Key result
QTL-informed molecular profiles accurately predict eight incident comorbidities including rapid eGFR decline in youth-onset T2D.
Why the study?
Youth-onset type 2 diabetes has rapid progression and early cardiorenal complications, making identification of molecular drivers critical for early detection and precision care.
Cohort (n=355)
Integration of genomics, proteomics, and metabolomics can accurately predict long-term cardiorenal and metabolic complications in youth-onset type 2 diabetes.
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May enable earlier cardiorenal risk stratification in youth-onset T2D; leaves open prospective validation before clinical adoption.
Introduction and Objective: Youth-onset type 2 diabetes (YT2D) is marked by rapid progression and early cardiorenal complications. Identifying molecular drivers of YT2D is critical for early detection and precision care. We integrated genomics, proteomics and metabolomics to predict incident outcomes in the TODAY study. Methods: We integrated whole-exome sequencing with 6596 plasma proteins, 93 plasma metabolites, and 58 urine metabolites measured in 355 TODAY participants to identify quantitative trait loci (QTLs). Colocalization was performed between QTLs and GWAS (UK Biobank) for T2D-related traits to evaluate shared causal variants. Cox models identified QTLs associated with 19 incident comorbidities (follow-up 12.4 ± 1.2 yrs). We applied cross-validation to ridge regression, lasso and mboost using molecular data to predict comorbidities. Results: We identified 1,119 QTLs at 407 genomic loci. GWAS colocalization revealed 25 YT2D-related traits sharing causal variants with QTLs, highlighting biological pathways relevant to metabolic risk. Cox models linked 528 QTLs to 19 incident outcomes. Eight comorbidities were accurately predicted (C-index >0.7), including rapid eGFR decline and hyperfiltration (Fig. 1). Conclusion: QTL-informed molecular profiles reveal early signatures of metabolic risk and show strong potential for predicting long-term complications in YT2D, supporting their integration into risk stratification and prevention strategies. Disclosure M. D'Antonio: None. P. Bjornstad: Consultant; Current; Bayer AG, Boehringer Ingelheim International GmbH, Lilly, Novo Nordisk. Y. Choi: None. L. Pyle: None. V. Das: Employee; Current; Novo Nordisk A/S. M. Grams: Other - Received a grant from the NKF that was funded by Vertex; Ended; Vertex Pharmaceuticals Incorporated. M. Kelsey: Research Support; Current; Rhythm Pharmaceuticals, Inc. R. Nelson: None. S. Srinivasan: Research Support; Current; Abbott, Eli Lilly and Company. K. Sulek: Employee; Current; Novo Nordisk A/S. K. Kiryluk: None. J. Goodrich: None. D. Gordin: Advisory Panel; Ended; Bayer AG, Boehringer Ingelheim International GmbH. Advisory Panel; Current; AstraZeneca. Advisory Panel; Ended; Astellas Pharma Inc., GE Healthcare Systems. Speaker's Bureau; Ended; Fresenius Medical Care, Novo Nordisk, Ratiopharm. Advisory Panel; Ended; Harald AI. E.D. Nguyen: None. L.M. Laffel: Other - Travel support for scientific presentations; Ended; Boehringer Ingelheim International GmbH. Other - DSMB Chair; Ended; Janssen Pharmaceuticals, Inc. Consultant; Current; Dexcom, Inc. Advisory Panel; Current; Medtronic, Sequel, Tandem Diabetes Care, Inc. Consultant; Current; Roche Diabetes Care, Sinocare. Advisory Panel; Ended; Sanofi. Advisory Panel; Current; MannKind Corporation. J.M. Forbes: None. H. Hampson: None. S. Ramesh: None. J.D. Weissenkampen: None. P. Narongkiatikhun: None. K. Tommerdahl: Advisory Panel; Current; Sanofi.
D’Antonio et al. (2026) conducted a cohort in Youth-onset type 2 diabetes (YT2D) (n=355). QTL-informed molecular profiles was evaluated on 19 incident comorbidities (C-index >0.7). QTL-informed molecular profiles accurately predicted eight incident comorbidities, including rapid eGFR decline and hyperfiltration, in youth-onset type 2 diabetes (C-index >0.7).
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