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Published on: May 2, 2025
Molecular Signature of Prediabetes With High-Risk of Diabetes Revealed by Deep Plasma Proteome
Yuanyuan Yin1,2,3, Xiaojing Gao1,2, Qingrun Li1
1Joint Lab of Shanghai Clinical Research and Trial Center Affiliated to ShanghaiTech University & National Facility for Protein Science in Shanghai Affiliated to Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai, China.
Aims:
Prediabetes is biologically heterogeneous, but molecular subtypes linked to diabetes progression remain poorly defined. We aimed to identify plasma proteome-based subtypes of impaired fasting glucose (IFG), characterise their molecular features and assess their association with future diabetes risk.
Materials And Methods:
We quantified 2584 plasma proteins using liquid chromatography-mass spectrometry in 538 IFG participants from a prospective discovery cohort (Nutrition and Health of Aging Population in China, NHAPC). Proteomic subtypes were defined by consensus clustering, linked to longitudinal changes in insulin sensitivity and incident type 2 diabetes mellitus (T2DM), which were further validated in an independent Shanghai Brain Aging Study (SBAS) cohort.
Results:
Two reproducible IFG molecular subtypes based on plasma proteomics were identified. The high-risk subtype showed higher incident diabetes and a greater 6-year decline in insulin sensitivity and was characterised by enrichment of glycolysis/gluconeogenesis, insulin signalling and neutrophil degranulation, together with a dyslipidemic lipidomic profile indicating co-dysregulation of glucose and lipid homeostasis. The low-risk subtype demonstrated a higher complement cascade and high-density lipoprotein particle remodelling signature. In the high-risk subtype, key proteins and lipids showed stronger associations with longitudinal declines in insulin sensitivity, including PPBP, PGK1 and ALDOA, as well as PE-P 18:0/20:3 and PE-P 18:1/20:3.
Conclusions:
Proteome-based molecular subtyping stratifies IFG individuals with similar fasting glucose levels but distinct biology and future diabetes risk, supporting earlier and more targeted prevention.
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