Please use this identifier to cite or link to this item: http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/9589
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dc.contributor.authorYOUSF, SALEEMen_US
dc.contributor.authorBatra, Hitender S.en_US
dc.contributor.authorJha, Rakesh M.en_US
dc.contributor.authorSardesai, Devika M.en_US
dc.contributor.authorAnanthamohan, Kalyanien_US
dc.contributor.authorCHUGH, JEETENDERen_US
dc.contributor.authorSharma, Shilpyen_US
dc.date.accessioned2025-04-15T06:54:18Z-
dc.date.available2025-04-15T06:54:18Z-
dc.date.issued2024-04en_US
dc.identifier.citationClinica Chimica Acta, 557, 117857.en_US
dc.identifier.issn0009-8981en_US
dc.identifier.issn1873-3492en_US
dc.identifier.urihttps://doi.org/10.1016/j.cca.2024.117857en_US
dc.identifier.urihttp://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/9589-
dc.description.abstractBackground: The prevalence of type 2 diabetes mellitus (T2DM), a progressive metabolic disorder characterized by chronic hyperglycemia and the development of insulin resistance, has increased globally, with worrying statistics coming from children, adolescents, and young adults from developing countries like India. Here, we investigated unique circulating metabolic signatures associated with prediabetes and T2DM in an Indian cohort using NMR-based metabolomics. Materials and methods: The study subjects included healthy volunteers (N = 101), prediabetic subjects (N = 75), and T2DM patients (N = 108). Serum metabolic profiling was performed using 1 H NMR spectroscopy and major perturbed metabolites were identified by multivariate analysis and receiver operating characteristic (ROC) modules. Results: Of the 36 aqueous abundant metabolites, 24 showed a statistically significant difference between healthy volunteers, prediabetics, and established T2DM subjects. On performing multivariate ROC curve analysis with 5 commonly dysregulated metabolites (namely, glucose, pyroglutamate, o-phosphocholine, serine, and methionine) in prediabetes and T2DM, AUC values obtained were 0.96 (95 % confidence interval (CI) = 0.93, 0.98) for T2DM; and 0.88 (95 % CI = 0.81, 0.93) for prediabetic subjects, respectively. Conclusion: We propose that the identified metabolite panel can be used in the future as a biomarker for clinical diagnosis, patient surveillance, and for predicting individuals at risk for developing diabetes.en_US
dc.language.isoenen_US
dc.publisherElsevier B.V.en_US
dc.subjectBiomarkeren_US
dc.subjectNuclear magnetic resonanceen_US
dc.subjectMetabolomicsen_US
dc.subjectO-phosphocholineen_US
dc.subjectPrediabetesen_US
dc.subject2024en_US
dc.titleIdentification of potential serum biomarkers associated with HbA1c levels in Indian type 2 diabetic subjects using NMR-based metabolomicsen_US
dc.typeArticleen_US
dc.contributor.departmentChhabra, Mohiten_US
dc.contributor.departmentSHANTHAMURTHY, CHETHAN D.en_US
dc.contributor.departmentKUMAR, NANJUDASWAMY VIJENDRAen_US
dc.contributor.departmentMARDHEKAR, SANDHYAen_US
dc.contributor.departmentVISHWESHWARA, SHARATH S.en_US
dc.contributor.departmentKIKKERI, RAGHAVENDRA et al.en_US
dc.identifier.sourcetitleClinica Chimica Actaen_US
dc.publication.originofpublisherForeignen_US
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