Genetic polymorphisms for estimating risk of atrial fibrillation: a literature-based meta-analysis
Version of Record online: 27 JUL 2012
© 2012 The Association for the Publication of the Journal of Internal Medicine
Journal of Internal Medicine
Volume 272, Issue 6, pages 573–582, December 2012
How to Cite
Smith, J. G., Almgren, P., Engström, G., Hedblad, B., Platonov, P. G., Newton-Cheh, C. and Melander, O. (2012), Genetic polymorphisms for estimating risk of atrial fibrillation: a literature-based meta-analysis. Journal of Internal Medicine, 272: 573–582. doi: 10.1111/j.1365-2796.2012.02563.x
- Issue online: 20 NOV 2012
- Version of Record online: 27 JUL 2012
- Accepted manuscript online: 12 JUN 2012 02:16PM EST
- atrial fibrillation;
- genome-wide association studies;
- single-nucleotide polymorphisms
Smith JG, Almgren P, Engström G, Hedblad B, Platonov PG, Newton-Cheh C, Melander O (Department of Cardiology, Lund University, Lund, Sweden; Department of Clinical Sciences, Lund University, Malmö, Sweden; Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA, USA; and Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA). Genetic polymorphisms for estimating risk of atrial fibrillation: a literature-based meta-analysis. J Intern Med 2012; doi: 10.1111/j.1365-2796.2012.02563.x
Background. Genetic polymorphisms associated with common aetiologically complex diseases have recently been identified through genome-wide association studies. Direct-to-consumer genetic testing for such polymorphisms, with provision of absolute genetic risk estimates, is marketed by several commercial companies. Polymorphisms associated with atrial fibrillation (AF) have shown relatively large risk estimates, but the robustness of such estimates across populations and study designs has not been investigated.
Design. A systematic literature review with meta-analysis and assessment of between-study heterogeneity was carried out for single-nucleotide polymorphisms (SNPs) in the six genetic regions associated with AF in genome-wide or candidate gene studies.
Results. Data were identified from 18 samples of European ancestry (n = 12 100 cases, 115,702 controls) for the single-nucleotide polymorphisms (SNP) on chromosome 4q25 (rs220733), from 16 samples (n = 12 694 cases, 132 602 controls) for the SNP on 16q22 (rs2106261) and from four samples (n = 5272 cases, 59 725 controls) for the SNP in KCNH2 (rs1805123). Only the publications in which the associations were initially reported were identified for SNPs on 1q21 and in GJA5 and IL6R, why meta-analyses were not performed for those SNPs. In overall random-effects meta-analyses, association with AF was observed for both SNPs on chromosomes 4q25 [odds ratio (OR), 1.67; 95% CI, 1.50–1.86, P = 2 × 10−21] and 16q22 (OR, 1.21; 95% CI, 1.13–1.29, P = 1 × 10−8) from genome-wide studies, but not the SNP in KCNH2 from candidate gene studies (P = 0.15). There was substantial effect heterogeneity across case–control and cross-sectional studies for both polymorphisms (I2 = 0.50–0.78, P < 0.05), but not across prospective cohort studies (I2 = 0.39, P = 0.15). Both polymorphisms were robustly associated with AF for each study design individually (P < 0.05).
Conclusions. In meta-analyses including up to 150 000 individuals, polymorphisms in two genetic regions were robustly associated with AF across all study designs but with substantial context-dependency of risk estimates.