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Journal of Hypertension:
doi: 10.1097/HJH.0000000000000209
ORIGINAL PAPERS: Genetic aspects

Cardiovascular consequences of a polygenetic component of blood pressure in an urban-based longitudinal study: the Malmö Diet and Cancer

Fava, Cristianoa,b,∗; Ohlsson, Theresea,∗; Sjögren, Marketaa; Tagetti, Angelab; Almgren, Petera; Engström, Gunnara; Nilsson, Petera; Hedblad, Boa; Minuz, Pietrob; Melander, Ollea

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Abstract

Background:

A recently published genome wide association study identified 29 single nucleotide polymorphisms (SNPs) influencing blood pressure (BP). Case–control studies suggest that a genetic risk score (GRS) based on these 29 SNPs affect the risk of cardiovascular disease (CVD), but its role for CVD at population level is unknown. Here, we prospectively evaluate the impact of this polygenetic BP component on CVD morbidity and mortality in a large urban-based middle-aged population.

Method:

The 29 previously BP associated SNPs were genotyped in the Swedish Malmö Diet and Cancer Study; (n = 27 003 with at least 24 valid SNPs). The number of BP elevating alleles of each SNPs, weighted by their effect size in the discovery studies, was summed into a BP-GRS.

Results:

Using regression models, we found significant associations of the BP-GRS, cross-sectionally, with BP and hypertension prevalence, prospectively, with incident cardiovascular morbidity and mortality during 14.2 ± 3.2 years of follow-up. After adjustment for traditional cardiovascular risk factors (TRF), including hypertension, the BP-GRS remained significantly associated only with CVDs [in terms of strokes and coronary artery disease; hazard ratio 1.15; 95% confidence interval (CI) 1.06–1.24 comparing the third vs. first tertile; P = 0.003]. Calibration, discrimination and reclassification analyses did not show a meaningful increment in prediction using the BP-GRS in addition to the model encompassing only the TRF.

Conclusion:

The polygenetic component of BP influences risk of cardiovascular morbidity and mortality. However, the effect size is small and unlikely to be useful for prediction at the population level.

© 2014 Wolters Kluwer Health | Lippincott Williams & Wilkins

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