Sex-specific transcriptome similarity networks elucidate comorbidity relationships.

ABSTRACT:

Background

Biological differences between women and men lead to variations in the prevalence and progression of many diseases, influencing diagnosis, management, and treatment outcomes. However, the biological mechanisms that contribute to sex differences in disease co-occurrence remain largely unexplored. This study aims to uncover the molecular processes underlying sex-specific patterns of comorbidity.

Methods

We analyze gene expression data from over 100 diseases, considering the biological sex of each sample (8906 samples, 43.06% women). For each sex, we construct disease similarity networks based on differential gene expression profiles and identify enriched biological processes. We then compare these networks with epidemiological data from population-level comorbidity

SUBMITTER: Sanchez-Valle J 

PROVIDER: S-EPMC12847782 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature