Accordingly, sex and gender of the patient are considered in clinical practice when treatment and intervention options are evaluated. However, the mechanisms contributing to these sex differences in health and disease remain poorly understood, which hinders the design and application of care that is optimal for each sex throughout the course of life. The underlying biology is undoubtedly complex with varying environmental and hormonal influences often assumed the primary culprits. Yet, increasing evidence also points to genetics playing a part in these male-female differences. Sex differences, nevertheless, have and still remain largely understudied in human complex traits genomics. Thus, we believe a comprehensive investigation of potential sex-biased genomic components in the context of human health and disease is well-warranted.
We believe that in order to build a comprehensive understanding to the origins and mechanisms underlying sex differences in complex traits, we need to combine information across multiple biological scales. Therefore, in our work we utilize both population and cellular-level data sets and integrate genetic, transcriptomic, and extensive phenotype, e.g., medical registry, information. We are particularly fascinated by gene expression and by how it adds a valuable functional layer of information to genetic associations. Therefore, a central focus in our work is in linking diverse transcriptomics data sets with genetic associations discovered in biobank-scale data sets to find the right genes, cell and tissue types, and molecular pathways, and thereby provide insight into the biology of complex traits and sex differences therein.