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Plasma Metabolomic Signatures of Chronic Obstructive Pulmonary Disease and the Impact of Genetic Variants on Phenotype-Driven Modules.

Authors :
Gillenwater LA
Pratte KA
Hobbs BD
Cho MH
Zhuang Y
Halper-Stromberg E
Cruickshank-Quinn C
Reisdorph N
Petrache I
Labaki WW
O'Neal WK
Ortega VE
Jones DP
Uppal K
Jacobson S
Michelotti G
Wendt CH
Kechris KJ
Bowler RP
Source :
Network and systems medicine [Netw Syst Med] 2020 Dec 01; Vol. 3 (1), pp. 159-181. Date of Electronic Publication: 2020 Dec 31.
Publication Year :
2020

Abstract

Background: Small studies have recently suggested that there are specific plasma metabolic signatures in chronic obstructive pulmonary disease (COPD), but there have been no large comprehensive study of metabolomic signatures in COPD that also integrate genetic variants. Materials and Methods: Fresh frozen plasma from 957 non-Hispanic white subjects in COPDGene was used to quantify 995 metabolites with Metabolon's global metabolomics platform. Metabolite associations with five COPD phenotypes (chronic bronchitis, exacerbation frequency, percent emphysema, post-bronchodilator forced expiratory volume at one second [FEV <subscript>1</subscript> ]/forced vital capacity [FVC], and FEV <subscript>1</subscript> percent predicted) were assessed. A metabolome-wide association study was performed to find genetic associations with metabolite levels. Significantly associated single-nucleotide polymorphisms were tested for replication with independent metabolomic platforms and independent cohorts. COPD phenotype-driven modules were identified in network analysis integrated with genetic associations to assess gene-metabolite-phenotype interactions. Results: Of metabolites tested, 147 (14.8%) were significantly associated with at least 1 COPD phenotype. Associations with airflow obstruction were enriched for diacylglycerols and branched chain amino acids. Genetic associations were observed with 109 (11%) metabolites, 72 (66%) of which replicated in an independent cohort. For 20 metabolites, more than 20% of variance was explained by genetics. A sparse network of COPD phenotype-driven modules was identified, often containing metabolites missed in previous testing. Of the 26 COPD phenotype-driven modules, 6 contained metabolites with significant met-QTLs, although little module variance was explained by genetics. Conclusion: A dysregulation of systemic metabolism was predominantly found in COPD phenotypes characterized by airflow obstruction, where we identified robust heritable effects on individual metabolite abundances. However, network analysis, which increased the statistical power to detect associations missed previously in classic regression analyses, revealed that the genetic influence on COPD phenotype-driven metabolomic modules was modest when compared with clinical and environmental factors.<br />Competing Interests: No competing financial interests exist.<br /> (© Lucas A. Gillenwater et al., 2020; Published by Mary Ann Liebert, Inc.)

Details

Language :
English
ISSN :
2690-5949
Volume :
3
Issue :
1
Database :
MEDLINE
Journal :
Network and systems medicine
Publication Type :
Academic Journal
Accession number :
33987620
Full Text :
https://doi.org/10.1089/nsm.2020.0009