Bioinformatic Insights and XGBoost Identify Shared Genetics in Chronic Obstructive Pulmonary Disease and Type 2 Diabetes.

ABSTRACT:

Background

The correlation between chronic obstructive pulmonary disease (COPD) and Type 2 diabetes mellitus (T2DM) has long been recognized, but their shared molecular underpinnings remain elusive. This study aims to uncover common genetic markers and pathways in COPD and T2DM, providing insights into their molecular crosstalk.

Methods

Utilizing the Gene Expression Omnibus (GEO) database, we analyzed gene expression datasets from six COPD and five T2DM studies. A multifaceted bioinformatics approach, encompassing the limma R package, unified matrix analysis, and weighted gene co-expression network analysis (WGCNA), was deployed to identify differentially expressed genes (DEGs) and hub genes. Functional enrichment and protein-protein interaction (PPI) analyses were conducted

SUBMITTER: Ji Q 

PROVIDER: S-EPMC11882755 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature