A multi‐omics risk score enables early and personalized screening for type 2 diabetes: A population‐based cohort study
Main finding · Discrimination for incident T2D (C-index)Result — go to the resultNRI 0.328Authors' conclusion
The combined multi-omics model enables more precise, earlier type 2 diabetes risk stratification, supporting personalized screening strategies years before clinical onset.
Study context
- Population
- UK Biobank cohort; independent validation in the Liyang Cohort (N = 10,056)UK Biobank
- Exposure
- Multi-omics combined risk score vs clinical risk score
- Outcome
- Incident T2D prediction: C-index and NRI
Methodological detailsprediction model development, Ridge Cox regression, independent validation of protein markers in Liyang Cohort
- Prediction model development
- Ridge Cox regression
- Independent validation of protein markers in Liyang Cohort
Main finding
Discrimination for incident T2D (C-index)
Net reclassification improvement (NRI)
0.328
P < 0.001
By group
Proteomics (ProS)
0.80
C-index
ComS
0.84
C-index
CliS
0.76
C-index
As reported in the abstract
Observational data: associations, not effects.
Further findings
Net benefit
- ComS reclassified additional T2D cases per 1000 participants not receiving intervention, without increasing false positives
- 73
Risk stratification (Kaplan-Meier)
- Superior risk stratification of ComS
- Log-rank p < 0.0001
- Metabolomics (MetS) and ProS identified high-risk individuals missed by CliS
Screening initiation age
- Screening before age 40 warranted for top risk quintile of MetS, ProS or ComS
Plasma FGF23 in T2D cases, Liyang Cohort
- Plasma FGF23 significantly elevated in T2D cases
- P < 0.05
Original publication
A multi‐omics risk score enables early and personalized screening for type 2 diabetes: A population‐based cohort study. Diabet Med. Published 11 April 2026. doi:10.
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