| Application: | 17847, GWAS for risk for sports injuries |
| Title: | Identification of 613 new loci associated with heel bone mineral density and a polygenic risk score for bone mineral density, osteoporosis and fracture |
| Size: | 6.7 MB |
| Archived: | 5 Oct 2020 |
| Stability: | Complete |
| Personal: | Contains individual-level data |
Return 2444
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Notes
Low bone mineral density (BMD) leads to osteoporosis, and is a risk factor for bone fractures, including stress fractures. Using data from UK Biobank, a genome-wide association study identified 1,362 independent SNPs that clustered into 899 loci of which 613 are new. These data were used to train a genetic algorithm using 22,886 SNPs as predictors and showing a correlation with heel bone mineral density of 0.415. Combining this genetic algorithm with height, weight, age and sex resulted in a correlation with heel bone mineral density of 0.496. Individuals with low scores (2.2% of total) showed a change in BMD of -1.16 T-score units, an increase in risk for osteoporosis of 17.4 fold and an increase in risk for fracture of 1.87 fold. Genetic predictors could assist in the identification of individuals at risk for osteoporosis or fractures.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 |
|---|---|---|---|
| 3374 | 17847 | Genetic variants associated with rotator cuff tearing utilizing multiple population-based genetic resources | 22 Apr 2021 |
1 Publication
| Pub ID | Title | Author(s) | Year | Journal |
|---|---|---|---|---|
| 2445 | Identification of 613 new loci associated with heel bone mineral density and a polygenic risk score for bone mineral density, osteoporosis and fracture | Stuart K. Kim | 2018 | PLOS ONE |
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