Novel genetic markers improve measures of atrial fibrillation risk prediction
Open accessAbstract
AIMS: Atrial fibrillation (AF) is associated with adverse outcome. Whether recently discovered genetic risk markers improve AF risk prediction is unknown. METHODS AND RESULTS: We derived and validated a novel AF risk prediction model from 32 possible predictors in the Women's Health Study (WHS), a cohort of 20 822 women without cardiovascular disease (CVD) at baseline followed prospectively for incident AF (median: 14.5 years). We then created a genetic risk score (GRS) comprised of 12 risk alleles in nine loci and assessed model performance in the validation cohort with and without the GRS. The newly derived WHS AF risk algorithm included terms for age, weight, height, systolic blood pressure, alcohol use, and smoking (current and past). In the validation cohort, this model was well calibrated with good discrimination [C-index (95% CI) = 0.718 (0.684-0.753)] and improved all reclassification indices when compared with age alone. The addition of the genetic score to the WHS AF risk algorithm model improved the C-index [0.741 (0.709-0.774); P = 0.001], the category-less net reclassification [0.490 (0.301-0.670); P < 0.0001], and the integrated discrimination improvement [0.00526 (0.0033-0.0076); P < 0.0001]. However, there was no improvement in net reclassification into 10-year risk categories of <1, 1-5, and 5+% [0.041 (-0.044-0.12); P = 0.33]. CONCLUSION: Among women without CVD, a simple risk prediction model utilizing readily available risk markers identified women at higher risk for AF. The addition of genetic information resulted in modest improvements in predictive accuracy that did not translate into improved reclassification into discrete AF risk categories.
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In the Women's Genome Health Study, those in the top quintile of AF-GRS had a greater than two-fold increased risk for incident AF in a model adjusted for non-genetic factors.
“In the WGHS analysis, those in the top quintile of AF-GRS had a greater than two-fold increased risk for incident AF in a model that adjusted for non-genetic factors.”
From Twelve-single nucleotide polymorphism genetic risk score identifies individuals at increased risk for future atrial fibrillation and stroke (2014) · cites this paper as [35]
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- Authors
- Everett, B. M., Cook, N. R., Conen, D., Chasman, D. I., Ridker, P. M., & Albert, C. M.
- Affiliations
- Brigham and Women's Hospital (US)
- University Hospital of Basel (CH)
- Corresponding author
- Everett, Brendan M.
- ORCID
- Venue
- European Heart Journal
- Publisher
- Oxford University Press (OUP)
- Published
- 2013-02-26
- Volume
- 34
- Issue
- 29
- Pages
- 2243-2251
- ISSN
- 0195-668X (ISSN-L)
- 1522-9645
- PMC
- PMC3730133
- OpenAlex
- W2115751016
- Cited by
- 141
- References
- 31
- Citations by year
- 2026: 3 · 2025: 7 · 2024: 5 · 2023: 3 · 2022: 8 · 2021: 16 · 2020: 11 · 2019: 5 · 2018: 13 · 2017: 15 · 2016: 26 · 2015: 12 · 2014: 12 · 2013: 4
- FWCI
- 12.23
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- cc-by-nc
- Locations
- European Heart Journal (publishedVersion, cc-by-nc)
- Europe PMC (PubMed Central) (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- reroDoc Digital Library (submittedVersion)
- Digital Access to Scholarship at Harvard (DASH) (Harvard University) (submittedVersion, cc-by)
- HighWire Press Open Archive (submittedVersion)
- Funders
- Donald W. Reynolds Foundation (CA-047988)
- American Heart Association (0835304N)
- Amgen (HL-043851, HL-080467, CA-047988)
- Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (133681)
- National Institutes of Health (5r01hl043851-10)
- National Heart, Lung, and Blood Institute (R01HL080467, HL043851, HL-093613, HL099355, R01HL116690, R21HL093613, RC1HL099355, HL080467)
- National Cancer Institute (HL-080467, HL-099355, HL-043851, CA 047988, R01CA047988)
- Topics
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Atrial Fibrillation Management and Outcomes
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiac electrophysiology and arrhythmias
- Keywords
- atrial fibrillation, polygenic risk score, risk prediction model, genetic risk markers, Women's Health Study, risk reclassification, integrated discrimination improvement
- MeSH terms
- Age Factors, Alcohol Drinking, Algorithms, Atrial Fibrillation, Body Height, Body Weight, Female, Genetic Markers, Humans, Middle Aged, Prospective Studies, Risk Factors, Smoking, Risk Assessment, Polymorphism, Single Nucleotide
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