Approved Research

Genetic risk prediction of non-contact ACL rupture using polygenic risk scores

Lay summary

Genome-wide association studies (GWAS) have identified tens of thousands of genetic components for numerous diseases and traits, including non-contact anterior cruciate ligament (ACL) rupture. Until recently, non-contact ACL rupture has been considered an injury that is common in sports medicine. Although family risk has been recognized for many years, it is only recently that the condition has been shown to have high heritability.

Therefore, non-contact ACL rupture should be thought of as a common complex disease, rather than an injury. Interpretation of past ACL rupture GWAS findings has been challenging. The complex correlation structure of genetic variants and their weak effects on disease risk highlight the importance of biologically functional genetic variants that are predictive of disease risk.

Leveraging rich data in the UK Biobank and ACL tissue transcriptome data from the University of Wisconsin-Madison, this project aims to use sophisticated data integration techniques to study non-contact ACL rupture heritability, polygenicity, and development methods for accurate prediction of disease risk.

We expect the initial stage for data management and GWAS analysis for various traits to take ~12 months to finish. Integrative analysis of GWAS, functional annotations, and development of a polygenic risk score prediction approach for accurate estimation of disease risk with take ~24 months.

Our results will provide fundamentally new insights into the genetic basis of non-contact ACL rupture. Some research outcomes such as fine-mapped genetic variants, improved effect size estimates, and more accurate polygenic risk scores, will greatly benefit other researchers who are interested in similar orthopaedic phenotypes, such as Achilles tendinopathy.

In addition, our proposed study will provide a principled framework to model the genetics of common orthopaedic complex diseases using single nucleotide polymorphism (SNP) data. Methodological advancements in polygenic risk score prediction of disease risk in this proposed project will benefit researchers of broad interest. Finally, our results for non-contact ACL rupture may guide future development of effective intervention/treatment strategies to improve population sports medicine health.