A cornerstone of sports genomics research is to identify genetic variants that are more common in athletes than the general population, under the assumption that specific polymorphisms contribute to the attainment of elite performance. Approximately 66% of the variance in athlete status is due to genetic factors (14), where heritable differences in anthropometry, physiological capacity, training adaptation, or tissue structure may be advantageous to general athletic ability and/or specific sports performance (2) and may also affect injury risk (12). The latter is especially important because injuries result in training interruptions, which are detrimental to physiological adaptation. Indeed, training experience is associated with individual performance in competitive running (20), where two-thirds of athletes report that their training has been interrupted by injury (28) and where training age (years) is inversely related to injury incidence (19). This suggests that the success of runners who reach elite level may, in part, be due to avoiding injury. Therefore, although polymorphisms associated with elite athlete status are typically assumed to augment training adaptations and/or enhance athletic performance, a lack of causal evidence means it is also possible that elite competitors are genetically more resistant to injury than most.
Ligament and tendon pathologies are among the most reported medical conditions in the developed world (5) and have serious implications for athletes (13). Distance running has a greater risk of overuse injury relative to other activities (7,23), with Achilles tendinopathy among the most commonly reported (15). Notably, evidence that similar injuries have a heritable component of ∼40% (22) suggests that genetically susceptible athletes may incur more frequent suspension of training, with those at a lower risk of injury able to maximize adaptation by sustained adherence to established training principles. Furthermore, it is possible that polymorphisms affecting the structure and function of connective tissues could influence both performance and injury phenotypes. For example, properties of the muscle-tendon unit (MTU), such as increased stiffness, are associated with a wide range of improved lower limb performance attributes (10) but may also increase injury incidence (12). It follows that interindividual variability in tissue properties has the potential to affect athletes' likelihood of injury and affect their performance.
The critical role of collagen in ligament and tendon (31) suggests that injuries to these tissues could be influenced by variation in collagen-encoding genes. Indeed, single-nucleotide polymorphisms (SNPs) of the collagen pro-α1 (I) chain (COL1A1) and collagen pro-α1 (V) chain (COL5A1) genes have been associated with collagenous tissue injury. COL1A1 encodes the collagen pro-α1 (I) chain protein, a major component of type I collagen involved in the structure of ligament and tendon, and a transversion substitution (rs1800012C > A) affecting the binding site of the Sp1 transcription factor is associated with greater α1 (I) chain mRNA and protein production (29). Increased COL1A1 expression is proposed as a mechanistic explanation for the reduced risk of ligament injury in carriers of the A allele (16) and rare AA genotype (21,37). The relationship of rs1800012 with tendon injuries is less understood, although the A allele was also associated, as part of a haplotype, with a reduced risk of Achilles tendon rupture (21). Together, this suggests that the rs1800012 CC genotype increases injury risk, with one or more copies of the A allele conferring protection.
COL5A1 encodes the collagen pro-α1 (V) chain protein, a major component of type V collagen that regulates the diameter of collagen fibrils, and the location of a SNP (rs12722C > T) in the 3′ untranslated region suggests it could affect the level, location, or timing of COL5A1 expression (40). The rs12722 T allele has been associated with not only a greater risk of Achilles tendinopathy (32), anterior cruciate ligament (ACL) injury (27,37), and exercise-induced muscle cramping (34) but also with faster running times (11,36). The link between the T allele and increased COL5A1 mRNA stability (26) underpins a hypothesis that the TT genotype influences the mechanical properties of collagenous tissue, including a reduction in the tensile strength of ligament and tendon (12). This may explain why the functional T allele and TT genotype have been associated with increased soft-tissue injury susceptibility (32,37) and the CC genotype with injury resistance.
Despite previous associations with injury and running performance, we are not aware of any studies investigating whether the frequency of COL1A1 rs1800012 and COL5A1 rs12722 genotypes differs between competitive runners and the general population. The polygenic nature of performance (42) and injury (33) phenotypes suggests that athletes possessing a greater number of favorable alleles from numerous SNPs have a greater chance of attaining elite status, either through enhanced performance or injury resistance. Furthermore, the interaction of types I and V collagen is believed to modulate collagen fibril diameter (9), suggesting that genotypes of collagen-encoding genes could also interact and affect tissue properties. Therefore, the aim of this study was to investigate the individual and combined associations of the COL1A1 rs1800012 and COL5A1 rs12722 SNPs with athlete status and performance in competitive runners. Based on previous associations with reduced injury risk, and because injury avoidance reduces training interruptions (20), it was hypothesized that the rs1800012 AA and rs12722 CC genotypes would be (a) individually more frequent among athletes than nonathletes, (b) observed in combination more frequently in athletes than nonathletes, and (c) associated, individually and in combination, with running performance.
Experimental Approach to the Problem
The aim of this study was to investigate whether COL1A1 and COL5A1 genotypes previously associated with soft-tissue injuries are associated, individually or in combination, with running performance. Genotype analysis was conducted in a cohort of competitive runners to investigate whether genotype and allele frequencies differed from a sample of nonathletes and whether there was a relationship between athlete's genotype and performance according to official retrospective records.
This study recruited 1,429 Caucasian subjects including 597 athletes (mean ± SD; age [range = 18–88 years]: 36 (9) years; height: 1.70 (0.24) m; mass: 60.8 (10.7) kg; 354 males and 243 females) and 832 nonathletes (age [range = 18–69 years]: 30 (16) years; height: 1.72 (0.17) m; mass: 73.6 (14.3) kg; 490 males and 342 females). All athletes were competitive runners primarily recruited from the London Marathon Pre-Race Registration Expo between 2012 and 2014, in addition to national or regional athletic clubs and organizations in the United Kingdom, and were 92.3 British, 1.0% Irish, and 6.7% from other nationalities. Athletes competed in a range of race distances, listing their primary competitive event as 800 m (4.4%), 1,500 m (7.0%), 3,000 m (2.9%), 5,000 m (30.2%), 10,000 m (25.6%), half-marathon (8.2%), or marathon (21.7%). Nonathletes were healthy, unrelated and recreationally active Caucasian subjects, including 89.3% British, 8.3% South African, and 2.4% from other nationalities, and were recruited through mail-outs, posters, and word of mouth. Genotyping for COL1A1 rs1800012 and COL5A1 rs12722 was performed in 1,177 (574 athletes and 603 nonathletes) and 1,159 (541 athletes and 618 nonathletes) subjects, respectively, with 907 subjects (518 athletes and 389 nonathletes) genotyped for both SNPs. Manchester Metropolitan University Ethics Committee approved the study, which was conducted in accordance with the Declaration of Helsinki (2013) with written informed consent from each subject.
Athletes' best individual times from competitive outdoor races approved by the International Amateur Athletics Federation (IAAF) were accessed using an up-to-date collaborative Python programming code (https://bitbucket.org/KzMilligan/personalbest/src/master/www.bitbucket.com) linked to official online records (www.thepowerof10.info). For male and female athletes, times were converted into seconds and compared with the median of the 10 best official race times (Best10) recorded at the time of analysis (November 2020) by individual athletes of the same sex for each respective distance to remove the exaggerated influence of exceptional performances. To control for the fact that participating runners competed in a range of race distances, the percentage difference between each athlete's personal best (PB) time and Best10 for the same event was calculated (PB time/Best10). For example, a PB time of 115.0 represents a performance that is 115.0% of Best10 (15.0% longer than) for that distance. For athletes who reported PB times for multiple race distances, the PB time closest to Best10 for that distance (i.e., with the smallest percentage difference) was selected as the athlete's best personal best (BPB) and used for subsequent analysis. Athlete inclusion criteria for this study were achievement of a BPB performance within 60% of Best10. Information on nonathlete subjects was collected using a self-reported questionnaire. Accordingly, the nonathletes included for analysis had no experience in any sport above a very low competitive level.
Blood (68%), buccal swab (23%), or saliva (9%) samples were obtained using the following protocols: Blood (5 ml) was drawn from the superficial forearm vein into an EDTA tube and stored in sterile tubes at −20 ° C until processed. Saliva samples were collected into Oragene DNA OG-500 collection tubes (DNA Genotek, Ottawa, ON, Canada) according to the manufacturer's protocol and stored at room temperature until processed. Sterile buccal swabs (Omni swab; Whatman, Springfield, Mill, United Kingdom) were rubbed against the buccal mucosa of the cheek for ∼30 seconds. Tips were ejected into sterile tubes and stored at −20° C until processed.
DNA Isolation and Genotyping
DNA isolation was conducted using the Qiagen QIAcube spin protocol (Qiagen, West Sussex, United Kingdom) performed using the QIAamp DNA Blood Mini kit according to manufacturer's instruction. Real-time polymerase chain reaction (PCR) genotyping was performed using a StepOnePlus (Applied Biosystems, Paisley United Kingdom) or Fluidigm EP1 system (Fluidigm, CA).
In 10 µL reactions, 5 µL of TaqMan GTXpress Master Mix or Genotyping Master Mix, 4.3 µL of nuclease-free H2O (Qiagen), and 0.5 µL of TaqMan SNP assay (Applied Biosystems) were mixed with subject's DNA solution and pipetted into individual wells of a 96-well plate. Adjustments were made to volumes of H2O and DNA solution depending on the sample origin, i.e., blood, saliva, or buccal. Thermocycling conditions using the Genotyping Master Mix were 95° C for 10 minutes followed by 40 cycles of 15 seconds at 95° C and 1 minute at 60° C. Using the GTXpress Master Mix, conditions were 20 seconds at 95° C followed by 50 cycles of 3 seconds at 95° C and 20 seconds at 60° C. Allele-specific probes identified by VIC/FAM dyes identified alleles of interest on the forward strand for COL5A1 rs12722 as 5′-CACACCCA[C/T]GCGCCCCG-3′ and for COL1A1 rs1800012 as 5′-CGCCC[A/C]CATTC-3'. Genotyping calls were performed using StepOnePlus analysis software version 2.3. All samples were genotyped in duplicate, and each run contained 3 positive controls and 1 negative control. All duplicates were in 100% agreement.
Analysis was performed using a Fluidigm EP1 system and BioMark 192.24 GT Dynamic Array Integrated Fluid Circuit (IFC) (Fluidigm, Cambridge, United Kingdom). A mixture of 2 μL of GTXpress Master Mix (Applied Biosystems), 0.2 μL of Fast GT Sample Loading Reagent (Fluidigm), 0.2 μL of nuclease-free H2O, and 1.6 μL of purified DNA (or H2O as control) was pipetted into each well of the IFC. In addition, 1.78 μL of TaqMan SNP Genotyping assay (Applied Biosystems), 1.78 μL of Assay Loading Reagent (Fluidigm), and 0.18 μL of ROX (Invitrogen, Paisley, United Kingdom) were combined per assay inlet. An integrated fluid circuit controller RX (Fluidigm) mixed samples and assays using a Load Mix (166x) script before PCR was performed using a real-time FC1 Cycler (Fluidigm) GT 192X24 Fast v1 protocol. Thermocycling conditions were 95 ° C for 120 seconds before 45 cycles of 2 seconds at 95° C and 20 seconds at 60° C. End point analysis was completed using Fluidigm SNP Genotyping Analysis software version 4.5.1. All samples were assayed in duplicate, and there was 100% genotype agreement between duplicates.
Injury-Resistance Score (RScore)
Based on previous literature (16,21,27,32,37), an injury-resistance score (RScore) was calculated for each subject from their rs1800012 and rs12722 genotypes. Specifically, the genotypes associated with injury-resistance rs1800012 AA and rs12722 CC each possess 2 copies of the protective allele and were considered most injury resistant. Accordingly, a maximum RScore of 4 was only possible in subjects of rs1800012 AA and rs12722 CC genotypes. A linear trend was applied to the remaining genotypes so that the heterozygous genotypes for each SNP (rs1800012 CA and rs12722 TC) were scored 1, and the homozygous genotypes with no injury-resistant alleles (rs1800012 CC and rs12722 TT) scored 0. Accordingly, the 5 possible RScores were 0, 1, 2, 3, and 4 based on the number of protective alleles possessed when combining both SNPs, and a superior RScore indicates a lower risk of injury.
Genotype distributions and allele frequencies were compared between athletes and nonathletes by χ2 goodness-of-fit tests with Bonferroni adjustment to control for multiple comparisons. The χ2 test of independence was used to determine Hardy-Weinberg equilibrium to investigate whether genotype frequencies differed between men and women in either cohort and to investigate the association of RScore with athletic status. Odds ratios (ORs) were calculated when genotype or RScore frequencies differed significantly between groups. Differences in athlete and nonathlete characteristics were investigated using the independent samples t test. One-way analysis of variance was used to investigate whether athletes' BPB was associated with individual genotypes or RScores. All statistical analyses were performed using R (version 3.5.1). p values <0.05 were considered statistically significant. All data are presented as mean (standard deviation).
Subject characteristics are presented in Table 1. In men, athletes were ∼7 years older (36 (9) and 29 (5) years, respectively; p < 0.001) and ∼13 kg lighter (66.1 (8.9) and 78.9 (12.9) kg, respectively; p < 0.001) than nonathletes. In women, athletes were ∼3 years older (35 (10) and 32 (18) years, respectively; p = 0.017) and ∼13 kg lighter (53.1 (8.2) and 66.0 (12.9) kg, respectively; p < 0.001) than nonathletes.
Table 1 -
Subject characteristics of athletes and nonathletes.*
||36 ± 9
||1.75 ± 0.24
||66.1 ± 8.9
||35 ± 10
||1.62 ± 0.22
||53.1 ± 8.2
||29 ± 15
||1.78 ± 0.18
||78.9 ± 12.9
||32 ± 18
||1.64 ± 0.11
||66.0 ± 12.9
*Values are presented as mean ± SD.
Genotype distributions met Hardy-Weinberg equilibrium for COL1A1 and COL5A1 in both athletes and nonathletes (p ≥ 0.184). No differences in genotype frequency were observed between male and female athletes (p ≥ 0.679) or nonathletes (p ≥ 0.663). The COL5A1 CC genotype was more common in athletes than nonathletes (19.8% vs. 15.5%, OR = 1.34, p = 0.020, Figure 1), with no difference in the COL1A1 genotype distribution between athletes and nonathletes (p = 0.659, Figure 1). In subjects genotyped for both SNPs (n = 907), athletes had lower odds of having an RScore of 0 (18.5% vs. 24.7%, OR = 1.45) and higher odds of having an RScore of 4 (0.6% vs. 0.3%, OR = 2.01) than nonathletes (p < 0.001, Figure 2). Athletes' BPB was not associated with the COL1A1 genotype (p = 0.933), COL5A1 genotype (p = 0.613), or RScore (p = 0.477, Table 2).
Table 2 -
Best personal best (BPB) performance
according to individual COL1A1
genotypes and injury-resistance score (RScore).*
| 122.3 ± 8.9
||122.1 ± 9.3
||121.7 ± 7.7
| 122.7 ± 10.2
||122.7 ± 8.6
||121.7 ± 8.6
| 124.3 ± 10.5
||121.5 ± 8.5
||122.6 ± 8.5
||123.6 ± 9.0
||114.6 ± 2.2
*Values are percentage (%) of Best10 presented as mean SD.
The aim of this study was to investigate whether the injury-resistant COL1A1 rs1800012 and COL5A1 rs12722 genotypes were associated with the athletic status of competitive runners, and whether these SNPs are, individually or in combination, associated with performance. The main findings were that athletes had 1.45 greater odds of having at least 1 injury-resistant allele than nonathletes. However, neither individual SNPs nor RScores were directly related to athlete performance. Athletes had 1.34 greater odds of being the COL5A1 CC genotype than nonathletes, with no difference in the COL1A1 genotype distribution according to athlete status. These findings suggest that competitive runners have ∼2 times greater odds of possessing the combination of injury-resistant COL1A1 AA and COL5A1 CC genotypes than nonathletes and that the COL5A1 CC genotype may be advantageous to competitive runners through a mechanism independent of performance enhancement per se. Nonetheless, the limited number of athletes with the optimal combination of genotypes suggests other factors, including additional beneficial genetic variants, probably contribute more to elite athlete status.
The rs1800012 AA and rs12722 CC genotype combination was more common in athletes than nonathletes. Previous associations of each genotype with a lower risk of injury (16,21,27,30,32) informed our hypothesis that possessing both genotypes would offer the greatest injury resistance and be advantageous for competitive running because fewer training interruptions would allow athletes to maximize physiological adaptation through sustained adherence to established training principles (15). However, less than 1% of subjects genotyped for both SNPs, and only 0.6% of athletes had the optimal combination of rs1800012 and rs12722 genotypes. Therefore, although the likelihood of possessing both genotypes is limited by a low rs1800012 minor allele frequency, most competitive runners in this study had one or more COL1A1 and/or COL5A1 “risk” alleles. Although it seems that possessing favorable genotypes at both rs1800012 and rs12722 may be advantageous to a small proportion of athletes, alternative genotype combinations at these SNPs do not seem to hinder the ability of most distance running athletes. This suggests that the combined influence of these “injury-resistant” COL1A1 and COL5A1 genotypes on running athlete status is small.
A higher frequency of the COL5A1 CC genotype in runners than nonathletes suggests this genotype may be advantageous. Indeed, the CC genotype was previously associated with a lower incidence of exercise-associated muscle cramping in Ironman and ultramarathon athletes (34) and with elite rugby status (24). We hypothesized that the rs12722 CC genotype would be more common in athletes than nonathletes because of an apparent protective effect against soft-tissue injuries (27,30,32), which is common in distance runners (7,23). In nonathletes, one study found greater quadriceps muscle-tendon stiffness in T allele carriers than CC homozygotes (25), whereas another found no association with the volume or elastic modulus of the patellar tendon (18). However, whether COL5A1 genotypes affect the mechanical properties of athletes' tendons and other tendons involved in running, such as the triceps surae tendon (17), remains unknown. Without injury records we cannot confirm that overrepresentation of the CC genotype in athletes is due to an injury-protective mechanism. Nevertheless, because exercise-associated muscle cramping (34) and the risk of ligament (27), tendon (32), and skeletal muscle injuries (30) are shown to be lower for CC homozygotes, we support Heffernan et al. (24) in proposing that soft-tissue injury resistance is likely to contribute to the association of rs12722 with athlete status.
No association was observed between COL1A1 and COL5A1 genotypes or RScores with athletes' BPB, indicating that neither SNP, individually or in combination, influences the competitive performance of distance runners. Despite associations with ligament injury (16), tendon injury (21), muscle strength (6), and bone mineral density (43), we are unaware of the literature investigating COL1A1 rs1800012 and athletic performance. Some (11,36), but not others (8), report associations of COL5A1 rs12722 with running ability. Specifically, TT homozygotes ran fastest during an ironman triathlon (36) and completed an ultra-marathon faster (11) than CC and CT genotypes, but neither running economy nor V̇o2max were related to rs12722 genotype (8). In the ultramarathon cohort, the T allele was associated with reduced range of motion and better performance (11), with authors suggesting that this supports the relationship between muscle-tendon stiffness and running economy (4) as a mechanistic link to endurance running. Although we found no association of rs12722 with performance, it is possible that the CC genotype is advantageous for longer duration running events such as an Ironman or ultramarathon, but not shorter events. Indeed, rs12722 was associated with performance during the marathon section of a 226-km Ironman Triathlon (36) and a 56-km ultramarathon (11), although not with shorter events in our investigation, nor with nonathletes’ running economy during 10 minutes of treadmill running (8). Theoretically, increased muscle-tendon stiffness in TT homozygotes as proposed by Collins et al. (12) may enhance force transmission during ground contact, minimizing changes in muscle fiber length and thus energy cost (17), which could offset or delay muscular fatigue. Therefore, COL5A1 variants might affect the contribution of collagenous tissue to running mechanics (41) in longer duration events.
Although not directly associated with performance within runners, our data demonstrate that the COL5A1 CC genotype is nevertheless more common in competitive runners than nonathletes. Some SNPs have been associated with running performance (38,39), with others demonstrating no relationship (35) or being solely associated with endurance athlete status (1). Athlete status is highly heritable (3,14), and elite athletes in particular are defined as such because of the achievement of elite performance. However, it remains possible that the association of polymorphisms with athlete status may not necessarily be due to performance-enhancing benefits. Indeed, most subjects with the optimal combination of injury-protective COL1A1 and COL5A1 genotypes (RScore 4) were athletes, but neither genotype was associated directly with performance, and the COL5A1 CC genotype was more frequent in athletes than nonathletes yet was also unrelated directly to performance. This suggests that the COL5A1 CC genotype provides an advantage to runners that is enhanced in combination with the rare COL1A1 AA genotype, which could be due to the influence of both SNPs on the mechanical properties of collagenous tissue and their relationship to injury resistance. It is also pertinent to consider the influence of environmental factors on athletic performance and injury resistance, including training periodization, recovery strategies, and nutritional support. Adherence to these established principles also contributes to the attainment of athlete status, and adherence is likely to be strongest when injuries are less frequent and less severe. Thus, a greater frequency of the COL5A1 CC genotype in competitive runners suggests that the rs12722 SNP may be one of many genes that contribute to the heritability of athlete status (3,14).
This study is the first to investigate the combined association of COL1A1 and COL5A1 SNPs with performance and athlete status in runners. However, we acknowledge some limitations. First, a lack of injury records means we are unable to evaluate directly whether genotype and RScore link to the athlete status extended phenotype through the intermediate phenotype of injury resistance. We also recognize that our association data would be complemented by measures of range of motion, flexibility, and tendon properties to provide greater context regarding potential underlying mechanisms, particularly considering the previous relationship between COL5A1 genotype, flexibility, and running performance (11,36). Despite restricting our sample to Caucasian subjects and recording data on nationality, we recognize that population stratification may influence our results, whereby the genotype differences between groups might also be influenced by geographic ancestry. It is also acknowledged that the candidate-gene approach cannot quantify the polygenic interaction of multiple genes, nor the possibility that epigenetic modifications at specific polymorphisms may also be important to physical performance and/or injury resistance, and we consequently advocate genome-wide and epigenome-wide association studies to address or circumvent such constraints. Finally, a low frequency of the rs1800012 A allele means that only a small proportion of the several hundred athletes in our investigation were AA homozygotes, which may limit the ability to detect associations with athlete status and/or performance.
Competitive runners seem more likely to possess a beneficial combination of injury-resistant COL1A1 rs1800012 AA and COL5A1 rs12722 CC genotypes than nonathletes. With neither SNP nor any combination of genotypes associated with running performance directly, our findings suggest that variants of collagen-encoding genes may offer an advantage to runners that is not itself performance enhancing. In line with previous work, we suggest that this combination of genotypes may be associated with greater injury resistance in competitive runners and, thus, continued sporting competition through more sustained adherence to established training principles.
The authors thank all subjects for their participation.
1. Ahmetov I, Kulemin N, Popov D, et al. Genome-wide association study identifies three novel genetic markers associated with elite endurance performance
. Biol Sport 32: 3–9, 2015.
2. Ahmetov II, Fedotovskaya ON. Current progress in sports genomics
. Adv Clin Chem 70: 247–314, 2015.
3. Andero J, Saulière G, Marck A, Toussaint JF. A medal in the Olympics runs in the family: A cohort study of performance
heritability in the games history. Front Physiol 9: 1313, 2018.
4. Arampatzis A, De Monte G, Karamanidis K, et al. Influence of the muscle-tendon unit's mechanical and morphological properties on running economy. J Exp Biol 209: 3345–3357, 2006.
5. Baar K. Minimizing injury and maximizing return to play: Lessons from engineered ligaments. Sports
Med 47(Suppl 1): 5–11, 2017.
6. Baumert P, G-REX Consortium, Stewart CE, Lake MJ, Drust B, Erskine RM. Variations of collagen-encoding genes are associated with exercise-induced muscle damage. Physiol Genomics
50: 691–693, 2018.
7. Bertola IP, Sartori RP, Corrêa DG, Zotz TG, Gomes AR. Profile of injures prevalence in athletes who participated in SESC Triathlon Caiobá-2011. Acta Ortop Bras 22: 191–196, 2014.
8. Bertuzzi R, Pasqua LA, Bueno S, et al. Is the COL5A1 rs12722 gene polymorphism associated with running economy? PLoS One 9: e106581. 2014.
9. Birk DE, Fitch JM, Babiarz JP, Doane KJ, Linsenmayer TF. Collagen fibrillogenesis in vitro: Interaction of types I and V collagen regulates fibril diameter. J Cell Sci 95: 649–657, 1990.
10. Brazier J, Maloney S, Bishop C, Read PJ, Turner AN. Lower extremity stiffness: Considerations for testing, performance
enhancement, and injury risk. J Strength Cond Res 33: 1156–1166, 2019.
11. Brown JC, Miller CJ, Posthumus M, Schwellnus MP, Collins M. The COL5A1 gene, ultra-marathon running performance
, and range of motion. Int J Sports
Physiol Perform 6: 485–496, 2011.
12. Collins M, Posthumus M. Type V collagen genotype and exercise-related phenotype relationships: A novel hypothesis. Exerc Sport Sci Rev 39: 191–198, 2011.
13. Collins M, September AV, Posthumus M. Biological variation in musculoskeletal injuries: Current knowledge, future research and practical implications. Br J Sports
Med 49: 1497–1503, 2015.
14. De Moor MH, Spector TD, Cherkas LF, et al. Genome-wide linkage scan for athlete status in 700 British female DZ twin pairs. Twin Res Hum Genet 10: 812–820, 2007.
15. Ericsson KA. Training history, deliberate practice and elite sports performance
: An analysis in response to tucker and Collins review--what makes champions? Br J Sports
Med 47: 533–535, 2013.
16. Ficek K, Cieszczyk P, Kaczmarczyk M, et al. Gene variants within the COL1A1 gene are associated with reduced anterior cruciate ligament injury in professional soccer players. J Sci Med Sport 16: 396–400, 2013.
17. Fletcher JR, Esau SP, MacIntosh BR. Changes in tendon stiffness and running economy in highly trained distance runners. Eur J Appl Physiol 110: 1037–1046, 2010.
18. Foster BP, Morse CI, Onambele GL, Williams AG. Human COL5A1 rs12722 gene polymorphism and tendon properties in vivo in an asymptomatic population. Eur J Appl Physiol 114: 1393–1402, 2014.
19. Francis P, Whatman C, Sheerin K, Hume P, Johnson MI. The proportion of lower limb running injuries by gender, anatomical location and specific pathology: A systematic review. J Sports
Sci Med 18: 21–31, 2019.
20. Fredericson M, Misra AK. Epidemiology and aetiology of marathon running injuries. Sports
Med 37: 437–439, 2007.
21. Gibbon A, Raleigh SM, Ribbans WJ, Posthumus M, Collins M, September AV. Functional COL1A1 variants are associated with the risk of acute musculoskeletal soft tissue injuries. J Orthop Res 38: 2290–2298, 2020.
22. Hakim AJ, Cherkas LF, Spector TD, MacGregor AJ. Genetic associations between frozen shoulder and tennis elbow: A female twin study. Rheumatology 42: 739–742, 2003.
23. Hauret KG, Bedno S, Loringer K, Kao TC, Mallon T, Jones BH. Epidemiology of exercise- and sports
-related injuries in a population of young, physically active adults: A survey of military servicemembers. Am J Sports
Med 43: 2645–2653, 2015.
24. Heffernan SM, Kilduff LP, Erskine RM, et al. COL5A1 gene variants previously associated with reduced soft tissue injury risk are associated with elite athlete status in rugby. BMC Genomics
18(Suppl 8): 29–37, 2017.
25. Kirk EA, Moore CW, Chater-Diehl EJ, Singh SM, Rice CL. Human COL5A1 polymorphisms and quadriceps muscle-tendon mechanical stiffness in vivo. Exp Physiol 101: 1581–1592, 2016.
26. Laguette MJ, Abrahams Y, Prince S, Collins M. Sequence variants within the 3'-UTR of the COL5A1 gene alters mRNA stability: Implications for musculoskeletal soft tissue injuries. Matrix Biol 30: 338–345, 2011.
27. Lulińska-Kuklik E, Rahim M, Domańska-Senderowska D, et al. Interactions between COL5A1
gene and risk of the anterior cruciate ligament rupture. J Hum Kinet 62: 65–71, 2018.
28. Lysholm J, Wiklander J. Injuries in runners. Am J Sports
Med 15: 168–171, 1987.
29. Mann V, Hobson EE, Li B, et al. A COL1A1 Sp1 binding site polymorphism predisposes to osteoporotic fracture by affecting bone density and quality. J Clin Invest 107: 899–907, 2001.
30. Massidda M, Bachis V, Corrias L, Piras F, Scorcu M, Calò CM. Influence of the COL5A1 rs12722 on musculoskeletal injuries in professional soccer players. J Sports
Med Phys Fitness 55: 1348–1353, 2015.
31. McKee TJ, Perlman G, Morris M, Komarova SV. Extracellular matrix composition of connective tissues: A systematic review and meta-analysis. Sci Rep 9: 1–15, 2019.
32. Mokone GG, Schwellnus MP, Noakes TD, Collins M. The COL5A1 gene and Achilles tendon pathology. Scand J Med Sci Sports
16: 19–26, 2006.
33. Nell EM, van der Merwe L, Cook J, Handley CJ, Collins M, September AV. The apoptosis pathway and the genetic predisposition to Achilles tendinopathy. J Orthop Res 30: 1719–1724, 2012.
34. O'Connell K, Posthumus M, Schwellnus MP, Collins M. Collagen genes and exercise-associated muscle cramping. Clin J Sport Med 23: 64–69, 2013.
35. Papadimitriou ID, Lockey SJ, Voisin S, et al. No association between ACTN3 R577X and ACE I/D polymorphisms and endurance
running times in 698 Caucasian athletes. BMC Genomics
19: 1–9, 2018.
36. Posthumus M, Schwellnus MP, Collins M. The COL5A1 gene: A novel marker of endurance
. Med Sci Sports
Exerc 43: 584–589, 2011.
37. Posthumus M, September AV, Keegan M, et al. Genetic risk factors for anterior cruciate ligament ruptures: COL1A1 gene variant. Br J Sports
Med 43: 352–356, 2009.
38. Rivera MA, Fahey TD, López-Taylor JR, Martínez JL. The association of aquaporin-1 gene with marathon running performance
level: A confirmatory study conducted in male hispanic marathon runners. Sports
Med Open 6: 1–8, 2020.
39. Stebbings GK, Williams AG, Herbert AJ, et al. TTN genotype is associated with fascicle length and marathon running performance
. Scand J Med Sci Sports
28: 400–406, 2018.
40. Tabor HK, Risch NJ, Myers RM. Candidate-gene approaches for studying complex genetic traits: Practical considerations. Nat Rev Genet 3: 391–397, 2002.
41. Werkhausen A, Cronin NJ, Albracht K, et al. Training-induced increase in Achilles tendon stiffness affects tendon strain pattern during running. PeerJ 7: 1–18, 2019.
42. Williams AG, Folland JP. Similarity of polygenic profiles limits the potential for elite human physical performance
. J Physiol 586: 113–121, 2008.
43. Zhang LQ, Liu H, Huang XF. Relation of JAGGED 1 and collagen type 1 alpha 1 polymorphisms with bone mineral density in Chinese postmenopausal women. Int J Clin Exp Pathol 7: 7142–7147, 2014.