Proteomic networks and related genetic variants associated with smoking and chronic obstructive pulmonary disease.

ABSTRACT:

Background

Studies have identified individual blood biomarkers associated with chronic obstructive pulmonary disease (COPD) and related phenotypes. However, complex diseases such as COPD typically involve changes in multiple molecules with interconnections that may not be captured when considering single molecular features.

Methods

Leveraging proteomic data from 3,173 COPDGene Non-Hispanic White (NHW) and African American (AA) participants, we applied sparse multiple canonical correlation network analysis (SmCCNet) to 4,776 proteins assayed on the SomaScan v4.0 platform to derive sparse networks of proteins associated with current vs. former smoking status, airflow obstruction, and emphysema quantitated from high-resolution computed tomography scans. We then used NetSHy, a d

SUBMITTER: Konigsberg IR 

PROVIDER: S-EPMC11370252 | biostudies-literature | 2024 Sep

REPOSITORIES: biostudies-literature