Leveraging data from bivariate genome-wide association meta-analysis to unravel novel pleiotropic pathways of bone-muscle crosstalk

The aging-related decline in bone (osteoporosis) and muscle (sarcopenia) mass represents a serious health issue increasing the rate of falls, fractures, and mortality in the elderly population. Several genes associated with bone and muscle have indicated possible pleiotropy; a genetic variant influencing multiple traits. However, the full impact of leveraging pleiotropy to improve musculoskeletal outcomes is still uncertain. This study aims to broaden our understanding of the shared molecular mechanisms underlying osteoporosis and sarcopenia by expanding the sample size and triangulating evidence from a variety of bioinformatics tools and datasets. More specifically, this study will be using SumRank—a novel approach for pleiotropy evaluation, minimizing false positives—and comparing its performance with existing tools. The potential therapeutic impact of several genes will be assessed using bioinformatics tools and validated using individual-level genetic data from 15 cohorts across the United States, Australia and Europe. Through a collaborative effort between McGill University and Erasmus Medical Center, this research initiative aims to synergize various research approaches, data analysis resources, and collective knowledge. The partnership holds promise for a more nuanced understanding of the intricate interplay between genetics and musculoskeletal health, potentially paving the way for improved interventions in the future.

Faculty Supervisor:

Daniel Taliun

Student:

Partner:

Erasmus University Rotterdam

Discipline:

Life Sciences

Sector:

Health and Related Sciences & Technology

University:

McGill University

Program: