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. 2017 Apr 4;135(14):1311-1320.
doi: 10.1161/CIRCULATIONAHA.116.024143. Epub 2016 Oct 28.

Genetic Risk Prediction of Atrial Fibrillation

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Free PMC article

Genetic Risk Prediction of Atrial Fibrillation

Steven A Lubitz et al. Circulation. .
Free PMC article

Abstract

Background: Atrial fibrillation (AF) has a substantial genetic basis. Identification of individuals at greatest AF risk could minimize the incidence of cardioembolic stroke.

Methods: To determine whether genetic data can stratify risk for development of AF, we examined associations between AF genetic risk scores and incident AF in 5 prospective studies comprising 18 919 individuals of European ancestry. We examined associations between AF genetic risk scores and ischemic stroke in a separate study of 509 ischemic stroke cases (202 cardioembolic [40%]) and 3028 referents. Scores were based on 11 to 719 common variants (≥5%) associated with AF at P values ranging from <1×10-3 to <1×10-8 in a prior independent genetic association study.

Results: Incident AF occurred in 1032 individuals (5.5%). AF genetic risk scores were associated with new-onset AF after adjustment for clinical risk factors. The pooled hazard ratio for incident AF for the highest versus lowest quartile of genetic risk scores ranged from 1.28 (719 variants; 95% confidence interval, 1.13-1.46; P=1.5×10-4) to 1.67 (25 variants; 95% confidence interval, 1.47-1.90; P=9.3×10-15). Discrimination of combined clinical and genetic risk scores varied across studies and scores (maximum C statistic, 0.629-0.811; maximum ΔC statistic from clinical score alone, 0.009-0.017). AF genetic risk was associated with stroke in age- and sex-adjusted models. For example, individuals in the highest versus lowest quartile of a 127-variant score had a 2.49-fold increased odds of cardioembolic stroke (95% confidence interval, 1.39-4.58; P=2.7×10-3). The effect persisted after the exclusion of individuals (n=70) with known AF (odds ratio, 2.25; 95% confidence interval, 1.20-4.40; P=0.01).

Conclusions: Comprehensive AF genetic risk scores were associated with incident AF beyond associations for clinical AF risk factors but offered small improvements in discrimination. AF genetic risk was also associated with cardioembolic stroke in age- and sex-adjusted analyses. Efforts are warranted to determine whether AF genetic risk may improve identification of subclinical AF or help distinguish between stroke mechanisms.

Keywords: atrial fibrillation; atrial flutter; forecasting; genetic association studies; stroke.

Figures

Figure 1
Figure 1
Pooled 5-year relative hazard of incident atrial fibrillation among individuals in the highest quartile of AF genetic risk relative to those in the lowest quartile. SNPs included in scores were derived using different thresholds of association between each SNP and atrial fibrillation in an earlier, independent study.
Figure 2
Figure 2
Risk of cardioembolic stroke in MGH-GASROS according to atrial fibrillation genetic risk. Odds ratios for cardioembolic stroke in relation to atrial fibrillation genetic risk scores among cardioembolic stroke cases and 3,028 controls. Blue histograms show distributions of genetic risk scores among cases and controls. Black dots indicate odds ratios for stroke for each quartile of genetic risk scores (bars indicate 95% confidence intervals). For panels A–C, genetic risk scores were based on 45 (A), 127 (B), and 701 (C) SNPs among 202 cardioembolic stroke cases (including 70 with known AF) and controls. For panels D-F, genetic risk scores were based 45 (D), 127 (E), and 701 (F) SNPs among 152 cardioembolic stroke cases (none with known AF) and controls. SNP totals may not equal those used in the incident atrial fibrillation analysis since some SNPs were unavailable in MGH-GASROS, in which case proxies were used when available (Supplemental Table 1).

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