Integration of metabolomics and transcriptomics reveals novel biomarkers in the blood for tuberculosis diagnosis in children

Abstract

Pediatric tuberculosis (TB) remains a major global health problem. Improved pediatric diagnostics using readily available biosources are urgently needed. We used liquid chromatography-mass spectrometry to analyze plasma metabolite profiles of Indian children with active TB (n = 16) and age- and sex-matched, Mycobacterium tuberculosis-exposed but uninfected household contacts (n = 32). Metabolomic data were integrated with whole blood transcriptomic data for each participant at diagnosis and throughout treatment for drug-susceptible TB. A decision tree algorithm identified 3 metabolites that correctly identified TB status at distinct times during treatment. N-acetylneuraminate achieved an area under the receiver operating characteristic curve (AUC) of 0.66 at diagnosis. Quinolinate achieved an AUC of 0.77 after 1 month of treatment, and pyridoxate achieved an AUC of 0.87 after successful treatment completion. A set of 4 metabolites (gamma-glutamylalanine, gamma-glutamylglycine, glutamine, and pyridoxate) identified treatment response with an AUC of 0.86. Pathway enrichment analyses of these metabolites and corresponding transcriptional data correlated N-acetylneuraminate with immunoregulatory interactions between lymphoid and non-lymphoid cells, and correlated pyridoxate with p53-regulated metabolic genes and mitochondrial translation. Our findings shed new light on metabolic dysregulation in children with TB and pave the way for new diagnostic and treatment response markers in pediatric TB.

Differential Diagnosis of Latent Tuberculosis Infection and Active Tuberculosis: A Key to a Successful Tuberculosis Control Strategy

“…Furthermore, they also found that the abundance of inosine was significantly lower in individuals with LTBI than in patients with TB and HCs (Weiner et al, 2012). More recently, Dutta et al (2020) analyzed the plasma metabolite profiles of 16 aTB children and 32 household contacts in India using liquid chromatography-mass spectrometry and identified three metabolites (N-acetylneuraminate, quinolinate, and pyridoxate) that could correctly discriminate TB status at distinct times during treatment, with AUCs of 0.66, 0.87, and 0.86, respectively. Although the above studies have used metabolomics techniques to identify abundant biomarkers for distinguishing aTB from individuals with LTBI, they have not linked metabolomics with transcriptomics and proteomics.…”

Plasma Metabolomics Reveals Dysregulated Metabolic Signatures in HIV-Associated Immune Reconstitution Inflammatory Syndrome

“…In an attempt to further delineate the implication of metabolomics in IRIS pathogenesis, we employed the MOFA model to incorporate the metabolome, transcriptome, and plasma biomarker profile. We have demonstrated the success of this approach previously in settings such as TB, diabetes, and leishmaniasis, providing important insights into the pathogenesis of these pathological conditions ( 40 , 41 , 67 ). The IRIS metabolome provided complementary information that expanded our understanding of the profound immune activation observed in IRIS patients.…”

Integrative Multi-Omics Reveals Serum Markers of Tuberculosis in Advanced HIV

“…All methods utilized a Waters ACQUITY UPLC and a Thermo Scientific Q-Exactive high resolution/accurate mass spectrometer (MS) interfaced with a heated electrospray ionization (HESI-II) source and Orbitrap mass analyzer operated at 35,000 mass resolution. Sample extract was dried and reconstituted in solvents for optimization of analysis as previously described (40). MS analysis used dynamic exclusion to alternate between MS and data-dependent MS n scans, with scan range covering 70-1000 m/z.…”

“…MS analysis used dynamic exclusion to alternate between MS and data-dependent MS n scans, with scan range covering 70-1000 m/z. Metabolon's hardware and software were used to extract, peak-identify, and QC-process raw data, as previously described (40). Metabolon libraries of purified standards or recurrent unknown entities were used to identify compounds.…”