Genetic Loci and Novel Discrimination Measures Associated with Blood Pressure Variation in African Americans Living in Tallahassee

<div><p>Sequencing of the human genome and decades of genetic association and linkage studies have dramatically improved our understanding of the etiology of many diseases. However, the multiple causes of complex diseases are still not well understood, in part because genetic and sociocultural risk factors are not typically investigated concurrently. Hypertension is a leading risk factor for cardiovascular disease and afflicts more African Americans than any other racially defined group in the US. Few genetic loci for hypertension have been replicated across populations, which may reflect population-specific differences in genetic variants and/or inattention to relevant sociocultural factors. Discrimination is a salient sociocultural risk factor for poor health and has been associated with hypertension. Here we use a biocultural approach to study blood pressure (BP) variation in African Americans living in Tallahassee, Florida by genotyping over 30,000 single nucleotide polymorphisms (SNPs) and capturing experiences of discrimination using novel measures of unfair treatment of self and others (n = 157). We perform a joint admixture and genetic association analysis for BP that prioritizes regions of the genome with African ancestry. We only report significant SNPs that were confirmed through our simulation analyses, which were performed to determine the false positive rate. We identify eight significant SNPs in five genes that were previously associated with cardiovascular diseases. When we include measures of unfair treatment and test for interactions between SNPs and unfair treatment, we identify a new class of genes involved in multiple phenotypes including psychosocial distress and mood disorders. Our results suggest that inclusion of culturally relevant stress measures, like unfair treatment in African Americans, may reveal new genes and biological pathways relevant to the etiology of hypertension, and may also improve our understanding of the complexity of gene-environment interactions that underlie complex diseases.</p></div

Illustration of the analyses performed.

<p>A) <b>S</b>tandard admixture mapping using a frequentist approach tested for association between genetic ancestry and BP. B) Standard association mapping using a frequentist approach tested for association between SNP and BP. Three progressive Bayesian joint admixture and genetic association analyses for BP were performed that prioritized regions of the genome with African ancestry when evaluating the strength of the association between a SNP and BP. C) Model 1 tested for association between SNP genotype and BP, D) Model 2 included discrimination measures, E) Model 3 tested for interaction effects between SNPs and discrimination measures that are associated with BP</p

Comparison of the significant genes that we found to be associated with BP with other reported phenotypes.

<p>Comparison of the significant genes that we found to be associated with BP with other reported phenotypes.</p

SNP x unfair treatment interaction effects associated with BP.

<p>BP levels are shown on the y-axis and unfair treatment (No/Yes) on the x-axis. SNP genotype is colored blue, gray or red. A) Significant association between SBP and UT-Self is dependent on SNP rs11190458 genotype in the <i>PKD2L1</i> gene. B) Significant association between DBP and UT-Self is dependent on SNP rs11190458 genotype in the <i>PKD2L1</i> gene. Significant associations between SBP and UT-Other are dependent on SNP genotypes C) rs35283004 upstream of <i>HTR4/ADRB2</i> genes D) rs11042725 upstream of <i>SBF2/ADM</i> genes and E) rs547330 in the <i>ABI3BP</i> gene.</p

Significant SNPs associated with SBP from joint ancestry and association analyses.

<p>Significant SNPs associated with SBP from joint ancestry and association analyses.</p

Bayesian Manhattan plots for joint ancestry and association testing with BP.

<p>Each association is plotted based on its chromosomal position (x axis) and the posterior probability that a locus affects BP (y axis). The dashed line indicates the threshold for genome-wide significance (posterior probability ≥0.5). Model 1 results are shown for A) SBP and B) DBP. Model 2/UT-Self plot for C) SBP and D) DBP. Model 2/UT-Other plot for E) SBP and F) DBP. Model 3/UT-Self No/Yes plot for G) SBP and H) DBP. Model 3/UT-Other No/Yes plot for I) SBP and J) DBP.</p