| Autor: |
Paranjpe I; The Charles Bronfman Institute for Personalized MedicineIcahn School of Medicine at Mount Sinai New York NY.; Mount Sinai Clinical Intelligence Center (MSCIC)Icahn School of Medicine at Mount Sinai New York NY.; The Hasso Plattner Institute for Digital Health at Mount SinaiIcahn School of Medicine at Mount Sinai New York NY., Tsao NL; Department of Surgery Perelman School of Medicine University of Pennsylvania Philadelphia PA., De Freitas JK; Mount Sinai Clinical Intelligence Center (MSCIC)Icahn School of Medicine at Mount Sinai New York NY.; The Hasso Plattner Institute for Digital Health at Mount SinaiIcahn School of Medicine at Mount Sinai New York NY.; Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY., Judy R; Department of Surgery Perelman School of Medicine University of Pennsylvania Philadelphia PA., Chaudhary K; The Charles Bronfman Institute for Personalized MedicineIcahn School of Medicine at Mount Sinai New York NY.; Mount Sinai Clinical Intelligence Center (MSCIC)Icahn School of Medicine at Mount Sinai New York NY.; Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY., Forrest IS; The Charles Bronfman Institute for Personalized MedicineIcahn School of Medicine at Mount Sinai New York NY.; Mount Sinai Clinical Intelligence Center (MSCIC)Icahn School of Medicine at Mount Sinai New York NY.; Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY., Jaladanki SK; The Charles Bronfman Institute for Personalized MedicineIcahn School of Medicine at Mount Sinai New York NY.; Mount Sinai Clinical Intelligence Center (MSCIC)Icahn School of Medicine at Mount Sinai New York NY.; The Hasso Plattner Institute for Digital Health at Mount SinaiIcahn School of Medicine at Mount Sinai New York NY., Paranjpe M; Division of Health Science and Technology Harvard Medical School Boston MA., Sharma P; Drexel University College of Medicine Philadelphia PA., Glicksberg BS; Mount Sinai Clinical Intelligence Center (MSCIC)Icahn School of Medicine at Mount Sinai New York NY.; The Hasso Plattner Institute for Digital Health at Mount SinaiIcahn School of Medicine at Mount Sinai New York NY.; Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY., Narula J; Zena and Michael A. Wiener Cardiovascular InstituteIcahn School of Medicine at Mount Sinai New York NY., Do R; The Charles Bronfman Institute for Personalized MedicineIcahn School of Medicine at Mount Sinai New York NY.; Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York NY., Damrauer SM; Department of Surgery Perelman School of Medicine University of Pennsylvania Philadelphia PA., Nadkarni GN; The Charles Bronfman Institute for Personalized MedicineIcahn School of Medicine at Mount Sinai New York NY.; Mount Sinai Clinical Intelligence Center (MSCIC)Icahn School of Medicine at Mount Sinai New York NY.; The Hasso Plattner Institute for Digital Health at Mount SinaiIcahn School of Medicine at Mount Sinai New York NY.; Division of Nephrology Department of Medicine Icahn School of Medicine at Mount Sinai New York NY.; Renal ProgramJames J. Peters VA Medical Center at Bronx New York NY. |
| Jazyk: |
angličtina |
| Zdroj: |
Journal of the American Heart Association [J Am Heart Assoc] 2021 Nov 16; Vol. 10 (22), pp. e021916. Date of Electronic Publication: 2021 Oct 29. |
| DOI: |
10.1161/JAHA.121.021916 |
| Abstrakt: |
Background Despite advances in cardiovascular disease and risk factor management, mortality from ischemic heart failure (HF) in patients with coronary artery disease (CAD) remains high. Given the partial role of genetics in HF and lack of reliable risk stratification tools, we developed and validated a polygenic risk score for HF in patients with CAD, which we term HF-PRS. Methods and Results Using summary statistics from a recent genome-wide association study for HF, we developed candidate PRSs in the Mount Sinai Bio Me CAD patient cohort (N=6274) by using the pruning and thresholding method and LDPred. We validated the best score in the Penn Medicine BioBank (N=7250) and performed a subgroup analysis in a high-risk cohort who had undergone coronary catheterization. We observed a significant association between HF-PRS score and ischemic HF even after adjusting for evidence of obstructive CAD in patients of European ancestry in both Bio Me (odds ratio [OR], 1.14 per SD; 95% CI, 1.05-1.24; P =0.003) and Penn Medicine BioBank (OR, 1.07 per SD; 95% CI, 1.01-1.13; P =0.016). In European patients with CAD in Penn Medicine BioBank who had undergone coronary catheterization, individuals in the top 10th percentile of PRS had a 2-fold increased odds of ischemic HF (OR, 2.0; 95% CI, 1.1-3.7; P =0.02) compared with the bottom 10th percentile. Conclusions A PRS for HF enables risk stratification in patients with CAD. Future prospective studies aimed at demonstrating clinical utility are warranted for adoption in the patient setting. |
| Databáze: |
MEDLINE |
| Externí odkaz: |
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