Integrated multiomic scores for cardiovascular disease prediction across multiancestral populations
- 1Cardiology Department, University Hospital Basel
Abstract
Background: Genomic, epigenomic, and proteomic data capture complementary aspects of cardiovascular disease biology, but the value of integrating these data for predicting multiple cardiovascular disease outcomes across ancestry groups remains uncertain. Methods: We derived disease-specific proteomic scores using 999 plasma proteins in 50,673 UK Biobank participants and validated them in 9,358 participants from the Prospective Urban and Rural Epidemiological (PURE) study. In PURE, we integrated these proteomic scores with 2,279 polygenic scores and 479 DNA methylation scores to develop 4 multiomic scores (MEGASCOREs) for myocardial infarction (MI), atrial fibrillation (AF), heart failure (HF), and cardiovascular mortality. Associations with incident cardiovascular disease, discrimination, calibration, and performance across ancestry groups were evaluated in PURE and 2 additional cohorts. Results: In pooled analyses, each standard deviation increase in the corresponding MEGASCORE was associated with MI (hazard ratio [HR], 2.13; 95% CI, 1.86-2.43), AF (HR, 1.94; 95% CI, 1.68-2.24), HF (HR, 3.33; 95% CI, 2.75-4.05), and cardiovascular mortality (HR, 3.28; 95% CI, 2.33-4.61). MEGASCOREs improved discrimination compared with clinical models, with strongest improvements for HF and cardiovascular mortality. MEGASCORE-CV-Death had a higher area under the receiver operating characteristic curve (AUC) than SCORE2 for cardiovascular mortality (0.83 [95% CI, 0.82-0.85] vs. 0.78 [95% CI, 0.77-0.80]). Its discrimination was also higher than that of SCORE2 across all 4 ancestry groups, with better calibration across non-European ancestry groups. MEGASCOREs remained associated with cardiovascular outcomes among participants without conventional cardiovascular risk factors. Conclusions: Integrated multiomic MEGASCOREs were associated with multiple cardiovascular outcomes and provided prognostic information beyond conventional clinical variables in PURE.
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BibTeX
@misc{meyre2026integrated,
title = {{Integrated multiomic scores for cardiovascular disease prediction across multiancestral populations}},
author = {P. B. Meyre and M. Chong and M. Pigeyre and S. Mao and M. Kamal and S. I. Bangdiwala and R. Kelishadi and A. Rosengren and F. Lanas and A. Yusufali and R. Yusuf and J. Chifamba and P. Lopez-Jaramillo and M. E. M. Abat and A. A. Junior and K. Yeates and M. L. Diaz and H. Mir and B. D. Keavney and S. S. Anand and K. Teo and S. Rangarajan and P. Joseph and H. C. Gerstein and S. Yusuf and G. Pare},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.23.26366372},
url = {https://www.medrxiv.org/content/10.64898/2026.10.23.26366372v1},
note = {CC BY-NC},
}
RIS
TY - UNPB
TI - Integrated multiomic scores for cardiovascular disease prediction across multiancestral populations
AU - P. B. Meyre
AU - M. Chong
AU - M. Pigeyre
AU - S. Mao
AU - M. Kamal
AU - S. I. Bangdiwala
AU - R. Kelishadi
AU - A. Rosengren
AU - F. Lanas
AU - A. Yusufali
AU - R. Yusuf
AU - J. Chifamba
AU - P. Lopez-Jaramillo
AU - M. E. M. Abat
AU - A. A. Junior
AU - K. Yeates
AU - M. L. Diaz
AU - H. Mir
AU - B. D. Keavney
AU - S. S. Anand
AU - K. Teo
AU - S. Rangarajan
AU - P. Joseph
AU - H. C. Gerstein
AU - S. Yusuf
AU - G. Pare
PY - 2026
DA - 2026/10/23
PB - medRxiv
DO - 10.64898/2026.10.23.26366372
UR - https://www.medrxiv.org/content/10.64898/2026.10.23.26366372v1
AB - Background: Genomic, epigenomic, and proteomic data capture complementary aspects of cardiovascular disease biology, but the value of integrating these data for predicting multiple cardiovascular disease outcomes across ancestry groups remains uncertain. Methods: We derived disease-specific proteomic scores using 999 plasma proteins in 50,673 UK Biobank participants and validated them in 9,358 participants from the Prospective Urban and Rural Epidemiological (PURE) study. In PURE, we integrated these proteomic scores with 2,279 polygenic scores and 479 DNA methylation scores to develop 4 multiomic scores (MEGASCOREs) for myocardial infarction (MI), atrial fibrillation (AF), heart failure (HF), and cardiovascular mortality. Associations with incident cardiovascular disease, discrimination, calibration, and performance across ancestry groups were evaluated in PURE and 2 additional cohorts. Results: In pooled analyses, each standard deviation increase in the corresponding MEGASCORE was associated with MI (hazard ratio [HR], 2.13; 95% CI, 1.86-2.43), AF (HR, 1.94; 95% CI, 1.68-2.24), HF (HR, 3.33; 95% CI, 2.75-4.05), and cardiovascular mortality (HR, 3.28; 95% CI, 2.33-4.61). MEGASCOREs improved discrimination compared with clinical models, with strongest improvements for HF and cardiovascular mortality. MEGASCORE-CV-Death had a higher area under the receiver operating characteristic curve (AUC) than SCORE2 for cardiovascular mortality (0.83 [95% CI, 0.82-0.85] vs. 0.78 [95% CI, 0.77-0.80]). Its discrimination was also higher than that of SCORE2 across all 4 ancestry groups, with better calibration across non-European ancestry groups. MEGASCOREs remained associated with cardiovascular outcomes among participants without conventional cardiovascular risk factors. Conclusions: Integrated multiomic MEGASCOREs were associated with multiple cardiovascular outcomes and provided prognostic information beyond conventional clinical variables in PURE.
ER -