Population-Based Sample Reveals Gene–Gender Interactions in Blood Pressure in White Americans
- 1 January 2007
- journal article
- research article
- Published by Wolters Kluwer Health in Hypertension
- Vol. 49 (1) , 96-106
- https://doi.org/10.1161/01.hyp.0000252029.35106.67
Abstract
The influence of genetic contributors, such as common single nucleotide polymorphisms, on blood pressure and essential hypertension may vary with the gender. We used the power of a large, community-based sample to probe whether gender interacts with genes in contributing to extremes of blood pressure in 611 male and 656 female age-matched white Americans within the top and bottom 5th percentiles of blood pressure among >53 000 people in a health maintenance program. This approach has >90% statistical power to detect genes contributing as little as 3% to trait (blood pressure) variation. We scored ≈60 000 genotypes in the subjects: 48 single nucleotide polymorphisms at 33 autosomal and 2 X-linked genes in adrenergic and renal pathways that regulate blood pressure. Six individual variants significantly affected blood pressure and demonstrated gene-by-gender interaction, yielding different effects of the single nucleotide polymorphism on blood pressure in males and females. In females, polymorphisms at β 1 -adrenergic receptor and α 2A -adrenergic receptor contributed to blood pressure, whereas in men, polymorphisms at β 2 -adrenergic receptor and angiotensinogen were associated. An α 2A -adrenergic receptor haplotype influenced blood pressure in women, whereas 2 angiotensinogen haplotypes were associated in men. We also detected gene-by-gene, gender-specific interactions (epistasis) in pathophysiological pathways. This study reveals gender-specific effects of single nucleotide polymorphisms, haplotypes, and gene-by-gene interactions that determine blood pressure in white Americans. Such genetic variants may define genetically and etiologically distinct subgroups of men and women with essential hypertension and may have implications for rational treatment selection.Keywords
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