Project 458895

Investigating sex as a biological variable (SABV) to better understand the role of sex in trait and disease development is critical for enhanced and personalized medicine. To date, sex differences in research has been largely neglected in studies which has led to a gap in knowledge regarding which traits and diseases are most and least impacted by sex. Additionally, there remains much debate over the mechanisms of sex differences. We aim to comprehensively characterize the role of SABV with genetic tools on complex traits and diseases to help us gain insights into the etiology of sex differences and reduce this gap in knowledge. We propose this by (1) elucidating the role of genetics in sex-specific differences on the risk of cardio-metabolic diseases and their associated risk factors and to (2) assess whether therapeutic interventions have consistent effects on major clinical outcomes between the sexes. We will use an in-house multiple linear regression method that can account for the effects of over a million genetic variants interacting with SABV on traits and disease to address (1). (2) We will utilize Mendelian Randomization (MR) analyses to test the causality of associations between the traits studied in (1) and disease/clinical outcomes as well as through a sex-specific systematic meta-analysis of randomized control trials (RCTs) on the identified outcomes of interest. Briefly, MR is powerful tool that uses the randomly allocated genetic variants in populations to create a "natural" RCT to assess the causality of epidemiological associations. We will use biobank data to conduct this study (UKB; N=325,000). Understanding the mechanisms of sex differences is urgently needed to improve risk stratification and improve therapeutic options for men and women. This study can be transformative in its translational ability to identify biological pathways that are similar or different between the sexes and incorporate those findings in clinical practices.