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Meta-Analysis
. 2009 Jul 8;302(2):168-78.
doi: 10.1001/jama.2009.978-a.

Genetic variants associated with cardiac structure and function: a meta-analysis and replication of genome-wide association data

Affiliations
Meta-Analysis

Genetic variants associated with cardiac structure and function: a meta-analysis and replication of genome-wide association data

Ramachandran S Vasan et al. JAMA. .

Abstract

Context: Echocardiographic measures of left ventricular (LV) structure and function are heritable phenotypes of cardiovascular disease.

Objective: To identify common genetic variants associated with cardiac structure and function by conducting a meta-analysis of genome-wide association data in 5 population-based cohort studies (stage 1) with replication (stage 2) in 2 other community-based samples.

Design, setting, and participants: Within each of 5 community-based cohorts comprising the EchoGen consortium (stage 1; n = 12 612 individuals of European ancestry; 55% women, aged 26-95 years; examinations between 1978-2008), we estimated the association between approximately 2.5 million single-nucleotide polymorphisms (SNPs; imputed to the HapMap CEU panel) and echocardiographic traits. In stage 2, SNPs significantly associated with traits in stage 1 were tested for association in 2 other cohorts (n = 4094 people of European ancestry). Using a prespecified P value threshold of 5 x 10(-7) to indicate genome-wide significance, we performed an inverse variance-weighted fixed-effects meta-analysis of genome-wide association data from each cohort.

Main outcome measures: Echocardiographic traits: LV mass, internal dimensions, wall thickness, systolic dysfunction, aortic root, and left atrial size.

Results: In stage 1, 16 genetic loci were associated with 5 echocardiographic traits: 1 each with LV internal dimensions and systolic dysfunction, 3 each with LV mass and wall thickness, and 8 with aortic root size. In stage 2, 5 loci replicated (6q22 locus associated with LV diastolic dimensions, explaining <1% of trait variance; 5q23, 12p12, 12q14, and 17p13 associated with aortic root size, explaining 1%-3% of trait variance).

Conclusions: We identified 5 genetic loci harboring common variants that were associated with variation in LV diastolic dimensions and aortic root size, but such findings explained a very small proportion of variance. Further studies are required to replicate these findings, identify the causal variants at or near these loci, characterize their functional significance, and determine whether they are related to overt cardiovascular disease.

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Figures

Figure 1
Figure 1. Genome-wide Signal Intensity Plots
The plots show the single-nucleotide polymorphism–wise log P values (based on the fixed-effects meta-analysis) against their genomic position for left ventricular mass, internal dimensions, wall thickness, and systolic dysfunction and for the aortic root diameter and left atrial size. Within each chromosome, shown on the x-axis, the results are plotted from the p-terminal end. The horizontal dotted lines indicate the significance threshold of P=5×10−7.
Figure 2
Figure 2. Seven Single-Nucleotide Polymorphisms Associated With Select Echocardiographic Traits in Stage 1 and Replicated in Stage 2
Individual studies are plotted against the individual effect sizes (β coefficients for continuous traits). The size of the box is inversely proportional to the estimated variance of the effect-size estimator. Horizontal lines are the confidence intervals corresponding to the P value threshold of 5×10−7. The vertical line indicates the value is consistent with no association. If a single-nucleotide polymorphism was not available in a study, there is no data point for that study. The diamond represents the meta-analytic effect size.

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