Networks Tools to Understand Sex- and Gender-Specific Drivers of Disease

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ABSTRACT Complex human diseases including chronic obstructive pulmonary disease and many human cancers, exhibit strong differences between males and females in risk, disease progression, and response to therapy. Our previous work in normal and disease tissues from males and females has shown that while there are rarely significant differences in genetic associations or gene expression that can explain the observed sex-based differences, modeling gene regulatory processes can lead to key insights into the likely drivers of sex differences in health and disease. This suggests that both sex-based factors and epigenetic variability likely work together to help define risk and response. This observation is further supported by the fact that sex-based differences are not static but rather evolve over the course of an individual’s lifespan, during which epigenetic state and hormonal regulation of gene expression likely change in related to gender-associated factors. In this application, we propose to merge the threads of DNA methylation variation, gene regulatory modeling, and sex-based regulatory network assessments to better understand the factors that drive the observed sex and gender-related differences in human diseases. We envision three specific aims within the context of our research plan, including: Developing tools for the inclusion of sex chromosomes in network models and methods for comparing male and female networks; Refinement of network tools for setting epigenetic priors and inclusion of DNA methylation data as a primary data for studying sex differences informed by gender; and Application to diseases with sex differences, including COPD and lung cancer as primary examples. We expand network methods to develop tools to better incorporate the effects of the allosomes in the process of gene regulation. This is particularly important as we have discovered current methods for normalization of sex chromosome gene expression can influence observed gene regulatory interactions. We will refine tools to incorporate epigenetic regulation into our sex-specific models, exploring how DNA methylation may capture gender to influence gene regulatory network structure and disease risk. Understanding the sex- and gender- related differences in this regulatory landscape will help us better understand human diseases and highlight approaches to identify sex-aware therapeutic targets. This proposal is highly responsive to the goals of RFA- OD-19-029: The Intersection of Sex and Gender Influences on Health and Disease as it will investigate a systems/network based approach to investigating sex and gender influences in human disease, as well as providing publicly available tools and networks to facilitate sex and gender research.