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<p>Diabetes mellitus is a complex, multifactorial metabolic disorder characterized by chronic hyperglycemia and progressive organ dysfunction. Conventional diagnostic and prognostic markers such as fasting glucose and glycated hemoglobin provide limited insight into disease heterogeneity, early molecular changes, and individualized risk of complications. In recent years, RNA-based biomarkers have emerged as powerful tools for capturing dynamic regulatory processes underlying diabetes onset, progression, and therapeutic response. These biomarkers include messenger RNAs (mRNAs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and transfer RNA-derived fragments (tRFs), which collectively orchestrate gene expression, metabolic signaling, immune modulation, and cellular stress responses. This review comprehensively examines the landscape of RNA-based biomarkers in diabetes, highlighting their mechanistic relevance, detection platforms, clinical utility, and translational challenges. We discuss how regulatory RNA networks reflect beta-cell dysfunction, insulin resistance, inflammation, and tissue-specific pathology, and how their integration into liquid biopsy approaches and computational frameworks may redefine precision diagnostics and personalized diabetes care.</p>

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Emerging RNA biomarkers for diabetes: Mechanistic insights and clinical relevance

  • 期刊论文

  • 发表日期：

    2026年7月16日

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  • Venkatesan Karthick,
  • Muthineni Haneesh,
  • Sharan Kumar Karthikeyan,
  • Singamoorthy Amalraj,
  • Rajkumar Thamarai,
  • Abdul Abduz Zahir

摘要

Diabetes mellitus is a complex, multifactorial metabolic disorder characterized by chronic hyperglycemia and progressive organ dysfunction. Conventional diagnostic and prognostic markers such as fasting glucose and glycated hemoglobin provide limited insight into disease heterogeneity, early molecular changes, and individualized risk of complications. In recent years, RNA-based biomarkers have emerged as powerful tools for capturing dynamic regulatory processes underlying diabetes onset, progression, and therapeutic response. These biomarkers include messenger RNAs (mRNAs), microRNAs (miRNAs), long non-coding RNAs (lncRNAs), circular RNAs (circRNAs), and transfer RNA-derived fragments (tRFs), which collectively orchestrate gene expression, metabolic signaling, immune modulation, and cellular stress responses. This review comprehensively examines the landscape of RNA-based biomarkers in diabetes, highlighting their mechanistic relevance, detection platforms, clinical utility, and translational challenges. We discuss how regulatory RNA networks reflect beta-cell dysfunction, insulin resistance, inflammation, and tissue-specific pathology, and how their integration into liquid biopsy approaches and computational frameworks may redefine precision diagnostics and personalized diabetes care.