Interrogating the pathogenesis of COPD using metabolomics and genomics data

Chronic lower respiratory diseases, including chronic obstructive pulmonary disease (COPD), are the third leading cause of death worldwide. While cigarette smoking is a common risk factor for COPD, the risk of disease also increases with age, and the disease can progress despite smoking cessation. Treatment options for COPD are limited: existing pharmacologic therapies have at best a modest impact on mortality on a subset of patients. Thus, a better understanding of the molecular pathophysiology of COPD is needed to guide the development of new treatments. Large-scale genome-wide association studies (GWAS) of lung function, and COPD have identified >1,000 independent association signals. Some of these associations are coding and have downstream targets, such as AGER and SFTPD, that have been implicated as biomarkers and drug targets for COPD by gene expression and protein data. However, the downstream metabolic implications of these GWAS signals have been largely unexplored, and substantial evidence links metabolomic signatures to COPD. We are expanding our previously established PrediXcan method, which was designed for the integration of GWAS with gene expression loci, to incorporate metabolomics data. This new tool, termed MetaboXcan, will extract more comprehensive mechanistic information from GWAS and unlock new insights into the pathophysiology of COPD. By applying a preliminary version of MetaboXcan to the most recent and comprehensive multi-ancestry GWAS of lung function, we identified metabolic pathways that overlap with strong candidates of interest from our prior work, including long-chain fatty acid metabolism. In this proposal, we will continue to develop our MetaboXcan method to incorporate additional metabolomic resources derived from individuals with COPD, as well as disease- free controls (Aim 1). We will further apply MetaboXcan to achieve enhanced interpretation of large-scale GWAS for pulmonary disease traits in NHLBI Cohorts (Aim 2) as well as perform validation studies of selected metabolites (Aim 3). To accomplish these Aims, we have assembled an interdisciplinary collaborative group representing expertise in statistical genetics, pulmonary epidemiology, integrative genomics, metabolomics, and pulmonary medicine. Completion of these Aims will establish an expanded view of the metabolomic targets and pathways influenced by genetic variation for COPD, which will also provide a foundation for future drug development efforts. Project Number: 1R01HL173613-01A1 | Fiscal Year: 2025 | NIH Institute/Center: National Heart Lung and Blood Institute (NHLBI) | Principal Investigator: ANI MANICHAIKUL (+2 co-PIs) | Institution: UNIVERSITY OF VIRGINIA, CHARLOTTESVILLE, VA | Award Amount: $800,679 | Activity Code: R01 | Study Section: Special Emphasis Panel[ZRG1 EPH-G (02)] View on NIH RePORTER: https://reporter.nih.gov/project-details/1R01HL17361301A1