Proteome atlas for mechanistic discovery and risk prediction of diabetic retinopathy

  • Shaopeng Yang
  • , Zhuoyao Xin
  • , Ruilin Xiong
  • , Ziyu Zhu
  • , Huangdong Li
  • , Yanping Chen
  • , Zhenghao Zhong
  • , Lanqi Du
  • , Lisa Zhuoting Zhu
  • , Xianwen Shang
  • , Wenyong Huang
  • , Lei Zhang
  • , Shida Chen
  • , Chang He
  • , Shaoying Tan
  • , Mingguang He
  • , Nathan Congdon
  • , Jost B Jonas
  • , Yih-Chung Tham
  • , Ching-Yu Cheng
  • Wei Wang

Research output: Contribution to journalArticlepeer-review

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Abstract

Proteomics offers an unprecedented opportunity to characterize and predict diabetic retinopathy (DR) with minimal invasiveness. Here we examine this in 10,873 individuals with (pre)diabetes from two ethnically distinct cohorts. By simultaneous profiling of ~3000 proteins, we identify 668 associations with mechanistically plausible directionality that constitute a comprehensive DR proteomic landscape with linkages to retinal tomographic structure and genetic predisposition, pointing to established and novel biological pathways conferring DR risk. Integrating DR proteomic profile markedly improves predictive performance beyond clinical and genetic predictors, with plexin B2, growth differentiation factor 15, and renin emerging as top proteins validated across cohorts and linked to retinal microvascular degeneration in Guangzhou Diabetic Eye Study (GDES) based on SS-OCTA. A parsimonious panel of these three proteins alone achieves comparable performance in predicting DR development and progression, while renin is confirmed as a causal promoter through genetic analyses. Our findings highlight the potential of large-scale proteomics in elucidating DR pathogenesis and advancing biomarker discovery, with broad implications for early detection and intervention.
Original languageEnglish
Article number9636
Number of pages21
JournalNature Communications
Volume16
DOIs
Publication statusPublished - 31 Oct 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

Keywords

  • Humans
  • Adult
  • Proteome - metabolism - genetics
  • Male
  • Nerve Tissue Proteins - metabolism - genetics
  • Proteomics - methods
  • Risk Factors
  • Female
  • Aged
  • Genetic Predisposition to Disease
  • Cohort Studies
  • Renin - metabolism - genetics
  • Biomarkers - metabolism
  • Retina - metabolism - pathology - diagnostic imaging
  • Diabetic Retinopathy - metabolism - genetics - diagnosis
  • Middle Aged

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