Small molecule bio‐signature in childhood intra‐thoracic tuberculosis identified by metabolomics

Author:

Sharma Nupur1,Upadhyay Deepti2,Gautam Hitender1,Sharma Uma2,Lodha Rakesh3,Kabra Sushil Kumar3,Das Bimal Kumar1,Kapil Arti1,Mohan Anant4,Jagannathan Naranamangalam Raghunathan25,Guleria Randeep46,Singh Urvashi Balbir1

Affiliation:

1. Department of Microbiology All India Institute of Medical Sciences New Delhi India

2. Department of Nuclear Magnetic Resonance All India Institute of Medical Sciences New Delhi India

3. Department of Pediatrics All India Institute of Medical Sciences New Delhi India

4. Department of Pulmonary Medicine & Sleep Disorders All India Institute of Medical Sciences New Delhi India

5. Department of Radiology Chettinad Academy of Research & Education Kelambakkam Tamil Nadu India

6. Department of Pulmonary Medicine Medanta Gurgaon Haryana India

Abstract

The diagnosis of pediatric tuberculosis (TB) remains a major challenge, hence the evaluation of new tools for improved diagnostics is urgently required. We investigated the serum metabolic profile of children with culture‐confirmed intra‐thoracic TB (ITTB) (n = 23) and compared it with those of non‐TB controls (NTCs) (n = 13) using proton NMR spectroscopy‐based targeted and untargeted metabolomics approaches. In targeted metabolic profiling, five metabolites (histidine, glycerophosphocholine, creatine/phosphocreatine, acetate, and choline) differentiated TB children from NTCs. Additionally, seven discriminatory metabolites (N‐α‐acetyl‐lysine, polyunsaturated fatty acids, phenylalanine, lysine, lipids, glutamate + glutamine, and dimethylglycine) were identified in untargeted metabolic profiling. The pathway analysis revealed alterations in six metabolic pathways. The altered metabolites were associated with impaired protein synthesis, hindered anti‐inflammatory and cytoprotective mechanisms, abnormalities in energy generation processes and membrane metabolism, and deregulated fatty acid and lipid metabolisms in children with ITTB. The diagnostic significance of the classification models obtained from significantly distinguishing metabolites showed sensitivity, specificity, and area under the curve of 78.2%, 84.6%, and 0.86, respectively, in the targeted profiling and 92.3%, 100%, and 0.99, respectively, in the untargeted profiling. Our findings highlight detectable metabolic changes in childhood ITTB; however, further validation is warranted in a large cohort of the pediatric population.

Publisher

Wiley

Subject

Spectroscopy,Radiology, Nuclear Medicine and imaging,Molecular Medicine

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