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DC Field | Value | Language |
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dc.contributor.author | YOUSF, SALEEM | en_US |
dc.contributor.author | Batra, Hitender S. | en_US |
dc.contributor.author | Jha, Rakesh M. | en_US |
dc.contributor.author | Sardesai, Devika M. | en_US |
dc.contributor.author | Ananthamohan, Kalyani | en_US |
dc.contributor.author | CHUGH, JEETENDER | en_US |
dc.contributor.author | Sharma, Shilpy | en_US |
dc.date.accessioned | 2025-04-15T06:54:18Z | - |
dc.date.available | 2025-04-15T06:54:18Z | - |
dc.date.issued | 2024-04 | en_US |
dc.identifier.citation | Clinica Chimica Acta, 557, 117857. | en_US |
dc.identifier.issn | 0009-8981 | en_US |
dc.identifier.issn | 1873-3492 | en_US |
dc.identifier.uri | https://doi.org/10.1016/j.cca.2024.117857 | en_US |
dc.identifier.uri | http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/9589 | - |
dc.description.abstract | Background: 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.iso | en | en_US |
dc.publisher | Elsevier B.V. | en_US |
dc.subject | Biomarker | en_US |
dc.subject | Nuclear magnetic resonance | en_US |
dc.subject | Metabolomics | en_US |
dc.subject | O-phosphocholine | en_US |
dc.subject | Prediabetes | en_US |
dc.subject | 2024 | en_US |
dc.title | Identification of potential serum biomarkers associated with HbA1c levels in Indian type 2 diabetic subjects using NMR-based metabolomics | en_US |
dc.type | Article | en_US |
dc.contributor.department | Chhabra, Mohit | en_US |
dc.contributor.department | SHANTHAMURTHY, CHETHAN D. | en_US |
dc.contributor.department | KUMAR, NANJUDASWAMY VIJENDRA | en_US |
dc.contributor.department | MARDHEKAR, SANDHYA | en_US |
dc.contributor.department | VISHWESHWARA, SHARATH S. | en_US |
dc.contributor.department | KIKKERI, RAGHAVENDRA et al. | en_US |
dc.identifier.sourcetitle | Clinica Chimica Acta | en_US |
dc.publication.originofpublisher | Foreign | en_US |
Appears in Collections: | JOURNAL ARTICLES |
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