Clustering-based COPD subtypes have distinct longitudinal outcomes and multi-omics biomarkers.

ABSTRACT:

Introduction

Chronic obstructive pulmonary disease (COPD) can progress across several domains, complicating the identification of the determinants of disease progression. In our previous work, we applied k-means clustering to spirometric and chest radiological measures to identify four COPD-related subtypes: 'relatively resistant smokers (RRS)', 'mild upper lobe-predominant emphysema (ULE)', 'airway-predominant disease (AD)' and 'severe emphysema (SE)'. In the current study, we examined the associations of these subtypes to longitudinal COPD-related health measures as well as blood transcriptomic and plasma proteomic biomarkers.

Methods

We included 8266 non-Hispanic white and African-American smokers from the COPDGene study. We used linear regression to investigate cluster a

SUBMITTER: Gregory A 

PROVIDER: S-EPMC9403129 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature