Genome-wide profiling of blood pressure in adults and children

Abstract

Hypertension is an important determinant of cardiovascular morbidity and mortality and has a substantial heritability, which is likely of polygenic origin. The aim of this study was to assess to what extent multiple common genetic variants contribute to blood pressure regulation in both adults and children and to assess overlap in variants between different age groups, using genome-wide profiling. Single nucleotide polymorphism sets were defined based on a meta-analysis of genome-wide association studies on systolic blood pressure and diastolic blood pressure performed by the Cohort for Heart and Aging Research in Genome Epidemiology (n=29 136), using different P value thresholds for selecting single nucleotide polymorphisms. Subsequently, genetic risk scores for systolic blood pressure and diastolic blood pressure were calculated in an independent adult population (n=2072) and a child population (n=1034). The explained variance of the genetic risk scores was evaluated using linear regression models, including sex, age, and body mass index. Genetic risk scores, including also many nongenome-wide significant single nucleotide polymorphisms, explained more of the variance than scores based only on very significant single nucleotide polymorphisms in adults and children. Genetic risk scores significantly explained ≤1.2% (P=9.6*10(-8)) of the variance in adult systolic blood pressure and 0.8% (P=0.004) in children. For diastolic blood pressure, the variance explained was similar in adults and children (1.7% [P=8.9*10(-10)] and 1.4% [P=3.3*10(-5)], respectively). These findings suggest the presence of many genetic loci with small effects on blood pressure regulation both in adults and children, indicating also a (partly) common polygenic regulation of blood pressure throughout different periods of life.

Figure 1. Increase in explained variance in systolic blood pressure by genetic risk scores

Bars represent the increase in explained variance (%) of systolic blood pressure, when adding the genetic risk scores for different p-value thresholds, to the base line model for systolic blood pressure including BMI, sex and age as covariates. The baseline model explained 12.8% and 5.2 % of the variance in systolic blood pressure for adults and children respectively. We evaluated the difference in explained variance between two subsequent models by calculating the Akaike Information Criterion (AIC) of each model. The difference in AIC follows a χ² distribution with one degree of freedom, from which the P-value was derived. * p < 0.05 ** p < 0.001 1a. Rotterdam Study III 1b. Generation R Study

Figure 2. Increase in explained variance in diastolic blood pressure by genetic risk scores

Bars represent the increase in explained variance (%) of diastolic blood pressure, when adding the genetic risk scores for different p-value thresholds, to the base line model for diastolic blood pressure including BMI, sex and age as covariates. The baseline model explained 8.4% and 1.4 % of the variance in diastolic blood pressure for adults and children respectively. We evaluated the difference in explained variance between two subsequent models by calculating the Akaike Information Criterion (AIC) of each model. The difference in AIC follows a χ² distribution with one degree of freedom, from which the P-value was derived. * p < 0.05 ** p < 0.001 2a. Rotterdam Study III 2b. Generation R Study

Figure 3. Increase in explained variance in hypertension by genetic risk scores

Bars represent the increase in explained variance (%) of hypertension in adults (SBP>140, DBP>90 or the use of anti hypertensive medication), when adding systolic and diastolic genetic risk scores for different p-value thresholds, to the base line model for systolic blood pressure including BMI, sex and age as covariates. The baseline model explained 15.9% of the variance in hypertension in adults. We evaluated the difference in explained variance between two subsequent models by calculating the Akaike Information Criterion (AIC) of each model. The difference in AIC follows a χ² distribution with one degree of freedom, from which the P-value was derived. * p < 0.05 ** p < 0.001 3a. Systolic blood pressure scores 3b. Diastolic blood pressure scores