Open AccessMolecular perturbations in pulmonary tuberculosis patients identified by pathway-level analysis of plasma metabolic features
Author(s) -
Nguyen Phuoc Long,
Da Young Heo,
Seongoh Park,
Nguyen Thi Hai Yen,
YongSoon Cho,
JaeGook Shin,
Jee Youn Oh,
Dong-Hyun Kim
Publication year - 2022
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0262545
Subject(s) - metabolomics , metabolic pathway , tuberculosis , pathway analysis , biology , metabolic network , mycobacterium tuberculosis , metabolism , medicine , adverse outcome pathway , bioinformatics , physiology , computational biology , biochemistry , gene , pathology , gene expression
Insight into the metabolic biosignature of tuberculosis (TB) may inform clinical care, reduce adverse effects, and facilitate metabolism-informed therapeutic development. However, studies often yield inconsistent findings regarding the metabolic profiles of TB. Herein, we conducted an untargeted metabolomics study using plasma from 63 Korean TB patients and 50 controls. Metabolic features were integrated with the data of another cohort from China (35 TB patients and 35 controls) for a global functional meta-analysis. Specifically, all features were matched to a known biological network to identify potential endogenous metabolites. Next, a pathway-level gene set enrichment analysis-based analysis was conducted for each study and the resulting p -values from the pathways of two studies were combined. The meta-analysis revealed both known metabolic alterations and novel processes. For instance, retinol metabolism and cholecalciferol metabolism, which are associated with TB risk and outcome, were altered in plasma from TB patients; proinflammatory lipid mediators were significantly enriched. Furthermore, metabolic processes linked to the innate immune responses and possible interactions between the host and the bacillus showed altered signals. In conclusion, our proof-of-concept study indicated that a pathway-level meta-analysis directly from metabolic features enables accurate interpretation of TB molecular profiles.