IISER MOHALI

Abstract: Despite having mostly shared genomes, males and females are strikingly different across taxa. Especially in humans, sex difference is widespread in complex disorders in the onset, prevalence or expression of the disorders. I am interested in understanding the underlying genetic basis of such sex differences in humans. Traditionally, in human genetics, sex differences have been studied at the level of single traits, but traits do not occur in isolation, and they are found in functionally related modules. Therefore, a multivariate framework considering correlated traits together gives us a complete biological overview of diseases or phenotypes. In this talk, I will present a multivariate framework for studying sex differences that explicitly accounts for genetic correlations among traits. I will first discuss a study of the multivariate genetic architecture of sex-hormones, particularly testosterone, and anthropometric traits in the UK Biobank. We found extensive sexual antagonism in the genetic architecture driven by testosterone. Using evolutionary simulations, we showed that the shared genetic architecture between the sexes can constrain the evolution of sex differences under sexually antagonistic selection. I will then extend this framework to brain disorders, focusing on schizophrenia, major depression, and bipolar disorder. Using a multi-trait approach, we identified sex differences at the genetic variant level as well as in the gene expression patterns associated with the brain disorders across developmental stages in males and females. Sex differences were also apparent at associations of the brain disorders with specific cell types. Our results showed that sex-specific genetic architecture can emerge even when much of the genome is shared between the sexes, highlighting the importance of multivariate analyses for understanding sex-specific disease risk.