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MERGING BIOMARKERS FOR EARLY DETECTION OF TYPE 2 DIABETES

  • Unique Paper ID: 170756
  • Volume: 11
  • Issue: 7
  • PageNo: 149-153
  • Abstract:
  • Type 2 diabetes mellitus (T2DM) is a prevalent metabolic disorder with a rising global burden, necessitating timely and effective detection strategies. Biomarkers have emerged as powerful tools for early diagnosis, aiding in identifying high-risk individuals and improving disease management. This review explores the integration of diverse biomarkers, including genetic, proteomic, metabolic, and inflammatory indicators, to enhance early T2DM detection. Emphasis is placed on their mechanistic roles, diagnostic accuracy, and predictive capabilities. Advanced analytical approaches, such as multi-omics platforms and machine learning, are discussed as critical enablers for merging biomarkers into comprehensive diagnostic models. The integration of these biomarkers offers a promising pathway toward personalized medicine, enabling proactive interventions and reducing the progression of diabetes-related complications. Future research priorities include large-scale validation studies, standardization of biomarker assays, and bridging gaps in clinical translation to achieve a reliable, early diagnostic framework for T2DM.
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Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 7
  • PageNo: 149-153

MERGING BIOMARKERS FOR EARLY DETECTION OF TYPE 2 DIABETES

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