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000307451 1001_ $$0P:(DE-He78)7089188e1b7bdb788ba48ba96f21df07$$aXie, Ruijie$$b0$$eFirst author$$udkfz
000307451 245__ $$aImproved sex-specific cardiovascular risk prediction with multi-omics data in people with type 2 diabetes.
000307451 260__ $$aLondon$$bBioMed Central$$c2025
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000307451 520__ $$aTo evaluate whether integrating proteomics, metabolomics, and a cardiovascular disease specific polygenic risk score (CVD-PRS) in the SCORE2-Diabetes model improves sex-specific 10-year prediction of major adverse cardiovascular events (MACE) in individuals with type 2 diabetes (T2D).Genome-wide association study (GWAS), plasma proteomics (with the Olink Explore 3072 platform), and metabolomics (with nuclear magnetic resonance spectroscopy by Nightingale Health) data were measured in the UK Biobank. A novel sex-specific protein algorithm was developed using bootstrap-LASSO (Least absolute shrinkage and selection operator) regression. The CVD-PRS and sex-specific metabolite algorithms were used from previous UK Biobank projects. In a subset of 990 participants with T2D, age 40-69 years, with no prior MACE, and complete multi-omics data, we evaluated, which omics data improved the SCORE2-Diabetes model performance using Harrell's C-index.Overall 9 proteins were selected for males and 7 for females and adding them to the SCORE2-Diabetes model significantly improved discrimination in the total population (C-index increase from 0.766 to 0.835 (P < 0.001)). Further adding of metabolites significantly improved model performance (C-index, 0.846, P = 0.035), which was mostly attributable to model improvement among males (∆C-index, 0.012, P = 0.078) but not among females (∆C-index, 0.004, P = 0.723). Further adding the CVD-PRS did not statistically significantly improve the SCORE2-Diabetes + proteomics + metabolomics model further in the total population (C-index, 0.848 (P = 0.070)).Sex-specific proteomic signatures markedly improved 10-year MACE risk prediction in individuals with T2D. In men but not in women, further integration of metabolomics may enhance model performance whereas adding the CVD-PRS is not needed. External validation is warranted.
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000307451 650_7 $$2Other$$aCardiovascular risk
000307451 650_7 $$2Other$$aMulti-omics
000307451 650_7 $$2Other$$aProteomics
000307451 650_7 $$2Other$$aSCORE2-diabetes
000307451 650_7 $$2Other$$aSex-specific
000307451 650_7 $$2Other$$aType 2 diabetes
000307451 7001_ $$aHerder, Christian$$b1
000307451 7001_ $$0P:(DE-He78)1d6f6305a65e2f7de2c7fbffbae83780$$aSha, Sha$$b2$$udkfz
000307451 7001_ $$0P:(DE-He78)90d5535ff896e70eed81f4a4f6f22ae2$$aBrenner, Hermann$$b3$$udkfz
000307451 7001_ $$0P:(DE-He78)7145565e57f6d4223f49daba4dd8cc96$$aCarlsson, Sigrid$$b4$$udkfz
000307451 7001_ $$0P:(DE-He78)c67a12496b8aac150c0eef888d808d46$$aSchöttker, Ben$$b5$$eLast author$$udkfz
000307451 773__ $$0PERI:(DE-600)2093769-6$$a10.1186/s12933-025-03036-5$$pnn$$tCardiovascular diabetology$$vnn$$x1475-2840$$y2025
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