ena-STUDY-Division of Exercise Science and Sports Medicine-21-02-2018-13:11:53:141-580
Genetic risk factors for musculoskeletal soft tissue injuries
Background: Musculoskeletal soft tissue injuries are complex phenotypes, with genetics as a proposed risk factor. Case-control association studies using the candidate gene approach have predominantly been used to identify risk loci for these injuries. However, the ability to identify all risk conferring variants using this approach alone is unlikely. Therefore, this study aimed to further define the genetic profile of these injuries using a multifaceted approach involving whole exome sequencing and a customized analyses pipeline. The exomes of ten exemplar asymptomatic controls and ten exemplar cases with Achilles tendinopathy were individually sequenced using a platform that included the coverage of the untranslated regions and miRBase miRNA genes. Approximately 200 000 variants were identified in the sequenced samples. Previous research was used to guide the targeted analysis of the TNC and COL27A1 genes located on chromosome 9. Selection of variants within these genes were however not predetermined but based on a tiered filtering strategy. Four variants in TNC (rs1061494, rs1138545, rs2104772 and rs1061495) and three variants in upstream COL27A1 gene (rs2567706, rs2241671 and rs2567705) were genotyped in larger Achilles tendinopathy and ACL rupture cohorts. The CC genotype of TNC rs1061494 (C/T) was associated with the risk of Achilles tendinopathy (p=0.018, OR: 2.5 95% CI: 1.2-5.1). Furthermore, the AA genotype of the TNC rs2104772 (A/T) variant was significantly associated with ACL ruptures in the female subgroup (p=0.035, OR: 2.3 95% CI: 1.1-5.1). Two overlapping inferred haplotypes in the TNC gene were also associated with the risk of Achilles tendinopathy and ACL ruptures respectively. These results provide a proof of concept for the use of a customized pipeline for the exploration of a larger genomic dataset. This approach, using previous research to guide a targeted analysis of the data has generated new genetic signatures in the biology of musculoskeletal soft tissue injuries.
Background: Musculoskeletal soft tissue injuries are complex phenotypes, with genetics as a proposed risk factor. Case-control association studies using the candidate gene approach have predominantly been used to identify risk loci for these injuries. However, the ability to identify all risk conferring variants using this approach alone is unlikely. Therefore, this study aimed to further define the genetic profile of these injuries using a multifaceted approach involving whole exome sequencing and a customized analyses pipeline. The exomes of ten exemplar asymptomatic controls and ten exemplar cases with Achilles tendinopathy were individually sequenced using a platform that included the coverage of the untranslated regions and miRBase miRNA genes. Approximately 200 000 variants were identified in the sequenced samples. Previous research was used to guide the targeted analysis of the TNC and COL27A1 genes located on chromosome 9. Selection of variants within these genes were however not predetermined but based on a tiered filtering strategy. Four variants in TNC (rs1061494, rs1138545, rs2104772 and rs1061495) and three variants in upstream COL27A1 gene (rs2567706, rs2241671 and rs2567705) were genotyped in larger Achilles tendinopathy and ACL rupture cohorts. The CC genotype of TNC rs1061494 (C/T) was associated with the risk of Achilles tendinopathy (p=0.018, OR: 2.5 95% CI: 1.2-5.1). Furthermore, the AA genotype of the TNC rs2104772 (A/T) variant was significantly associated with ACL ruptures in the female subgroup (p=0.035, OR: 2.3 95% CI: 1.1-5.1). Two overlapping inferred haplotypes in the TNC gene were also associated with the risk of Achilles tendinopathy and ACL ruptures respectively. These results provide a proof of concept for the use of a customized pipeline for the exploration of a larger genomic dataset. This approach, using previous research to guide a targeted analysis of the data has generated new genetic signatures in the biology of musculoskeletal soft tissue injuries.