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.