug; 38 (8): 1476-83 Vergauwen L, Brouns F, Hespel P. Carbohydrate supplementation improves stroke performance in tennis. Med Sci Sports Exerc 1998 Aug; 30 (8): 1289-95 Widrick JJ, Costill DL, Fink WJ, et al. Carbohydrate feedings and exercise performance: effect of initial muscle glycogen concentration. J Appl Physiol 1993; 74 (6): 2998-3005 Wilber RL, Moffatt RJ. Influence of carbohydrate ingestion on blood glucose and performance in runners. Int J Sport Nutr 1992; 2 (4): 317-27 Williams C, Nute MG, Broadbank L, et al. Influence of fluid intake on endurance running performance: a comparison between water, glucose and fructose solutions. Eur J Appl Physiol Occup Physiol 1990; 60 (2): 112-9 Winnick JJ, Davis JM, Welsh RS, et al. Carbohydrate feedings during team sport exercise preserve physical and CNS function. Med Sci Sports Exerc 2005 Feb; 37 (2): 306-15 Wright DA, Sherman WM, Dernbach AR. Carbohydrate feedings before, during, or in combination improve cycling endurance performance. J Appl Physiol 1991; 71 (3): 1082-8 Yaspelkis 3rd BB, Patterson JG, Anderla PA, et al. Carbohydrate supplementation spares muscle glycogen during variable-intensity exercise. J Appl Physiol 1993; 75 (4): 1477-85 Zachwieja JJ, Costill DL, Beard GC, et al. The effects of a carbonated carbohydrate drink on gastric emptying, gastrointestinal distress, and exercise performance. Int J Sport Nutr 1992; 2 (3): 239-50 Lipsey MW, Wilson GR. Practical meta-analysis. Vol. 49. Thousand Oaks (CA): Sage, 2001 Cohen J. Statistical power analysis for the behavioral sciences. 2nd ed. Hillsdale (NJ): Lawrence Erlbaum Associates, 1988 Bonen A, Malcolm SA, Kilgour RD, et al. Glucose ingestion before and during intense exercise. J Appl Physiol 1981; 50 (4): 766-71 Mitchell JB, Braun WA, Pizza FX, et al. Pre-exercise carbohydrate and fluid ingestion: influence of glycemic response on 10-km treadmill running performance in the heat. J Sports Med Phys Fitness 2000; 40 (1): 41-50
Sports Med 2010; 40 (9)
Carbohydrate Administration and Performance
90. Allen DG, Lamb GD, Westerblad H. Skeletal muscle fatigue: cellular mechanisms. Physiol Rev 2008 Jan; 88 (1): 287-332 91. Ament W, Verkerke GJ. Exercise and fatigue. Sports Med 2009; 39 (5): 389-422 92. Fitts RH. Cellular mechanisms of muscle fatigue. Physiol Rev 1994; 74 (1): 49-94 93. Dumke CL, McBride JM, Nieman DC, et al. Effect of duration and exogenous carbohydrate on gross efficiency during cycling. J Strength Cond Res 2007 Nov; 21 (4): 1214-9 94. Newsholme EA, Acworth IN, Blomstrand E. Amino acids, brain neurotransmitters and a functional link between muscle and brain that is important in sustained exercise. London: John Libby Eurotext, 1987 95. Bequet F, Gomez-Merino D, Berthelot M, et al. Exerciseinduced changes in brain glucose and serotonin revealed by microdialysis in rat hippocampus: effect of glucose supplementation. Acta Physiol Scand 2001; 173 (2): 223-30 96. Davis JM, Bailey SP. Possible mechanisms of central nervous system fatigue during exercise. Med Sci Sports Exerc 1997; 29 (1): 45-57 97. Curzon G, Friedel J, Knott PJ. The effect of fatty acids on the binding of tryptophan to plasma protein. Nature 1973; 242 (5394): 198-200 98. Davis JM, Bailey SP, Woods JA, et al. Effects of carbohydrate feedings on plasma free tryptophan and branched-chain amino acids during prolonged cycling. Eur J Appl Physiol Occup Physiol 1992; 65 (6): 513-9 99. Dalsgaard MK, Secher NH. The brain at work: a cerebral metabolic manifestation of central fatigue? J Neurosci Res 2007 Nov 15; 85 (15): 3334-9 100. Pardridge WM. Brain metabolism: a perspective from the blood-brain barrier. Physiol Rev 1983 Oct; 63 (4): 1481-535 101. Koslowski S, Brzezinska K, Nazae E, et al. Carbohydrate availability for the brain and muscle as a factor modifying sympathetic activity during exercise in dogs. In: Poortmans J, Niset G, editors. Biochemistry of exercise. Baltimore (MD): University Park Press, 1981: 54-62 102. Nybo L. CNS fatigue and prolonged exercise: effect of glucose supplementation. Med Sci Sports Exerc 2003; 35 (4): 589-94 103. Horowitz JF, Coyle EF. Metabolic responses to preexercise meals containing various carbohydrates and fat. Am J Clin Nutr 1993 Aug; 58 (2): 235-41 104. King P, Kong MF, Parkin H, et al. Well-being, cerebral function, and physical fatigue after nocturnal hypoglycemia in IDDM. Diabetes Care 1998 Mar; 21 (3): 341-5 105. Claassen A, Lambert EV, Bosch AN, et al. Variability in exercise capacity and metabolic response during endurance exercise after a low carbohydrate diet. Int J Sport Nutr Exerc Metab 2005 Apr; 15 (2): 97-116 106. Collardeau M, Brisswalter J, Vercruyssen F, et al. Single and choice reaction time during prolonged exercise in trained subjects: influence of carbohydrate availability. Eur J Appl Physiol 2001; 86 (2): 150-6 107. Welsh RS, Davis JM, Burke JR, et al. Carbohydrates and physical/mental performance during intermittent exercise to fatigue. Med Sci Sports Exerc 2002; 34 (4): 723-31 108. Carter JM, Jeukendrup AE, Jones DA. The effect of carbohydrate mouth rinse on 1-h cycle time trial performance. Med Sci Sports Exerc 2004 Dec; 36 (12): 2107-11
ª 2010 Adis Data Information BV. All rights reserved.
761
109. Chambers ES, Bridge MW, Jones DA. Carbohydrate sensing in the human mouth: effects on exercise performance and brain activity. J Physiol 2009 Apr 15; 587 (Pt 8): 1779-94 110. Pottier A, Bouckaert J, Gilis W, et al. Mouth rinse but not ingestion of a carbohydrate solution improves 1-h cycle time trial performance. Scand J Med Sci Sports. Epub 2008 Nov 3 111. Coggan AR, Coyle EF. Reversal of fatigue during prolonged exercise by carbohydrate infusion or ingestion. J Appl Physiol 1987 Dec; 63 (6): 2388-95 112. Currell K, Jeukendrup AE. Superior endurance performance with ingestion of multiple transportable carbohydrates. Med Sci Sports Exerc 2008 Feb; 40 (2): 275-81 113. Conlee RK. Muscle glycogen and exercise endurance: a twenty-year perspective. Exerc Sport Sci Rev 1987; 15: 1-28 114. Tsintzas K, Williams C. Human muscle glycogen metabolism during exercise: effect of carbohydrate supplementation. Sports Med 1998; 25 (1): 7-23 115. Bergstrom J, Hultman E. A study of the glycogen metabolism during exercise in man. Scand J Clin Lab Invest 1967; 19 (3): 218-28 116. Arkinstall MJ, Bruce CR, Nikolopoulos V, et al. Effect of carbohydrate ingestion on metabolism during running and cycling. J Appl Physiol 2001; 91 (5): 2125-34 117. Chryssanthopoulos C, Williams C, Nowitz A. Influence of a carbohydrate-electrolyte solution ingested during running on muscle glycogen utilisation in fed humans. Int J Sports Med 2002; 23 (4): 279-84 118. Coggan AR, Coyle EF. Reversal of fatigue during prolonged exercise by carbohydrate infusion or ingestion. J Appl Physiol 1987; 63 (6): 2388-95 119. Coyle EF, Hamilton MT, Alonso JG, et al. Carbohydrate metabolism during intense exercise when hyperglycemic. J Appl Physiol 1991; 70 (2): 834-40 120. Febbraio MA, Keenan J, Angus DJ, et al. Preexercise carbohydrate ingestion, glucose kinetics, and muscle glycogen use: effect of the glycemic index. J Appl Physiol 2000; 89 (5): 1845-51 121. Febbraio MA, Stewart KL. CHO feeding before prolonged exercise: effect of glycemic index on muscle glycogenolysis and exercise performance. J Appl Physiol 1996; 81 (3): 1115-20 122. Hargreaves M, Briggs CA. Effect of carbohydrate ingestion on exercise metabolism. J Appl Physiol 1988; 65 (4): 1553-5 123. Hargreaves M, Costill DL, Fink WJ, et al. Effect of preexercise carbohydrate feedings on endurance cycling performance. Med Sci Sports Exerc 1987; 19 (1): 33-6 124. Gorski J, Zendzian-Piotrowska M, Gorska M, et al. Effect of hyperglycaemia on muscle glycogen mobilization during muscle contractions in the rat. Eur J Appl Physiol Occup Physiol 1990; 61 (5-6): 408-12 125. Hargreaves M, Costill DL, Coggan A, et al. Effect of carbohydrate feedings on muscle glycogen utilization and exercise performance. Med Sci Sports Exerc 1984 Jun; 16 (3): 219-22 126. Bjorkman O, Sahlin K, Hagenfeldt L, et al. Influence of glucose and fructose ingestion on the capacity for longterm exercise in well-trained men. Clin Physiol 1984 Dec; 4 (6): 483-94
Sports Med 2010; 40 (9)
Karelis et al.
762
127. Tsintzas OK, Williams C, Boobis L, et al. Carbohydrate ingestion and glycogen utilization in different muscle fibre types in man. J Physiol 1995; 489 (Pt 1): 243-50 128. Tsintzas K, Williams C, Constantin-Teodosiu D, et al. Phosphocreatine degradation in type I and type II muscle fibres during submaximal exercise in man: effect of carbohydrate ingestion. J Physiol 2001; 537 (Pt 1): 305-11 129. Chin ER, Allen DG. Effects of reduced muscle glycogen concentration on force, Ca2+ release and contractile protein function in intact mouse skeletal muscle. J Physiol 1997 Jan 1; 498 (Pt 1): 17-29 130. Helander I, Westerblad H, Katz A. Effects of glucose on contractile function, [Ca2+]i, and glycogen in isolated mouse skeletal muscle. Am J Physiol Cell Physiol 2002 Jun; 282 (6): C1306-12 131. Goodman C, Blazev R, Stephenson G. Glycogen content and contractile responsiveness to T-system depolarization in skinned muscle fibres of the rat. Clin Exp Pharmacol Physiol 2005 Sep; 32 (9): 749-56 132. Stephenson DG, Nguyen LT, Stephenson GM. Glycogen content and excitation-contraction coupling in mechanically skinned muscle fibres of the cane toad. J Physiol 1999 Aug 15; 519 (Pt 1): 177-87 133. Sahlin K, Tonkonogi M, Soderlund K. Energy supply and muscle fatigue in humans. Acta Physiol Scand 1998; 162 (3): 261-6 134. Westerblad H, Allen DG, Lannergren J. Muscle fatigue: lactic acid or inorganic phosphate the major cause? News Physiol Sci 2002; 17: 17-21 135. Allen DG, Lamb GD, Westerblad H. Impaired calcium release during fatigue. J Appl Physiol 2008 Jan; 104 (1): 296-305 136. Lewis SF, Haller RG. The pathophysiology of McArdle’s disease: clues to regulation in exercise and fatigue. J Appl Physiol 1986; 61 (2): 391-401 137. Snow RJ, Carey MF, Stathis CG, et al. Effect of carbohydrate ingestion on ammonia metabolism during exercise in humans. J Appl Physiol 2000; 88 (5): 1576-80 138. Spencer MK, Yan Z, Katz A. Carbohydrate supplementation attenuates IMP accumulation in human muscle during prolonged exercise. Am J Physiol 1991; 261 (1 Pt 1): C71-6 139. Duhamel TA, Green HJ, Stewart RD, et al. Muscle metabolic, SR Ca (2+)-cycling responses to prolonged cycling, with and without glucose supplementation. J Appl Physiol 2007 Dec; 103 (6): 1986-98 140. Phillips SK, Wiseman RW, Woledge RC, et al. The effect of metabolic fuel on force production and resting inorganic phosphate levels in mouse skeletal muscle. J Physiol 1993; 462: 135-46 141. Bowtell JL, Marwood S, Bruce M, et al. Tricarboxylic acid cycle intermediate pool size: functional importance for oxidative metabolism in exercising human skeletal muscle. Sports Med 2007; 37 (12): 1071-88 142. Sahlin K, Katz A, Broberg S. Tricarboxylic acid cycle intermediates in human muscle during prolonged exercise. Am J Physiol 1990; 259 (5 Pt 1): C834-41 143. Baldwin J, Snow RJ, Gibala MJ, et al. Glycogen availability does not affect the TCA cycle or TAN pools during prolonged, fatiguing exercise. J Appl Physiol 2003; 94 (6): 2181-7 144. Dawson KD, Baker DJ, Greenhaff PL, et al. An acute decrease in TCA cycle intermediates does not affect aerobic
ª 2010 Adis Data Information BV. All rights reserved.
145.
146.
147.
148. 149.
150.
151.
152.
153.
154.
155.
156.
157.
158.
159.
160.
161.
energy delivery in contracting rat skeletal muscle. J Physiol 2005 Jun 1; 565 (Pt 2): 637-43 Gibala MJ, Gonzalez-Alonso J, Saltin B. Dissociation between muscle tricarboxylic acid cycle pool size and aerobic energy provision during prolonged exercise in humans. J Physiol 2002 Dec 1; 545 (Pt 2): 705-13 Spencer MK, Yan Z, Katz A. Carbohydrate supplementation attenuates IMP accumulation in human muscle during prolonged exercise. Am J Physiol 1991 Jul; 261 (1 Pt 1): C71-6 Nieman DC. Influence of carbohydrate on the immune response to intensive, prolonged exercise. Exerc Immunol Rev 1998; 4: 64-76 Nieman DC. Marathon training and immune function. Sports Med 2007; 37 (4-5): 412-5 McAnulty S, McAnulty L, Nieman D, et al. Carbohydrate effect: hormone and oxidative changes. Int J Sports Med 2007 Nov; 28 (11): 921-7 McAnulty SR, McAnulty LS, Morrow JD, et al. Influence of carbohydrate, intense exercise, and rest intervals on hormonal and oxidative changes. Int J Sport Nutr Exerc Metab 2007 Oct; 17 (5): 478-90 Febbraio MA, Mesa JL, Chung J, et al. Glucose ingestion attenuates the exercise-induced increase in circulating heat shock protein 72 and heat shock protein 60 in humans. Cell Stress Chaperones 2004 Winter; 9 (4): 390-6 Akerstrom TC, Birk JB, Klein DK, et al. Oral glucose ingestion attenuates exercise-induced activation of 50 -AMPactivated protein kinase in human skeletal muscle. Biochem Biophys Res Commun 2006 Apr 14; 342 (3): 949-55 Scharhag J, Meyer T, Auracher M, et al. Effects of graded carbohydrate supplementation on the immune response in cycling. Med Sci Sports Exerc 2006 Feb; 38 (2): 286-92 McAnulty SR, McAnulty LS, Nieman DC, et al. Effect of resistance exercise and carbohydrate ingestion on oxidative stress. Free Radic Res 2005 Nov; 39 (11): 1219-24 McAnulty SR, McAnulty LS, Nieman DC, et al. Influence of carbohydrate ingestion on oxidative stress and plasma antioxidant potential following a 3 h run. Free Radic Res 2003 Aug; 37 (8): 835-40 Vasankari T, Kujala U, Sarna S, et al. Effects of ascorbic acid and carbohydrate ingestion on exercise induced oxidative stress. J Sports Med Phys Fitness 1998 Dec; 38 (4): 281-5 Lee-Young RS, Palmer MJ, Linden KC, et al. Carbohydrate ingestion does not alter skeletal muscle AMPK signaling during exercise in humans. Am J Physiol Endocrinol Metab 2006 Sep; 291 (3): E566-73 Nielsen OB, Clausen T. The Na+/K(+)-pump protects muscle excitability and contractility during exercise. Exerc Sport Sci Rev 2000; 28 (4): 159-64 Overgaard K, Nielsen OB, Flatman JA, et al. Relations between excitability and contractility in rat soleus muscle: role of the Na+-K+ pump and Na+/K+ gradients. J Physiol 1999; 518 (Pt 1): 215-25 Allen DG, Lannergren J, Westerblad H. The use of caged adenine nucleotides and caged phosphate in intact skeletal muscle fibres of the mouse. Acta Physiol Scand 1999; 166 (4): 341-7 Okamoto K, Wang W, Rounds J, et al. ATP from glycolysis is required for normal sodium homeostasis in resting
Sports Med 2010; 40 (9)
Carbohydrate Administration and Performance
162.
163.
164.
165.
166.
167.
168.
fast-twitch rodent skeletal muscle. Am J Physiol Endocrinol Metab 2001; 281 (3): E479-88 Karelis AD, Peronnet F, Gardiner PF. Glucose infusion attenuates muscle fatigue in rat plantaris muscle during prolonged indirect stimulation in situ. Exp Physiol 2002; 87 (5): 585-92 Marcil M, Karelis AD, Peronnet F, et al. Glucose infusion attenuates fatigue without sparing glycogen in rat soleus muscle during prolonged electrical stimulation in situ. Eur J Appl Physiol 2005 Mar; 93 (5-6): 569-74 Clausen T, Andersen SL, Flatman JA. Na(+)-K+ pump stimulation elicits recovery of contractility in K(+)-paralysed rat muscle. J Physiol 1993 Dec; 472: 521-36 Karelis AD, Peronnet F, Gardiner PF. Insulin does not mediate the attenuation of fatigue associated with glucose infusion in rat plantaris muscle. J Appl Physiol 2003; 95 (1): 330-5 Stewart RD, Duhamel TA, Foley KP, et al. Protection of muscle membrane excitability during prolonged cycle exercise with glucose supplementation. J Appl Physiol 2007 Jul; 103 (1): 331-9 Green HJ, Duhamel TA, Foley KP, et al. Glucose supplements increase human muscle in vitro Na+-K+-ATPase activity during prolonged exercise. Am J Physiol Regul Integr Comp Physiol 2007 Jul; 293 (1): R354-62 Harrison AP, Flatman JA. Measurement of force and both surface and deep M wave properties in isolated rat soleus muscles. Am J Physiol 1999; 277 (6 Pt 2): R1646-53
ª 2010 Adis Data Information BV. All rights reserved.
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169. Fitts RH, Balog EM. Effect of intracellular and extracellular ion changes on E-C coupling and skeletal muscle fatigue. Acta Physiol Scand 1996; 156 (3): 169-81 170. Sejersted OM, Sjogaard G. Dynamics and consequences of potassium shifts in skeletal muscle and heart during exercise. Physiol Rev 2000; 80 (4): 1411-81 171. Karelis AD, Peronnet F, Gardiner PF. Resting membrane potential of rat plantaris muscle fibers after prolonged indirect stimulation in situ: effect of glucose infusion. Can J Appl Physiol 2005 Feb; 30 (1): 105-12 172. Verburg E, Thorud HM, Eriksen M, et al. Muscle contractile properties during intermittent nontetanic stimulation in rat skeletal muscle. Am J Physiol Regul Integr Comp Physiol 2001; 281 (6): R1952-65 173. Xu KY, Zweier JL, Becker LC. Functional coupling between glycolysis and sarcoplasmic reticulum Ca2+ transport. Circ Res 1995 Jul; 77 (1): 88-97 174. Ortenblad N, Stephenson DG. A novel signalling pathway originating in mitochondria modulates rat skeletal muscle membrane excitability. J Physiol 2003; 548 (Pt 1): 139-45
Correspondence: Dr Antony Karelis, Department of Kinesiology, University of Quebec at Montreal, Case postale 8888 succursale Centre-ville, Montreal, QC H3C 3P8, Canada. E-mail:
[email protected]
Sports Med 2010; 40 (9)
RESEARCH REVIEW ARTICLE
Sports Med 2010; 40 (9): 765-801 0112-1642/10/0009-0765/$49.95/0
ª 2010 Adis Data Information BV. All rights reserved.
Neuroplasticity – Exercise-Induced Response of Peripheral Brain-Derived Neurotrophic Factor A Systematic Review of Experimental Studies in Human Subjects Kristel Knaepen,1 Maaike Goekint,1,2 Elsa Marie Heyman1,3 and Romain Meeusen1 1 Vrije Universiteit Brussel, Department of Human Physiology & Sports Medicine, Brussels, Belgium 2 Aspirant of the Research Foundation Flanders, Brussels, Belgium 3 Universite´ Lille 2, Physical Activity, Sport, Health, Lille, France
Abstract
Exercise is known to induce a cascade of molecular and cellular processes that support brain plasticity. Brain-derived neurotrophic factor (BDNF) is an essential neurotrophin that is also intimately connected with central and peripheral molecular processes of energy metabolism and homeostasis, and could play a crucial role in these induced mechanisms. This review provides an overview of the current knowledge on the effects of acute exercise and/or training on BDNF in healthy subjects and in persons with a chronic disease or disability. A systematic and critical literature search was conducted. Articles were considered for inclusion in the review if they were human studies, assessed peripheral (serum and/or plasma) BDNF and evaluated an acute exercise or training intervention. Nine RCTs, one randomized trial, five non-randomized controlled trials, five non-randomized non-controlled trials and four retrospective observational studies were analysed. Sixty-nine percent of the studies in healthy subjects and 86% of the studies in persons with a chronic disease or disability, showed a ‘mostly transient’ increase in serum or plasma BDNF concentration following an acute aerobic exercise. The two studies regarding a single acute strength exercise session could not show a significant influence on basal BDNF concentration. In studies regarding the effects of strength or aerobic training on BDNF, a difference should be made between effects on basal BDNF concentration and training-induced effects on the BDNF response following an acute exercise. Only three out of ten studies on aerobic or strength training (i.e. 30%) found a training-induced increase in basal BDNF concentration. Two out of six studies (i.e. 33%) reported a significantly higher BDNF response to acute exercise following an aerobic or strength training programme (i.e. compared with the BDNF response to an acute exercise at baseline). A few studies of low quality (i.e. retrospective observational studies) show that untrained or moderately trained healthy subjects have higher basal BDNF concentrations than highly trained subjects. Yet, strong evidence still has to come from good methodological studies. Available results suggest that acute aerobic, but not strength exercise increases basal peripheral BDNF concentrations, although the effect is transient.
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From a few studies we learn that circulating BDNF originates both from central and peripheral sources. We can only speculate which central regions and peripheral sources in particular circulating BDNF originates from, where it is transported to and to what purpose it is used and/or stored at its final destination. No study could show a long-lasting BDNF response to acute exercise or training (i.e. permanently increased basal peripheral BDNF concentration) in healthy subjects or persons with a chronic disease or disability. It seems that exercise and/or training temporarily elevate basal BDNF and possibly upregulate cellular processing of BDNF (i.e. synthesis, release, absorption and degradation). From that point of view, exercise and/or training would result in a higher BDNF synthesis following an acute exercise bout (i.e. compared with untrained subjects). Subsequently, more BDNF could be released into the blood circulation which may, in turn, be absorbed more efficiently by central and/or peripheral tissues where it could induce a cascade of neurotrophic and neuroprotective effects.
Neuroplasticity refers to the ability of the brain and CNS to adapt to environmental change, respond to injury and to acquire novel information by modifying neural connectivity and function. Neurotrophins support (activity-dependent) neuroplasticity; in particular, they are capable of signalling neurons to survive, differentiate or grow.[1-5] Therefore, neurotrophins gain increasing attention in research for the treatment and prevention of neurodegenerative and, more recently, metabolic diseases.[5-10] Neurotrophic factors not only play a role in neurobiology, but also in central and peripheral energy metabolism.[11] Their effect on synaptic plasticity in the CNS involves elements of cellular energy metabolism[12] and in the periphery they take part in metabolic processes such as enhancing lipid oxidation in the skeletal muscle via activation of AMPK (i.e. adenosine monophosphate-activated protein kinase).[10] Physical activity and, in particular, acute exercise and training seem to be key interventions to trigger the processes through which neurotrophins mediate energy metabolism and in turn neural plasticity.[1-3,13-17] Of all neurotrophins, brainderived neurotrophic factor[18] (BDNF) seems to be the most susceptible to regulation by exercise and physical activity.[2,3,5] BDNF is a basic protein of 252 amino acids that is coded by the BDNF gene. This gene extends over 70 kb, is located on chromosome 11, band p13 and contains 11 exons and 9 functional promoters.[19-21] As ª 2010 Adis Data Information BV. All rights reserved.
in all other neurotrophins, BDNF has a single coding exon; the 30 exon that encodes for most of the protein.[21] Recently, a variant in the human BDNF gene has been identified,[22] Val66Met, a single nucleotide polymorphism (SNP) at nucleotide 196 (G/A) that encodes an amino acid substitution (i.e. a valine [Val] to methionine allele [Met]) at codon 66 in the prodomain of the BDNF gene.[22,23] This gene mutation occurs in 20–30% of the human population[24,25] and results in a decreased activity-induced response of BDNF.[23] Casey et al.[25] predict that carriers of the variant BDNFMet allele will have less neurotrophic support for plasticity at a certain moment in their development, whereas carriers of the BDNFVal allele will experience the inverse.[25,26] It is generally accepted that BDNF has a wide repertoire of neurotrophic and neuroprotective properties in the CNS and the periphery; namely, neuronal protection and survival, neurite expression, axonal and dendritic growth and remodelling, neuronal differentiation and synaptic plasticity such as synaptogenesis in arborizing axon terminals, and synaptic transmission efficacy.[27-31] Animal studies also revealed a neuroendocrine and/or metabotrophic capacity of BDNF in the periphery, which (i) reduces food intake; (ii) increases oxidation of glucose; (iii) lowers blood glucose levels; and (iv) increases insulin sensitivity.[32-36] In addition, Molteni et al.[37] found that, in animals, a high-fat diet reduces hippocampal levels of Sports Med 2010; 40 (9)
BDNF and Exercise in Humans
BDNF, but exercise is able to reverse this dietary decrease. Komori et al.[38] showed a central interaction between the adipocyte-derived hormone leptin that plays a key role in regulating appetite and energy metabolism and BDNF expression in the hypothalamus of mice. A human case study revealed a clinical phenotype of impaired cognitive function, hyperactivity and severe obesity associated with a chromosomal inversion of a region encompassing the BDNF gene and a reduction of serum BDNF.[39] Additionally, Araya et al.[40] found that serum BDNF was increased in insulinresistant, overweight and obese subjects after a reduced-calorie diet. These findings confirm that BDNF is not only essential in the neuronal system, but is also intimately connected with central and peripheral molecular processes of energy metabolism and homeostasis.[11,41] In search of mechanisms underlying plasticity and brain health, exercise is known to induce a cascade of molecular and cellular processes that support (brain) plasticity. BDNF could play a crucial role in these induced mechanisms. Therefore, since the early 1990s, studies started to investigate the effects of physical activity, acute exercise and/or training on BDNF concentration, first in animals[42-46] and then, since 2003, in humans.[47] The first human study examined the effect of acute exercise on peripheral BDNF in subjects with a neurodegenerative disease (i.e. multiple sclerosis [MS]) in order to explore the restorative potential of exercise.[47] Since then, two dozen other studies on the effects of acute exercise and/or training on BDNF have been conducted of which most concern healthy subjects. The purpose of the current review is to provide an insight in the overall effect of physical activity on peripheral concentration of BDNF. 1. Literature Search Methodology 1.1 Search Strategy
A comprehensive literature search was conducted in 2009–10. The following seven databases were consulted: PubMed, Web of Science, SportDiscus, Cochrane Library, PEDro, Darenet and Narcis. Databases were screened on relª 2010 Adis Data Information BV. All rights reserved.
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evant literature from the beginning of each database up to July 2010. The search combined the following keywords: ‘BDNF’, ‘exercise’, ‘training’, ‘physical activity’, ‘neuroplasticity’, ‘neuroplasticity proteins’, ‘neurotrophins’, ‘activity-dependent plasticity’ and ‘neurogenesis’. Eligibility of the studies based on titles, abstracts and full-text articles was initially determined by the first author (figure 1). The second author independently came to the same selection of studies after screening the literature. 1.2 Criteria for Consideration
Studies were selected using predetermined inclusion and exclusion criteria. An initial raw screening resulted in a selection of 860 articles. A more profound screening of titles, abstracts and fulltext articles, based on specific criteria, resulted in a final selection of 24 studies. Figure 1 shows the progress of the literature screening and the reasons for inclusion or exclusion. Inclusion criteria were as follows: healthy subjects; persons with a chronic disability or disease; acute aerobic and strength exercise protocols (low to high intensity); endurance/aerobic, strength/ resistance training protocols (low to high intensity); randomized controlled trials; controlled trials; clinical trials; comparative and evaluation studies; assessment of peripheral (serum and plasma) BDNF concentrations; and articles written in English, French, Dutch or German. Studies were excluded when they concerned animals, no exercise/training intervention, no physical activity, behavioural studies, reviews, studies on cognitive learning, no assessment of peripheral BDNF and general studies on neuroplasticity/neurogenesis. Inclusion and exclusion criteria were selected to be able to give an answer to the question whether acute exercise or training has an effect on peripheral BDNF, in particular, in humans. This question is of interest as acute exercise and training could be a viable treatment of neurodegenerative and metabolic diseases through their possible effect on neurotrophins and, thus, neuroplasticity. Four studies with no acute exercise or training intervention were nevertheless included in this review because of their possible relevant contribution. The four studies research the relation Sports Med 2010; 40 (9)
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Potentially relevant studies based on search terms (n = 860) • PubMed (n = 373) • Web of Science (n = 320) • SportDiscus® (n = 39) • Cochrane Library (n = 66) • PEDro (n = 4) • Narcis/Darenet (n = 28) • VUB database (n = 30)
Potentially relevant studies retrieved for abstract evaluation (n = 138)
Studies excluded after screening titles (n = 722) • duplicates • animal studies • no exercise/training intervention • no assessment of peripheral BDNF • behavioural studies • reviews • studies on cognitive learning Studies excluded after evaluation of abstracts (n = 114) • no assessment of peripheral BDNF • general studies on neuroplasticiy • general studies on neurogenesis
Potentially relevant studies retrieved for full text evaluation (n = 24) No studies were excluded after full text evaluation Studies included in systematic review (n = 24) Fig. 1. Flow diagram of the systematic literature research.[48,49] BDNF = brain-derived neurotrophic factor.
between the level of physical fitness and basal peripheral BDNF concentration. 1.3 Data Extraction
The 24 included studies were reviewed for relevant information by the first author. Data on study design, sample size, study population, intervention, outcome measures and results were collected and are summarized in table I. 2. Exercise and Peripheral Brain-Derived Neurotrophic Factor (BDNF) The main purpose of this literature review is to provide an insight in the effects of exercise and/or training on peripheral concentration of BDNF. The second purpose is to review the materials and methods that were used to research the efª 2010 Adis Data Information BV. All rights reserved.
fects of exercise and/or training on BDNF. The following sections summarize the study populations, exercise protocols, biochemical analysis, basal BDNF concentrations and the effects of exercise or training on peripheral BDNF in all included studies. 2.1 Number and Type of Studies
Twenty-four studies were included; nine studies were randomized controlled trials,[50,54,56,60,66-69,71] one was a randomized non-controlled trial,[72] five were non-randomized controlled trials,[47,51,57-59] five were non-randomized, non-controlled comparative trials (the study of Rojas Vega et al.[63] has a corrigendum that was published a year later;[64] we always refer to this study and the corrigendum)[62-65,70,75] and four studies were retrospective observational studies.[52,53,55,61] Sports Med 2010; 40 (9)
Study design
Sample size; sex; age (mean – SD)
Intervention; Groups
Outcome measures
Baker et al.[50] (2010)
RCT
33 patients with mild cognitive impairment; 48% M; 70.0 – 8.3 y
24-wk aerobic training, pre-/post-training GXT; Aerobic training and stretching control group
Castellano and White[51] 2008)
CT
22 subjects (11 MS patients, 11 healthy controls); 27.3% M; 40.0 – 10.0 y
8-wk aerobic training, pretraining: GXT, pre-/mid-/posttraining: LMI; Persons with MS and healthy control group
Chan et al.[52] (2008)
ROS
85 healthy subjects; 48.2% M; 36.1 – 7.8 y
No intervention; Highly and moderately trained
Currie et al.[53] (2009)
ROS
44 healthy subjects; 63.6% M; 34.3 – 10.9 y
No intervention; High cardio-respiratory and low cardio-respiratory fit group
Ferris et al.[54] (2007)
RCT (crossover)
15 healthy subjects; 73.3% M; 25.4 – 1.0 y
Acute aerobic exercise: LMI and HI, pre exercise: GXT; LMI and HI (crossover) group
HR, [BDNF]s, lactate, cognitive assessment
GXT: › in [BDNF]s; [BDNF]s ~ [lactate] LMI: fi in [BDNF]s HI: › in [BDNF]s Cognitive function › after LMI and HI
Floe¨l et al.[55] (2010)
ROS
75 healthy subjects; 32.9% M; 60.5 – 6.9 y
No intervention
[BDNF]s, [G-CSF]s, MRI, test and questionnaire on physical activity and memory encoding
No correlation between [BDNF]s and level physical activity [G-CSF]s › ~ level physical activity › Memory encoding › ~ level physical activity › Gray matter volume › ~ level physical activity ›
Goekint et al.[56] (2008)
RCT (doubleblind, placebo, crossover)
11 healthy trained subjects; all M; 22.9 – 4.3 y
Acute aerobic exercise: LMI and HI, acute drug administration (reboxetine), pre-exercise: GXT; No drug and drug group
HR, [BDNF]s, [COR]s, RPEb, cognitive assessment
LMI and HI: › in [BDNF]s HI › > LMI › No influence of drug on [BDNF]s, but › in [COR]s, HR and memory
. VO2peak, [BDNF]p, [insulin]p, [COR]p, [IGF-1]p, [b-amyloids 40-42]p, cognitive tests
. VO2peak, [BDNF]s, [IGF-1]s
[BDNF]s, questionnaire on lifestyle
. VO2max (estimated), HR, [BDNF]s, HPA index
Results [BDNF]p in F with MCI > [BDNF]p in M with MCI (p = 0.09) Wk 24 at rest: fl in [BDNF]p in F and › in [BDNF]p in M vs controlsa; [BDNF]p ~ [cortisol]p in aerobic training group Wk 0 at rest: [BDNF]s in MS < [BDNF]s in controls Wk 0 after LMI: [BDNF]s fl in MS and controls Wk 4 at rest: [BDNF]s › in MS; [BDNF]s fi in controls Wk 4 after LMI: [BDNF]s fl in MS and controls Wk 8 at rest: [BDNF]s fi in MS and controls Wk 8 after LMI: [BDNF]s fl in MS and controls BDNF was measured 30 min, 2 h and 3 h postLMI [BDNF]s highly trained < [BDNF]s moderately trained [BDNF]s ~ watching television at younger age [BDNF]s in high cardio-respiratory fit subjects < [BDNF]s in low cardio-respiratory fit subjects
Continued next page
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Study (year)
BDNF and Exercise in Humans
ª 2010 Adis Data Information BV. All rights reserved.
Table I. Data extraction from 24 included studies
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ª 2010 Adis Data Information BV. All rights reserved.
Table I. Contd Study design
Sample size; sex; age (mean – SD)
Intervention; Groups
Outcome measures
Results
Goekint et al.[57] (2010)
CT
23 healthy subjects; 78.3% M; 20.8 – 0.6 y
Acute strength exercise, 10-wk strength training; Strength training and control group
[BDNF]s, [IGF-1]s, [IGFBP-3]s, cognitive assessment
Acute strength exercise, after sixth session: [BDNF]s fi , [IGF1]s fi , [IGFBP3]s fi After thirtieth session: [BDNF]s fi , [IGF1]s fi , [IGFBP3]s fi Strength training, wk 10 at rest: [BDNF]s fi , [IGF1]s fi , [IGFBP3]s fi in strength training group and controls; short-term memory › in both groups (no differences between strength training group and controls); wk 10 after strength exercise: [BDNF]s fi , [IGF1]s fi , [IGFBP3]s fi in strength training group and controls
Gold et al.[47] (2003)
CT
45 subjects (25 MS patients, 20 healthy controls); 33.3% M; 39.9 – 1.9 y
Acute aerobic exercise: LMI, pre-exercise: GXT; Persons with MS and healthy control group
Gustafsson et al.[58] (2009)
CT
36 subjects (18 patients with MDD, 18 healthy controls); 50% M; 34.0 y
Acute aerobic exercise: LMI and HI; Patients with moderate MDD and healthy control group
Laske et al.[59] (2010)
CT
55 subjects (35 patients with remitted MDD, 20 healthy controls); 0% M; 60.0 – 6.9 y
Acute aerobic exercise: HI; Patients with remitted MDD and healthy control group
. VO2max, HR, [BDNF]s, [NGF]p, lactate
HR, RPEb, [BDNF]p, [COR], MADRSscore
. VO2peak, ECG, RPEb, lactate, [BDNF]s, HAMD-scale, MMSE and DemTect score, HPA index
At rest: [NGF]p in MS > [NGF]p in controls; [BDNF]s in MS = [BDNF]s in controls LMI: [BDNF]s › in MS and controls (no differences between MS and controls)
At rest: [BDNF]p in MDD = [BDNF]p in controls LMI: [BDNF]p › in M MDD; [BDNF]p fi in M controls, F MDD and F controls HI: [BDNF]p › in M MDD at 0 min and 60 min post-HI exercise; [BDNF]p › in F MDD and M controls at 0 min post-HI; [BDNF]p fi in F controls at 0 min post-HI; [BDNF]p fi in F MDD and F and M controls at 60 min post-HI; [BDNF]p fi in M and F MDD and controls at 30 min post-HI No correlation between: [BDNF]p and cortisol; [BDNF]p and MADRS scores
At rest: [BDNF]s in MDD < [BDNF]s in healthy controls; BMI in MDD > BMI in healthy controls; physical fitness in MDD < physical fitness in healthy controls; [BDNF]s ~ HAMD-score in MDD HI: [BDNF]s › in MDD, [BDNF]s fi in healthy controls at 0 min post-HI; [BDNF]s fl in MDD, [BDNF]s fl 30 min post-HI Continued next page
Knaepen et al.
Sports Med 2010; 40 (9)
Study (year)
Study design
Sample size; sex; age (mean – SD)
Intervention; Groups
Outcome measures
Results
Levinger et al.[60] (2008)
RCT
49 healthy untrained subjects; 51.0% M; 50.9 – 6.2 y
10-wk strength training; HiMF and LoMF group
[BDNF]p, [TG]p, [HDL]p, [glucose]p, [insulin]p, [HbA1c]p, anthropometry, muscle strength, MetS, blood pressure
Wk 0 at rest: [BDNF]p in HiMF > [BDNF]p in LoMF Wk 10 at rest: [BDNF]p fi , muscle strength ›, lean body mass › [BDNF]p ~ risk factors for MetS ([TG]p, [glucose]p, [HbA1c]p, insulin resistance)
Nofuji et al.[61] (2008)
ROS
26 healthy subjects; all M; 22.1 – 1.1 y
No intervention; Sedentary and trained group
[BDNF]s, [BDNF]p, HbA1c, FBG, TC, HDL-C, TG, BMI, body fat (%), WHR, psychological assessment, physical activity
[BDNF]s in sedentary > [BDNF]s in trained subjects [BDNF]p in sedentary = [BDNF]p in trained subjects [BDNF]s negative ~ TEE, MEE and WC No differences in age, anthropometric and psychological parameters between sedentary and trained subjects
Rasmussen et al.[62] (2009)
T
8 healthy subjects; all M; 22–40 y
Acute aerobic exercise: HI, pre-exercise: GXT; No groups
HR, [BDNF]p, lactate, glucose, SaO2, SjvO2, PaCO2
At rest: [BDNF]p arterial < [BDNF]p a-v diff < [BDNF]p vena jug; ƒBDNF = 72 – 32% HI: [BDNF]p arterial › , [BDNF]p vena jug › , [BDNF]p a-v diff › ; [BDNF]p arterial < [BDNF]p a-v diff < [BDNF]p vena jug; ƒBDNF = 84 – 8%
Rojas Vega et al.[63,64] (2006, 2007)
T
8 healthy athletes; all M; 24.6 – 1.3 y
Acute aerobic exercise: LMI and HI, pre-exercise: GXT; No groups
Rojas Vega et al.[65] (2008)
T
11 SCI athletes; all M; 40.6 – 6.3 y
Acute aerobic exercise: LMI and HI, pre-exercise: GXT; No groups
Schiffer et al.[66] (2009)
RCT
27 healthy subjects; NS; 22.2 – 1.8 y
12-wk strength training, 12-wk aerobic training, pre-/posttraining: GXT; Aerobic, strength training and control group
. VO2max, HR, [BDNF]s, [COR]s, lactate, RPEb
. VO2max, HR, [BDNF]s, [IGF-1]s, [PRL]s, [COR]s, lactate
. VO2max, HR, [BDNF]p, [IGF-1]p, lactate
LMI: [BDNF]s fi , [COR]s fi , lactate fi HI: [BDNF]s › , lactate › ; [COR]s › during recovery (10 min and 15 min post-HI)
At restc: [BDNF]s › ; [IGF-1]s, [PRL]s, [COR]s normal LMI: [BDNF]s › , [IGF-1]s › , [PRL]s fi , [COR]s fi HI: [BDNF]s fi , [IGF-1]s › ; [PRL]s › , [COR]s › Wk 12 at rest, strength training: [BDNF]p fi , strength › , [IGF-1]p fl ; aerobic training: [BDNF]p fi , aerobic performance › , [IGF-1]p fl – controls: [BDNF]p fi , [IGF-1]p fl Continued next page
771
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Study (year)
BDNF and Exercise in Humans
ª 2010 Adis Data Information BV. All rights reserved.
Table I. Contd
772
ª 2010 Adis Data Information BV. All rights reserved.
Table I. Contd Study design
Sample size; sex; age (mean – SD)
Intervention; Groups
Outcome measures
Schulz et al.[67] (2004)
RCT
28 MS patients; 32.1% M; 39.5 – 10 y
8-wk aerobic training, pre-/post-training: GXT and LMI; Persons with MS and MS control (no intervention) group
Seifert et al.[68] (2010)
RCT
12 obese subjects; all M; 30.0 – 6.5 y
12-wk aerobic training, pretraining: GXT, pre-/posttraining: LMI and HI; Aerobic training and control group
Stro¨hle et al.[69] (2010)
RCT (crossover)
24 subjects (12 patients with panic disorder, 12 healthy controls); 25% M; 31.4 – 2.4 y
Acute aerobic exercise: LMI; LMI, quiet rest and healthy control group
VASarousal/anxiety, [BDNF]s
At rest: [BDNF]s fl in subjects with panic disorder LMI: [BDNF]s › in subjects with panic disorder, [BDNF]s in healthy controls; [BDNF]s ~ VASarousal/anxiety
Tang et al.[70] (2008)
T
16 healthy subjects; 50% M; 19–30 y
Acute aerobic exercise: LMI; No groups
HR, [BDNF]s
At rest: large inter-individual differences in [BDNF]s; LMI: [BDNF]s ›
Winter et al.[71] (2007)
RCT (crossover)
27 healthy subjects; all M; 22.2 – 1.7 y
Acute aerobic exercise: LMI and HI, pre-exercise: GXT; LMI, HI and control group
HR, [BDNF]s, [DA]p, [NE]p, [E]p, lactate, RPEb, cognitive assessment, mood rating
LMI: [BDNF]s › , [DA]p › , [NE]p › , [E]p › HI: [BDNF]s › , [DA]p › , [NE]p › , [E]p › [BDNF]s: HI › > controls ›
. VO2max, HR, [BDNF]s, [NGF]s, [IL-6]p, [sIL-6R]p, [ACTH]p, [COR]p, [NE]p, [E]p, [lactate]s, assessment of coordinative function, psychological assessment
. VO2max, HR, [BDNF]p arterial and [BDNF]p vena jug, MCA Vmean, CBF
Results Wk 0 after LMI: [BDNF]s › d Wk 8 after LMI (vs rest at wk 8): lactate fl , [BDNF]s › d Wk 8 at rest and after LMI vs wk 0: [BDNF]s fi , [NGF]s fi , [IL-6]p fi , [sIL-6R]p fi , [ACTH]p fi , [COR]p fi , [NE]p fi , [E]p fi ; diseasespecific quality of life › < - > wk 8 at rest and after LMI: [BDNF]s › in MS, but difference with MS control group and assessment at wk 0 was not significant Wk 0 after HI: [BDNF]p arterial › , [BDNF]p vena jug fi ; [BDNF]p vena jug in trained > [BDNF]p vena jug in control; [BDNF]p a-v diff in trained [BDNF]p a-v diff in control Wk 12 at rest: [BDNF]p arterial fi , [BDNF]p vena jug › , [BDNF]p a-v diff › ; [BDNF]p vena jug in trained > [BDNF]p vena jug in control; [BDNF]p a-v diff in trained [BDNF]p a-v diff in control Wk 12 after HI: [BDNF]p arterial fi compared with pre-training after HI; [BDNF]p arterial › compared with post-training at rest; [BDNF]p vena jug fi compared with pre-training after HI and to post-training at rest; [BDNF]p vena jug in trained > [BDNF]p vena jug in control; [BDNF]p a-v diff in trained [BDNF]p a-v diff in control
Continued next page
Knaepen et al.
Sports Med 2010; 40 (9)
Study (year)
Study (year)
Study design
Sample size; sex; age (mean – SD)
Intervention; Groups
Outcome measures
Results [DA]p: HI › = LMI › = controls › [NE]p: HI › > LMI › > controls › [E]p: HI › > controls › Cognitive assessment: 20% better after HI compared with LMI and controls
Yarrow et al.[72] (2010)
RT
20 healthy subjects; all M; 21.9 – 0.8 y
Acute strength exercise: 5-wk strength training; TRAD and ECC+ group
Zoladz et al.[75] (2008)
T
13 healthy subjects; all M; 22.7 – 0.5 y
5-wk aerobic training, pre-/post-training: GXT; No groups
[BDNF]s, [testosterone]s, [growth hormone]s, [lactate]s[73,74]
. VO2max, HR, [BDNF]p, [insulin]p, [glucose]p, [lactate]p
Acute strength exercise (wk 0): [BDNF]s fi in TRAD and ECC+ Strength training, wk 5 at rest: [BDNF]s fi in TRAD and ECC+; wk 5 after strength exercise: [BDNF]s › in TRAD and ECC+ › [BDNF]s from rest to post-strength exercise is 98% greater in post-strength training compared with baseline › [BDNF]s is load dependent
BDNF and Exercise in Humans
ª 2010 Adis Data Information BV. All rights reserved.
Table I. Contd
Wk 0 after GXT: [BDNF]p fi Wk 5 at rest: [BDNF]p › Wk 5 after GXT: [BDNF]p › Wk 5: [BDNF]p › after GXT > [BDNF]p › at rest
a
This is a sex-specific effect of aerobic training versus stretching on [BDNF]p (i.e. group X sex ANOVA, F1,23 = 4.68; p = 0.04).[50]
b
See Borg[76] for the RPE = rating of perceived exertion.
c Rojas Vega et al.[65] did not include a control group of healthy subjects in their study. Consequently, the finding that baseline [BDNF]s is increased compared with able-bodied subjects cannot be verified. d
Schulz et al.[67] found no statistically significant differences at wks 0 and 8 of aerobic training at rest or after LMI between the MS group and the MS control group. The differences that are mentioned in this table are not significant.
773
Sports Med 2010; 40 (9)
ACTH = adrenocorticotropic hormone; BDNF = brain-derived neurotrophic factor; [BDNF]p arterial = [BDNF] measured in arterial plasma; [BDNF]p vena jug = [BDNF] measured in jugular venous plasma; [BDNF]p a-v diff = difference between arterial and jugular venous plasma BDNF concentration; BMI = body mass index; CBF = cerebral blood flow; COR = cortisol; CT = non-randomized controlled trial; DA = dopamine; DemTect = cognitive screening for diagnosis of mild cognitive impairment and dementia ; E = epinephrine; ECC+ = eccentric-enhanced resistance exercise/training; ECG = electrocardiogram; F = female; FBG = fasting blood glucose; ƒBDNF = cerebral fractional release of BDNF; G-CSF = granulocyte colony stimulating factor; GXT = graded exercise test; HAMD-scale = Hamilton rating scale for depression; HbA1c = glycated hemoglobin A1c; HDL = high density lipoprotein; HI = high-intensity exercise; HiMF = high metabolic risk group; HPA-index = Baecke habitual physical activity index; HR = heart rate; IGF-1 = insulin-like growth factor-1; IGFBP-3 = insulin-like growth factor binding protein 3; IL = interleukin; LMI = low to moderate intensity exercise; LoMF = low metabolic risk group; M = male; MADRSscore = Montgomery-Asberg depression rating scale; MCA Vmean = mean flow velocity of middle cerebral artery; MCI = mild cognitive impairment; MDD = major depressive disorder; MEE = movement-related energy expenditure; MetS = metabolic risk factor; MMSE = mini-mental status examination; MRI = magnetic resonance imaging; MS = multiple sclerosis; NE = norepinephrine; NGF = neuronal growth factor; NS = not specified; PaCO2 = arterial carbon dioxide tension; PRL = prolactin; RCT = randomized controlled trial; ROS = retrospective observational study; RPE = rating of perceived exertion; RT = randomized non-controlled trial; SaO2 = arterial haemoglobin oxygen saturation; SCI = spinal cord injured; TG = triglycerides; SjvO2 = jugular venous haemoglobin oxygen saturation; T = non-randomized non-controlled trial; TC = cholesterol; TEE = total daily energy expenditure; . TH = threshold; TRAD = traditional resistance exercise/training; VASarousal/anxiety = visual analogue scale for arousal and anxiety; Vth = ventilator threshold; VO2max = maximal oxygen . uptake; VO2peak = peak oxygen uptake; WC = walking count; WHR = waist-to-hip ratio; []s indicates serum concentration; []p indicates plasma concentration; ~ indicates correlation; › indicates significant increase; fl indicates significant decrease; fi indicates no significant difference.
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2.2 Study Populations
The sample size of trials that were included in this review varied from 8[62-64] to 55[59] subjects with a mean sample size of 24 subjects. For the four retrospective observational studies, sample sizes were larger, ranging from 26[61] and over 44[53] and 75[55] to 85[52] subjects. Proof of evidence would become more solid if all studies included an a priori power analysis to determine the appropriate sample size. Study populations were drawn from several sources; for example, general population,[47,54,57,60,66] students,[66] athletes,[56,63,64] spinal cord injured (SCI) athletes,[65] persons with major depression,[58,59] cognitive impairment[50] or MS.[47,51,67] Thirteen studies examined both males and females,[47,50-55,57-58,60,67,69-70] while nine studies examined only males[56,61-65,68,71-72,75] and one study only females.[59] The mean age of participants in all the included studies ranged from 20.8 – 0.6 years[57] to 70.0 – 8.3 years.[50] Three studies examined a population of the elderly (i.e. mean age ‡55.0 years)[50,55,59] and no study that included children or adolescents (i.e. mean age £18.0 years). Lommatzsch et al.[77] showed that basal concentrations of BDNF significantly changes with increasing age. Katoh-Semba et al.[78] stated that children and adolescents could be prone to changes in neurotrophines due to maturation and growth. Therefore, it might be interesting to study possible differences in effects of acute exercise and training on peripheral concentration of BDNF between young and old healthy subjects or in young and old persons with a chronic disease or disability. In most of the included studies, it is not always clear whether it concerns untrained, moderately trained or well trained subjects. Studies should report on the level of. fitness, expressed in maximal oxygen uptake (VO2max) or maximal power output, of their study population. It is likely that the effects of acute exercise and training on peri-
pheral BDNF depend on the physical fitness of the subjects, as BDNF could be involved in processes of energy metabolism.[37,40,79] 2.3 Exercise Protocols
Twenty out of 24 studies applied an exercise intervention. In general, four different interventions can be distinguished as follows: an acute aerobic or strength exercise; and an aerobic or strength training programme. 2.3.1 Acute Exercise Protocols
Predominantly, the effect of an acute aerobic exercise on peripheral BDNF has been investigated in human subjects. However, there is a large variation in the protocols used to apply to an acute aerobic exercise intervention (tables II and III). Graded exercise tests (GXTs) should be distinguished from acute aerobic exercise protocols of long or short duration. Sixteen of 20 interventional studies carried out a GXT until exhaustion a few days prior to the intervention or as an intervention on its own. In these studies, GXTs are mainly performed to determine the intensity of an acute aerobic exercise or training protocol. In three studies, a GXT was used as an isolated intervention to study its effect on circulating concentrations of BDNF.[54,59,75] In these cases, a GXT is evaluated as a short acute exercise of high intensity (table III). In two studies a GXT was part of a prolonged acute exercise protocol of high intensity1.[55,62,63] Protocols of all GXTs can be found in table II. Fifteen of 20 studies applied an acute aerobic exercise intervention (table III). Seven of those studies (table III) investigated the effect of both low to moderate and high-intensity aerobic exercises,[54,56,58,63-65,68,71] five studies focused only on exercises of low to moderate intensity[47,51,67,69,70] and three on the effects of an isolated high-intensity exercise[59,62,75] on concentration of BDNF. The protocols of the acute exercise interventions differ in each study, which makes it difficult to
1 It should be noted that in the studies of Rojas Vega et al.[63,64] and Gustafsson et al.,[58] an acute exercise of low to moderate intensity preceded the GXT. This could influence the effect of a GXT on peripheral BDNF levels. The preceding exercise of low to moderate intensity, together with the GXT, has also been evaluated as a prolonged acute exercise protocol of high intensity and will be discussed in section 2.6.1.
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Sports Med 2010; 40 (9)
Study (year)
GXT
Exercise
GXT protocol
GXT until exhaustion (mean maximal exercise values at baseline)
BDNF measured pre- and post-GXT
Acute aerobic exercise protocols Castellano and White[51] (2008)
Yes
Cycling
NS + 5–20 W every 2 min
Yes (NS: symptom-limited maximum or 85% of estimated HRmax)
No
Ferris et al.[54] (2007)
Yes
Cycling
NS
WRmax (293.47 – 17.65 W); . VO2max (2805.80 – 164.31 mL/min); HRmax (175.67 – 3.19 bpm), % pred HRmax (90.31 – 1.75 %); RER (1.27 – 0.02); lactate (10.67 – 0.66 mmol/L)
Yes ›
No
Goekint et al.[56] (2008)
Yes
Cycling
80 W + 40 W every 3 min
Yes (NS)
Gold et al.[47] (2003)
Yes
Cycling
25 W + 25 W every 2 min
Yes (NS)
No
Gustafsson et al.[58] (2009)
Yes
Cycling
50 W (30 W F) + 5 W every 20 s (30 s F)
Yes (NS)
Yes › a,b
Laske et al.[59] (2010)
Yes
Treadmill
3 km/h at 0% inclination + simultaneous › in speed and inclination every 3 minc
. VO2max (1.9 – 0.3 mol/L/min); Wmax/kg (1.3 – 0.4 W/kg)
Yes › d
Rasmussen et al.[62] (2009)
Yes
Rowing
NS
Yes (NS)
No
Rojas Vega et al.[63,64] (2006, 2007)
Yes
Cycling
NS + 40 W every 5 min
Yes › a
Rojas Vega et al.[65] (2008)
Yes
Handcycling
20 W + 20 W every 5 min
Time test (7.3 – 1.1 min); Wpeak (431.3 – 57.9 W); relative Wpeak (5.9 – . 0.7 W/kg); VO2max (56.6 – 8.6 mL/kg/min); HRmax (189.3 – 10.3 bpm) . Wmax (158.2 – 28.9 W); HRmax (183 – 11.8 bpm); VO2max (34.5 – 9.2 mL/kg/min); RPEmax (19.5 – 1.2)
BDNF and Exercise in Humans
ª 2010 Adis Data Information BV. All rights reserved.
Table II. Protocols for graded exercise tests (GXTs) until volitional fatigue prior to or following an acute exercise or training protocol
No
Stro¨hle et al.[69] (2010)
No
NS
NS
NS
NS
Tang et al.[70] (2008)
No
NS
NS
NS
NS
Winter et al.[71] (2007)
Yes
Running (field)
8 km/h + 2 km/h every 3 min
Yes (NS)
No
Acute strength exercise protocols Goekint et al.[57] (2010)
No
NS
NS
NS
NS
Yarrow et al.[72] (2010)
No
NS
NS
NS
NS
Baker et al.[50] (2010)
Pre/post
Treadmill walking
2 km/h + NSe
. VO2peak (22.95 – 4.35 mol/L/kg)
No
Castellano and White[51] (2008)
Pre
Cycling
NS + 5–20 W every 2 min
Yes (NS: symptom-limited maximum or 85% of estimated maximum heart rate)
No
Yes (NS: RER >1.1; HR >190; lactate > 8) . Wmax (168.8 – 40.5 W); VO2max (31.0 – 7.45 mL/kg/min) . VO2max (3.45 – 0.3 L/min); RER >1.14 . VO2max (3472 – 94 ml/min [or 45.29 – 0.93 mL/kg/min]); Wmax (255 – 7 W)
No
Aerobic training protocols
Pre/post
Running
7 km/h + 1.5 km/h; NS
Schulz et al.[67] (2004)
Pre/post
Cycling
25 W + 25 W every 2 min
Seifert et al.[68] (2010)
Pre
Cycling
75 W + 25 W every 1 min
Zoladz et al.[75] (2008)
Pre/post
Cycling
30 W + 30 W every 3 min
No No Yes fi
Continued next page
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Schiffer et al.[66] (2009)
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ª 2010 Adis Data Information BV. All rights reserved.
% pred HRmax = percentage of predicted maximal heart rate; BDNF = brain-derived neurotrophic factor; bpm = beats per minute; F = female; HI = exercise of high-intensity; HR = heart . rate; HRmax = maximal heart rate; M = male; NS = not specified; RER = respiratory exchange ratio; RPEmax = maximal rating of perceived exertion[82]; VO2max = maximal oxygen uptake; . VO2peak = peak oxygen uptake; Wmax = maximal power output; WRmax = maximal work rate; › indicates significant increase; fi indicates no significant difference.
d Significant increase in [BDNF]s in MDD patients following a GXT but not in healthy control subjects (Laske et al.[59]).
e Baker et al.[50] used the modified Balke test[81] for their aerobic training protocol.
Significant increase in [BDNF]p in M and F MDD patients and healthy M control subjects following a GXT but not in healthy F control subjects (Gustaffson et al.[58]). b
c Laske et al.[59] used the same protocol as Porszasz et al.[80] for the acute aerobic exercise protocol.
NS NS NS NS No
In the studies of Gustaffson et al.[58] and Rojas Vega et al.,[63,64] the GXT was preceded by an acute aerobic exercise of moderate intensity, so the increase in BDNF may not be exclusively contributed to the effect of a GXT on its own. Protocols of both studies will be considered as a prolonged acute aerobic exercise protocol of high-intensity exercise and will be described in table III.
Yarrow et al.[72] (2010)
a
No Yes (NS: RER >1.1; HR >190; lactate >8) 7 km/h + 1.5 km/h every NS Pre/post Schiffer et al.[66] (2009)
Running
NS
NS
NS
NS
NS
NS
NS No
No Levinger et al.[60] (2008)
Strength training protocols
NS
Exercise GXT Study (year)
Table II. Contd
Goekint et al.[57] (2010)
BDNF measured pre- and post-GXT GXT protocol
GXT until exhaustion (mean maximal exercise values at baseline)
776
compare between studies. Nevertheless, all studies could be categorized according to their exercise intensity (i.e. based on exercise load and duration) [table III]. In four studies the acute exercise intervention was part of the test protocol before and after an aerobic training programme. The effect of an aerobic training programme on the BDNF response from rest to the end of a standardized acute exercise of low, moderate or high intensity was studied.[51,67,68,75] Recently, the relation between an acute strength exercise session and concentration of BDNF was researched in two studies.[57,72] Goekint et al.[57] and Yarrow et al.[72] used an acute strength exercise session to analyse the change in BDNF from rest to immediately post-exercise and this was repeated at the end of a strength training programme. Table III shows that the moments of blood acquisition for analysis of BDNF are similar in most of the 16 studies on acute exercise: (i) at baseline; (ii) immediately following a low-, moderate- or high-intensity strength or aerobic exercise; and (iii) 15-60 minutes following the acute exercise. In two cases blood was not collected immediately following the acute exercise[51,70] and only Castellano and White[51] collected blood more than 60 minutes following the acute exercise. 2.3.2 Exercise Training Protocols
Six studies implemented an aerobic training programme ranging from 5 to 24 weeks, two to seven sessions a week of different loads, mode and duration.[50,51,66-68,75] Except for Baker et al.[50] and Schiffer et al.,[66] all studies on aerobic training investigated the effects of training on basal concentration of BDNF and on BDNF concentration following an acute exercise. Details on the aerobic training programme can be found in table IV. A strength training programme was conducted in four studies during 5, 10 or 12 weeks, respectively, three sessions a week of different intensity and repetitions.[57,60,66,72,83] Goekint et al.[57] and Yarrow et al.[72] studied the effects of strength training on basal concentration of BDNF and on BDNF concentration following an acute strength exercise session. A complete body workout with strength training devices was Sports Med 2010; 40 (9)
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Table III. Protocols for acute aerobic and strength exercise interventions in 17 studies (i.e. acute exercise protocols, not graded exercise tests [GXTs]) Study (year)
Setting
Exercise
Protocol
Moment of BDNF collection before, during and after the acute exercise
Acute aerobic exercise protocols LMI Castellano and White[51] (2008)
Laboratory
Cycling
. 30 min at 60% VO2peak
T0 // T30, T120, T180 post-LMI
Gold et al.[47] (2003)
Laboratory
Cycling
. 30 min at 60% VO2max
T0 // T0, T30 post-LMI
Schulz et al.[67] (2004)
Laboratory
Cycling
. 30 min at 60% VO2max
T0 // T0, T30 post-LMI
Stro¨hle et al.[69] (2010)
Laboratory
Walking
. 30 min at 70% VO2max
T0 // T0 post-LMI
Tang et al.[70] (2008)
Laboratory
Stepping
15 min
T0 // T10, T35 post-LMI
Ferris et al.[54] (2007)
Laboratory
Cycling
LMI: 30 min at Vth - 20% HI: 30 min at Vth + 10% GXT (see table II)
T0 // T0 post-LMI and -HI
Goekint et al.[56] (2008)
Climatic chamber
Cycling
LMI: 60 min at 55% Wmax HI: LMI + TT equal to 30 min at 75% Wmax
T0, T60 // T0, T15 post-HI
Gustafsson et al.[58] (2009)
Laboratory
Cycling
LMI in F: (30 W + 5 W every 30 s) + 6 min at Wconstant HI in F: LMI + GXT until exhaustion LMI in M/HI in M: idem as in F but with different intensity: 50 W + 5 W every 20 s
T0 // T0 post-LMI; T0, T30, T60 post-HI
Rojas Vega et al.[63,64] (2006, 2007)
Laboratory
Cycling
LMI: 10 min at 2 W/kg + 2 min at 2 W/kg HI: LMI + GXT with 25 W every 30 s until exhaustion + 15 min active recovery
T0, T10 // T0, T3, T6, T10, T15 postHI
Rojas Vega et al.[65] (2008)
Laboratory
Handcycling
T0, T10 // T0 post-HI
Seifert et al.[68] (2010)
Laboratory
Cycling
LMI: 10 min warm up at 54% HRmax HI: LMI + TT over 42 km at 89% HRmax . LMI: 15 min at 70% VO2max . . HI: 60%VO2max with 10% VO2max every 4 min (6 min . rest between workloads until 100% VO2max)
Winter et al.[71] (2007)
Laboratory
Running
LMI and HI
LMI: 40 min at fixed individual HR and lactate <2 mM/L HI: 3 min sprint – 2 min rest – 3 min sprint at 8 km/h and every 10 s + 2 km/h until exhaustion and lactate >10 mmol/L
T0, T5, T10, T15 // and at the end of each workload during incremental cycling T0 // T0 post-HI // T0 post-learning task
HI Laske et al.[59] (2010) Rasmussen et al.[62] (2009)
See table II (GXT) Laboratory
Rowing
Zoladz et al.[75] (2008)
240 at 10–15% below LT
T0, T120 // T0, T60 post-HI
See table II (GXT)
Acute strength exercise protocols Goekint et al.[57] (2010)
Fitness centre
6 strength exercises
Warm up: 20 repetitions at 30% 1RM Exercise: 3 · 10 repetitions at 80% 1RM
T0 // T0 post-strength training session both in UC and TC Continued next page
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Table III. Contd Study (year)
Setting
Exercise
Protocol
Moment of BDNF collection before, during and after the acute exercise
Yarrow et al.[72] (2010)
Laboratory (NS)
2 strength exercises per group
TRAD group: 4 · 6 repetitions at 52.5% 1RM concentrically and eccentrically ECC+ group: 3 · 6 repetitions at 40% 1RM concentrically and 100% 1RM eccentrically
T0 // T1, T30 and T60 post-strength exercise
1RM = one repetition maximum; BDNF = brain-derived neurotrophic factor; ECC+ = eccentric-enhanced resistance exercise/training; F = female; HI = exercise of high-intensity; HR = heart rate; HRmax = maximal HR; LMI = exercise of low to moderate intensity; LT = lactate threshold; M = male; NS = not specified; T = moment of BDNF collection e.g. T120 = at 120 minutes following the start of the acute exercise or T60 post HI = 60 minutes following the end of the high-intensity exercise; TC = trained condition (at 30th strength training session); TT = time trial; TRAD = traditional resistance exercise/training; UC = untrained condition (at sixth strength training session); Vth = ventilatory threshold; . . VO2max = maximal oxygen uptake; VO2peak = peak oxygen uptake; Wconstant = constant power output; Wmax = maximal power output; [] indicates concentration; // separates moments of BDNF collection in time e.g. T0 // T0 post HI = T0 is at the start of the high intensity exercise, T0 post HI is the first BDNF collection immediately at the end of the high intensity exercise; so ‘//’ separates moments of BDNF collection during and following an acute exercise.
accomplished in three out of four strength training studies.[57,60,66] Only Yarrow et al.[72] used just two strength exercises for the workout. In all studies circulating BDNF was analysed pre-/posttraining and in two cases also halfway through the training programme.[50,51] Overall, training protocols differed in all studies (table IV). 2.4 Blood Sampling and Biochemical Analysis
For the analysis of free circulating peripheral BDNF, blood serum (16 studies) is preferred to that of blood plasma (eight studies). This could be due to the fact that blood serum has been the conventional standard for most biochemical analysis although, generally, the choice between blood serum and plasma is determined by the requirements of the individual laboratory. In some studies, preference is given to blood serum because the addition of anticoagulants (e.g. heparin or EDTA) in blood plasma can activate blood platelets and change the concentration of the constituents to be measured.[84,85] Concentrations of serum BDNF are approximately 200fold higher relative to those of plasma BDNF, indicating that low concentrations of BDNF are circulating free in the blood and higher amounts of BDNF are stored in platelets or in immune cells.[86,87] Moreover, platelets circulate for up to 11 days in peripheral blood, whereas BDNF protein circulates in plasma for <1 hour, indicating that platelets could be a storage compartment and its BDNF could represent a long-term marª 2010 Adis Data Information BV. All rights reserved.
ker of varying plasma BDNF concentrations.[87,88] To finally unravel the link between plasma and serum BDNF, measurement of both plasma and serum BDNF could be interesting in future studies. Table V provides an overview of the biochemical analysis of BDNF throughout the 24 studies. Methods for biochemical analysis of BDNF in venous blood samples were very heterogeneous and poorly described in most of the studies. Details of the blood sample collection and the preparation and storage of serum or plasma are generally not clarified enough in the materials and methods of the given studies. Yet, it is important to report accurately on the methodology used in order to interpret the given results because methodological factors could strongly influence measured BDNF values. When serum is being used, time to clot and temperature of clotting is often not mentioned. However, KatohSemba et al.[78] showed that BDNF in serum is gradually released from platelets at 4C, while at room temperature of 26C it immediately degrades. Moreover, a maximum concentration of BDNF could be found 24 hours after blood collection and remained stable until 42 hours.[78] This indicates the importance of the time the blood is left to clot prior to serum extraction and the temperature at which clotting occurs. A study of Trajkovska et al.[89] showed a decreased BDNF concentration in whole blood stored at 4C but not at -20C, whereas storage at -20C of blood serum was associated with a significant decrease in BDNF concentration over time (i.e. after 6–10 Sports Med 2010; 40 (9)
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Table IV. Protocols for aerobic and strength training interventions in nine studies Study (year)
Exercise mode
Duration
Protocol
GXT
Standardized acute exercise
Moment of BDNF collection during the training period
45-60 min at 75–85% HRreserve
Pre- and post-training
NS
At 0, 12 and 24 wk at rest
. 30 min at 60% VO2peak
Pre-training
Pre-, mid- and post-training
At 0, 4 and 8 wk at rest and T30, T120 and T180 post-LMI
Aerobic training protocols Baker et al.[50] (2010)
Treadmill, cycling ergometer, elliptical trainer
4 ·/wk for 24 wk
Castellano and White[51] (2008)
Cycling
3 ·/wk for 8 wk
Schiffer et al.[66] (2009)
Running
3 ·/wk for 12 wk
45 min at 80% HR of aerobicanaerobic threshold
Pre- and post-training
NS
At 0 and 12 wk at rest
Schulz et al.[67] (2004)
Cycling
2 ·/wk for 8 wk
30 min interval training at maximum 75% Wmax and . 60% VO2max
Pre- and post-training
Pre- and posttraining
At 0 and 8 wk at rest and T0 and T30 post-LMI
Seifert et al.[68] (2010)
Cycling, swimming, running or rowing
7 ·/wk for 12 wk
60 min at 70% of HRmax or . 65% of VO2max
Pre-training
Pre- and posttraining
At 0 and 12 wk at rest and post-HI
Zoladz et al.[75] (2008)
Cycling
4 ·/wk for 5 wk
2 ·/wk 40 min at PO of 90% . VO2 at LT; 2 ·/wk 4 · 6 min unloaded + 3 min loaded at 50% D (= PO at LT + 0.5 [POmax + POLT])
Pre- and post-training
NS
At 0 and 5 wk at rest and post-GXT
Strength training protocols Goekint et al.[57] (2010)
Complete body workout with strength training devices
3 ·/wk for 10 wk
0–2 wk: warm-up 20 repetitions at 30% 1RM; 3 · 10 repetitions at 50–70% 1RM; 2–10 wk: warm-up 20 repetitions at 30% 1RM; 3 · 10 repetitions at 80% 1RM
NS
Pre-a and posttraining
At 0 and 10 wk at rest and T0 poststrength exercise
Levinger et al.[60] (2008)
Complete body workout with strength training devices
3 ·/wk for 10 wk
0–2 wk: 2 · 15–20 repetitions at 40–50% 1RM; 2–10 wk: 3 · 8–20 repetitions at 50–85% 1RM
NS
NS
At 0 and 10 wk at rest
Schiffer et al.[66] (2009)
Complete body workout with strength training devices
3 ·/wk for 12 wk
3 · 8–10 repetitions at 70–80% 1RM
Pre- and post-training
NS
At 0 and 12 wk at rest
Yarrow et al.[72] (2010)
2 strength exercises with strength training devices
3 ·/wk for 5 wk
TRAD group: 4 · 6 repetitions at 52.5–75% 1RM concentrically and eccentrically; ECC+: 3 · 6 repetitions at 40–50% 1RM concentrically and 100–120% 1RM eccentrically
NS
NS
At 0 and 5 wk at rest and T1, T30 and T60 poststrength exercise
a
The first assessment of BDNF following a standardized acute strength exercise took place on the sixth session of the strength training programme instead of the first session. Goekint et al.[57] considered the sixth training session as the ‘untrained condition’ so that subjects were capable of completing the training session.
1RM = 1 repetition maximum; BDNF = brain-derived neurotrophic factor; ECC+ = eccentric-enhanced resistance exercise/training; GXT = graded exercise test; HR = heart rate; HRmax = maximal HR; HRreserve = heart rate reserve; LT = lactate threshold; NS = not specified; PO = power collection e.g. T60 output; POLT = power output at lactate threshold; POmax = maximal power output; T = moment of BDNF . . post HI = 60 minutes . following the end.of the high-intensity exercise; TRAD = traditional resistance exercise/training; VO2 = oxygen uptake; VO2max = maximal VO2; . VO2peak = peak VO2; Wmax = maximal power output; ·/wk = sessions per week; [] indicates concentration; D indicates PO at LT + 0.5 (POmax + POLT).
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months). These results suggest that when BDNF is stored in platelets, it is protected from degradation.[89] When plasma is being used, the type of anticoagulant that is added to the collection tubes is not clarified and only one study corrected plasma BDNF for platelet reactivity.[50] However, Schneider et al.[85] pointed out that some anticoagulants (i.e. EDTA) may activate blood platelets and thus influence the concentration of plasma BDNF ex vivo. Rasmussen et al.[62] and Seifert et al.[68] centrifuged blood plasma a second time to ensure that platelets were spun down and thus removed from the surfactant. Nevertheless, to ascertain plasma BDNF is not influenced by BDNF stored in platelets, a correction for platelet reactivity is recommended. For both plasma as well as serum, details of centrifugation are lacking in 12 studies and details of storage temperature after centrifugation are missing in eight studies. In the studies of Gold et al.[47] and Schulz et al.,[67] blood serum was analysed for BDNF; nevertheless, they report on the use of heparinized tubes for the collection of blood samples. As a result, it is not clear whether they analysed serum or plasma BDNF. Additionally, only two of the 24 studies[71,72] reported on corrections of BDNF concentrations for changes in serum or plasma volume following acute exercise or training. BDNF values could change due to haemoconcentration following acute exercise or pseudo anemia following training.[90,91] Kargotich et al.[92,93] pointed out that moderate to intense exercise results in a decrease of blood volume or also haemoconcentration. As a result, changes in blood solutes after exercise or training could represent an inherent change in haemoconcentration due to shifts in blood volume instead of a real exercise-induced change in BDNF concentration.[92,93] Future studies should present corrected serum and plasma BDNF concentrations (i.e. corrected for the shift in plasma volume by the formula of Van Beaumont and colleagues[94]). In all studies, the diagnostic biochemical technique used to detect BDNF in blood serum or plasma is the ELISA. Trajkovska et al.[89] showed that ELISA-kits (ChemiKine; Millipore, Billerica, MA, USA) are an accurate, valid and reª 2010 Adis Data Information BV. All rights reserved.
producible analysis tool for peripheral BDNF. ELISA-kits of different manufacturers were used and details on the sensitivity of the assay or intraand interassay variations were not always given (table V). Guidelines on how to handle the samples from collection until analysis or on storage conditions are not provided in the manuals of any of the kits. With regard to the biochemical analysis of BDNF, laboratories and/or manufacturers of analysis kits should reach a uniform consensus on the peripheral assessment of BDNF from the collection of blood until the analysis with ELISA. Meanwhile, researchers should repeatedly use uniform collection and analysing techniques within their own laboratories. 2.5 Basal Concentrations of BDNF 2.5.1 Healthy Subjects
For serum, basal BDNF concentrations in healthy subjects range from 1.5[55] to 30.9 ng/mL throughout the 24 studies.[70] Literature confirms that basal values of serum BDNF in healthy subjects (non-athletes) vary extremely.[77,86,95-99] Values could be influenced by different factors such as diurnal fluctuations, physical fitness, age, sex, bodyweight, nutrition and possible neurological, immunological or metabolic disorders.[77,100] A remarkable finding is that basal serum BDNF values in the studies of Floe¨l et al.[55] 1.5 – 0.5 ng/mL, Currie et al.[53] (7.2 – 2.7 ng/mL), Gold et al.[47] (4.7 – 0.5 ng/mL) and Rojas Vega et al.[63,64] (5.8 – 1.9 ng/mL), were low compared with values in all other studies. The study of Rojas Vega et al.[63,64] concerned recreational athletes and the study of Currie et al.[53] included predominantly subjects engaged in some level of recreational and sportbased activity. Two other studies confirm that basal BDNF concentrations in athletes could be lower than in untrained subjects,[52,61] while the studies of Zoladz et al.[75] and Seifert et al.[68] disagree with this. A lower level of BDNF in trained subjects and athletes could indicate that BDNF clearance in trained subjects or athletes is more effective (i.e. a higher disappearance rate), with less stored or circulating BDNF in the periphery as a result. Alternatively, plasma volume increases by 10–20% following regular physical training, Sports Med 2010; 40 (9)
Analysis kit (manufacturer)
Sample
Time to clot (min)
Clotting temp.
Centrifugation
Storage temp. after centrifugation (C)
Sensitivity of assay
Intra-assay; inter-assay variations (%)a
Corrected for change in plasma volume
[BDNF]; mean – SD (mean – SE)
Acute aerobic exercise protocols ELISA (ChemiKine, Millipore, Temecula, CA, USA)
Serum
NS
NS
1300 g for 12 min
-80
7.8–500 pg/mL
3.7 [1.7]b; 8.5
NS
Pre-exercise: 18.17 (– 1.19 ng/mL)
Goekint et al.[56] (2008)
ELISA (ChemiKine, Millipore, Temecula, CA, USA)
Serum
60
Room temp.
NS
-80
7.8-500 pg/mL
NS
NS
Pre-exercise in placebo controls: 17.12 (– 3.45 ng/mL) Pre-exercise in reboxetine group: 18.36 (– 3.20 ng/mL)
Gold et al.[47] (2003)
ELISA (Promega, Madison, WI, USA)
Serum (NS)
NS
NS
NS
NS
1 pg/mL
NS
NS
Pre-exercise in healthy controls: 4.72 – 0.49 ng/mL Pre-exercise in MS: 4.44 – 0.53 ng/mL
Gustafsson et al.[58] (2009)
ELISA (ChemiKine, Millipore, Temecula, CA, USA)
Plasma
NS
Ice cooled
3000 rpm for 10 min at 4C
-70
NS
<15; <15
NS
Pre-exercise in healthy controls: 299 pg/mL Pre-exercise in MDD: 427 pg/mL T0 post-LMI exercise in healthy controls: 664 pg/mL T0 post-LMI exercise in MDD: 602 pg/mL T0 post-HI exercise in healthy controls: 1239 pg/mL T0 post-HI exercise in MDD: 1135 pg/mL T60 post-HI exercise in healthy controls: 457 pg/mL T60 post-HI exercise in MDD: 790 pg/mL Continued next page
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ª 2010 Adis Data Information BV. All rights reserved.
Table V. Biochemical analysis of blood samples for determination of plasma and/or serum brain-derived neurotrophic factor (BDNF) Study (year)
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Table V. Contd Analysis kit (manufacturer)
Sample
Time to clot (min)
Clotting temp.
Centrifugation
Storage temp. after centrifugation (C)
Sensitivity of assay
Intra-assay; inter-assay variations (%)a
Corrected for change in plasma volume
[BDNF]; mean – SD (mean – SE)
Laske et al.[59] (2010)
ELISA (R&D Systems, Minneapolis, MN, USA)
Serum
<30
Ice cooled
2500 g for 30 min at 4C
-20
NS
NS; <10
NS
Rasmussen et al.[62] (2009)
ELISA (R&D Systems, Minneapolis, MN, USA)
Plasma
NS
NS
2600 g for 15 min at 4C; 10 000 g for 10 min at 4Cc
-80
NS
NS
NS
Rojas Vega et al.[63,64] (2006, 2007)
ELISA (ChemiKine, Millipore, Temecula, CA, USA) ELISA (ChemiKine, Millipore, Temecula, CA, USA) ELISA (Promega, Madison, WI, USA)
Serum
NS
NS
3000 rpm for 10 min at 4C
-70
7.8–500 pg/mL
3.7; 8.5
NS
Pre-exercise in healthy controls: 30.5 – 6.9 ng/mL Pre-exercise in MDD: 24.4 – 6.1 ng/mL T0 post-exercise in healthy controls: 31.0 – 8.1 ng/mL T0 post-exercise in MDD: 28.5 – 7.3 ng/mL T30 post-exercise in healthy controls: 26.7 – 7.2 ng/mL T30 post-exercise in MDD: 21.4 – 7.1 ng/mL Pre-exercise ([BDNF]vena jug): 442 – 272 pg/mL Pre-exercise ([BDNF]p a-v diff): -347 – 316 pg/mL T0 post-exercise ([BDNF]vena jug): 1172 – 968 pg/mL T0 post-exercise ([BDNF]p a-v diff): -902 – 876 pg/mL Pre-exercise: 5.79 – 1.9 ng/mL
Serum
NS
NS
4000 rpm for 10 min at 4C
-70
7.8–500 pg/mL
3.7; 8.5
NS
Pre-exercise in SCI: 37.2 – 19.8 ng/mL
Serum
NS
NS
NS
NS
1 pg/mL
– 6.7; – 34.1
NS
NS
Rojas Vega et al.[65] (2008)
Stro¨hle et al.[69] (2010)
Continued next page
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Sports Med 2010; 40 (9)
Study (year)
Study (year)
Analysis kit (manufacturer)
Sample
Time to clot (min)
Clotting temp.
Centrifugation
Storage temp. after centrifugation (C)
Sensitivity of assay
Intra-assay; inter-assay variations (%)a
Corrected for change in plasma volume
[BDNF]; mean – SD (mean – SE)
Tang et al.[70] (2008)
ELISA (Promega, Madison, WI, USA)
Serum
NS
NS
NS
NS
NS
NS
NS
Pre-exercise: 30.9 ng/mL T25 post-exercise: 34.5 ng/mL T50 post-exercise: 31.0 ng/mL
Winter et al.[71] (2007)
ELISA (R&D Systems, Minneapolis, MN, USA)
Serum
NS
NS
NS
NS
NS
NS
Yes
NS
BDNF and Exercise in Humans
ª 2010 Adis Data Information BV. All rights reserved.
Table V. Contd
Acute strength exercise protocols Goekint et al.[57] (2010)
ELISA (ChemiKine, Millipore, Temecula, CA, USA)
Serum
60
Room temp.
1300 g for 12 min at 4C
-80
7.8–500 pg/mL
– 3.5; – 8.5
NS
Pre-exercise in UC: 15.2 – 0.8 ng/mL Pre-exercise in TC: 15.7 – 0.6 ng/mL Post-exercise in UC: 15.7 – 1.0 ng/mL Post-exercise in TC: 15.5 – 1.0 ng/mL
Yarrow et al.[72] (2010)
ELISA (R&D Systems, Minneapolis, MN, USA)
Serum
NS
NS
3000 g for 12 min
-80
20 pg/mL
<6.2; NS
Yes
Pre-exercise: 23.3 – 1.8 ng/mL Post-exercise: 30.8 ng/mLd
Aerobic training protocols ELISA (Promega, Madison, WI, USA)
Plasma
NS
NS
NS
NS
NS
NS
NS
NS
Castellano and White[51] (2008)
ELISA (R&D Systems, Minneapolis, MN, USA)
Serum
NS
NS
3000 g for 15 min at 4C
-80
<20 pg/mL
8; 5
NS
Healthy controls at rest: 20.15 ng/mL; MS at rest: 10.05 ng/mL
Continued next page
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ª 2010 Adis Data Information BV. All rights reserved.
Table V. Contd Analysis kit (manufacturer)
Sample
Time to clot (min)
Clotting temp.
Centrifugation
Storage temp. after centrifugation (C)
Sensitivity of assay
Intra-assay; inter-assay variations (%)a
Corrected for change in plasma volume
[BDNF]; mean – SD (mean – SE)
Schiffer et al.[66] (2009)
ELISA (ChemiKine, Millipore, Temecula, CA, USA)
Plasma
NS
NS
3000 rpm for 10 min at 4C
-70
NS
NS
NS
Pre-training at rest: 128.4 – 90.2 pg/mL Post-training at rest: 102.6 – 66.2 pg/mL Pre-training controls at rest: 102.2 – 108.7 pg/mL Post-training controls at rest: 98.9 – 78.6 pg/mL
Schulz et al.[67] (2004)
ELISA (Promega, Madison, WI, USA)
Serum
NS
NS
NS
NS
1 pg/mL
NS
NS
Pre-training in MS at rest: 4.35 – 3.22 ng/mL Post-training in MS at rest: 5.93 – 5.18 ng/mL Pre-training in control MS at rest: 5.08 – 2.31 ng/mL Post-training in control MS at rest: 4.20 – 2.07 ng/mL
Seifert et al.[68] (2010)
ELISA (R&D Systems, Minneapolis, MN, USA)
Plasma
NS
NS
2600 g for 15 min at 4C; 7500 g for 10 min at 4Cc
-80
NS
NS
NS
[BDNF]arterial: Pre-training at rest: 1.2 – 0.6 ng/mL; posttraining at rest: 1.0 – 0.3 ng/mL; pre-training after HI: 2.4 – 1.3 ng/mL; post-training after HI: 2.0 – 0.9 ng/mL [BDNF]vena jug: Pre-training at rest: 2.5 – 2.4 ng/mL; post-training at rest: 5.5 – 2.3 ng/mL; pre-training after HI: 4.4 – 2.4 ng/mL; post-training after HI: 5.9 – 3.9 ng/mL Continued next page
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Sports Med 2010; 40 (9)
Study (year)
Study (year)
Analysis kit (manufacturer)
Sample
Time to clot (min)
Clotting temp.
Centrifugation
Storage temp. after centrifugation (C)
Sensitivity of assay
Intra-assay; inter-assay variations (%)a
Corrected for change in plasma volume
[BDNF]; mean – SD (mean – SE)
Zoladz et al.[75] (2008)
ELISA (Phoenix Pharmaceuticals Inc., Burlingame, CA, USA)
Plasma
NS
NS
NS
NS
7.8–500 pg/mL
<10; <12
NS
Pre-training at rest: 10.3 (– 1.4 pg/mL) Post-training at rest: 16.8 (– 2.1 pg/mL) Pre-training after GXT: 10.9 (– 2.3 pg/mL) Post-training after GXT: 68.4 (– 16.0 pg/mL) in untrained at rest: 10.3 (– 1.4 pg/mL) in athletes at rest: 29.5 (– 9.5 pg/mL)
Strength training protocols ELISA (ChemiKine, Millipore, Temecula, CA, USA)
Serum
60
Room temp.
1300 g for 12 min at 4C
-80
7.8–500 pg/mL
– 3.5; – 8.5
NS
Pre-training at rest: 13.6 – 0.8 ng/mL Post-training at rest: 14.6 – 0.5 ng/mL Pre-training controls at rest: 14.9 – 1.4 ng/mL Post-training controls at rest: 15.4 – 0.7 ng/mL
Levinger et al.[60] (2008)
ELISA (R&D Systems, Minneapolis, MN, USA)
Plasma
NS
NS
NS
-20
NS
NS
NS
Pre-training in LoMF at rest: 709.6 – 243.0 pg/mL Pre-training in HiMF at rest: 898.2 – 240.1 pg/mL
Schiffer et al.[66] (2009)
ELISA (ChemiKine, Millipore, Temecula, CA, USA)
Plasma
NS
NS
3000 rpm for 10 min at 4C
-80
NS
NS
NS
Pre-training at rest: 136 – 109 pg/mL Post-training at rest: 117.2 – 94.9 pg/mL Pre-training controls at rest: 102.2 – 108.7 pg/mL Post-training controls at rest: 98.9 – 78.6 pg/mL
Yarrow et al.[72] (2010)
ELISA (R&D Systems,
Serum
NS
NS
3000 g for 12 min
-80
20 pg/mL
<6.2; NS
Yes
Pre-training at rest: 23.3 – 1.8 ng/mL Continued next page
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ª 2010 Adis Data Information BV. All rights reserved.
Table V. Contd
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ª 2010 Adis Data Information BV. All rights reserved.
Table V. Contd Study (year)
Analysis kit (manufacturer)
Sample
Time to clot (min)
Clotting temp.
Centrifugation
Storage temp. after centrifugation (C)
Sensitivity of assay
Intra-assay; inter-assay variations (%)a
Corrected for change in plasma volume
Minneapolis, MN, USA)
Trained vs untrained; no intervention
[BDNF]; mean – SD (mean – SE)
Pre-training after strength exercise: 30.8 ng/mLd; Post-training at rest: 19.4 – 1.9 ng/mL Post-training after strength exercise : 34.4 ng/mLd At rest: 28.9 – 6.6 ng/mL
Chan et al.[52] (2008)
ELISA (Promega, Madison, WI, USA)
Serum
30
Room temp.
1000 g
-70
NS
NS
NS
Currie et al.[53] (2009)
ELISA (ChemiKine, Millipore, Temecula, CA, USA) ELISA (R&D Systems, Minneapolis, MN, USA) ELISA (Promega, Madison, WI, USA)
Serum
NS
NS
NS
NS
NS
NS
NS
At rest: 7.17 – 2.68 ng/mL
Serum
NS
NS
NS
-80
NS
NS
NS
At rest: 1.473 – 0.51 ng/mL
Serum/plasma
NS
NS
NS
-80
NS
NS
NS
[BDNF]s in trained at rest: 19.5 – 4.5 ng/mL [BDNF]s in untrained at rest: 23.6 – 2.9 ng/mL [BDNF]p in trained at rest: 1143.6 – 600.5 pg/mL [BDNF]p in untrained at rest: 1440.6 – 1090.3 pg/mL
Floe¨l et al.[55] (2010) Nofuji et al.[61] (2008)
a
Predicted intra-assay and inter-assay variations as given in the manual of the ELISA kit.
b
1.7 % = intra-assay variation between duplicates as measured in the applied assay kit.
c Blood samples were immediately spun at 2600 g for 15 min at 4C. Plasma was isolated and re-spun at 7500 g[62] and 10 000 g[68] for 10 min at 4C. Point values for [BDNF]s post strength exercise at baseline and after strength training were not given. To complete this table we calculated these values from the baseline point values and the percentage of increase of [BDNF]s[72]
[BDNF]arterial = arterial concentration of BDNF; [BDNF]p a-v diff = difference between arterial and jugular venous plasma BDNF concentration; [BDNF]vena jug = vena jugular concentration of BDNF; ELISA = Enzyme-Iinked ImmunoSorbent Assay; GXT = graded exercise test; HI = high-intensity exercise, HiMF = group with two or more metabolic risk factors for MetS; LoMF = group with one or no metabolic risk factors for MetS; MDD = major depression disorder; MetS = metabolic syndrome; MS = multiple sclerosis; NS = not specified; rpm = rounds per minute; SCI = spinal cord injury; SD = standard deviation; SE = standard error; T = moment of BDNF collection e.g. T60 post-HI-exercise = 60 minutes following the end of the highintensity exercise; TC = trained condition (at thirtieth strength training session); temp. = temperature; UC = untrained condition (at sixth strength training session); [] indicates concentration.
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Sports Med 2010; 40 (9)
d
BDNF and Exercise in Humans
thus lower levels of BDNF could merely represent the shift in blood volume instead of a true increase in BDNF.[90,91] The study of Floe¨l et al.[50] indicates no correlation between the level of physical activity and basal BDNF, and five out of seven studies on strength or aerobic training in healthy subjects showed no short term effect on basal concentration of BDNF.[56,57,60-61,72] Nevertheless, it should be noted that more studies with a longer duration of the training period and in different populations (i.e. trained versus untrained, healthy versus diseased) are necessary to elucidate whether basal plasma and serum BDNF concentrations are influenced by the level of physical fitness/activity. Not only physical fitness, but also factors such as sex, age, bodyweight and nutrition could influence basal concentration of BDNF. For instance, the low basal serum BDNF value in the studies of Gold et al.[47] and Floe¨l et al.[55] could be due to sex effects. (i.e. 6/14,[49] 28/47[50] male/female, respectively). According to Lommatzsch et al.,[77] women display significantly lower concentrations of platelet BDNF levels than men (i.e. groups matched for bodyweight) because of the sex-specific differences in BDNF expression of resident cells or organs and thus experience an altered uptake of BDNF into platelets. However, Gustaffson et al.,[58] Katoh-Semba et al.[78] and Ziegenhorn et al.[88] found no sex-related differences regarding serum and plasma BDNF, while Trajkovska et al.[89] and Baker et al.[50] reported higher concentrations of whole blood and plasma BDNF, respectively, in women. The mean basal serum BDNF level (i.e. 30.5 – 6.9 ng/mL) measured in healthy control women in the study of Laske et al.[59] is the second highest value reported in 13 of the included studies. Basal values of serum BDNF could also be influenced by age and/or bodyweight. Katoh-Semba et al.[78] found an increase of serum BDNF over the first several years in healthy individuals and then a slight decrease after reaching adult age (i.e. mean level in 30- to 39-year-old age group). Also, Ziegenhorn et al.[88] observed a decreasing concentration of serum BDNF with increasing age, while Lommatzsch et al.[77] reported the same in plasma concentration of BDNF but, on the other hand, no age-related ª 2010 Adis Data Information BV. All rights reserved.
787
influence on platelet concentration of BDNF. Floe¨l et al.[55] measured basal BDNF concentration in 75 healthy older individuals (i.e. mean age 60.5 – 6.9 years) and reported the lowest serum BDNF concentration of all 24 included studies (i.e. 1.5 – 0.5 ng/mL). On the other hand, Laske et al.[59] reported very high concentrations of serum BDNF in healthy older female controls (mean age 58.9 – 6.6 years; [BDNF]serum 30.5 – 6.9 ng/mL). Monteleone et al.[101] suggest that serum BDNF concentration is also increased with increasing bodyweight. The studies of Floe¨l et al.[55] and Castellano and White[51] both studied healthy (control) subjects with a mean BMI > 27, yet found very different basal concentrations of serum BDNF (i.e. 1.5 vs 20.2 ng/mL). It is likely that, next to age or sex, alternations in energy balance and nutritional variables also influence peripheral BDNF concentrations,[101] yet it is still unclear in which direction. In plasma, basal BDNF concentrations in the 24 included studies range from 10.3[75] pg/mL to 2.5 ng/mL[61] in healthy subjects. Thus, basal plasma values of BDNF vary even greater than in serum values. Three other studies in the literature also report strongly varying resting BDNF values, ranging from 77.0 over 92.5 to 1700.0 pg/mL.[77,86,96] Overall, the large variations in plasma BDNF concentration confirm the hypothesis of Lommatzsch et al.[77] and Ziegenhorn et al.[88] that peripheral BDNF is stored, for most of the time, in the blood platelets and varying concentrations of BDNF are released from the platelets upon agonist stimulation and circulate free in the blood plasma, depending on the specific need of BDNF in certain tissues.[96] Moreover, not only between studies, but also within a study, large variations in basal plasma BDNF concentrations can be observed, as pointed out by the large standard deviations of plasma BDNF concentrations in five studies.[60,61,66,75,96] This clearly indicates that basal plasma BDNF concentrations are extremely fluctuating. In the six studies on plasma BDNF concentration, it is not clear which type of anticoagulant was used. Only in the studies of Rasmussen et al.[62] and Seifert et al.[68] was it specified that tubes containing EDTA were used. It is possible that the type of anticoagulant influences platelet activation Sports Med 2010; 40 (9)
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in vitro and, thus, plasma BDNF concentration.[85] Only Baker et al.[50] adjusted plasma BDNF levels for the contribution of activated platelets to ensure only plasma BDNF is measured. Peripheral BDNF is also subject to sex-related diurnal variations.[102-104] In men, plasma BDNF peaks in the morning and decreases substantial during the day similar to the cortisol circadian rhythm.[102,103] This rhythmic circadian variation and correlation with cortisol levels is less explicit in plasma BDNF of women.[103,104] In women, hormonal fluctuations blunt the diurnal rhythm related to cortisol.[104] Researchers should take these circadian hormonal fluctuations into account when measuring plasma BDNF. 2.5.2 Persons with a Chronic Disease or Disability
Only one study investigated SCI athletes and recorded a basal serum BDNF concentration of 37.2 ng/mL. Yet, the sample size of the study was small (n = 8), it concerned athletes and there was no control group to verify this result.[65] In persons with MS, basal serum BDNF values range from 4.4[47,67] to 10.0 ng/mL.[51] This means that in MS, basal serum BDNF concentrations were significantly lower (i.e. £10.0 ng/mL) compared with the pool of BDNF data we found in the literature for healthy subjects. Nevertheless, Gold et al.[47] found equal concentrations of BDNF in MS and healthy controls in their study. Gold et al.[47] used stable persons with MS (i.e. persons with an acute relapse were excluded from their study).[47] Castellano and White,[51] on the other hand, reported significantly lower values of basal BDNF in MS versus healthy controls. According to Azoulay et al.,[105] lower concentrations of serum BDNF in MS could suggest that there is a reduction in tissue protection by BDNF or that there is an increase in the consumption of BDNF by the CNS due to damaged tissue. In the elderly and in persons with MS, the low level of BDNF at rest could also be due to a reduced production of BDNF as a result of lower levels of messenger RNA (mRNA);[106] this can be confirmed by animal studies.[107-109]
Gustafsson et al.[58] and Laske et al.[59] both studied the effects of exercise on BDNF in subjects with major depressive disorder (MDD). Only Laske et al.[59] found decreased basal serum BDNF concentrations in female patients with MDD. Gustafsson et al.[58] included only moderately depressed patients. According to Stro¨hle et al.[69] basal BDNF concentration in patients with panic disorder is also decreased. Thus, most studies on persons with a chronic disease or disability found deviating concentrations of serum BDNF compared with levels in young, healthy, untrained subjects. This is in agreement with other studies on neurodegenerative and metabolic diseases. Altered peripheral BDNF concentrations could be observed in persons with depression,[97] anorexia nervosa[101] (serum BDNF is decreased), and in persons with allergic asthma[95] and obesity[101] (serum BDNF is increased). All point values on basal BDNF concentration can be found in table V. 2.6 Exercise-Induced Response of BDNF 2.6.1 Effect of an Acute Aerobic Exercise
Fifteen studies investigated the effect of an acute aerobic exercise protocol on circulating concentrations of BDNF (tables III and VI). Thirteen studies reported on the effects in healthy (control) subjects[54,56,58,59,62-64,68-71] and seven on the effects in persons with a chronic disease or disability.[47,51,58,59,65,67,69] Sixty-nine percent of the studies[47,54,56,58,62-65,67-68,70-71] in healthy subjects and 86% of the studies in persons with a chronic disease or disability,[47,51,58,59,65,67,69] found a ‘mostly transient’ increase in peripheral BDNF (ranging from 11.7% to 410.0%) following an acute exercise protocol, with the tendency of acute high-intensity exercise protocols and GXTs having larger increases in BDNF concentrations than acute low-intensity exercise protocols. Except for the studies of Zoladz et al.,[75] Rojas Vega et al.[65] and Laske et al.,2 [59] an acute aerobic exercise of high intensity or a GXT increases basal BDNF concentrations in healthy
2 In the study of Laske et al.,[59] BDNF concentration in healthy control subjects did not increase following an acute exercise of high intensity.
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Table VI. Significant (p < 0.05) acute exercise- and training-induced effects on brain-derived neurotrophic factor (BDNF) Subjects
Result (p < 0.05)
[BDNF] increase or decrease (%)a
Castellano and White[51] (2008)
H
LMI: fl in [BDNF]s at wk 0, 4 and 8 of aerobic trainingb
LMI at wk 0: -13.2a,c
Ferris et al.[54] (2007)
H
GXT: › in [BDNF]s HI: › in [BDNF]s LMI: fi in [BDNF]s
GXT: 30.0 HI: 13.0 LMI: 10.0
Goekint et al.[56] (2008)
H
HI and LMI: › in [BDNF]s (HI > LMI)
HI: 42.7d LMI: 25.4d
Gold et al.[47] (2003)
H
LMI: › in [BDNF]s
LMI: 43.1a
Gustafsson et al.[58] (2009)
H
LMI: fi in [BDNF]p in M fi in [BDNF]p in F HI: › in [BDNF]p in M, ( fi LMI + GXT = HI) fi in [BDNF]p in F
LMI in M: 87.9 LMI in F: 142.8 HI in M: 398.2 HI in F: 265.5
Laske et al.[59] (2010)
H
GXT: fi in [BDNF]s 0 min after acute exercise fl in [BDNF]s 30 min after acute exercise
GXT at T0 after exercise: 1.6 GXT at T30 after exercise: -12.5
Rasmussen et al.[62] (2009)
H
HI: › in [BDNF]p arterial, [BDNF]p vena jug and [BDNF]p a-v diff
HI: [BDNF]p vena jug 165.2 [BDNF]p a-v diff 159.9
Rojas Vega et al.[63,64] (2006, 2007)
H
LMI: fi in [BDNF]s HI: › in [BDNF]s (LMI + GXT = HI)
LMI: 1.3a HI: 38.7a
Seifert et al.[68] (2010)
H
LMI: no results given HI: › in [BDNF]p arterial at wk 0 and 12 of aerobic training fi in [BDNF]p vena jug at wk 0 and 12 of aerobic training
LMI: NS HI at wk 0, [BDNF]p arterial: 100.0 [BDNF]p vena jug: 76.0
Stro¨hle et al.[69] (2010)
H
LMI: fi in [BDNF]s
LMI: -9.1a
Tang et al.[70] (2008)
H
LMI: › in [BDNF]s
LMI: 11.7
Winter et al.[71] (2007)
H
HI and LMI: › in [BDNF]s
HI: 12.0a LMI: 15.6a
Study (year) Acute aerobic exercise
Zoladz et al.[75] (2008)
H
GXT: fi in [BDNF]p at wk 0
GXT at wk 0: 5.8
Castellano and White[51] (2008)
D
Baseline at rest: [BDNF]s in MS < [BDNF]s healthy controls at wk 0 LMI: fl in [BDNF]s at wk 0, 4 and 8 of aerobic trainingb
LMI at wk 0: -42.1a,c,e
Gold et al.[47] (2003)
D
Baseline at rest: [BDNF]s in MS = [BDNF]s in healthy controls at wk 0 LMI: › in [BDNF]s
LMI: 35.3a
Gustafsson et al.[58] (2009)
D
Baseline at rest: [BDNF]p in MDD = [BDNF]p in healthy controls LMI: › in [BDNF]p in M fi in [BDNF]p in F HI: › in [BDNF]p in M, (LMI + GXT = HI), › in [BDNF]p in F
LMI in M: 66.3 LMI in F: 7.4 HI in M: 234.1 HI in F: 74.9
Laske et al.[59] (2010)
D
Baseline at rest: [BDNF]s in F with MDD < [BDNF]s healthy F controls GXT: › in [BDNF]s 0 min after acute exercise fl in [BDNF]s 30 min after acute exercise
GXT at T0 after exercise: 16.8 GXT at T30 after exercise: -11.1
Continued next page
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Table VI. Contd Subjects
Result (p < 0.05)
[BDNF] increase or decrease (%)a
D
Baseline at rest: [BDNF]s › in SCI athletesf LMI: › in [BDNF]s HI: fi in [BDNF]s
LMI: 44.6a HI: 16.1a
Schulz et al.[67] (2004)
D
LMI: trainingg
LMI at wk 0: 410.0
Stro¨hle et al.[69] (2010)
D
Baseline at rest: [BDNF]s in persons with panic disorder < [BDNF]s in healthy controls LMI: › in [BDNF]s
LMI: 86.2a
Goekint et al.[57] (2010)
H
fi in [BDNF]s
3.6i
Yarrow et al.[72] (2010)
H
› in [BDNF]s
32i
Goekint et al.[57] (2010)
H
At rest: fi in [BDNF]s at 10 wk After strength exercise: fi in [BDNF]s at 10 wk
At rest: 10.2k After strength exercise: -2.1i
Levinger et al.[60] (2008)
H
Baseline at rest: [BDNF]p in HiMF > [BDNF]p in LoMF At rest: fi in [BDNF]p at 10 wk
At rest HiMF: -0.5a At rest LoMF: -8.7a
Schiffer et al.[66] (2009)
H
At rest:
At rest: -13.8
Yarrow et al.[72] (2010)
H
At rest: fi in [BDNF]s at 5 wk After strength exercise: TRAD: › in [BDNF]s at wk 5; ECC+: › in [BDNF]s at wk 5
Castellano and White[51] (2008)
H
At rest: After LMI:
fi in [BDNF]s at 4 and 8 wk fl in [BDNF]s at 0, 4 and 8 wk vs rest at 0, 4 and 8 wk fi in [BDNF]s at wk 8 vs LMI at wk 0 and 4
NS NS NS
Schiffer et al.[66] (2009)
H
At rest:
fi in [BDNF]p at 12 wk
At rest: -20.1
Seifert et al.[68] (2010)
H
At rest: [BDNF]p arterial fi [BDNF]p vena jug › [BDNF]p a-v diff › at wk 12 After LMI: no results given After HI: [BDNF]p arterial › , [BDNF]p vena jug fi at wk 0 [BDNF]p arterial fi vs HI at wk 0 [BDNF]p arterial › vs rest at wk 12 [BDNF]p vena jug fi vs HI at wk 0 and rest at wk 12
LMI: NS HI at wk 12 vs HI at wk 0: [BDNF]p arterial: -16.7; [BDNF]p vena jug: 34.1; HI at wk 12 vs rest at wk 12: [BDNF]p arterial: 100.0; [BDNF]p vena jug: 7.3
At rest: › in [BDNF]p at 5 wk After GXT: › in [BDNF]p at 5 wk vs rest at wk 5 › in [BDNF]p at 5 wk vs GXT at wk 0
At rest: 63.1 GXT at wk 5 vs rest at wk 5: 307.1 GXT at wk 5 vs GXT at wk 0: 527.5
Study (year) Rojas Vega et al. (2008)
[65]
› in [BDNF]s at 0 and 8 wk of aerobic
Acute strength exerciseh
Strength trainingj
fi in [BDNF]p at 12 wk
At rest: -16.6i after strength exercise: TRAD: 79i; ECC+: 74i
Aerobic training
Zoladz et al.[75] (2008)
H
At rest [BDNF]p arterial: -16.7 [BDNF]p vena jug:120.0
Continued next page
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Table VI. Contd Subjects
Result (p < 0.05)
[BDNF] increase or decrease (%)a
D
At baseline: [BDNF]p in M > [BDNF]p in F (not significant p = 0.09) At rest: fl in [BDNF]p in M and › in [BDNF]p in F vs controlsk
NS
At baseline: [BDNF]s in MS < [BDNF]s healthy controls at wk 0 At rest: fi in [BDNF]s at 8 wk (> – < › [BDNF]s at 4 wk) After LMI: fl in [BDNF]s at 0, 4 and 8 wk vs rest at 0, 4 and 8 wk fi in [BDNF]s at wk 8 vs LMI at wk 0 and 4
NS
D
At rest: After LMI:
At rest: 36.2 LMI at wk 8 vs rest at wk 8: 365.2 LMI at wk 8 vs LMI at wk 0: 24.3
Chan et al.[52] (2008)
H
[BDNF]s highly trained subjects < [BDNF]s moderately trained subjects
ND
Currie et al.[53] (2009)
H
[BDNF]s in high cardio-respiratory fit subjects < [BDNF]s in low cardio-respiratory fit subjects
ND
Floe¨l et al.[55] (2010)
H
No correlation between [BDNF]s and level physical activity
ND
Nofuji et al.[61] (2008)
H
[BDNF]s trained subjects < [BDNF]s untrained subjects [BDNF]p trained subjects = [BDNF]p untrained subjects
ND
Zoladz et al.[75] (2008)
H
[BDNF]p trained subjects > [BDNF]p untrained subjects
ND
Study (year) [50]
Baker et al.
(2010)
Castellano and White[51] (2008)
Schulz et al.[67] (2004)
D
fi in [BDNF]s at 8 wk › in [BDNF]s at 0 and 8 wk vs restg fi in [BDNF]s at wk 8 vs LMI at wk 0
NS
NS NS NS
Trained/untrained subjects
a
Percentage of increase or decrease of [BDNF] immediately following the acute exercise or training protocol (i.e. 0 min post-exercise and within a week post-training), compared with baseline measurements. To get an idea of the order of magnitude of the effects of an acute exercise or training protocol on peripheral levels of BDNF, percentages of increase or decrease in BDNF compared with basal values were calculated. However, 8 studies did not provide point values of BDNF levels, therefore percentages of increase or decrease of BDNF can only be estimated from graph values. An increase in BDNF is expressed as a positive value; a decrease in BDNF is expressed as a negative value.[47,51,54,60,63-65,71]
b
No significant decrease 30 min following exercise, yet significant decrease after 2 h and 3 h post-exercise.[51]
c
BDNF was not assessed at 0 min post-exercise, values that are given here, are those of 30 min post-exercise at wk 0.[51]
d
These values account for the control subjects, not the experimental group (administration of reboxetine).[56]
e
In contradiction with the significant decrease 2 h and 3 h post-exercise, an increase in [BDNF]s (not significant) could be found 30 min postexercise.[51]
f
Rojas Vega et al.[65] did not include a control group of healthy subjects in their study. Consequently, the finding that baseline [BDNF]s is increased compared with able-bodied subjects can not be verified.
g
Schulz et al.[67] found no statistically significant differences at week 0 and 8 of aerobic training at rest or after LMI between the MS group and the MS control group. Yet, a significant increase in BDNF following an acute exercise was observed in both groups at wk 0 and 5.
h
No studies available on the effects of acute strength exercises on BDNF in disabled or diseased subjects.
i
No significant differences between groups.[57,72]
j
No studies available on the effects of strength training on BDNF in disabled or diseased subjects.
k
This is a sex-specific effect of aerobic training vs stretching on [BDNF]p (i.e. group X sex ANOVA, F1,23 = 4.68; p = 0.04).[50]
[BDNF]arterial = arterial [BDNF]; [BDNF]p a-v diff = difference between arterial and jugular venous plasma BDNF concentration; [BDNF]vena jug = vena jugular [BDNF]; D = persons with a disease or disability; ECC+ = eccentric-enhanced resistance exercise/training; F = female; GXT = graded exercise protocol; H = healthy subjects; HI = high-intensity exercise; HiMF = high metabolic risk group; LMI = low to moderate intensity; LoMF = low metabolic risk group; M = male; MDD = major depression disorder; MS = multiple sclerosis; ND = no data; NS = not specified; rpm = rounds per minute; SCI = spinal cord injury; T = moment of BDNF collection, e.g. T60 after exercise = 60 min following the end of the exercise; TC = trained condition (at the thirtieth strength training session); UC = untrained condition (at the sixth strength training session); › indicates significant increase; fl indicates significant decrease; fi indicates no significant differences; [] indicates concentration; []s indicates serum concentration; []p indicates plasma concentration; > – < indicates as opposed to.
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subjects and persons with a disease or disability.3 [54,56,58,62-64,68,71] Acute aerobic exercise of low to moderate intensity is less effective to increase basal BDNF concentrations in healthy subjects (i.e. in only 44% of the studies),[51,54,58,63,64,69] but not in persons with a disease or disability. In these subjects an exercise of low to moderate intensity almost always increases basal BDNF concentration (i.e. in 83% of the studies in persons with a disease or disability4).[47,58,65,67,69] Remarkably, in the study on SCI subjects of Rojas Vega et al.,[65] the intensitydependent character of the BDNF response is inverse to that reported in healthy subjects; a low to moderate acute exercise increases basal BDNF concentration while the immediately following highintensity exercise decreases this concentration again to baseline. Furthermore, the study of Castellano and White[51] reported very different effects of an acute exercise of low to moderate intensity on concentration of BDNF (table VI).[51,67] Castellano and White[51] measured a decrease in BDNF concentration in healthy subjects and persons with MS compared with baseline BDNF values. An explanation for this odd result can be found in the assessment of peripheral BDNF; blood samples were not taken immediately following the acute exercise trial but 30 minutes, 2 hours and 3 hours post-exercise. In 73% of the studies, serum concentration of BDNF was analysed; only in the studies of Zoladz et al.,[75] Rasmussen et al.,[62] Gustafsson et al.[58] and Seifert et al.[68] plasma concentration of BDNF was measured (tables V and VI). Thus, acute exercise induces a transient increase in peripheral BDNF in both healthy subjects and in persons with a chronic disease or disability. Moreover, a dose-response relationship exists between the intensity of the exercise and peripheral BDNF concentration. In persons with a chronic disease or disability BDNF concentration increases already following an acute exercise of low to moderate intensity whereas BDNF concentration in healthy subjects
Knaepen et al.
benefits significantly more from high-intensity exercise. 2.6.2 Effect of an Acute Strength Exercise
Goekint et al.[57] and Yarrow et al.[72] were the first to study the exercise-induced BDNF response following an acute strength exercise. Yarrow et al.[72] reported a significant strength exercise-induced increase of 32% in serum BDNF while Goekint et al.[57] did not find a significant change (i.e. 3.6%) in BDNF following an acute strength exercise session. Goekint et al.[57] speculated that exercise intensity in their study was too low (i.e. six strength exercises of 3 · 10 repetitions at 80% of 1 repetition maximum (1RM) with relatively large resting periods between efforts). However, Yarrow et al.[72] implemented two strength exercise protocols of different intensity as follows: (i) traditional resistance exercise/training (TRAD), which incorporates two strength exercises of 4 · 6 repetitions at 52.5% 1RM concentrically and eccentrically; and (ii) eccentric-enhanced resistance exercise/training (ECC+), which incorporates two strength exercises of 3 · 6 repetitions at 40% 1RM concentrically and 100% 1RM eccentrically. They found similar transient increases in BDNF in both groups, independent of training intensity. However, the groups were matched for training volume. Presumably, an acute strength exercise stimulates peripheral BDNF on the condition that the exercise load is intensive enough. 2.6.3 BDNF Response during Passive Recovery
The increase of peripheral BDNF following an acute aerobic or strength exercise is transient. In most studies BDNF concentration returned to baseline within 10–60 minutes post-exercise, showing a fast disappearance rate of circulating BDNF after cessation of an aerobic or strength exercise. Castellano and White[51] and Yarrow et al.[72] observed a significant decrease below baseline concentration in peripheral BDNF concentration 2- and 3-hours post-exercise, both in
3 In the study of Gustafsson et al.,[58] a significant increase in [BDNF]p following an acute exercise of high intensity was only found in male control subjects. 4 In the study of Gustafsson et al.,[58] a significant increase in [BDNF]p following an acute exercise of low to moderate intensity was only found in male persons with MDD.
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Sports Med 2010; 40 (9)
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persons with MS and healthy (control) subjects. The exercise-induced response of peripheral BDNF seems to include an elevated release of BDNF into the blood circulation on the one hand and a greater tissue absorption on the other hand. 2.6.4 Effect of Aerobic Training
Schiffer et al.,[66] Castellano and White[51] and Schulz et al.[67] reported no training-induced effect on basal BDNF concentration in healthy subjects[51,66] and in persons with MS, respectively.[51,67] Only Zoladz et al.[75] and Seifert et al.[68] observed an increase in basal plasma BDNF5 concentration following a period of aerobic training. However, Zoladz et al.[75] did not include a control group. Furthermore, Seifert et al.[68] found that BDNF from the brain (vena jugularis) was increased but no differences were seen in plasma BDNF concentration in a peripheral artery. Also, they included overweight men in their study who lost weight and body fat due to aerobic training. Furthermore, the training group experienced a higher loss in adipose tissue than the control group so that elevated basal BDNF concentration in the training group could be the result of altered energy metabolism.[10-12] Baker et al.[50] reported an elevated basal plasma BDNF concentration in men with mild cognitive impairment following aerobic training as compared with a stretching programme. In women they reported the inverse phenomenon. In both sexes plasma cortisol concentration fluctuated accordingly to plasma BDNF (i.e. plasma cortisol concentration increased in men and decreased in women relative to controls). When the change in BDNF from rest to post-acute exercise was assessed at the end of an aerobic training period, Zoladz et al.,[75] Schulz et al.[67] and Seifert et al.[68] reported a significant increase in peripheral BDNF concentration (307.1%, 365.2% and 100.0%, respectively) following an acute exercise compared with basal BDNF concentrations at the end of the training period. Nevertheless, Schulz et al.[67] and Seifert et al.[68] observed the same
793
acute exercise-induced increase (i.e. 100.0%) at baseline. Thus, only according to Zoladz et al.[75] an aerobic training programme elevates the BDNF response to an acute exercise; however, they did not use a control group in their study.[75] The findings of Zoladz et al.,[75] Schulz et al.[67] and Seifert et al.[68] are in contradiction with those of Castellano and White,[51] where a decrease in serum BDNF concentrations following an acute exercise was found at the end of the training period. However, also at baseline, BDNF concentration decreased following an acute exercise; assessment of peripheral BDNF was not performed immediately following the acute exercise, but 30 minutes, 2 hours and 3 hours following the acute exercise. Similar results could be found in persons with MS and healthy (control) subjects, although the disappearance rate of BDNF in persons with MS following the acute exercise differed significantly between week 4 (86%) and week 8 (59%).[51] Thus, results differ when it comes to the point of a BDNF response to aerobic training. Three studies6 observed an elevated basal plasma BDNF concentration following a training period.[50,68,75] Remarkably, these studies use a more intensive training protocol as compared with the other studies[51,66,67] (i.e. training ratio, respectively, 4–7 ·/week as compared with 2–3 ·/week and training intensity at a. higher percentage of the heart rate reserve or VO2max) [table IV]. As with strength training, only one study on aerobic training observed a greater plasma BDNF response to acute exercise following a period of aerobic training (i.e. as compared with the BDNF response to acute exercise at baseline).[75] However, this study lacked a control group.[75] More studies are requested to unravel the benefits of aerobic training on peripheral BDNF concentration and/or cellular processing. 2.6.5 Effect of Strength Training
Four studies examined the effect of strength training on peripheral BDNF concentration in
5 Seifert et al.[68] found an increase in [BDNF]p measured in the vena jugularis but not in arterial [BDNF]p following an aerobic training programme. 6 Baker et al.[50] only found an increase in men with mild cognitive impairment.
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healthy subjects.[57,60,66,72] Protocols can be found in table IV. The studies of Goekint et al.,[57] Levinger et al.,[60] and Schiffer et al.,[66] used similar strength training protocols. Yarrow et al.[72] limited strength training to two exercises and used two groups who trained the same volume but at different training intensities (i.e. traditional versus eccentric-enhanced strength training). All studies agree that strength training has no effect on basal peripheral BDNF concentration. However, Goekint et al.[57] and Yarrow et al.,[72] also studied the BDNF response to a single strength exercise following a strength training programme. Only Yarrow et al.[72] reported a significant increase of serum BDNF concentration post-acute exercise, both at baseline and after completion of a strength training programme. Moreover, the change in BDNF from rest to immediately postacute exercise was 98% greater at the completion of the 5-week strength training programme than at baseline. Except for the study of Levinger et al.,[60] who investigated middle-aged individuals with clusters of metabolic risk factors, no other study investigated the effects of strength training on peripheral BDNF concentration in persons with a chronic disease or disability. From four studies, the inquiry for whether strength training influences peripheral concentrations of BDNF remains inconclusive. It can be assumed that a strength training programme does not elevate basal BDNF concentration; therefore, maybe strength training protocols are not strenuous enough (i.e. training ratio of 3 ·/week) [table IV]. Strength training could possibly trigger a greater BDNF response to acute exercise in trained as compared with untrained subjects, although more research is necessary to support this hypothesis. 2.6.6 Basal BDNF in Trained versus Untrained Subjects
Zoladz et al.[75] reported a lower concentration of plasma BDNF in untrained subjects compared with trained subjects. The other studies concerning this topic did not perform an experimental intervention protocol but observed the concentration of peripheral BDNF in trained and untrained subjects.[52,53,61] Moderately trained, untrained or low cardio-respiratory fit subjects ª 2010 Adis Data Information BV. All rights reserved.
seem to have higher concentrations of serum levels of BDNF than trained subjects. This was observed in athletes and untrained subjects at rest by Currie et al.,[53] Nofuji et al.[61] and Chan et al.[52] As suggested earlier (section 2.5.1), a lower level of BDNF in trained subjects and athletes could indicate that BDNF clearance is more effective (i.e. a higher disappearance rate) than in untrained subjects. However, no clinical trial has been performed to support this hypothesis. Moreover, Floe¨l et al.[55] could not find a correlation between BDNF concentration and level of physical activity. A longitudinal randomized clinical trial with trained and untrained subjects in a crossover design could give a more definite answer to whether basal BDNF concentration in trained subjects is lower than in untrained subjects. Moreover, it is also possible that lower concentrations of BDNF could represent the shift in blood volume instead of a true increase in BDNF as plasma volume increases by 10–20% following regular physical training.[90,91] 2.7 Guidelines for Future Research
An acute aerobic exercise induces an increase in peripheral BDNF concentration in healthy subjects, as well as in persons with a chronic disease or disability. Most studies found a statistically significant dose-response relationship between the intensity of an acute aerobic exercise protocol and concentration of BDNF. Although, Seifert et al.[68] measured BDNF concentration at different exercise. intensities (i.e. starting from 60% to 100% of VO2max) and could not observe a change in BDNF response. Independently of the intensity of the exercise, BDNF concentration generally returns back to baseline within 15–60 minutes and tends to decrease below baseline after 60 minutes. From the results of the 24 included studies, it is difficult to determine the essential exercise parameters (i.e. intensity, duration and mode) that are necessary to induce an increase in peripheral BDNF concentration. It is most likely that exercise parameters are related to each other and that BDNF response is triggered when exercise becomes strenuous. Therefore, it would be interesting to Sports Med 2010; 40 (9)
BDNF and Exercise in Humans
objectivate exercise intensity and relate it to ratings of perceived exertion following exercise[53] and to monitor mean and maximal heart rate values. When it comes to the mode of acute exercise, we can conclude from the included studies that acute aerobic exercise is more likely to elevate BDNF concentration than acute strength exercise. Presumably, in the two studies on acute strength exercise, the load of the exercise is not intensive enough for the given subjects to influence basal BDNF concentration. Moreover, in strength exercise resting periods between efforts are often implemented, which results in a decrease in heart rate, lactate, minute ventilation etc. between repetitions and between sessions. Within acute aerobic exercise cycling, hand cycling, running, rowing and stepping all bring on an exercise-induced BDNF response. To better understand the relationship between the nature of an acute exercise and peripheral BDNF concentrations, future studies should look at doseresponse relationships between percentages of increase in BDNF on the one hand, and exercise parameters such as intensity, duration and mode of exercise on the other. The nature of an acute exercise and also subject characteristics, determine the BDNF response; in healthy subjects high-intensity exercise is more likely to induce a BDNF response, while in persons with a chronic disease or disability an exercise of low to moderate intensity seems already strenuous enough to trigger a BDNF response. Metabolic response to exercise or training is known to differ between healthy subjects and persons with a disease or disability and, therefore, probably also BDNF response, will be different. Thus, more studies are required on the BDNF response to different exercise intensities, both in healthy subjects and in persons with a disease or disability. Next to this, Chen et al.[110] and Egan et al.[22] point out that activity-dependent secretion of BDNF is diminished in subjects with the BDNF polymorphism, Val66Met. Future studies should, whenever possible, identify whether subjects are carriers of the genetic variant of the BDNF gene (Val66Met) [i.e. 20–30% of human population[24,25]]. Also, for an appropriate comparison between studies, it would be better if changes in BDNF concentraª 2010 Adis Data Information BV. All rights reserved.
795
tion would be expressed in relative units (e.g. in percentages of changes – the standard deviations). Finally, it would not only be interesting to determine the amount of increase in BDNF, but also the disappearance rate of peripheral BDNF following acute exercise (e.g. BDNF assessment at 0, 30, 60 and 120 minutes post-exercise or by marking BDNF protein in vivo). Three of six studies reported an aerobic training-induced response on basal BDNF while none of the four studies on strength training was capable of elevating basal BDNF concentration. Two of six training studies (i.e. one on aerobic and one on strength training) observed an elevated circulating BDNF response to an acute exercise following a training period. Because of the greater effect of strength training on insulin-like growth factor (IGF)-1 production[111] compared with aerobic training,[112] there could be a possible differential effect of aerobic and strength exercise and/ or training on peripheral concentration of BDNF. It is well known that IGF-1 is needed to transform pro-BDNF into BDNF in the CNS[113] and that IGF-1 easily crosses the blood-brain-barrier. Nevertheless, with regard to training-induced effects on peripheral concentration of BDNF, inconsistent findings and too few studies impede to draw a distinct conclusion whether a training period elevates basal BDNF concentration and/or upregulates the cellular processing of BDNF. Future studies on training-induced BDNF response should systematically investigate effects on basal BDNF concentration but also on BDNF response to an acute exercise. Another issue which demands some attention, is whether exercise-induced BDNF increase is limited or not and which physiological and/or environmental factors determine the ceiling effect. 2.8 Origin of Exercise-Induced BDNF Response
The cellular origin of the exercise-induced BDNF response remains partially unclear. Recently, Rasmussen et al.[62] found evidence for a release of BDNF from the brain, as BDNF is able to cross the blood-brain barrier.[114,115] They reported that the brain has a significant BDNF production both at rest and during prolonged Sports Med 2010; 40 (9)
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exercise (i.e. 2- to 3-fold increase of the production at rest) in healthy subjects. Confirming these results, Seifert et al.[68] very recently showed that indeed BDNF is released from the brain (vena jugularis), and that aerobic training in obese subjects increases basal BDNF concentration. The brain contributes for almost 75% of circulating BDNF, suggesting that the brain is the major, but not sole, contributor to circulating BDNF in healthy subjects.[62] Yet, it remains to be elucidated from which regions in the CNS and the brain (e.g. hippocampus, cerebral cortex, prosencephalon, cerebellum, hypothalamus) BDNF originates. Animal studies agree that exercise principally upregulates messenger RNA (mRNA) expression in the hippocampus.[4,68,116] A quarter of circulating BDNF seems to stem from a peripheral source. It has been speculated that the exercise-induced BDNF response originates partially from the contracting muscle cells. However, Matthews et al.[10] showed that, in vitro, BDNF is indeed synthesized by skeletal muscle cells during contraction, and that muscle-derived BDNF is not released into circulation but used to enhance fat oxidation in the muscle cell. However, more studies are necessary to confirm that, in vivo, skeletal muscles do not release BDNF into the circulation following high-intensity contractions. Several other studies revealed some sources of BDNF within the blood circulation. Initially, low concentrations of BDNF in plasma suggest that BDNF is normally not present in the circulation but it is stored in the blood platelets until activation.[117] Yamamoto and Gurney[118] stated that platelets contain BDNF mRNA derived from the cytoplasm of the megakaryocyte and that they release BDNF protein upon agonist stimulation.[96] Consequently, platelets might also synthesize BDNF protein. However, platelets have limited protein synthesis capacity[119] and Fujimura et al.[96] found extremely low or no concentration of BDNF mRNA in blood platelets. Therefore, it is more likely that BDNF is sequestered from the blood circulation, and originates for a major part in the brain and for some part elsewhere.[62,96,119] Other sources of human BDNF circulating in blood plasma and serum or stored in blood platelets could be peripheral cells ª 2010 Adis Data Information BV. All rights reserved.
or endocrine organs such as vascular endothelial cells,[119] immune or peripheral blood mononuclear cells (e.g. T and B lymphocytes,[120-122] eosinophils,[123,124] monocytes,[121,122,125] vascular smooth muscle cells,[126] the pituitary gland,[127] salivary glands such as the submandibular glands).[128,129] Synthesis and release of BDNF into the blood circulation increases as a result of a physical stimulus in a dose-response manner. The more intense the acute stimulus or (positive) stress is, the greater the BDNF response. Normalization of the BDNF concentration occurs when the stressor disappears, indicating that BDNF is used or stored elsewhere or/and that elevated BDNF secretion has ceased. Following exercise, peripheral BDNF clearance could be elevated indicating that circulating BDNF is used in the periphery or that BDNF is transported via the blood circulation to the brain where it crosses the blood-brain barrier to enhance neural health.[82] When the same stimulus or stressor is repeatedly administered, for example an exercise training programme, it is possible that a ceiling effect occurs because subjects become accustomed to the stimulus or enriched condition and homeostatic mechanisms take over again.[130] To verify this hypothesis, it would be interesting to perform a longitudinal study comparing training-induced BDNF response in well trained subjects to sedentary subjects. Recently, Berchtold et al.[82] showed that both daily exercise and alternating days of exercise increased rat hippocampal BDNF protein, and concentrations progressively increased with longer running duration. They found that hippocampal BDNF protein remained elevated for several days after exercise ceased and could easily be induced again by another brief exercise exposure.[82] These findings could indicate that peripheral BDNF is indeed retrogradely transported and used in the brain following exercise, and that long lasting effects of exercise on BDNF are only traceable in the CNS. 3. Conclusions This review gives a summary of the current knowledge on the exercise-induced response of Sports Med 2010; 40 (9)
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BDNF in healthy subjects and persons with a chronic disease or disability. When interpreting the results of this review, the selection process must be kept in mind. Taken together, it is difficult to compare studies because of varying study populations, sample sizes, different acute exercise and training protocols and different biochemical analysis techniques. Research concerning acute exercise or training interventions should clearly define protocol parameters that result in a functional benefit regarding peripheral BDNF concentration. Also, exercise-induced changes in BDNF should be expressed in relative units (for example in percentages of changes – the standard deviations). Overall, an acute aerobic exercise unmistakably influences circulating BDNF concentration, although the effect is transient. In healthy subjects it is rather unlikely that regular exercise (i.e. training) results in an elevated basal BDNF concentration, although the current amount of studies is insufficient to be able to exclude any traininginduced effect on basal BDNF. However, the BDNF response to exercise is most probably an epiphenomenon of what happens centrally, and exercising regularly could induce central effects without elevating peripheral basal BDNF concentration. Circulating BDNF probably originates for a large part in the brain; we can only speculate where the other part of circulating BDNF originates from, where it is transported to and for what purpose it is used or stored at its final destination. Furthermore, future research has to show whether repeated administration of an enriched condition, stimulus or stressor (i.e. acute exercise, training and/or reduced-calorie diet) influences the efficiency of the cellular processing of BDNF or basal BDNF concentration (i.e. increase of basal BDNF and disappearance rate). Instead of a training programme consisting of the same exercise protocol during each training session, a protocol with a new exercise stimulus for every few sessions could be implemented. Whether the use of acute exercise and training is viable for the treatment of neurodegenerative and metabolic diseases (seen from its effects on peripheral BDNF), seems plausible. Recent studies show that BDNF plays a role in regulating ª 2010 Adis Data Information BV. All rights reserved.
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central (i.e. through interaction with leptin and through the hypothalamic pathway that controls bodyweight and energy homeostasis) and peripheral energy metabolism (i.e. BDNF as a contraction-inducible protein in skeletal muscle). As a result, central and/or peripheral BDNF could possibly mediate some of the health benefits of exercise in metabolic disorders. On the other hand, effects of repeated exercise on peripheral BDNF concentration could be important with regard to the treatment and prevention of neurological diseases and impairments such as MS, Parkinson’s disease and SCI. Long-term effects of exercise on symptoms of neurodegenerative diseases and neurological disorders and its relation with BDNF, have not yet been investigated. The synergistic effect of a combination of BDNFstimulating factors such as acute exercise or training, changes in the nutrient content of a diet, and key pharmaceuticals could be a next step to study. Acknowledgements The preparation of this article was funded by the Vrije Universiteit Brussel and by the Research Foundation Flanders. The authors have no conflicts of interest that are directly relevant to the content of this review.
References 1. Hennigan A, O’Callaghan RM, Kelly AM. Neurotrophins and their receptors: roles in plasticity, neurodegeneration and neuroprotection. Biochem Soc Trans 2007; 35: 424-7 2. Johnston MV. Plasticity in the developing brain: implications for rehabilitation. Dev Disabil Res Rev 2009; 15: 94-101 3. Neeper SA, Go´mez-Pinilla F, Choi J, et al. Exercise and brain neurotrophins [letter]. Nature 1995; 373 (6510): 109 4. Neeper SA, Go´mez-Pinilla F, Choi J, et al. Physical activity increases mRNA for brain-derived neurotrophic factor and nerve growth factor in rat brain. Brain Res 1996; 726 (1-2): 49-56 5. Vaynman S, Gomez-Pinilla F. License to run: exercise impacts functional plasticity in the intact and injured central nervous system by using neurotrophin. Neurorehab Neur Repair 2005; 19 (4): 283-94 6. Murer MG, Yan Q, Raisman-Vozari R. Brain-derived neurotrophic factor in the control human brain, and in Alzheimer’s disease and Parkinson’s disease. Prog Neurobiol 2001; 63: 71-124 7. Sarchielli P, Greco L, Stipa A, et al. Brain-derived neurotrophic factor in patients with multiple sclerosis. J Neuroimmunol 2002; 132: 180-8
Sports Med 2010; 40 (9)
798
8. White LJ, Castellano V. Exercise and brain health – implications for multiple sclerosis: part 1 – neuronal growth factors. Sports Med 2008; 38 (2): 91-100 9. Liguori M, Fera F, Patitucci A, et al. A longitudinal observation of brain-derived neurotrophic factor mRNA levels in patients with relapsing-remitting multiple sclerosis. Brain Res 2009; 1256: 123-8 10. Matthews VB, Astro¨m MB, Chan MH, et al. Brain-derived neurotrophic factor is produced by skeletal muscle cells in response to contraction and enhances fat oxidation via activation of AMP-activated protein kinase. Diabetologica 2009; 52 (7): 1409-18 11. Pedersen BK, Pedersen M, Krabbe KS, et al. Role of exercise-induced brain-derived neurotrophic factor production in the regulation of energy homeostasis in mammals. Exp Physiol 2009; 94 (12): 1153-60 12. Gomez-Pinilla F, Vanyman S, Ying Z. Brain-derived neurotrophic factor functions as a metabotrophin to mediate the effects of exercise on cognition. Eur J Neurosci 2008; 28: 2278-87 13. Vaynman S, Ying Z, Gomez-Pinilla F. Hippocampal BDNF mediates the efficacy of exercise on synaptic plasticity and cognition. Eur J Neurosci 2004; 20: 2580-90 14. Dishman RK, Berthoud HR, Booth FW, et al. Neurobiology of exercise. Obesity 2006; 14 (3): 345-55 15. Cotman CW, Berchtold NC, Christie LA. Exercise builds brain health: key roles of growth factor cascades and inflammation. Trends Neurosci 2007; 30 (9): 464-72 16. Van Praag H. Neurogenesis and exercise: past and future directions. Neuromol Med 2008; 10: 128-40 17. van Praag H. exercise and the brain: something to chew on. Trends Neurosci 2009; 32 (5): 283-90 18. Barde YA, Edgar D, Thoenen H. Purification of a new neurotrophic factor from mammalian brain. EMBO J 1982; 1 (5): 549-53 19. Maisonpierre PC, Le Beau MM, Espinosa R, et al. Human and rat brain-derived neurotrophic factor and neurotrophin-3: gene structures, distributions, and chromosomal localizations. Genomics 1991; 10 (3): 558-68 20. Binder DK, Scharfman HE. Brain-derived neurotrophic factor. Growth Factors 2004; 22 (3): 123-31 21. Pruunsild P, Kazantseva A, Aid T, et al. Dissecting the human BDNF locus: bidirectional transcription, complex splicing, and multiple promoters. Genomics 2007; 90 (3): 397-406 22. Egan MF, Kojima M, Callicott JH, et al. The BDNF Val66Met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function. Cell 2003; 112: 257-69 23. Chen Z, Bath K, McEwan B, et al. Impact of genetic variant BDNF (Val66Met) on brain structure and function. Novartis Found Symp 2008; 289: 180-95 24. Shimizu E, Hashimoto K, Iyom M. Ethnic differences of the BDNF 196 G/A (val66met) polymorphism frequencies: the possibility to explain ethnic metal traits. Am J Med Genet B Neuropsychiatr Genet 2004; 126: 122-3 25. Casey BJ, Glatt CE, Tottenham N, et al. Brain-derived neurotrophic factor as a model system for examining gene by environment interactions across development. Neuroscience 2009; 164: 108-20
ª 2010 Adis Data Information BV. All rights reserved.
Knaepen et al.
26. Gratacos M, Gonzalez JR, Mercader JM, et al. Brainderived neurotrophic factor Val66Met and psychiatric disorders: meta-analysis of case-control studies confirm association to substance-related disorders, eating disorders and schizophrenia. Biol Psychiatry 2007; 61 (7): 911-22 27. Barde YA. Neurotrophins: a family of proteins supporting the survival of neurons. Prog Clin Biol Res 1994; 390: 45-56 28. Lindsay RM. Neurotrophic growth factors and neurodegenerative diseases: therapeutic potential of the neurotrophins and ciliary neurotrophic factor. Neurobiol Aging 1994; 15 (2): 249-51 29. Lewin GR. Neurotrophins and the specification of neuronal phenotype. Philos Trans R Soc Lond B Biol Sci 1996; 351 (1338): 405-11 30. Alsina B, Vu T, Cohen-Cory S. Visualizing Synapse formation in arborizing optic axons in vivo: dynamics and modulation by BDNF. Nat Neurosci 2001; 4 (11): 1093-101 31. Cotman CW, Berchtold NC. Exercise: a behavioral intervention to enhance brain health and plasticity. Trends Neurosci 2002; 25 (6): 295-301 32. Tsuchida A, Nonomura T, Ono-Kishino M, et al. Acute effects of brain-derived neurotrophic factor on energy expenditure in obese diabetic mice. Int J Obesity 2001; 25: 1286-93 33. Nakagawa T, Ono-Kishino M, Sugaru E, et al. Brain-derived neurotrophic factor (BDNF) regulates glucose and energy metabolism in diabetic mice. Diabetes Metab Res Rev 2002; 18 (3): 185-91 34. Lebrun B, Bariohay B, Moyse E, et al. Brain-derived neurotrophic factor (BDNF) and food intake regulation: a minireview. Auton Neurosci 2006; 126-127: 30-8 35. Tsao D, Thomsen HK, Chou J, et al. TrkB agonists ameliorate obesity and associated metabolic conditions in mice. Endocrinology 2008; 149 (3): 1038-48 36. Yamanaka M, Itakura Y, Ono-Kishino M, et al. Intermittent administration of brain-derived neurotrophic factor (BDNF) ameliorates glucose metabolism and prevents pancreatic exhaustion in diabetic mice. J Biosci Bioeng 2008; 105 (4): 395-402 37. Molteni R, Wu A, Vaynman S. Exercise reverses the harmful effects of consumption of a high-fat diet on synaptic and behavioral plasticity associated to the action of brain-derived neurotrophic factor. Neuroscience 2004; 123 (2): 429-40 38. Komori T, Morikawa Y, Nanjo K, et al. Induction of brain-derived neurotrophic factor by leptin in the ventromedial hypothalamus. Neuroscience 2006; 139: 1107-15 39. Gray J, Yeo GS, Cox JJ, et al. Hyperphagia, severe obesity, impaired cognitive function, and hyperreactivity associated with functional loss of one copy of the brainderived neurotrophic factor (BDNF) gene. Diabetes 2006; 55 (12): 3366-71 40. Araya AV, Orellana X, Espinoza J. Evaluation of the effect of caloric restriction on serum BDNF in overweight and obese subjects: preliminary evidences. Endocrine 2008; 33 (3): 300-4 41. Wisse BE, Schwartz MW. The skinny on neurotrophins. Nat Neurosci 2003; 6 (7): 655-6
Sports Med 2010; 40 (9)
BDNF and Exercise in Humans
42. Huang AM, Jen CJ, Chen HF, et al., Compulsive exercise acutely upregulates rat hippocampal brain-derived neurotrophic factor. J Neural Transm 2006; 113 (7): 803-11 43. Radak Z, Toldy A, Szabo Z, et al., The effects of training and detraining on memory, neurotrophins and oxidative stress markers in rat brain. Neurochem Int 2006; 49 (4): 387-92 44. Ploughman M, Granter-Button S, Chernenko G, et al. Exercise intensity influences the temporal profile of growth factors involved in neuronal plasticity following focal ischemia. Brain Res 2007; 1150: 207-16 45. Soya H, Nakamura T, Deocaris CC, et al. BDNF induction with mild exercise in the rat hippocampus. Biochem Biophys Res Commun 2007; 358 (4): 961-7 46. Aguiar AS, Speck AE, Prediger RD, et al. Downhill training upregulates mice hippocampal and stratial brainderived neurotrophic factor levels. J Neural Transm 2008; 115 (9): 1251-5 47. Gold SM, Schulz K, Hartmann S, et al., Basal serum levels and reactivity of nerve growth factor and brain-derived neurotrophic factor to standardized acute exercise in multiple sclerosis and controls. J Neuroimmunol 2003; 183: 99-105 48. Moher D, Cook DJ, Eastwood S, et al., Improving the quality of reports of meta-analyses of randomised controlled trials: the QUOROM statement. Lancet 1999; 354: 1896-900 49. van Tulder M, Furlan A, Bombardier C. Updated method guidelines for systematic reviews in the Cochrane collaboration back review group. Spine 2003; 28 (12): 1290-9 50. Baker LD, Frank LL, Foster-Schubert K, et al. Effects of aerobic exercise on mild cognitive impairment. Arch Neurol 2010; 67(1): 71-9 51. Castellano V, White LJ. Serum brain-derived neurotrophic factor response to aerobic exercise in multiple sclerosis. J Neurol Sci 2008; 269 (1-2): 85-91 52. Chan KL, Tong KY, Yip SP. Relationship of serum brainderived neurotrophic factor (BDNF) and health-related lifestyle in healthy human subjects. Neurosci Lett 2008; 447 (2-3): 124-12 53. Currie J, Ramsbottom R, Ludlow H, et al. Cardio-respiratory fitness, habitual physical activity and serum brain derived neurotrophic factor (BDNF) in men and women. Neurosci Lett 2009; 451 (2): 152-5 54. Ferris LT, Williams JS, Shen C. The effect of acute exercise on serum brain-derived neurotrophic factor levels and cognitive function. Med Sci Sports Exerc 2007; 39 (4): 728-34 55. Floe¨l A, Ruscheweyh R, Kru¨ger K, et al. Physical activity and memory functions: are neurotrophins and cerebral gray matter volume the missing link? NeuroImage 2010; 49: 2756-63 56. Goekint M, Heyman E, Roelands B, et al. No influence of noradrenaline manipulation on acute exercise-induced increase of brain-derived neurotrophic factor. Med Sci Sports Exerc 2008; 40 (11): 1990-6 57. Goekint M, De Pauw K, Roelands B, et al. Strength training does not influence serum brain-derived neurotrophic factor. Eur J Appl Physiol. Epub 2010 May 14
ª 2010 Adis Data Information BV. All rights reserved.
799
58. Gustafsson G, Lira CM, Johansson J, et al. The acute response of plasma brain-derived neurotrophic factor as a result of exercise in major depression. Psychiatry Res 2009; 94 (12): 1159-60 59. Laske C, Banschbach S, Stransky E, et al. Exercise-induced normalization of decreased BDNF serum concentration in elderly women with remitted major depression. Int J Neuropsychopharmacol 2010; 13: 595-602 60. Levinger I, Goodman C, Matthews V, et al. BDNF, metabolic risk factors and resistance training in middle-aged individuals. Med Sci Sports Exerc 2008; 40 (3): 535-41 61. Nofuji Y, Suwa M, Moriyama Y, et al. Decreased serum brain-derived neurotrophic factor in trained men. Neurosci Lett 2008; 437 (1): 29-32 62. Rasmussen P, Brassard P, Adser H, et al. Evidence for a release of BDNF from the brain during exercise. Exp Physiol 2009; 94 (10): 1062-9 63. Rojas Vega S, Stru¨der H, Vera Wahrmann B, et al. Acute BDNF and cortisol response to low intensity exercise and following ramp incremental exercise to exhaustion in humans. Brain Res 2006; 1121 (1): 59-65 64. Rojas Vega S, Stru¨der HK, Vera Wahrman B, et al. Corrigendum to ‘acute BDNF and cortisol response to low intensity exercise and following ramp incremental exercise to exhaustion in humans’. Brain Res 2007; 1156: 174-5 65. Rojas Vega S, Abel T, Lindschulten R, et al. Impact of exercise on neuroplasticity-related proteins in spinal cord injured humans. Neuroscience 2008; 153 (4): 1064-70 66. Schiffer T, Schulte S, Hollmann W, et al. Effects of strength and endurance training on brain-derived neurotrophic factor and insulin-like growth factor 1 in humans. Horm Metab Res 2009; 41 (3): 250-4 67. Schulz K, Gold SM, Witte J, et al. Impact of aerobic training on immune-endocrine parameters, neurotrophic factors, quality of life and coordinative function in multiple sclerosis. J Neurol Sci 2004; 225 (1-2): 11-8 68. Seifert T, Brassard P, Wissenberg M, et al. Endurance training enhances BDNF release from the human brain. Am J Physiol Regul Integr Comp Physiol 2010; 298 (2): R372-7 69. Stro¨hle A, Stoy M, Graetz B, et al. Acute exercise ameliorates reduced brain-derived neurotrophic factor in patients with panic disorder. Psychoneuroendocrinology 2010; 35: 364-8 70. Tang SW, Chu E, Hui T, et al. Influence of exercise on serum brain-derived neurotrophic factor concentrations in healthy human subjects. Neurosci Lett 2008; 431 (1): 62-5 71. Winter B, Breitenstein C, Mooren FC, et al. High impact running improves learning. Neurobiol Learn Mem 2007; 87 (4): 597-609 72. Yarrow JF, White LJ, McCoy SC, et al. Training augments resistance exercise induced elevation of circulating brain derived neurotrophic factor (BDNF). Neurosci Lett 2010; 479 (2): 161-5 73. Yarrow JF, Borsa PA, Borst SE, et al. Neuroendocrine responses to an acute bout of eccentric-enhanced resistance exercise. Med Sci Sport Ex 2007; 39: 941-7 74. Yarrow JF, Borsa PA, Borst SE, et al. Early-phase neuroendocrine responses and strength adaptations following
Sports Med 2010; 40 (9)
Knaepen et al.
800
75.
76. 77.
78.
79.
80.
81. 82.
83.
84.
85.
86.
87.
88.
89.
90. 91.
eccentric-enhanced resistance training. J Strength Cond Res 2008; 22: 1205-14 Zoladz JA, Pilic A, Majerczak J, et al., Endurance training increases plasma brain-derived neurotrophic factor concentration in young healthy men. J Physiol Pharmacol 2008; 59 (7): 119-32 Borg GA. Psychophysical bases of perceived exertion. Med Sci Sports Exerc 1982; 14 (5): 377-81 Lommatzsch M, Zingler D, Schuhbaeck K. The impact of age, weight and gender on BDNF levels in human platelets and plasma. Neurobiol Aging 2005; 26: 115-23 Katoh-Semba R, Wakako R, Komori T. Age-related changes in BDNF protein levels in human serum: differences between autism cases and normal controls. Int J Devl Neurosci 2007; 25: 367-72 Vaynman S, Gomez-Pinilla F. Revenge of the ‘Sit’: how lifestyle impact neuronal and cognitive health through molecular systems that interface energy metabolism with neuronal plasticity. J Neurosci Res 2006; 84: 699-715 Proszasz J, Casaburi R, Somfay A, et al. A treadmill ramp protocol using simultaneous changes in speed and grade. Med Sci Sport Ex 2003; 35: 1596-603 Hagberg JM. Exercise assessment of arthritic and elderly individuals. Baillieres Clin Rheumatol 1994; 8 (1): 29-52 Berchtold NC, Chinn G, Chou M, et al. Exercise primes a molecular memory for brain-derived neurotrophic factor protein induction in the rat hippocampus. Neurosci 2005; 133 (3): 853-61 Levinger I, Goodman C, Hare DL, et al. The effect of resistance training on functional capacity and quality of life in individuals with high and low numbers of metabolic risk factors. Diabetes Care 2007; 30 (9): 2205-10 Banfi G, Bauer K, Brand W, et al. Use of anticoagulants in diagnostic laboratory investigations and stability of blood, plasma and serum samples [report no. WHO/DIL/LAB/99.1 rev. 2]. Geneva: World Health Organization, 2002 Schneider DJ, Tracy PB, Mann KG, et al. Differential effects of anticoagulants on the activation of platelets ex vivo. Circulation 1997; 96: 2877-83 Rosenfeld RD, Zeni L, Haniu M, et al. Purification and identification of brain-derived neurotrophic factor from human serum. Protein Expr Purif 1995; 6: 465-71 Lommatzsch M, Schloetcke K, Klotz J, et al., Brainderived neurotrophic factor in platelets and airflow limitation in asthma. Am J Respir Crit Care Med 2005; 171 (2): 115-20 Ziegenhorn AA, Schulte-Herbru¨ggen O, Danker-Hopfe H. Serum neurotrophins: a study on the time course and influencing factors in a large old age sample. Neurobiol Aging 2007; 28: 1436-45 Trajkovska V, Marcussen AB, Vinberg M, et al. Measurements of brain-derived neurotrophic factor: methodological aspects and demographical data. Brain Res Bull 2007; 73: 143-9 Ba¨rtsch P, Mairba¨url H, Friedmann B. Pseudo-anemia caused by sports. Ther Umsch 1998; 55(4): 251-5 Watts E. Athletes’ anaemia: a review of possible causes and guidelines on investigation. Br J Sports Med 1989; 23: 81-3
ª 2010 Adis Data Information BV. All rights reserved.
92. Kargotich S, Goodman C, Keast D, et al. The influence of exercise-induced plasma volume changes on the interpretation of biochemical data following high-intensity exercise. Clin J Sport Med 1997; 7 (3): 185-91 93. Kargotich S, Goodman C, Keast D, et al. The influence of exercise-induced plasma volume changes on the interpretation of biochemical parameters used for monitoring exercise, training and sport. Sports Med 1998; 26 (2): 101-17 94. van Beaumont W, Underkofler S, van Beaumont S. Erythrocyte volume, plasma volume, and acid-base changes in exercise and heat dehydration. J Appl Physiol 1981; 50 (6): 1255-62 95. Noga O, Hanf G, Scha¨per C, et al. The influence of inhalative corticosteroids on circulating nerve growth factor, brain-derived neurotrophic factor and neurotrophin-3 in allergic asthmatics. Clin Exp Allergy 2001; 31: 1906-12 96. Fuijimura H, Altar CA, Chen R, et al. Brain-derived neurotrophic factor is stored in human platelets and released by agonist stimulation. J Thromb Haemost 2002; 87: 728-34 97. Karege F, Perret G, Bondolfi G. Decreased serum brainderived neurotrophic factor levels in major depressed patients. Psychiatry Res 2002; 109: 143-8 98. Toyooka K, Asama K, Watanabe Y. Decreased levels of brain-derived neurotrophic factor in serum of chronic schizophrenic patients. Psychiatry Res 2002; 110 (3): 249-57 99. Shimizu E, Hashimoto K, Watanabe H, et al. Serum brainderived neurotrophic factor (BDNF) levels in schizophrenia are indistinguishable from controls. Neurosci Lett 2003; 351 (2): 111-4 100. Kozicz T, Tilburg-Ouwens D, Faludi G, et al. Gender-related urocortin 1 and brain-derived neurotrophic factor expression in the adult human midbrain of suicide victims with major depression. Neurosci 2008; 152 (4): 1015-23 101. Monteleone P, Tortorella A, Martiadis V. Opposite changes in the serum brain-derived neurotrophic factor in anorexia nervosa and obesity. Psychosom Med 2004; 66: 744-8 102. Begliuomini S, Lenzi E, Ninni F, et al. Plasma brainderived neurotrophic factor daily variations in men: correlation with cortisol circadian rhythm. J Endocrinol 2008; 197: 429-35 103. Piccinni A, Marazziti D, Del Debbio A, et al. Diurnal variation of plasma brain-derived neurotrophic factor (BDNF) in humans: an analysis of sex differences. Chronobiol Int 2008; 25 (5): 819-26 104. Pluchino N, Cubeddu A, Begliuomini S, et al. Daily variation of brain-derived neurotrophic factor and cortisol in women with normal menstrual cycles, undergoing oral contraception and in postmenopause. Hum Reprod 2009; 24 (9): 2303-9 105. Azoulay D, Vachapova V, Shihman B, et al. Lower brainderived neurotrophic factor in serum of relapsing remitting MS: reversal by glaturamer acetate. J Neuroimmunol 2005; 167: 215-8 106. Webster MJ, Herman MM, Kleinman JE, et al. BDNF and trkB mRNA expression in the hippocampus and temporal cortex during the human lifespan. Gene Expr Patterns 2006; 6: 941-51 107. Hayashi M, Yamashita A, Shimizu K, et al. Somatostatin and brain-derived neurotrophic factor mRNA expression
Sports Med 2010; 40 (9)
BDNF and Exercise in Humans
108.
109.
110.
111.
112.
113.
114.
115.
116.
117.
118.
119.
in the primate brain: decreased levels of mRNA during aging. Brain Res 1997; 749: 283-9 Silhol M, Bonnichon V, Rage F, et al. Age-related changes in brain-derived neurotrophic factor and tyrosine kinase receptor isoforms in the hippocampus and hypothalamus in male rats. Neuroscience 2005; 132: 613-24 Silhol M, Arancibia S, Perrin D, et al. Effect of aging on brain-derived neurotrophic factor, proBDNF, and their receptors in the hippocampus of Lou/C rats. Rejuvenation Res 2008; 11 (6): 1031-40 Chen ZY, Patel PD, Sant G. Variant brain-derived neurotrophic factor (Met66) alters the intracellular trafficking and activity-dependent secretion of wild type BDNF in neurosecretory cells and cortical neurons. J Neurosci 2004; 24 (18): 4401-11 Cassilhas RC, Viana VA, Grassmann V, et al. The impact of resistance exercise on the cognitive function of the elderly. Med Sci Sports Exerc 2007; 39 (8): 1401-7 Vitiello MV, Wilkinson CW, Merriam GR, et al. Successful 6-month endurance training does not alter insulin like growth factor-I in healthy older men and women. J Gerontol A Biol Sci Med Sci 1997; 52 (3): M149-54 Ding Q, Vaynman S, Akhavan M, et al. Insulin-like growth factor I interfaces with brain-derived neurotrophic factormediated synaptic plasticity to modulate aspects of exercise-induced cognitive function. Neuroscience 2006; 140: 823-33 Poduslo JF, Curran GL. Permeability at the blood-brain and blood-nerve barriers of the neurotrophic factors: NGF, CNTF, NT-3, BDNF. Brain Res Mol Brain Res 1996; 36: 280-6 Pan W, Banks WA, Fasold MB, et al. Transport of brainderived neurotrophic factor across the blood-brain barrier. Neuropharmacol 1998; 37: 1553-61 Griffin EW, Bechara RG, Birch AM. Exercise enhances hippocampal-dependent learning in the rat: evidence for a BDNF-related mechanism. Hippocampus 2009; 19: 973-80 Radka SF, Holst PA, Fritsche M, et al. Presence of brainderived neurotrophic factor in brain and human and rat but not mouse serum detected by a sensitive and specific immunoassay. Brain Res 1996; 709: 122-30 Yamamoto H, Gurney ME. Human platelets contain brain-derived neurotrophic factor. J Neurosci 1990; 10 (11): 3469-76 Nakahashi T, Fujimura H, Altar CA. Vascular endothelial cells synthesize and secrete brain-derived neurotrophic factor. FEBS Lett 2000; 470: 113-7
ª 2010 Adis Data Information BV. All rights reserved.
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120. Sobue G, Yamamoto M, Doyu M. Expression of mRNAs for neurotrophins (NGF, BDNF, and NT-3) and their receptors (p75NGFR, trk, trkB, and trkC) in human peripheral neuropathies. Neurochem Res 1998; 23 (6): 821-9 121. Besser M, Wank R. Cutting edge: clonally restricted production of the neurotrophins brain-derived neurotrophic factor and neurotrophin-3 mRNA by human immune cells and Th1/Th2-polarized expression of their receptors. J Immunol 1999; 162(11): 6303-6 122. Kerschensteiner M, Gallmeier E, Behrens L, et al. Activated human T cells, B cells, and monocytes produce brain-derived neurotrophic factor in vitro and in inflammatory brain lesions: a neuroprotective role or inflammation? J Exp Med 1999; 189 (5): 865-70 123. Noga O, Englmann C, Hanf G, et al. The production, storage and release of the neurotrophins nerve growth factor, brain-derived neurotrophic factor and neurotrophin-3 by human peripheral eosinophils in allergics and non-allergics. Clin Exp Allergy 2003; 33: 649-54 124. Raap U, Goltz C, Deneka N, et al. Brain-derived neurotrophic factor is increased in atopic dermatitis and modulates eosinophil functions compared with that seen in nonatopic subjects. J Allergy Clin Immunol 2005; 115 (6): 1268-75 125. Rost B, Hanf G, Ohnemus U, et al. Monocytes of allergics and non-allergics produce, store and release the neurotrophins NGF, BDNF and NT-3. Regul Pept 2005; 124 (1-3): 19-25 126. Donovan MJ, Miranda RC, Kraemer R, et al. Neurotrophin and neurotrophin receptors in vascular smooth muscle cells: regulation of expression in response to injury. Am J Pathol 1995; 147 (2): 309-24 127. Smith MA, Makino S, Kim SY. Stress increases brain-derived neurotrophic factor messenger ribonucleic acid in the hypothalamus and pituitary. Endocrinology 1995; 136 (9): 3743-50 128. Tsukinoki K, Saruta J, Sasaguri Y, et al. Immobilization stress induces BDNF in rat submanidbular glands. J Dent Res 2006; 85: 844-8 129. Tsukinoki K, Saruta J, Muto N, et al. Submandibular glands contribute to increase in plasma BDNF. J Dent Res 2007; 86: 260-4 130. Adlard PA, Perreau VM, Cotman CW. The exerciseinduced expression of BDNF within the hippocampus varies across life-span. Neurobiol Aging 2005; 26: 511-20
Correspondence: Prof. Dr Romain Meeusen, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Pleinlaan 2 B-1050 Brussels, Belgium. E-mail:
[email protected]
Sports Med 2010; 40 (9)
CORRESPONDENCE
Sports Med 2010; 40 (9): 803-807 0112-1642/10/0009-0803/$49.95/0
ª 2010 Adis Data Information BV. All rights reserved.
New Horizons for the Methodology and Physiology of Training Periodization Block Periodization: New Horizon or a False Dawn? Professor Issurin’s review[1] is to be commended on its overview of the historical evolution of periodization planning theory and the interesting general discussion. However, the central contention of the review, i.e. that block periodization represents a ‘new horizon’ in training planning, is, I suggest, premature and unsupported. To substantiate this position, consider the two layers of evidence and rationale within Professor Issurin’s review promoting the superiority of block periodization in elite training contexts. The first layer is anecdotal, and consists of selected exemplar cases of athletes and coaches who have achieved high levels of success employing block-training designs. However, within the elite sports environment it would seem readily apparent that high honours are commonly achieved using a variety of training approaches, reflecting distinct coaching philosophies and differing planning models. Hence, while the offered examples are undoubtedly interesting and deserve consideration, they remain unconvincing as evidence, lacking both contextual detail and critical comparisons. The second layer of supporting evidence refers to ‘‘two contemporary scientific concepts’’ that have been instrumental in the formulation of the block-periodized model; namely, the cumulative training effect and the residual training effect. However, within the review, the key citations for these concepts do not pertain to scientific evidence but, rather, refer to self-referenced opinion pieces by the author and another well known block-periodization advocate.[2] In reality, acknowledging that the benefits of physical training gradually accumulate over time (the cumulative effect) and that these benefits persist for some
period after training is terminated (the residual effect) are, perhaps, better described as self-evident truths, as opposed to scientific constructs. Indeed, Matveyev,[3] the foremost formulizer of the traditional periodization model, also considers the cumulative training effect and concepts corresponding to the residual training effect in his influential Fundamentals of Sports Training. What is not clear is how an awareness of such poorly understood concepts provide scientific support for block-periodization principles. In order to discriminate between either traditional or blockplanning methods on the basis of these very broad concepts, specific knowledge would be required relating to (i) the projected timeframes for retention or decay of specific fitness attributes; (ii) an understanding of how ongoing training interacts with previously conducted training to either accelerate or delay the erosion of previously developed fitness components; and (iii) an understanding of how these factors interact with a spectrum of individual-specific considerations, such as training histories and genetic predispositions. This is a knowledge base that clearly does not exist. Consequently, while the proffered anecdotal examples and accompanying logic may be alluring, block periodization cannot be rightly framed as a scientifically-validated planning construct, any more than could Matveyev’s seminal model or the raft of subsequently proposed periodization derivations.[4-7] Here, I hasten to add, experienced coach/scientist opinion is certainly not to be devalued or dismissed. However, before block periodization can rightly claim to be scientifically supported, an evidence-led, conceptuallyvalid chain of reasoning surely needs to be more coherently outlined. As an additional concern, while there is an apparent dearth of evidence supporting the blockperiodization concept, there is existing evidence that would appear to strongly challenge its central premise, i.e. that ‘‘each of these (fitness) targets requires specific physiological, morphological and psychological adaptation, and many of these workloads are not compatible, causing conflicting responses,’’ and that hence, ‘‘high performance athletes enhance their preparedness and performance
804
through large amounts of training stimuli that can hardly be obtained using multi-targeted mixed training’’[1] (page 194). Unravelling the interactivity of multi-targeted mixed training modes is obviously a complex task to address empirically. However, it has been tangentially explored in studies investigating the effects of concurrent strength and endurance training. The training modes required to develop strength and endurance frequently appear diametrically opposed, and these attributes would seem prime candidates for exhibiting inhibited training responses consequent to concurrent training. Hickson[8] classically demonstrated an ‘interference effect’ between concurrent strength and endurance training resulting in compromised strength development in previously untrained subjects, with similar findings subsequently reported by several other authors.[9-12] More recently, studies have demonstrated that concurrent training can be as effective in developing both strength and endurance as single attribute-focused interventions.[13,14] More pertinently, studies in a variety of sports, variously using well trained, elite and world-class athletes, have established that simultaneously training for both strength and endurance can bestow synergistic benefits to a variety of athletic performance measures, above and beyond the benefits realized by single modality training.[15-28] Without doubt, there is still much to be learned in relation to the intricacies of concurrent training. However, it appears clear that (i) the ‘optimized’ development of a single fitness attribute does not necessarily preclude the simultaneous advancement of other attributes; and (ii) mixed modality training has the potential, in an evidenced range of circumstances, to bestow synergisticallyadditive performance benefits. A more conceptual, less demonstrable, challenge to the logic presented in Professor Issurin’s review, relates to an implicit conceptual dogma evident throughout the periodized planning literature. Specifically, the paradoxical assumption that, despite the evident complexity and inherent unpredictability of the human adaptive response to any set of imposed stressors,[29-35] the future training of an inherently complex biological system is best pre-planned using deterministic logic, ª 2010 Adis Data Information BV. All rights reserved.
Letter to the Editor
mechanistic design frameworks and generalized rules. Reflecting on the evidence, it would appear premature to herald block periodization as a ‘new horizon’ in training planning, partly because of a fundamental lack of supporting evidence and clearly delineated rationale, and partly because contradictory evidence exists questioning its universal efficacy in elite contexts. What block periodization does positively contribute to current planning methodologies is a more formal description of a particular planning tactic that may be advantageously added to the elite coaches menu of potential planning options. Therefore, while blocked-training schemes may be useful ploys in specific training contexts, the claim that this framework represents a new departure in training planning may be somewhat overly enthusiastic. Hence, perhaps a more appropriate description of block periodization is ‘new variation’, rather than a ‘new horizon’, in sports training planning. John Kiely UK Athletics, Solihull, UK
Acknowledgements The author has no conflicts of interest that are directly relevant to the content of this letter.
References 1. Issurin VB. New horizons for the methodology and physiology of training periodization. Sports Med 2010; 40 (3): 189-206 2. Bondarchuk AP. Transfer of training in sports. Muskegon (MI): Ultimate Athlete Concepts, 2007 3. Matveyev L. Fundamentals of sports training. Moscow: Fizkultura i Sport, 1981 4. Brown LE. Nonlinear versus linear periodization models. Strength Cond J 2001; 23 (1): 42-4 5. Brown LE, Greenwood M. Periodization essentials and innovations in resistance training protocols. J Strength Cond Res 2005; 27 (4): 80-5 6. Rhea MR, Ball SD, Phillips WT, et al. A comparison of linear and daily undulating periodized programs with equated volume and intensity. J Strength Cond Res 2002 May; 16 (2): 250-5 7. Verkhoshansky YV. Programming and organization of training. Livonia (MI): Sportivny Press, 1988 8. Hickson RC. Interference of strength development by simultaneously training for strength and endurance. Eur J Appl Physiol Occup Physiol 1980; 45: 2-3
Sports Med 2010; 40 (9)
Letter to the Editor
9. Hennessy LC, Watson WS. The interference effects of training for strength and endurance simultaneously. J Strength Cond Res 1994; 8 (1): 12-9 10. Dudley GA, Djamil R. Incompatibility of endurance- and strength-training modes of exercise. J Appl Physiol 1985; 59: 1446-51 11. Hunter G, Demment R, Miller D. Development of strength and maximum oxygen uptake during simultaneous training for strength and endurance. J Sports Med Phys Fitness 1987; 27 (3): 269-75 12. Nelson AG, Arnall DA, Loy SF, et al. Consequences of combining strength and endurance training regimens. Phys Ther 1990 May; 70 (5): 287-94 13. McCarthy JP, Agre JC, Graf BK, et al. Compatibility of adaptive responses with combining strength and endurance training. Med Sci Sports Exerc 1995 Mar; 27 (3): 429-36 14. Shaw BS, Shaw I, Brown GA. Comparison of resistance and concurrent resistance and endurance training regimes in the development of strength. J Strength Cond Res 2009 Dec; 23 (9): 2507-14 15. Yamamoto LM, Klau JF, Casa DJ, et al. The effects of resistance training on road cycling performance among highly trained cyclists: a systematic review. J Strength Cond Res 2010 Feb; 24 (2): 560-6 16. Izquierdo-Gabarren M, Gonza´lez de Txabarri Expo´sito R, Garcı´ a-Pallare´s J, et al. Concurrent endurance and strength training not to failure optimizes performance gains. Med Sci Sports Exerc. Epub 2009 Dec 9 17. Balabinis CP, Psarakis CH, Moukas M, et al. Early phase changes by concurrent endurance and strength training. J Strength Cond Res 2003 May; 17 (2): 393-401 18. Davis WJ, Wood DT, Andrews RG, et al. Concurrent training enhances athletes’ strength, muscle endurance, and other measures. J Strength Cond Res 2008 Sep; 22 (5): 1487-502 19. Hickson RC, Dvorak BA, Gorostiaga EM, et al. Potential for strength and endurance training to amplify endurance performance. J Appl Physiol 1988 Nov; 65 (5): 2285-90 20. Mikkola JS, Rusko HK, Nummela AT, et al. Concurrent endurance and explosive type strength training increases activation and fast force production of leg extensor muscles in endurance athletes. J Strength Cond Res 2007 May; 21 (2): 613-20 21. Mikkola J, Rusko H, Nummela A, et al. Concurrent endurance and explosive type strength training improves neuromuscular and anaerobic characteristics in young distance runners. Int J Sports Med 2007 Jul; 28 (7): 602-11 22. Paavolainen L, Ha¨kkinen K, Ha¨ma¨la¨inen I, et al. Explosivestrength training improves 5-km running time by improving running economy and muscle power. J Appl Physiol 1999 May; 86 (5): 1527-33 23. Millet GP, Jaouen B, Borrani F, et al. Effects of concurrent endurance and strength training on running economy and VO2 kinetics. Med Sci Sports Exerc 2002; 34: 1351-9 24. Hickson RC, Dvorak BA, Gorostiaga EM, et al. Potential for strength and endurance training to amplify endurance performance. J Appl Physiol 1988; 65: 2285-90 25. Rønnestad BR, Hansen EA, Raastad T. Strength training improves 5-min all-out performance following 185 min of cycling. Scand J Med Sci Sports. Epub 2009 Nov 9
ª 2010 Adis Data Information BV. All rights reserved.
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26. Hoff J, Gran A, Helgerud J. Maximal strength training improves aerobic endurance performance. Scand J Med Sci Sports 2002; 12: 288-95 27. Hoff J, Helgerud J, Wisloff U. Maximal strength training improves work economy in trained female cross country skiers. Med Sci Sports Exerc 1999; 31: 870-7 28. Støren O, Helgerud J, Støa EM, et al. Maximal strength training improves running economy in distance runners. Med Sci Sports Exerc 2008; 40: 1087-92 29. Kudielka BM, Hellhammer DH, Wust S. Why do we respond so differently? Reviewing determinants of human salivary cortisol responses to challenge. Psychoneuroendochrinology 2009; 34: 2-18 30. Bouchard C, Rankinen T, Chagnon YC, et al. Genomic scan for maximal oxygen uptake and its response to training in the HERITAGE Family Study. J Appl Physiol 2000; 88 (2): 551-9 31. Skinner JS, Jasko´lski A, Jasko´lska A, et al. Age, sex, race, initial fitness, and response to training: the HERITAGE Family Study. J Appl Physiol 2001 May; 90 (5): 1770-6 32. Van Regenmortel M. The rational design of biological complexity: a deceptive metaphor. Proteomics 2007; 7: 965-75 33. Foster RG, Kreitzman L. Rhythms of life: the biological clocks that control the daily lives of every living thing. New Haven (CT) and London: Yale University Press, 2004 34. Beavan CM, Gill ND, Cook CJ. Salivary testosterone and cortisol responses in professional rugby players after four resistance exercise protocols. J Strength Cond Res 2008 Mar; 22 (2): 426-31 35. Beavan CM, Cook CJ, Gill ND. Significant strength gains observed in rugby players after specific resistance exercise protocols based on individual salivary testosterone responses. J Strength Cond Res 2008 Mar; 22 (2): 419-25
The Author’s Reply A letter to the editor has become a reason to continue consideration of training periodization on the pages of Sports Medicine.[1] I appreciate it and would like to thank Mr Kiely for this opportunity. The letter to the editor contains a number of issues, which need clarification. I will address them in the order of their appearance in the letter. Block periodization (BP) as an alternative to the traditional model has drawn the attention of Mr Kiely, who has marked two ‘‘layers of evidence and rationale...’’ based on his understanding of their importance. 1. The first layer in Mr Kiely’s view belongs to ‘‘anecdotal reports’’ which, as far as I could understand, he estimates as having low value as a source. My own evaluation of these sources is quite the opposite. Having worked for the major part of my life in close cooperation with coaches Sports Med 2010; 40 (9)
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(including world known and highly recognized experts in their sports), I have developed great respect for anecdotal reports as a source of successful experience, common sense and real creativity. However, be that as it may, in this concrete case my opponent is wrong; the sources cited in the review are not ‘‘anecdotal’’ they are serious publications, which summarize the data of well documented long-term projects with world-class athletes who have acheived the highest awards.[2-7] In saying that, the outcomes of the projects mentioned are not supported by ‘‘contextual details and critical comparisons,’’ which makes no sense; the review format does not allow the insertion of details, which interested readers can find in the cited items. In addition to the references mentioned, a number of newer publications can be listed in which the results of block periodized preparations are considered in accordance with standards of peer reviewed journals. A long-term project of a Spanish research group, complete with critical comparisons and serious analysis, resulted in a gold medal in the Beijing Olympic Games;[8] a similar project by Belorussian researchers was followed by high awards at the Athens and Beijing Olympic Games;[9] and a well balanced study in Alpine skiing was completed in Switzerland.[10] A number of PhD dissertations devoted to various aspects of BP training were defended.[11-13] Of course, as a new branch of the coaching science, BP needs many serious studies. In the meantime, curious readers can refer to my own recently published books,[14,15] which are also listed in the review.[1] 2. The second layer, as Mr Kiely has defined it, refers to concepts of cumulative and residual training effects. These essential basic concepts of training theory are qualified in the letter as ‘‘self-evident truths.’’ Having expressed familiarity with one book on the theory of training, Mr Kiely has confused the commonplaces of training science reality. Professor Matveyev[16] as ‘‘the foremost formuliser of traditional periodization,’’ described the cumulative training effect approximately 4 decades ago, but he never used or even mentioned the term ‘‘residual training effect,’’ not in Russian, not in English, not in Chinese. This term was proposed and conceptualized by James and Brian Counsilman 3 decades later.[17] The importance of these ª 2010 Adis Data Information BV. All rights reserved.
Letter to the Editor
generalized concepts for coaching science and training practice can not be underestimated. The text on page 260 of the review[1] clarifies the role of ‘‘residual training effect’’ in elucidating BP. Those requiring additional explanations for a better understanding of BP and how it differs from the traditional model can refer to earlier publications where these issues are clarified.[14,15,18] 3. Another part of the letter is devoted to consideration of the potential benefits of concurrently developing many targeted abilities, as proposed in the traditional model. Mr Kiely has cited 16 publications where the benefits of combined training for strength and endurance are proposed. He does not take into account that the number of targeted abilities (about nine to ten) greatly exceeds the number of proposed abilities by BP block mesocycles. Apparently, each mesocycle should be focused on developing a number (usually three) of abilities – but not one. Mr Keily totally ignores the fact that the block-mesocycle accumulation for developing basic motor abilities (page 201) prescribes concurrent training for muscular strength and aerobic endurance. Therefore, the 16 references cited in the letter do not refute, but rather support the methodic approach of BP, which proposes combined development of compatible abilities and separating work on incompatible training modalities. Thus, this critical attack seems to stem from a careless reading of the review. 4. The final part of the letter contains a passage on the ‘‘...inherent unpredictability of the human adaptive response to any set of imposed stressors... ,’’ which is supported by citations from a number of scientific publications. Addressing such a statement to a serious sport science journal seems strange at best. It is commonly accepted that each training system, every researcher and the approach of each coach is based on the supposition that expected response will be adequate for transmitting athlete stimulation. This doesn’t mean that each estimate of adaptive response can be numerically predicted. However, limitations on predictability do not imply a lack of determinism in training response but could be caused by an insufficiency of available information. This generally accepted deterministic approach completely corresponds to evidence provided by Professor Bouchard Sports Med 2010; 40 (9)
Letter to the Editor
807
and co-workers in publications[19,20] cited by Mr Kiely in support of his agnostic declaration. Ongoing studies by this research group are intended to unravel the reasons underlying human heterogeneity in response to regular training. Finally, Mr Kiely considers pre-planned training following deterministic logic and generalized rules as a ‘‘paradoxical assumption.’’ It is known that various paths can be used to lead to outstanding athletic achievements but it is hard for me to imagine that anyone can excel in contemporary sport by working contrary to deterministic logic and generalized rules. I hope this additional consideration of my paper will attract further interest by the Sports Medicine audience in the actual problems of highperformance athletic training.
6.
7.
8.
9.
10.
11.
Vladimir Issurin Professor of Exercise and Sport Science, Elite Sport Department at the Wingate Institute for Physical Education and Sport, Netanya, Israel
12.
13.
Acknowledgements The author has no conflict of interest that is directly relevant to content of this letter.
14. 15.
References 1. Issurin VB. New horizons for the methodology and physiology of training periodization. Sports Med 2010; 40 (3): 189-206 2. Bondarchuk AP. Training of track and field athletes. Kiev: Health Publishing (Zdorovie), 1986 3. Bondarchuk AP. Constructing a training system. Track Technique 1988; 102: 3254-69 4. Issurin V, Kaverin V. Planning and design of annual preparation cycle in canoe-kayak paddling. In: Samsonov EB, Kaverin VF, editors. Grebnoj sport (Rowing, Canoeing, Kayaking) [in Russian]. Moscow: FiS Publishing, 1985: 25-9 5. Kaverin V, Issurin V. Performance analysis and preparation’s concept of the USSR canoe-kayak national team in the
ª 2010 Adis Data Information BV. All rights reserved.
16. 17. 18. 19.
20.
XXIV Seoul Olympic Games. Sport-Science Gerald 1989; 1-2: 45-7 Pyne DB, Touretski G. An analysis of the training of Olympic Sprint Champion Alexandre Popov. Australian Swim Coach 1993; 10 (5): 5-14 Touretski G. Preparation of sprint events. 1998 ASCTA Convention. Canberra, ACT: Australian Institute of Sport, 1998 Garcia-Pallares J, Garcia-Fernandes M, Sanches-Medina L, et al. Performance changes in world-class kayakers following two different training periodization models. Eur J Appl Physiol. Epub 2010 Apr 23 Shantarovich VV, Narskin AG, Shantarovich AV. Block training system within Olympic preparation cycle of toplevel canoe-kayak paddlers. In: Bondar AI, editor. Actual problems of high-performance sport towards the XXIX Beijing Olympic Games. Minsk: Research Sport Institute of Belarus, 2006: 113-7 Breil FA, Weber SN, Koller S, et al. Block training periodization in alpine skiing: effects of 11-day HIT on VO2max and performance. Eur J Appl Physiol. Epub 2010 Apr 3 Klementiev II. Training program of long standing technical improvement for achievement and maintenance of outstanding sportsmanship [dissertation]. Riga: Latvian Sport Pedagogical Academy, 1993 Kaufman LY. Individual simulation of specialized training and strength improvement in high-level swimmers coaching [dissertation]. Riga: Latvian Pedagogical University, 2001 Shkliar VI. Structure, organization and steering in highperformance sport on the regional level (on the example of Jerusalem) [dissertation in Russian]. Moscow: All-Russian Research Institute for Physical Culture and Sport, 2002 Issurin V. Block Periodization: breakthrough in sport training. Muskegon (MI): Ultimate Training Concepts Publishing, 2008 Issurin V. Principles and basics of advanced training of athletes. Muskegon (MI): Ultimate Athletes Concepts Publishing, 2008 Matveyev LP. The bases of sport training [in Russian]. Moscow: FiS Publishing, 1977 Counsilman BE, Counsilman J. The residual effects of training. J Swim Res 1991; 7: 5-12 Issurin V. Block Periodization versus traditional training theory: a review. J Sports Med Phys Fitness 2008; 48 (1): 65-75 Bouchard C, Rankinen T, Chagnon YC, et al. Genomic scan for maximal oxygen uptake and its response to training in the HERITAGE Family Study. J Appl Physiol 2000; 88 (2): 551-9 Skinner JS, Jasko´lski A, Jasko´lska A, et al. Age, sex, race, initial fitness, and response to training: the HERITAGE Family Study. J Appl Physiol 2001 May; 90 (5): 1770-6
Sports Med 2010; 40 (9)
CORRESPONDENCE
Sports Med 2010; 40 (9): 803-807 0112-1642/10/0009-0803/$49.95/0
ª 2010 Adis Data Information BV. All rights reserved.
New Horizons for the Methodology and Physiology of Training Periodization Block Periodization: New Horizon or a False Dawn? Professor Issurin’s review[1] is to be commended on its overview of the historical evolution of periodization planning theory and the interesting general discussion. However, the central contention of the review, i.e. that block periodization represents a ‘new horizon’ in training planning, is, I suggest, premature and unsupported. To substantiate this position, consider the two layers of evidence and rationale within Professor Issurin’s review promoting the superiority of block periodization in elite training contexts. The first layer is anecdotal, and consists of selected exemplar cases of athletes and coaches who have achieved high levels of success employing block-training designs. However, within the elite sports environment it would seem readily apparent that high honours are commonly achieved using a variety of training approaches, reflecting distinct coaching philosophies and differing planning models. Hence, while the offered examples are undoubtedly interesting and deserve consideration, they remain unconvincing as evidence, lacking both contextual detail and critical comparisons. The second layer of supporting evidence refers to ‘‘two contemporary scientific concepts’’ that have been instrumental in the formulation of the block-periodized model; namely, the cumulative training effect and the residual training effect. However, within the review, the key citations for these concepts do not pertain to scientific evidence but, rather, refer to self-referenced opinion pieces by the author and another well known block-periodization advocate.[2] In reality, acknowledging that the benefits of physical training gradually accumulate over time (the cumulative effect) and that these benefits persist for some
period after training is terminated (the residual effect) are, perhaps, better described as self-evident truths, as opposed to scientific constructs. Indeed, Matveyev,[3] the foremost formulizer of the traditional periodization model, also considers the cumulative training effect and concepts corresponding to the residual training effect in his influential Fundamentals of Sports Training. What is not clear is how an awareness of such poorly understood concepts provide scientific support for block-periodization principles. In order to discriminate between either traditional or blockplanning methods on the basis of these very broad concepts, specific knowledge would be required relating to (i) the projected timeframes for retention or decay of specific fitness attributes; (ii) an understanding of how ongoing training interacts with previously conducted training to either accelerate or delay the erosion of previously developed fitness components; and (iii) an understanding of how these factors interact with a spectrum of individual-specific considerations, such as training histories and genetic predispositions. This is a knowledge base that clearly does not exist. Consequently, while the proffered anecdotal examples and accompanying logic may be alluring, block periodization cannot be rightly framed as a scientifically-validated planning construct, any more than could Matveyev’s seminal model or the raft of subsequently proposed periodization derivations.[4-7] Here, I hasten to add, experienced coach/scientist opinion is certainly not to be devalued or dismissed. However, before block periodization can rightly claim to be scientifically supported, an evidence-led, conceptuallyvalid chain of reasoning surely needs to be more coherently outlined. As an additional concern, while there is an apparent dearth of evidence supporting the blockperiodization concept, there is existing evidence that would appear to strongly challenge its central premise, i.e. that ‘‘each of these (fitness) targets requires specific physiological, morphological and psychological adaptation, and many of these workloads are not compatible, causing conflicting responses,’’ and that hence, ‘‘high performance athletes enhance their preparedness and performance
804
through large amounts of training stimuli that can hardly be obtained using multi-targeted mixed training’’[1] (page 194). Unravelling the interactivity of multi-targeted mixed training modes is obviously a complex task to address empirically. However, it has been tangentially explored in studies investigating the effects of concurrent strength and endurance training. The training modes required to develop strength and endurance frequently appear diametrically opposed, and these attributes would seem prime candidates for exhibiting inhibited training responses consequent to concurrent training. Hickson[8] classically demonstrated an ‘interference effect’ between concurrent strength and endurance training resulting in compromised strength development in previously untrained subjects, with similar findings subsequently reported by several other authors.[9-12] More recently, studies have demonstrated that concurrent training can be as effective in developing both strength and endurance as single attribute-focused interventions.[13,14] More pertinently, studies in a variety of sports, variously using well trained, elite and world-class athletes, have established that simultaneously training for both strength and endurance can bestow synergistic benefits to a variety of athletic performance measures, above and beyond the benefits realized by single modality training.[15-28] Without doubt, there is still much to be learned in relation to the intricacies of concurrent training. However, it appears clear that (i) the ‘optimized’ development of a single fitness attribute does not necessarily preclude the simultaneous advancement of other attributes; and (ii) mixed modality training has the potential, in an evidenced range of circumstances, to bestow synergisticallyadditive performance benefits. A more conceptual, less demonstrable, challenge to the logic presented in Professor Issurin’s review, relates to an implicit conceptual dogma evident throughout the periodized planning literature. Specifically, the paradoxical assumption that, despite the evident complexity and inherent unpredictability of the human adaptive response to any set of imposed stressors,[29-35] the future training of an inherently complex biological system is best pre-planned using deterministic logic, ª 2010 Adis Data Information BV. All rights reserved.
Letter to the Editor
mechanistic design frameworks and generalized rules. Reflecting on the evidence, it would appear premature to herald block periodization as a ‘new horizon’ in training planning, partly because of a fundamental lack of supporting evidence and clearly delineated rationale, and partly because contradictory evidence exists questioning its universal efficacy in elite contexts. What block periodization does positively contribute to current planning methodologies is a more formal description of a particular planning tactic that may be advantageously added to the elite coaches menu of potential planning options. Therefore, while blocked-training schemes may be useful ploys in specific training contexts, the claim that this framework represents a new departure in training planning may be somewhat overly enthusiastic. Hence, perhaps a more appropriate description of block periodization is ‘new variation’, rather than a ‘new horizon’, in sports training planning. John Kiely UK Athletics, Solihull, UK
Acknowledgements The author has no conflicts of interest that are directly relevant to the content of this letter.
References 1. Issurin VB. New horizons for the methodology and physiology of training periodization. Sports Med 2010; 40 (3): 189-206 2. Bondarchuk AP. Transfer of training in sports. Muskegon (MI): Ultimate Athlete Concepts, 2007 3. Matveyev L. Fundamentals of sports training. Moscow: Fizkultura i Sport, 1981 4. Brown LE. Nonlinear versus linear periodization models. Strength Cond J 2001; 23 (1): 42-4 5. Brown LE, Greenwood M. Periodization essentials and innovations in resistance training protocols. J Strength Cond Res 2005; 27 (4): 80-5 6. Rhea MR, Ball SD, Phillips WT, et al. A comparison of linear and daily undulating periodized programs with equated volume and intensity. J Strength Cond Res 2002 May; 16 (2): 250-5 7. Verkhoshansky YV. Programming and organization of training. Livonia (MI): Sportivny Press, 1988 8. Hickson RC. Interference of strength development by simultaneously training for strength and endurance. Eur J Appl Physiol Occup Physiol 1980; 45: 2-3
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9. Hennessy LC, Watson WS. The interference effects of training for strength and endurance simultaneously. J Strength Cond Res 1994; 8 (1): 12-9 10. Dudley GA, Djamil R. Incompatibility of endurance- and strength-training modes of exercise. J Appl Physiol 1985; 59: 1446-51 11. Hunter G, Demment R, Miller D. Development of strength and maximum oxygen uptake during simultaneous training for strength and endurance. J Sports Med Phys Fitness 1987; 27 (3): 269-75 12. Nelson AG, Arnall DA, Loy SF, et al. Consequences of combining strength and endurance training regimens. Phys Ther 1990 May; 70 (5): 287-94 13. McCarthy JP, Agre JC, Graf BK, et al. Compatibility of adaptive responses with combining strength and endurance training. Med Sci Sports Exerc 1995 Mar; 27 (3): 429-36 14. Shaw BS, Shaw I, Brown GA. Comparison of resistance and concurrent resistance and endurance training regimes in the development of strength. J Strength Cond Res 2009 Dec; 23 (9): 2507-14 15. Yamamoto LM, Klau JF, Casa DJ, et al. The effects of resistance training on road cycling performance among highly trained cyclists: a systematic review. J Strength Cond Res 2010 Feb; 24 (2): 560-6 16. Izquierdo-Gabarren M, Gonza´lez de Txabarri Expo´sito R, Garcı´ a-Pallare´s J, et al. Concurrent endurance and strength training not to failure optimizes performance gains. Med Sci Sports Exerc. Epub 2009 Dec 9 17. Balabinis CP, Psarakis CH, Moukas M, et al. Early phase changes by concurrent endurance and strength training. J Strength Cond Res 2003 May; 17 (2): 393-401 18. Davis WJ, Wood DT, Andrews RG, et al. Concurrent training enhances athletes’ strength, muscle endurance, and other measures. J Strength Cond Res 2008 Sep; 22 (5): 1487-502 19. Hickson RC, Dvorak BA, Gorostiaga EM, et al. Potential for strength and endurance training to amplify endurance performance. J Appl Physiol 1988 Nov; 65 (5): 2285-90 20. Mikkola JS, Rusko HK, Nummela AT, et al. Concurrent endurance and explosive type strength training increases activation and fast force production of leg extensor muscles in endurance athletes. J Strength Cond Res 2007 May; 21 (2): 613-20 21. Mikkola J, Rusko H, Nummela A, et al. Concurrent endurance and explosive type strength training improves neuromuscular and anaerobic characteristics in young distance runners. Int J Sports Med 2007 Jul; 28 (7): 602-11 22. Paavolainen L, Ha¨kkinen K, Ha¨ma¨la¨inen I, et al. Explosivestrength training improves 5-km running time by improving running economy and muscle power. J Appl Physiol 1999 May; 86 (5): 1527-33 23. Millet GP, Jaouen B, Borrani F, et al. Effects of concurrent endurance and strength training on running economy and VO2 kinetics. Med Sci Sports Exerc 2002; 34: 1351-9 24. Hickson RC, Dvorak BA, Gorostiaga EM, et al. Potential for strength and endurance training to amplify endurance performance. J Appl Physiol 1988; 65: 2285-90 25. Rønnestad BR, Hansen EA, Raastad T. Strength training improves 5-min all-out performance following 185 min of cycling. Scand J Med Sci Sports. Epub 2009 Nov 9
ª 2010 Adis Data Information BV. All rights reserved.
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26. Hoff J, Gran A, Helgerud J. Maximal strength training improves aerobic endurance performance. Scand J Med Sci Sports 2002; 12: 288-95 27. Hoff J, Helgerud J, Wisloff U. Maximal strength training improves work economy in trained female cross country skiers. Med Sci Sports Exerc 1999; 31: 870-7 28. Støren O, Helgerud J, Støa EM, et al. Maximal strength training improves running economy in distance runners. Med Sci Sports Exerc 2008; 40: 1087-92 29. Kudielka BM, Hellhammer DH, Wust S. Why do we respond so differently? Reviewing determinants of human salivary cortisol responses to challenge. Psychoneuroendochrinology 2009; 34: 2-18 30. Bouchard C, Rankinen T, Chagnon YC, et al. Genomic scan for maximal oxygen uptake and its response to training in the HERITAGE Family Study. J Appl Physiol 2000; 88 (2): 551-9 31. Skinner JS, Jasko´lski A, Jasko´lska A, et al. Age, sex, race, initial fitness, and response to training: the HERITAGE Family Study. J Appl Physiol 2001 May; 90 (5): 1770-6 32. Van Regenmortel M. The rational design of biological complexity: a deceptive metaphor. Proteomics 2007; 7: 965-75 33. Foster RG, Kreitzman L. Rhythms of life: the biological clocks that control the daily lives of every living thing. New Haven (CT) and London: Yale University Press, 2004 34. Beavan CM, Gill ND, Cook CJ. Salivary testosterone and cortisol responses in professional rugby players after four resistance exercise protocols. J Strength Cond Res 2008 Mar; 22 (2): 426-31 35. Beavan CM, Cook CJ, Gill ND. Significant strength gains observed in rugby players after specific resistance exercise protocols based on individual salivary testosterone responses. J Strength Cond Res 2008 Mar; 22 (2): 419-25
The Author’s Reply A letter to the editor has become a reason to continue consideration of training periodization on the pages of Sports Medicine.[1] I appreciate it and would like to thank Mr Kiely for this opportunity. The letter to the editor contains a number of issues, which need clarification. I will address them in the order of their appearance in the letter. Block periodization (BP) as an alternative to the traditional model has drawn the attention of Mr Kiely, who has marked two ‘‘layers of evidence and rationale...’’ based on his understanding of their importance. 1. The first layer in Mr Kiely’s view belongs to ‘‘anecdotal reports’’ which, as far as I could understand, he estimates as having low value as a source. My own evaluation of these sources is quite the opposite. Having worked for the major part of my life in close cooperation with coaches Sports Med 2010; 40 (9)
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(including world known and highly recognized experts in their sports), I have developed great respect for anecdotal reports as a source of successful experience, common sense and real creativity. However, be that as it may, in this concrete case my opponent is wrong; the sources cited in the review are not ‘‘anecdotal’’ they are serious publications, which summarize the data of well documented long-term projects with world-class athletes who have acheived the highest awards.[2-7] In saying that, the outcomes of the projects mentioned are not supported by ‘‘contextual details and critical comparisons,’’ which makes no sense; the review format does not allow the insertion of details, which interested readers can find in the cited items. In addition to the references mentioned, a number of newer publications can be listed in which the results of block periodized preparations are considered in accordance with standards of peer reviewed journals. A long-term project of a Spanish research group, complete with critical comparisons and serious analysis, resulted in a gold medal in the Beijing Olympic Games;[8] a similar project by Belorussian researchers was followed by high awards at the Athens and Beijing Olympic Games;[9] and a well balanced study in Alpine skiing was completed in Switzerland.[10] A number of PhD dissertations devoted to various aspects of BP training were defended.[11-13] Of course, as a new branch of the coaching science, BP needs many serious studies. In the meantime, curious readers can refer to my own recently published books,[14,15] which are also listed in the review.[1] 2. The second layer, as Mr Kiely has defined it, refers to concepts of cumulative and residual training effects. These essential basic concepts of training theory are qualified in the letter as ‘‘self-evident truths.’’ Having expressed familiarity with one book on the theory of training, Mr Kiely has confused the commonplaces of training science reality. Professor Matveyev[16] as ‘‘the foremost formuliser of traditional periodization,’’ described the cumulative training effect approximately 4 decades ago, but he never used or even mentioned the term ‘‘residual training effect,’’ not in Russian, not in English, not in Chinese. This term was proposed and conceptualized by James and Brian Counsilman 3 decades later.[17] The importance of these ª 2010 Adis Data Information BV. All rights reserved.
Letter to the Editor
generalized concepts for coaching science and training practice can not be underestimated. The text on page 260 of the review[1] clarifies the role of ‘‘residual training effect’’ in elucidating BP. Those requiring additional explanations for a better understanding of BP and how it differs from the traditional model can refer to earlier publications where these issues are clarified.[14,15,18] 3. Another part of the letter is devoted to consideration of the potential benefits of concurrently developing many targeted abilities, as proposed in the traditional model. Mr Kiely has cited 16 publications where the benefits of combined training for strength and endurance are proposed. He does not take into account that the number of targeted abilities (about nine to ten) greatly exceeds the number of proposed abilities by BP block mesocycles. Apparently, each mesocycle should be focused on developing a number (usually three) of abilities – but not one. Mr Keily totally ignores the fact that the block-mesocycle accumulation for developing basic motor abilities (page 201) prescribes concurrent training for muscular strength and aerobic endurance. Therefore, the 16 references cited in the letter do not refute, but rather support the methodic approach of BP, which proposes combined development of compatible abilities and separating work on incompatible training modalities. Thus, this critical attack seems to stem from a careless reading of the review. 4. The final part of the letter contains a passage on the ‘‘...inherent unpredictability of the human adaptive response to any set of imposed stressors... ,’’ which is supported by citations from a number of scientific publications. Addressing such a statement to a serious sport science journal seems strange at best. It is commonly accepted that each training system, every researcher and the approach of each coach is based on the supposition that expected response will be adequate for transmitting athlete stimulation. This doesn’t mean that each estimate of adaptive response can be numerically predicted. However, limitations on predictability do not imply a lack of determinism in training response but could be caused by an insufficiency of available information. This generally accepted deterministic approach completely corresponds to evidence provided by Professor Bouchard Sports Med 2010; 40 (9)
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and co-workers in publications[19,20] cited by Mr Kiely in support of his agnostic declaration. Ongoing studies by this research group are intended to unravel the reasons underlying human heterogeneity in response to regular training. Finally, Mr Kiely considers pre-planned training following deterministic logic and generalized rules as a ‘‘paradoxical assumption.’’ It is known that various paths can be used to lead to outstanding athletic achievements but it is hard for me to imagine that anyone can excel in contemporary sport by working contrary to deterministic logic and generalized rules. I hope this additional consideration of my paper will attract further interest by the Sports Medicine audience in the actual problems of highperformance athletic training.
6.
7.
8.
9.
10.
11.
Vladimir Issurin Professor of Exercise and Sport Science, Elite Sport Department at the Wingate Institute for Physical Education and Sport, Netanya, Israel
12.
13.
Acknowledgements The author has no conflict of interest that is directly relevant to content of this letter.
14. 15.
References 1. Issurin VB. New horizons for the methodology and physiology of training periodization. Sports Med 2010; 40 (3): 189-206 2. Bondarchuk AP. Training of track and field athletes. Kiev: Health Publishing (Zdorovie), 1986 3. Bondarchuk AP. Constructing a training system. Track Technique 1988; 102: 3254-69 4. Issurin V, Kaverin V. Planning and design of annual preparation cycle in canoe-kayak paddling. In: Samsonov EB, Kaverin VF, editors. Grebnoj sport (Rowing, Canoeing, Kayaking) [in Russian]. Moscow: FiS Publishing, 1985: 25-9 5. Kaverin V, Issurin V. Performance analysis and preparation’s concept of the USSR canoe-kayak national team in the
ª 2010 Adis Data Information BV. All rights reserved.
16. 17. 18. 19.
20.
XXIV Seoul Olympic Games. Sport-Science Gerald 1989; 1-2: 45-7 Pyne DB, Touretski G. An analysis of the training of Olympic Sprint Champion Alexandre Popov. Australian Swim Coach 1993; 10 (5): 5-14 Touretski G. Preparation of sprint events. 1998 ASCTA Convention. Canberra, ACT: Australian Institute of Sport, 1998 Garcia-Pallares J, Garcia-Fernandes M, Sanches-Medina L, et al. Performance changes in world-class kayakers following two different training periodization models. Eur J Appl Physiol. Epub 2010 Apr 23 Shantarovich VV, Narskin AG, Shantarovich AV. Block training system within Olympic preparation cycle of toplevel canoe-kayak paddlers. In: Bondar AI, editor. Actual problems of high-performance sport towards the XXIX Beijing Olympic Games. Minsk: Research Sport Institute of Belarus, 2006: 113-7 Breil FA, Weber SN, Koller S, et al. Block training periodization in alpine skiing: effects of 11-day HIT on VO2max and performance. Eur J Appl Physiol. Epub 2010 Apr 3 Klementiev II. Training program of long standing technical improvement for achievement and maintenance of outstanding sportsmanship [dissertation]. Riga: Latvian Sport Pedagogical Academy, 1993 Kaufman LY. Individual simulation of specialized training and strength improvement in high-level swimmers coaching [dissertation]. Riga: Latvian Pedagogical University, 2001 Shkliar VI. Structure, organization and steering in highperformance sport on the regional level (on the example of Jerusalem) [dissertation in Russian]. Moscow: All-Russian Research Institute for Physical Culture and Sport, 2002 Issurin V. Block Periodization: breakthrough in sport training. Muskegon (MI): Ultimate Training Concepts Publishing, 2008 Issurin V. Principles and basics of advanced training of athletes. Muskegon (MI): Ultimate Athletes Concepts Publishing, 2008 Matveyev LP. The bases of sport training [in Russian]. Moscow: FiS Publishing, 1977 Counsilman BE, Counsilman J. The residual effects of training. J Swim Res 1991; 7: 5-12 Issurin V. Block Periodization versus traditional training theory: a review. J Sports Med Phys Fitness 2008; 48 (1): 65-75 Bouchard C, Rankinen T, Chagnon YC, et al. Genomic scan for maximal oxygen uptake and its response to training in the HERITAGE Family Study. J Appl Physiol 2000; 88 (2): 551-9 Skinner JS, Jasko´lski A, Jasko´lska A, et al. Age, sex, race, initial fitness, and response to training: the HERITAGE Family Study. J Appl Physiol 2001 May; 90 (5): 1770-6
Sports Med 2010; 40 (9)
