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Molecular perturbations in pulmonary tuberculosis patients identified by pathway-level analysis of plasma metabolic features

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  • Nguyen Phuoc Long
  • Da Young Heo
  • Seongoh Park
  • Nguyen Thi Hai Yen
  • Yong-Soon Cho
  • Jae-Gook Shin
  • Jee Youn Oh
  • Dong-Hyun Kim

Abstract

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.

Suggested Citation

  • Nguyen Phuoc Long & Da Young Heo & Seongoh Park & Nguyen Thi Hai Yen & Yong-Soon Cho & Jae-Gook Shin & Jee Youn Oh & Dong-Hyun Kim, 2022. "Molecular perturbations in pulmonary tuberculosis patients identified by pathway-level analysis of plasma metabolic features," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-13, January.
  • Handle: RePEc:plo:pone00:0262545
    DOI: 10.1371/journal.pone.0262545
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    1. Akul Singhania & Raman Verma & Christine M. Graham & Jo Lee & Trang Tran & Matthew Richardson & Patrick Lecine & Philippe Leissner & Matthew P. R. Berry & Robert J. Wilkinson & Karine Kaiser & Marc Ro, 2018. "A modular transcriptional signature identifies phenotypic heterogeneity of human tuberculosis infection," Nature Communications, Nature, vol. 9(1), pages 1-17, December.
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