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Review
. 2010 Feb;12(1):17-25.
doi: 10.1007/s11906-009-0086-6.

Genome-wide association studies: contribution of genomics to understanding blood pressure and essential hypertension

Georg B Ehret  1
Affiliations
Review

Genome-wide association studies: contribution of genomics to understanding blood pressure and essential hypertension

Georg B Ehret. Curr Hypertens Rep. 2010 Feb.

Abstract

Contemporary genomic tools now allow the fast and reliable genotyping of hundreds of thousands of variants and permit an unbiased interrogation of the common variability across the human genome. These technical advances have been the basis of numerous recent investigations of genes underlying complex genetic traits, and the results for blood pressure and hypertension have been of particular interest. The pathophysiology of the complex genetic trait blood pressure and hypertension is unclear. The heritability of essential hypertension is high and insights can be gained by finding associated genes. Current genome-wide association studies (GWAS) have identified 10 to 20 loci in or near genes that generally were not expected to be associated with blood pressure or essential hypertension; more significant variants will be discovered when even larger and more refined studies become available. This article gives a short introduction to GWAS and summarizes the current findings for blood pressure and hypertension.

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Conflict of interest statement

Disclosure No potential conflicts of interest relevant to this article were reported.

Figures

Fig. 1
Fig. 1
Spectrum of allele frequency and effect size in genetic disease
Fig. 2
Fig. 2
a Manhattan plot (−log10[P] genome-wide association plot) of a genome-wide association study on systolic blood pressure in 29,136 individuals in Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE). The genome-wide significance level is set at 5 × 10−8 and plotted as the dotted line. Any single nucleotide polymorphism (SNP) within a region of 5 Mb containing a SNP reaching the genome-wide significance threshold is colored in green. The most significant SNP in this experiment is colored in red (rs2681492 in the ATP2B1 gene). The P value is indicated for demonstration. b Quantile-quantile (QQ) plot of the data shown in the Manhattan plot. c QQ plot of simulated data showing an early separation of the observed from the expected, suggesting population stratification. (a and b adapted from Levy et al. [22••], with permission.)
See this image and copyright information in PMC

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