01 - Set-based Methods to Identify Genetic Variants Associated with Falls and Fractures Susceptibility

Combining multiple outcomes in genetic association tests can increase statistical power while identifying key biomarkers that are associated with multiple traits. In this work, we develop a set-based inference method for jointly testing the association between multiple interval-censored outcomes and a group of genetic mutations, such as those in a gene or pathway. This variance components score test only requires fitting the null model once, so it is well-suited for genome-wide application. Our work shows that combining multiple interval-censored outcomes can detect causal variants with increased power over using a test that only considers single outcomes. We further validate the value of jointly testing multiple correlated interval-censored outcomes by testing for the genetic effects of both number of falls and bone fracture data from the UK Biobank. Fall susceptibility and risk of fractures, which have been shown to be heritable traits, are important to investigate because of their prevalence in healthcare and the high cost associated with these outcomes. This application of our method identified genes that have been shown through previous literature to be associated with muscle and bone related diseases, showing the potential to further identify genes that may be associated with these outcomes.

Survival Analysis

GWAS

Set-based Inference

Interval-Censored

Multiple Outcomes 

Mid-Level

Knowledge

Women in Statistics and Data Science 2022