Mentoring in Patient Oriented Research in Lung Disease through a Sex and Gender Lens

ABSTRACT Lung diseases exhibit differences between males and females in risk, progression, symptoms, and response to therapy; rigorous investigation is needed to define the molecular reasons for these differences. Our previous work has demonstrated that modeling Omics data using gene regulatory networks can discover key differences driving health and disease. The goal of this K24 is to merge our prior approach to modeling sex differences with mentoring researchers in sex- and gender-aware data science. Methods will support modelling gender and sex as a biologic variable using a data science framework, to promote translation of data from the NHLBI Trans-Omics for Precision Medicine(TOPMed) program to actionable clinical innovations for COPD. The goal of this Patient Oriented Research program is to mentor trainees in Omics data science and Network Medicine through a sex and gender lens, which requires not only considering biology(sex) but societal constructs(gender); to date this approach has been limited for lung diseases. To advance the dissemination of data analytic approaches for COPD research, we will focus on sex and gender aware epidemiology, Omic analyses inclusive of X and Y chromosome data, and gene regulatory network methods. In addition to mentoring and career development, trainees will pursue the hypothesis that somatic mosaicism on the X chromosome (mCA X) and loss of Y (LoY) will associate with COPD phenotypes and COPD progression. To facilitate mentoring, scientific Aims include 1) Investigating whether mCA X and LoY mediate sex and gender divergent features of COPD and 2) Defining pathway and gene regulatory network rewiring associated with mCA X and LoY, using single Omic and network-based approaches. Innovative aspects include the evaluation of gender as well as sex associations with COPD; investigation of mCA X and LoY and COPD; extension of gene regulatory network approaches to include somatic mosaicism; and development of a sex- and gender-aware data science toolkit. Understanding sex and gender differences using tools to integrate Omics and the gene regulatory landscapes with mCA X and LoY will improve our understanding of COPD and support precision medicine initiatives. This paradigm shifting K24 will support the training of the next generation of pulmonary data scientists interested in sex and gender-aware Patient Oriented Research, with specific application to COPD, a leading cause of death with sex divergent features.