Genomic prediction of coronary heart disease
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Abstract
AIMS: Genetics plays an important role in coronary heart disease (CHD) but the clinical utility of genomic risk scores (GRSs) relative to clinical risk scores, such as the Framingham Risk Score (FRS), is unclear. Our aim was to construct and externally validate a CHD GRS, in terms of lifetime CHD risk and relative to traditional clinical risk scores. METHODS AND RESULTS: We generated a GRS of 49 310 SNPs based on a CARDIoGRAMplusC4D Consortium meta-analysis of CHD, then independently tested it using five prospective population cohorts (three FINRISK cohorts, combined n = 12 676, 757 incident CHD events; two Framingham Heart Study cohorts (FHS), combined n = 3406, 587 incident CHD events). The GRS was associated with incident CHD (FINRISK HR = 1.74, 95% confidence interval (CI) 1.61-1.86 per S.D. of GRS; Framingham HR = 1.28, 95% CI 1.18-1.38), and was largely unchanged by adjustment for known risk factors, including family history. Integration of the GRS with the FRS or ACC/AHA13 scores improved the 10 years risk prediction (meta-analysis C-index: +1.5-1.6%, P < 0.001), particularly for individuals ≥60 years old (meta-analysis C-index: +4.6-5.1%, P < 0.001). Importantly, the GRS captured substantially different trajectories of absolute risk, with men in the top 20% of attaining 10% cumulative CHD risk 12-18 y earlier than those in the bottom 20%. High genomic risk was partially compensated for by low systolic blood pressure, low cholesterol level, and non-smoking. CONCLUSIONS: A GRS based on a large number of SNPs improves CHD risk prediction and encodes different trajectories of lifetime risk not captured by traditional clinical risk scores.
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GPSCAD performed substantially better than two previously published polygenic scores for CAD that included 50 and 49,310 variants.
“GPSCAD performed substantially better than two previously published polygenic scores for coronary artery disease that included 50 and 49,310 variants, respectively (Supplementary Table 7 and Supplementary Fig. 1).17,18”
From Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations (2018) · cites this paper as [18]
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“disease risk, and should they be included in the PRS? When a PRS is constructed based on 2 million of SNPs of which, say, 100 are able to change predicted risks before the decimal, will we tell a patient that their risk is calculated using 2 million or 100 SNPs? When researchers relax the SNP inclusion thresholds to i…”
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- Authors
- Abraham, G., Havulinna, A. S., Bhalala, O. G., Byars, S. G., De Livera, A. M., Yetukuri, L., Tikkanen, E., Perola, M., Schunkert, H., Sijbrands, E. J., Palotie, A., Samani, N. J., Salomaa, V., Ripatti, S., & Inouye, M.
- Affiliations
- The University of Melbourne (AU)
- Finnish Institute for Health and Welfare (FI)
- University of Helsinki (FI)
- German Centre for Cardiovascular Research (DE)
- Erasmus MC (NL)
- Broad Institute (US)
- University of Leicester (GB)
- Corresponding author
- Samani, Nilesh J.
- Salomaa, Veikko
- Ripatti, Samuli
- Inouye, Michael
- ORCID
- Venue
- European Heart Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2016-09-21
- Volume
- 37
- Issue
- 43
- Pages
- 3267-3278
- ISSN
- 0195-668X (ISSN-L)
- 1522-9645
- PMC
- PMC5146693
- OpenAlex
- W2521147375
- Cited by
- 338
- References
- 39
- Citations by year
- 2026: 11 · 2025: 18 · 2024: 31 · 2023: 31 · 2022: 34 · 2021: 49 · 2020: 44 · 2019: 50 · 2018: 35 · 2017: 25 · 2016: 10
- FWCI
- 5.44
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- European Heart Journal (publishedVersion)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- EUR Research Repository (Erasmus University Rotterdam) (publishedVersion)
- Minerva Access (University of Melbourne) (submittedVersion, cc-by)
- Apollo (University of Cambridge) (submittedVersion, cc-by)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- EUR Research Repository (Erasmus University Rotterdam) (submittedVersion)
- RMIT Research Repository (RMIT University Library) (submittedVersion, other-oa)
- Figshare (submittedVersion, cc-by)
- Työväentutkimus Vuosikirja (submittedVersion)
- Leicester Research Archive (University of Leicester) (submittedVersion, cc-by)
- mediaTUM – the media and publications repository of the Technical University Munich (Technical University Munich) (submittedVersion)
- HighWire Press Open Archive (submittedVersion)
- STM:n Hallinnonalan avoin julkaisuarkisto (Julkari) (submittedVersion)
- Apollo (cc-by)
- Funders
- American Heart Association
- Foundation for Cardiovascular Research
- Wellcome Trust (FP7/2007–2013, 085475, R01 HL087676, 076113)
- Broad Institute
- National Institute for Health and Care Research (FP7/2007–2013, NF-SI-0611-10170)
- British Heart Foundation
- European Commission (2007–2013, FP7 2007-2013, 261433, FP7/2007, 285380)
- National Heart Foundation of Australia (1061435)
- Academy of Finland (286500, 285380, 251217)
- NordForsk (62721)
- Sydäntutkimussäätiö (62721)
- National Institutes of Health (FP7/2007-2013)
- Medical Research Council (MR/N01104X/1)
- National Health and Medical Research Council (1061435, 1090462, 1062227)
- National Heart, Lung, and Blood Institute (R01HL087676)
- National Center for Research Resources
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Health and Risk Factors
- Keywords
- coronary artery disease, genomic risk score, genetic risk prediction, Framingham risk score, clinical risk score, lifetime cardiovascular risk, single nucleotide polymorphisms, external validation, systolic blood pressure, cholesterol, smoking, older adults
- MeSH terms
- Coronary Disease, Female, Heart Diseases, Humans, Male, Risk Factors, Risk Assessment, Polymorphism, Single Nucleotide, Genomics
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