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Metabolic fingerprinting on retinal pigment epithelium thickness for individualized risk stratification of type 2 diabetes mellitus

Author

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  • Shaopeng Yang

    (Sun Yat-sen University
    Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science
    Guangdong Provincial Clinical Research Center for Ocular Diseases
    Sun Yat-sen University)

  • Zhuoting Zhu

    (Royal Victorian Eye and Ear Hospital)

  • Shida Chen

    (Sun Yat-sen University
    Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science
    Guangdong Provincial Clinical Research Center for Ocular Diseases
    Sun Yat-sen University)

  • Yixiong Yuan

    (Sun Yat-sen University
    Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science
    Guangdong Provincial Clinical Research Center for Ocular Diseases
    Sun Yat-sen University)

  • Mingguang He

    (Sun Yat-sen University
    The Hong Kong Polytechnic University)

  • Wei Wang

    (Sun Yat-sen University
    Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science
    Guangdong Provincial Clinical Research Center for Ocular Diseases
    Sun Yat-sen University)

Abstract

The retina is an important target organ of diabetes mellitus, with increasing evidence from patients and animal models suggesting that retinal pigment epithelium (RPE) may serve as an early marker for diabetes-related damages. However, their longitudinal relationship and the biological underpinnings remain less well understood. Here, we demonstrate that reduced in vivo measurements of RPE thickness (RPET) represents a significant risk factor for future type 2 diabetes mellitus (T2DM) and its microvascular phenotypes. After performing systematic analyses of circulating plasma metabolites using two complementary approaches, we identify a wide range of RPET metabolic fingerprints that are independently associated with reduced RPET. These fingerprints hold their potential to improve predictability and clinical utility for stratifying future T2DM and related microvascular phenotypes beyond traditional clinical indicators, providing insights into the promising role of retinas as a window to systemic health.

Suggested Citation

  • Shaopeng Yang & Zhuoting Zhu & Shida Chen & Yixiong Yuan & Mingguang He & Wei Wang, 2023. "Metabolic fingerprinting on retinal pigment epithelium thickness for individualized risk stratification of type 2 diabetes mellitus," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-42404-1
    DOI: 10.1038/s41467-023-42404-1
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    References listed on IDEAS

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