Bioinformatics approaches to study molecular sex differences in complex diseases#

Authors#

Rebecca Ting Jiin Loo, Mohamed Soudy, Francesco Nasta, Mirco Macchi, Enrico Glaab

Abstract#

Many complex diseases exhibit pronounced differences between the sexes, which can affect both the initial risk of developing the disease, as well as clinical disease symptoms, molecular manifestations, disease progression and the risk of developing comorbidities. Despite this, computational studies on molecular data for complex diseases often treat sex merely as a confounding variable, aiming to filter out sex-specific effects rather than attempting to interpret them. A more systematic, in-depth exploration of sex-specific disease mechanisms could significantly improve our understanding of pathological and protective processes with sex-dependent profiles. This survey discusses dedicated bioinformatics approaches for studying molecular sex differences in complex diseases. It highlights that, beyond classical statistical methods to investigate sex differences, approaches are needed to interpret sex-dependent alterations in diseases mechanistically, integrating prior knowledge of relevant hormone signaling interactions, gene regulatory networks, and sex linkage of genes. The review explores and compares the benefits, pitfalls, and limitations of different conventional statistical and systems level mechanistic analyses to this end, including tailored pathway and network analysis techniques. Overall, this review highlights the potential of specialized bioinformatics techniques to systematically investigate molecular sex differences in complex diseases, to inform biomarker signature modeling, and guide more personalized treatment approaches.