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Effect of COL5A1, GDF5, and PPARA Genes on a Movement Screen and Neuromuscular Performance in Adolescent Team Sport Athletes

Stastny, Petr1; Lehnert, Michal2; De Ste Croix, Mark3; Petr, Miroslav1; Svoboda, Zdenek2; Maixnerova, Eliska2; Varekova, Renata2; Botek, Michal2; Petrek, Martin4; Kocourkova, Lenka4; Cięszczyk, Pawel5,6

The Journal of Strength & Conditioning Research: August 2019 - Volume 33 - Issue 8 - p 2057–2065
doi: 10.1519/JSC.0000000000003142
Original Research
Open

Stastny, P, Lehnert, M, De Ste Croix, M, Petr, M, Svoboda, Z, Maixnerova, E, Varekova, R, Botek, M, Petrek, M, Lenka, K, and Cięszczyk, P. Effect of COL5A1, GDF5, and PPARA genes on a movement screen and neuromuscular performance in adolescent team sport athletes. J Strength Cond Res 33(8): 2057–2065, 2019—The risk of injury increases with adolescents' chronological age and may be related to limited muscle function neuromuscular, genetic, and biomechanical factors. The purpose of this study was to determine whether COL5A1, PPARA, and GDF5 genes are associated with muscle functions and stretch-shortening cycle performance in adolescent athletes. One hundred forty-six youth players (14.4 ± 0.2 years) from various team sports (basketball n = 54, soccer n = 50, handball n = 32) underwent a manual test for muscle function, maturity estimation, functional bend test (FBT), passive straight leg raise (SLR) test, leg stiffness test, test of reactive strength index (RSI), and gene sampling for COL5A1, PPARA, and GDF5. The χ2 test did not show any differences in allele or genotype frequency between participants before and after peak height velocity. Multivariate analysis of variance showed that COL5A1 rs12722 CT heterozygotes had worse score in FBT (p < 0.001), worse score in SLR (p = 0.003), and lower maturity offset (p = 0.029, only in females) than TT homozygotes. Male GDF5 rs143383 GG homozygotes showed better score in SLR than AA and AG genotypes (p = 0.003), and AA and AG genotypes in both sex had greater RSI than GG homozygotes (p = 0.016). The PPARA rs4253778 CC homozygotes had greater RSI than GG and GC genotypes (p = 0.004). The CT genotype in COL5A1 rs12722 is possible predictor of functional movement disruption in the posterior hip muscle chain, causing shortening in FBT and SLR, which includes hamstrings function. CT genotype in COL5A1 rs12722 should be involved in programs targeting hamstring and posterior hip muscle chain.

1Department of Sport Games, Faculty of Physical Education and Sport, Charles University, Prague, Czech Republic;

2Department of Sport, Faculty of Physical Culture, Palacky University Olomouc, Olomouc, Czech Republic;

3School of Sport and Exercise, Exercise and Sport Research Center, University of Gloucestershire, Gloucester, United Kingdom;

4Faculty of Medicine, Palacky University Olomouc, Olomouc, Czech Republic;

5Department of Physical Education, Gdansk University of Physical Education and Sport, Gdansk, Poland; and

6The Jerzy Kukuczka Academy of Physical Education in Katowice, Katowice, Poland

Address correspondence to Dr. Stastny Petr, stastny@ftvs.cuni.cz.

This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

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Introduction

Sports games are popular among adolescent at various performance levels and are important for the development of physical health, mental health, and for social development (46,64). Adolescence is characterized by maturation, which evokes muscle-tendon unit growth resulting in a steep increase in strength and power performance on the one hand (34) and an increased risk of injury on the other (45,58). Both physical performance and noncontact injuries are multifactorial domains including many intrinsic and extrinsic factors, which should also include the genetic profile (38,46). However, the effect of genetics on muscle injury predictors and neuromuscular performance in adolescents is scarce in current research.

It has been acknowledged that the risk of injury increases with chronological age and may be related to important periods during growth and maturation (45). According to a previous study, the 13- to 18-year-old age group is subject to the greatest risk, and most injuries are likely to occur during this period (53,58). Others have suggested that injury incidence is highest around the time of peak height velocity (PHV) (62), and that females seem to have a greater relative risk of a noncontact injury compared with males when hours of athlete exposure are taken into account (63). The higher incidence of injury during PHV in women may be explained by anatomical, neuromuscular, and hormonal differences (20), or by genetic factors influencing the soft tissue (2,33,56). Therefore, current efforts focus on injury prediction during the high-risk maturation period because a sustained injury itself is one of the strongest reinjury predictors (12,23).

Physical performance and the risk of injury have been associated with ligament and tendon properties, which are dependent on individual genotypes. The collagen alpha chain (COL5A1) gene has been associated with mechanical properties of tendon structure in the knee extensors in vivo (26), and tendon and ligament injuries (57). Specifically, the COL5A1 rs12722 CT heterozygotes have been linked to poorer flexibility than CC and TT homozygotes (6) during a sit and reach test. Peroxisome proliferator–activated receptor alpha (PPARA) and growth differentiation factor (GDF5) genes have been associated with power performance (48), stress fractures (66), and muscle regeneration (18). Specifically, it has been suggested that PPARA predicts anaerobic trainability (1), and aerobic trainability (43,47,49), while GDF5 regulates the response of the proliferation satellite cell (18) (crucial after resistance training), meniscus injury incidents, and knee joint function recovery (14). Therefore, the combination of candidate genes determining the loading response, injury incident, and recovery rate might be important during the period of maturation. Moreover, the above-mentioned genes polymorphisms might be related to stretch-shortening cycle capability (determined from leg stiffness [LS] and reactive strength index [RSI]) (30,31), but the importance of these parameters still need to be identified within young sporting population. The collagen tissue quality is genetically determined, inter alia, by genes encoding collagens, where the COL5A1 gene (rs12722, rs3196378, and rs11103544) seems to play a key role in the probability of knee and Achilles tendon injury (57) and muscle flexibility (6). Therefore, the relationship between mechanical properties such as LS and RSI might be correlated with the COL5A1 gene in addition to genes related to performance (PPARA), injury, and recovery predisposition (GDF5).

The genetic predisposition for collagen production (COL5A1), carbohydrate and protein metabolism (PPARA), cell differentiation, and the transforming growth factor-β superfamily (GDF5) has a potential to determine overuse injuries or complex phenotypes related to tissue properties such as LS or RSI (33). Specifically, the GDF5 rs143383 A allele carriers have been shown to have lower GDF5 transcriptional activity in chondrogenic cells than GG homozygotes, which might influence the mount of cartilage of the vertebrae, limb dimensions, or joint angles (42,55). In addition to above-mentioned genetic predisposition, the power and stretch-shortening cycle performance is related to PPARA rs4253778, where C allele carriers have shown greater power-related outcomes than TT homozygotes (48) in adult athletes; however, this relationship has not yet been confirmed in adolescents.

Stiffness of the whole limb is affected by muscle and tendon mechanical properties as well as elastic properties of the joint structures and stiffness arising from muscle actions (21). Lower-limb stiffness points to an ability to generate strength and to be able to resist deformation resulting from movement, including a direct transition from eccentric to concentric muscle contraction (44) in a stretch-shortening cycle. Therefore, LS should be closely related to the RSI (30), which has been reported as a predictor of injury in adolescent athletes (51). Leg stiffness and RSI are typically based on a squat-jump movement pattern, where the hip extensor (posterior) muscle chain is crucial for successful technical execution of the test. This posterior muscle chain includes several critical muscle groups such as the hamstrings and low-back extensors, whose shortening or other imbalances have been identified as injury predictors (10,16,24,40).

The current research has identified muscle flexibility, functional movement screens, LS, RSI, and muscle strength as injury predictors, all of which depend on the collagen tissue condition (21). As the predictability of musculotendinous conditions by genetic factors is not sufficiently documented, the purpose of this study was to determine whether the COL5A1, PPARA, and GDF5 genes are associated with muscle functions and stretch-shortening cycle performance in adolescent athletes.

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Methods

Experimental Approach to the Problem

At the beginning of the competitive season, a cross-sectional measurement of anthropometry and muscle function was performed by each participant. An injury record for the past 12 months was obtained by a physician specialized in neurophysiology and muscle function. The participants were screened for anthropometry, DNA, muscle function, and neuromuscular performance (RSI and LS during vertical jumps). The participants were also requested not to exercise in excess of their normal training habits 2 days before the test to exclude the effects of delayed muscle soreness on muscle function (37).

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Subjects

The participants were 146 youth players (mean ± SD: age 13–15 year, 14.4 ± 0.2 years) of various team sports (basketball n = 54, soccer n = 50, handball n = 32), both sex (90 male, 56 female) with a high potential of lower limb soft-tissue injury (Table 1). All participants were players in the highest league in their sport with at least 6 years of organized training experience, and their current habitual training cycle met the following criteria as minimum: 6 training sessions per week, 160 minutes of conditioning work, 120 minutes of technical-tactical training, 190 minutes of game time, and 130 minutes of warm-ups. The research and the informed consent form were approved by the institutional review board of the Palacky University Olomouc, Faculty of Physical Culture in accordance with the ethical standards of the Helsinki Declaration of 2013, and a signed written informed consent form was obtained from the parents of all adolescents participating in this study before measurements as well as the underage subjects.

Table 1

Table 1

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Procedures

Biological Maturity

Biological maturity was determined using the sex-specific equation determined by Mirwald (41) based on measurement of leg length, body mass, standing, and sitting heights. The equation for maturity offset in males (years) was −9.236 + (0.0002708 [leg length and sitting height interaction]) − (0.001663 [age and leg length interaction]) + 0.007216 (age and sitting height interaction) + (0.02292 [body mass by height ratio]) with reported coefficient of determination R2 = 0.915 and standard error of estimate (SEE) = 0.490 (41). The equation for maturity offset in female (years) was −9.376 + (0.0001882 [leg length and sitting height interaction]) + (0.0022 [age and leg length interaction]) + 0.005841 (age and sitting height interaction) −0.002658 (age and body mass interaction) + 0.07693 (body mass by height ratio) with reported coefficient of determination R2 = 0.910 and SEE = 0.499 (41). The maturity offset was used as categorical value to identify the group of participants before PHV (pre-PHV) and after PHV (post-PHV), where any negative maturity offset prediction was classified as pre-PHV and any positive prediction as post-PHV. The numerical value of maturity offset was used as a value representing biological maturity in other analyses.

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Anthropometry

Anthropometry measurements were used to describe the participants, biological maturity estimation and normalization of LS. All measurements were undertaken by an experienced anthropometric technician according to the procedures of the International Society for the Advancement of Kinanthropometry (36). Leg length, tibia length, standing, and sitting heights were measured using the A-226 Anthropometer (Trystom, Olomouc, Czech Republic) with sliding telescopic sleeves. Body mass has been measured using the 2-axis force platform PS-2142 (Pasco, Roseville, CA, USA).

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DNA Analyses

DNA was extracted from Flinders Technology Associates Classic cards (Cat. no. WB120305; Whatman International Ltd., Piscataway, NJ, USA) according to the Whatman FTA Elute protocol. A panel of single‐nucleotide polymorphisms in the genes associated with genes previously related to tendon structure, ligament structure, and muscle function were selected as candidate variants for this study (Table 2); the selected SNPs were examined using MALDI-TOF MS-based MassARRAY (Agena Bioscience, San Diego, CA, USA) genotyping assay (25).

Table 2

Table 2

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Functional Movement Screen Tests

The test of muscle functions included a functional bend test (FBT), passive straight leg raise test (SLR), and individual muscle tests of the hip adductors, rectus femoris, tensor fascia lata, and iliopsoas. All manual muscle tests had acceptable reliability: FBT test (coefficient of variation [CV] = 9.86%; intraclass correlation coefficient [ICC] = 0.89), SLR (CV = 5.46%; ICC = 0.85), and lower limb muscle tests (SEM below 10%, ICC above 0.88) (5). The tests were selected according to the fact that altered musculotendinous functions such as flexibility may be associated with musculotendinous injuries (10,16,24,40,51). The functional screening measurements were conducted by the same experienced researcher. The SLR was performed according to the procedures of Göeken (15) using a 3-point scale (1 flexible, 3 moderate, and 3 stiff); the FBT, known also as the Thomayer or toe touch test, was performed according to the procedures of Janda (22,27) using a 5-point scale (1 hyperflexible, 2 flexible, 3 medium, 4 stiff, and 5 extremely stiff); and individual muscle tests were performed according to the procedures of Janda (22) using a 3-point scale (1 flexible, 3 moderate, and 3 stiff). All functional tests were assessed twice, and the average score was used for further analyses.

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Leg Stiffness

Absolute LS was measured during the submaximal bilateral hopping test performed using a mobile 2-axis force platform PS-2142 (Pasco) at a hopping frequency of 2.5 Hz. This frequency was chosen to ensure that the movement patterns are reflective of typical spring-mass model behavior (30). Relative LS was normalized to leg length and body mass (39). The participants were asked to hop two-legged on the force plates for 20 consecutive hops. Leg stiffness (kN·m−1) was calculated using the measures of body mass, contact times, and flight times, which is known to be a valid and reliable method (11) with a reported ICC = 0.93 and CV = 9.48% in children (30).

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Reactive Strength Index

The RSI was determined during a 5-maximum hop test that was performed on a mobile contact mat (FITRO Jumper; Fitronic, Bratislava, Slovakia). The RSI been shown to have high test-retest reliability (13) with reported ICC = 0.90 and CV = 14.24% in children (30). The participants were instructed to maximize jump height and minimize ground contact time (11) and performed 3 trials. The RSI variable was calculated using the equation by Flanagan and Comyns (13), where RSI = jump height (mm)/ground contact time (ms) and jump height (m) = (gravity·[flight time]2)/8, where gravity is 9.81 m·s−1 and flight time in seconds. The first hop served as a countermovement jump and was consequently excluded from analysis, with the 4 remaining hops averaged for analysis of RSI. Players performed 3 trials with 2-minute rest between trials. The greatest value recorded from the 3 attempts was used in further analysis.

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Statistical Analyses

The phenotype and genotype data are presented in the supporting information file. The data were processed using the ORIGINE software (version 2018b SR0; OriginLab, Wellesley Hills, MA, USA) where statistical significance was set up at α < 0.05. All analyses were performed separately for each sex. Genotype and allele frequencies between pre-PHV and post-PHV groups were compared using χ2 test to identify potential differences in maturity status. In addition to frequency analyses, the phenotypes according to maturity status were compared using a Wilcoxon Mann-Whitney U test. All variables in the genotype groups were tested for normality using the Kolmogorov-Smirnov test. As all variables were normally distributed, the data are expressed as mean and SDs. A multivariate analysis of variance (MANOVA) for unequal sample sizes (phenotype outcome × sex × polymorphism) was used to evaluate the differences between genotype groups, where p ≤ 0.05; post hoc Tukey tests, with Hays ω2 > 0.09, were considered significant. The ω2 0.10–0.29, 0.30–0.49 and >0.50 were considered as weak, moderate, and strong associations, respectively (19).

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Results

The genotype frequency did not disrupt the Hardy Weinberg equilibrium and did not show any differences in genotype frequency in comparison with an EU population and the population of Utah with Northern and Western European Ancestry (Table 3). Some genotype groups contained a low sample of carriers: men rs12722 CC genotypes (n = 1), women rs12722 CC genotypes (n = 1), and women rs11103544 CC genotypes (n = 2). The low sample groups were eliminated from statistical analyses if appropriate. The Kolmogorov-Smirnov test revealed no grounds for rejecting the hypothesis of normality in any genotype group included in MANOVA.

Table 3

Table 3

Biological maturity status did not show any differences between pre-PHV and post-PHV groups (Table 4) in genotype frequencies, allele frequencies (Table 5 and 6), and in phenotype values (Table 7). The MANOVA showed differences in maturity offset between female COL5A1 rs12722 genotype groups (F1, 78 = 12.1, p = 0.029, ω2 = 0.22), where CT heterozygotes showed a lower maturity offset than TT homozygotes (Figure 1).

Table 4

Table 4

Table 5

Table 5

Table 6

Table 6

Table 7

Table 7

Figure 1

Figure 1

The FBT showed differences between COL5A1 rs12722 genotype groups in males (F1, 39 = 10, p = 0.003, ω2 = 0.18) and females (F1, 37 = 8.5, p < 0.001, ω2 = 0.16), where CT heterozygotes had lower functional test scores than TT homozygotes (Figure 2). The FBT showed differences between male COL5A1 rs11103544 genotype groups (F2, 83 = 8.1, p = 0.049, ω2 = 0.14), where TT and CC homozygotes resulted in better FBT scores than TC heterozygotes (Figure 2).

Figure 2

Figure 2

The SLR showed differences between COLA1 rs12722 genotype groups in males (F1, 39 = 5.3, p = 0.027, ω2 = 0.11) and females (F1, 37 = 5.6, p = 0.027, ω2 = 0.10), where CT heterozygotes showed lower test scores than TT homozygotes (Figure 3). The SLR showed differences in males between GDF5 rs143383 genotype groups (F2, 82 = 5.9, p = 0.030, ω2 = 0.11), where GG homozygotes showed lower (better) test scores than AA and AG genotypes (Figure 3).

Figure 3

Figure 3

The RSI differed between GDF5 rs143383 genotype groups in males (F2, 73 = 5.8, p = 0.050, ω2 = 0.10) and females (F2, 48 = 3.9, p = 0.033, ω2 = 0.11), where AA homozygotes and AG heterozygotes had greater RSI than GG homozygotes (Figure 4). The best RSI differed between PPARA rs4253778 in males (F2, 74 = 5.9, p = 0.049, ω2 = 0.11) and females (F2, 49 = 4.6, p = 0.034, ω2 = 0.12), where CC homozygotes had a greater RSI than GG homozygotes and GC heterozygotes (Figure 4).

Figure 4

Figure 4

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Discussion

The main finding of this study is that COL5A1 and GDF5 gene variants are associated with injury risk predictors represented by functional movement tests scores in adolescents. PPARA and GDF5 gene variants are also associated with RSI, and COL5A1 genes variants might determine the maturation status in females. Specifically, COL5A1 is a good predictor of muscle functional screening for males and females. Previous studies have shown that CT heterozygotes in COL5A1 rs12722 are associated with decreased flexibility in the posterior fascial chain (hamstrings and erector spinae) during a sit and reach and SLR test, where heterozygotes were less flexible than homozygous individuals (TT and CC genotypes) (6). The results of this study support this previous findings (6) for a team sport population in relation to posterior muscle chain function, which is the muscle group tested in the FBT. Moreover, TC heterozygotes in COL5A1 rs11103544 were associated with a lower FBT score than TT homozygotes in males and GG male heterozygotes in GDF5 rs143383 with a better SLR score than AA and AG. Thus, a new possible relationship with functional muscle test in COL5A1 and GDF5 has been identified in the current study. However, the sample size did not allow COL5A1 and GDF5 gene interactions; therefore, this type of analysis should be performed in a future study with larger samples.

It has previously been reported that COL5A1 rs12722 variation has an effect on ROM during aging and with respect to physical activity (3); however, this study is the first to include a group of young athletes at a high risk of musculotendinous injury. Although there is no experimental evidence, the authors believe that increased type V collagen production is influenced by COL5A1 rs12722 T allele variant (8), which might be especially important in terms of changes to bone and soft-tissue mechanical properties during the period of maturation. Seven polymorphisms in 3′-UTR of COL5A1 forming T allele of rs12722 has been associated with increased mRNA stability (28). This suggests that T allele of rs12722 could be responsible for different connective tissue phenotypes, where increased stiffness can be beneficial for increased performance but simultaneously also for increased injury risk (7). Moreover, maturity offset was delayed in female rs12722 CT heterozygotes, which might mean that these individuals might be under a higher risk of injury because of muscle function tests and hormonal factors in general (20). An opposite trend of faster maturation in rs12722 TT female homozygotes might mean that those girls might be preferred for elite teams due to a biological age bias. To the best of our knowledge, our finding that COL5A1 rs11103544 was related to FBT in males seems to be novel since this polymorphism relationship to the range of movement has been suggested, but not confirmed by previous research (6).

Although GDF5 protein is involved in bone and tissue growth in youth and adults (4), this did not identify a direct link with GDF5 and players' maturity offset. The GDF5 rs143383 A allele carriers has been previously associated with decreased stature and sitting height (55,65) in Euro-American population and British population (55). Our study did not find an association between stature, sitting height or maturation offset (derived from stature and sitting height), and rs143383, which might be explained by our relatively low sample or the ongoing maturation process itself. Moreover, GDF5 rs143383 has not been associated with pubertal height growth in a previous genome-wide association study (9). Therefore, it is possible that GDF5 gene expression does not differ at different stages of maturity estimated by anthropometrics, such that it was showed for other polymorphisms such as disruptor of telomeric silencing 1-like (DOT1-like) or mitogen-activated protein kinase 3 (MAPK3) (9,59).

The results of this study suggest that GDF5 rs143383 polymorphism might play a role in male SLR score, where GG homozygotes do not have an increased test score; on the other hand, GG homozygotes had lower RSI in both sexes. Thus, it might be speculated that rs143383 GG homozygotes showed equal development of performance and mechanical properties of the lower limbs, which might protect these individuals from a potential injury. The situation in which performance is ahead of mechanical property development might be understood as a potential injury risk factor, especially in the period of accelerated growth, during which most anthropometric changes take place (34,35).

CC homozygotes in PPARA gene in this study showed better jump performance represented by RSI, which had been suggested by previous studies (1,48). However, the finding that this predisposition is identical in adults, and adolescents should be considered when training methods are selected, especially as PPARs and their coactivators are associated with improvements in training programs for weight reduction (29), aerobic performance (49,52,60,61), and resistance training load capabilities (1). In this manner, the ketogenesis and other metabolic factors determined by PPARA indicate an individual response to strength and power training (1), and satellite cell proliferation determined by GDF5 can indicate a potential to regenerate from a long-term physical load (18). Regarding the fact that the interaction of these genes in terms of performance, injury prevention, and fatigue factors was not analyzed, the authors suggest that this analysis should be performed in future studies.

Limitations of this study include the relatively small sample size and potential effects of other environmental (e.g., dietary) or genetic factors; therefore, the results of this study cannot be generalized to other populations. Validation in other cohorts and further studies are necessary to address the detailed role of the chosen polymorphisms of COL5A1, GDF5, and PPARA genes within the complex phenotype of strength and power performance. Our polymorphism selection has been performed in relation to muscle function and performance phenotypes, but not to specific polymorphisms previously related to growth and maturation, which we suggest for future studies performed on adolescents. The maturation status has been found to have effect on functional movement including SL (50) and the muscle strength and power performance (17). Our phenotype results (without considering anthropometry in Table 4) showed no difference between pre-PHV and post-PHV young male (Table 7), which is in accordance with previous studies where, e.g., LS and RSI did not significantly differ between pre-PHV and post-PHV in males (31,54). This might be explained by low range of our PHV groups (13–15 year) or by complex training effects, where plyometric training might be more effective in pre-PHV than post-PHV participants and where other training responses might be similar in both maturity groups (32). Although numbers of training sessions slightly differ between sports and the sexes, all participants were in a structured training program (with a minimum of 6 training sessions per week) designed to promote progressive musculoskeletal adaptation. Moreover, all participants had been in systematic training for a number of years (minimum 6 years), which might mean that any potential confounding variables did not influence our genotype results.

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Practical Applications

This study showed that CT genotype in COL5A1 rs12722 is a possible predictor of decreased muscle function in the posterior hip muscle chain, causing shortening in FBT and SLR test. Therefore, COL5A1 rs12722 CT heterozygotes should be involved in specific programs targeting hamstring and posterior hip muscle chain flexibility, muscle functions, and any other muscle imbalances. Woman with COL5A1 rs12722 TT homozygosity might be used as a predictor of faster maturation; therefore, their carriers might have a biological advantage in adolescent categories, and their performance should not be overestimated in practice. PPARA rs4253778 CC homozygotes and GDF5 rs143383 AG and AA genotypes might have greater stretch-shortening cycle performance represented by RSI; therefore, those athletes have a good potential to develop strength, power, and speed in training.

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Acknowledgments

This study has been supported by the GACR grant No. 16‐13750S and by grant IGA_PU_LF 2018_015/2019_009.

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Keywords:

collagen; maturation; injury prevention; growth factor; reactive strength index; hamstrings

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