Research Article: Genome-wide association screens for Achilles tendon and ACL tears and tendinopathy

Date Published: March 30, 2017

Publisher: Public Library of Science

Author(s): Stuart K. Kim, Thomas R. Roos, Andrew K. Roos, John P. Kleimeyer, Marwa A. Ahmed, Gabrielle T. Goodlin, Michael Fredericson, John P. A. Ioannidis, Andrew L. Avins, Jason L. Dragoo, James H-C Wang.

http://doi.org/10.1371/journal.pone.0170422

Abstract

Achilles tendinopathy or rupture and anterior cruciate ligament (ACL) rupture are substantial injuries affecting athletes, associated with delayed recovery or inability to return to competition. To identify genetic markers that might be used to predict risk for these injuries, we performed genome-wide association screens for these injuries using data from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort consisting of 102,979 individuals. We did not find any single nucleotide polymorphisms (SNPs) associated with either of these injuries with a p-value that was genome-wide significant (p<5x10-8). We found, however, four and three polymorphisms with p-values that were borderline significant (p<10−6) for Achilles tendon injury and ACL rupture, respectively. We then tested SNPs previously reported to be associated with either Achilles tendon injury or ACL rupture. None showed an association in our cohort with a false discovery rate of less than 5%. We obtained, however, moderate to weak evidence for replication in one case; specifically, rs4919510 in MIR608 had a p-value of 5.1x10-3 for association with Achilles tendon injury, corresponding to a 7% chance of false replication. Finally, we tested 2855 SNPs in 90 candidate genes for musculoskeletal injury, but did not find any that showed a significant association below a false discovery rate of 5%. We provide data containing summary statistics for the entire genome, which will be useful for future genetic studies on these injuries.

Partial Text

Achilles tendinopathy or rupture and anterior cruciate ligament (ACL) ruptures are frequent sources of pain and dysfunction in recreational and elite athletes. Recent studies have tested a few single-nucleotide polymorphisms (SNPs) in a small number of candidate genes for association with Achilles tendon injury or ACL rupture in athletes. For Achilles tendon injury, studies found 19 DNA variations residing in 12 genes that were associated with Achilles tendinopathy at p<0.05 using cohorts containing between 52 and 184 athletes [1–12]. In one case (rs12722 in COL5A1), the association with Achilles tendinopathy was found to replicate in an independent cohort (p = .024)[4]. For ACL rupture, studies have previously found nine DNA variations in eight genes with p < .05 where the number of cases ranged between 86 and 358 [7,13, 14–22]. rs180012 in COL1A1 was replicated in several studies [14–18]. None of the remaining SNPs have been replicated for either Achilles tendon injury or ACL rupture. Genome-wide association screens were performed for either Achilles tendon injury (defined as tendinopathy, rupture or repair) or ACL rupture using data from the Genetic Epidemiology Research on Adult Health and Aging (GERA) cohort. The generation of the data and pipeline for data analysis have been previously described in Jorgenson et al., 2015 and Roos et al., 2016 [23] [24]. Achilles tendon and ACL injury are common in recreational and elite athletes, and even in non-athletes [35–40]. Prior studies have identified 12 genes associated with Achilles tendinopathy and 8 genes associated with ACL rupture [1,2,4–12,13, 14–22]. These prior studies, however, evaluated a small number of candidate genes among small cohorts of athletes. With the advent of large-scale genotyping programs, it is now possible to screen the entire genome for polymorphisms associated with sports injury risks such as Achilles tendon or ACL injury. In principle, a genome-wide screen for injury could provide new insight about the differences between individuals regarding their inherent propensity for injury. Furthermore, because the genotype data includes most common polymorphisms, a genome-wide screen reports the strongest associations in the genome without bias, and these associations are the most useful for predicting individual risks for injury.   Source: http://doi.org/10.1371/journal.pone.0170422