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Publications

Journal Article Review Epublish

PubMed: 40162315 DOI: 10.3389/fendo.2025.1520436

Multi-omics approaches for biomarker discovery and precision diagnosis of prediabetes.

Front Endocrinol (Lausanne) 16:1520436

Authors: Jielin Song, Chuanfu Wang, Tong Zhao, Yu Zhang, Jixiang Xing, Xuelian Zhao, Yunsha Zhang, Zhaohui Zhang

Affiliations

  • Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, China. TCM Institute of Sore and Ulcer, Tianjin University of Traditional Chinese Medicine, Tianjin, China. Tianjin Institute of Traditional Chinese Medicine Surgery, Tianjin, China.
  • Department of Encephalopathy, Liangping District Hospital of Traditional Chinese Medicine, Chongqing, China.
  • Graduate School, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
  • TCM Institute of Sore and Ulcer, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
  • Tianjin Institute of Traditional Chinese Medicine Surgery, Tianjin, China.
  • TCM Institute of Sore and Ulcer, Tianjin University of Traditional Chinese Medicine, Tianjin, China. Tianjin Institute of Traditional Chinese Medicine Surgery, Tianjin, China. School of Integrative Medicine, Tianjin University of Traditional Chinese Medicine, Tianjin, China.
  • TCM Institute of Sore and Ulcer, Tianjin University of Traditional Chinese Medicine, Tianjin, China. Tianjin Institute of Traditional Chinese Medicine Surgery, Tianjin, China. Department of Traditional Chinese Medicine Surgery, The Second Affiliated Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.

Abstract

Recent advancements in multi-omics technologies have provided unprecedented opportunities to identify biomarkers associated with prediabetes, offering novel insights into its diagnosis and management. This review synthesizes the latest findings on prediabetes from multiple omics domains, including genomics, epigenomics, transcriptomics, proteomics, metabolomics, microbiomics, and radiomics. We explore how these technologies elucidate the molecular and cellular mechanisms underlying prediabetes and analyze potential biomarkers with predictive value in disease progression. Integrating multi-omics data helps address the limitations of traditional diagnostic methods, enabling early detection, personalized interventions, and improved patient outcomes. However, challenges such as data integration, standardization, and clinical validation and translation remain to be resolved. Future research leveraging artificial intelligence and machine learning is expected to further enhance the predictive power of multi-omics technologies, contributing to the precision diagnosis and tailored management of prediabetes.

MeSH

Genomics, Multiple Chronic Conditions, Biomarkers, Prediabetic State, Diagnosis