Notes
Background
The etiology of rotator cuff tearing is likely multifactorial, including a potential genetic predisposition. The purpose of the study was to identify genetic variants associated with rotator cuff tearing utilizing the UK Biobank (UKB) cohort, confirm variants using a separate genetic database, and evaluate tissue expression of genes with associated variants following rotator cuff tearing using RNA sequencing.
Methods
Genome-wide association study (GWAS): A GWAS was performed using data from UKB with 5701 cases of rotator cuff injury. RNA sequencing analyses: rotator cuff biopsies were obtained from 24 patients with full-thickness rotator cuff tears who underwent arthroscopic rotator cuff repair (cases) and 9 patients who underwent open reduction internal fixation for a proximal humerus fracture (controls). Total RNA was extracted and differential gene expression was measured by RNAseq for genes with variants associated with rotator cuff tearing.
Results
The results of the UKB GWAS identified 3 loci that reached genome-wide statistical significance: 2 loci on chromosome 7 in GLCCI1 (rs4725069; P = 5.0e-09) and THSD7A (rs575224171; P = 5.3e-09), and 1 locus on chromosome 2 in ZNF804A (rs775583810; P = 3.9e-09). The association with rotator cuff injury of the GLCCI1 single-nucleotide polymorphism (SNP; rs4725069) was confirmed in the Kaiser Permanente Research Bank cohort (P = .008). Twenty previously reported SNPs in 12 genes were evaluated using summary statistics from the UKB GWAS, which confirmed 3 SNPs in TNC with rotator cuff injury (rs1138545, rs72758637, and rs7021589; all P < .0024). Of 17 genes with variants associated with rotator cuff injury (14 previously from literature plus 3 new genes from current UKB GWAS), TIMP2, Col5A1, TGFBR1, and TNC were upregulated (P < .001 for all) and THSD7A was downregulated (P = .005) in tears vs. controls in the RNA sequencing data set.
Conclusion
The UKB GWAS has identified 3 novel loci associated with rotator cuff tearing (ZNF804A, GLCCI1, THSD7A). Expression of the THSD7A gene was significantly downregulated in rotator cuff tears vs. controls supporting a potential functional role. Three previously reported SNPs in the TNC gene were validated in the UKB GWAS, supporting a role for this gene in rotator cuff tearing. Finally, TIMP2, Col5A1, TGFBR1, and TNC genes were found to have significantly upregulated tissue expression in cases vs. controls supporting a biologic role in tearing for these genes.
Application 17847
GWAS for risk for sports injuries
GWAS for sports injury risk could provide a rich source of new genetic knowledge that can be used to reduce injuries in athletes. Until now, gene association studies have been limited to candidate gene studies for only a few types of injuries. We would like to use the UK Biobank to perform a whole-genome screen for SNPs for a diverse array of sports injuries, such as ACL rupture and Rotator Cuff Injury. Use of this genetic information may aid in the development of a personalized injury prevention program for athletes, which could provide a new edge for successful competition.
The proposed research is to benefit the health of athletes. The results will be made publicly available via publication and deposition of data in public databases. All the data will be de-identified and protected on a secure server. We have IRB approval for a similar project using the RPGEH cohort, and it should be straightforward to extend the IRB application for the UK Biobank data. We propose to perform a GWAS analysis for nine types of musculoskeletal injuries. The nine injuries are: Anterior Cruciate Ligament (knee)
Posterior cruciate ligament rupture
Medial collateral ligament rupture
Patella tendon rupture
Quadriceps tendon rupture
Achilles tendon rupture and tendonosis
Shoulder dislocation
Rotator cuff muscle rupture
The GWAS will be a case/control analysis, using genotype, sex, ancestry and age as covariates, as appropriate. Each of the injuries are encoded in the electronic medical records with an ICD9 code.
We will use standard methods for the GWAS analysis (i.e. PLINK and IMPUTE2).
full cohort
Lead investigator: | Dr Stuart Kim |
Lead institution: | Stanford University |
1 related Return
Return ID | App ID | Description | Archive Date |
2444 | 17847 | Identification of 613 new loci associated with heel bone mineral density and a polygenic risk score for bone mineral density, osteoporosis and fracture | 5 Oct 2020 |