Why the study?
To advance precision medicine in T2D by identifying proteomic signatures across glycemic stages and evaluating proteins associated with T2D risk and GLP-1 receptor agonist response.
Population
Median of 47,963 UK Biobank participants across normoglycemia, prediabetes, and T2D
Comparison
Protein associations across glycemic stages integrated with GLP1RA intervention trial data (STEP 1/2)
Design
Observational cohort study integrating trial data
Key result
A proteogenomic atlas of 47,963 participants identified 23,290 significant protein-trait associations, improving prediction of metabolic traits with combined R² up to 0.8.
Authors
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May aid T2D risk stratification; leaves open causal validation and therapeutic targeting of intransigent proteins.
Observational (n=47,963)
Effect estimate: combined R² up to 0.8
A proteogenomic atlas identified 'therapeutically intransigent' proteins associated with incident complications like CVD, suggesting targets for combined therapies to mitigate residual risk in T2D.
Patel et al. (2026) conducted an observational in Type 2 Diabetes (n=47,963). Proteomic signatures was evaluated on Protein-trait associations and prediction of metabolic traits (combined R² up to 0.8). A proteogenomic atlas of 47,963 participants identified 23,290 significant protein-trait associations, improving prediction of metabolic traits with combined R² up to 0.8.
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