Identification of serum biomarkers for active pulmonary tuberculosis using a targeted metabolomics approach

Yonggeun Cho, Youngmok Park, Bora Sim, Jungho Kim, Hyejon Lee, Sang Nae Cho, Young Ae Kang, Sang Guk Lee

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9 Citations (Scopus)

Abstract

Although tuberculosis (TB) is a severe health problem worldwide, the current diagnostic methods are far from optimal. Metabolomics is increasingly being used in the study of infectious diseases. We performed metabolome profiling to identify potential biomarkers in patients with active TB. Serum samples from 21 patients with active pulmonary TB, 20 subjects with latent TB infection (LTBI), and 28 healthy controls were analyzed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) followed by multivariate and univariate analyses. Metabolic profiles indicated higher serum levels of glutamate, sulfoxy methionine, and aspartate and lower serum levels of glutamine, methionine, and asparagine in active TB patients than in LTBI subjects or healthy controls. The ratios between metabolically related partners (glutamate/glutamine, sulfoxy methionine/methionine, and aspartate/asparagine) were also elevated in the active TB group. There was no significant difference in the serum concentration of these metabolites according to the disease extent or risk of relapse in active TB patients. Novel serum biomarkers such as glutamate, sulfoxy methionine, aspartate, glutamine, methionine, and asparagine are potentially useful for adjunctive, rapid, and noninvasive pulmonary TB diagnosis.

Original languageEnglish
Article number3825
JournalScientific reports
Volume10
Issue number1
DOIs
Publication statusPublished - 2020 Dec 1

Bibliographical note

Funding Information:
This research was supported by a grant from the Korea Health Technology R&D Project through the Korea Health Industry Development Institute (KHIDI), funded by the Ministry of Health & Welfare, Republic of Korea (grant number: HI14C1324), and a grant from the National Research Foundation of Korea (NRF) funded by the Korean Government (MSIP) (grant number: NRF-2017R1C1B5015044). The funding sources had no role in the study process, including the design, sample collection, analysis, or interpretation of the results.

Publisher Copyright:
© 2020, The Author(s).

All Science Journal Classification (ASJC) codes

  • General

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