Investigating the complex genetic architecture of ankle-brachial index, a measure of peripheral arterial disease, in non-Hispanic whites

<p>Abstract</p> <p>Background</p> <p>Atherosclerotic peripheral arterial disease (PAD) affects 8–10 million people in the United States and is associated with a marked impairment in quality of life and an increased risk of cardiovascular events. Noninvasive assessment of PAD is performed by measuring the ankle-brachial index (ABI). Complex traits, such as ABI, are influenced by a large array of genetic and environmental factors and their interactions. We attempted to characterize the genetic architecture of ABI by examining the main and interactive effects of individual single nucleotide polymorphisms (SNPs) and conventional risk factors.</p> <p>Methods</p> <p>We applied linear regression analysis to investigate the association of 435 SNPs in 112 positional and biological candidate genes with ABI and related physiological and biochemical traits in 1046 non-Hispanic white, hypertensive participants from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. The main effects of each SNP, as well as SNP-covariate and SNP-SNP interactions, were assessed to investigate how they contribute to the inter-individual variation in ABI. Multivariable linear regression models were then used to assess the joint contributions of the top SNP associations and interactions to ABI after adjustment for covariates. We reduced the chance of false positives by 1) correcting for multiple testing using the false discovery rate, 2) internal replication, and 3) four-fold cross-validation.</p> <p>Results</p> <p>When the results from these three procedures were combined, only two SNP main effects in <it>NOS3</it>, three SNP-covariate interactions (<it>ADRB2 </it>Gly 16 – lipoprotein(a) and <it>SLC4A5 </it>– diabetes interactions), and 25 SNP-SNP interactions (involving SNPs from 29 different genes) were significant, replicated, and cross-validated. Combining the top SNPs, risk factors, and their interactions into a model explained nearly 18% of variation in ABI in the sample. SNPs in six genes (<it>ADD2, ATP6V1B1, PRKAR2B, SLC17A2, SLC22A3, and TGFB3</it>) were also influencing triglycerides, C-reactive protein, homocysteine, and lipoprotein(a) levels.</p> <p>Conclusion</p> <p>We found that candidate gene SNP main effects, SNP-covariate and SNP-SNP interactions contribute to the inter-individual variation in ABI, a marker of PAD. Our findings underscore the importance of conducting systematic investigations that consider context-dependent frameworks for developing a deeper understanding of the multidimensional genetic and environmental factors that contribute to complex diseases.</p

Complexity in the genetic architecture of leukoaraiosis in hypertensive sibships from the GENOA Study

<p>Abstract</p> <p>Background</p> <p>Subcortical white matter hyperintensity on magnetic resonance imaging (MRI) of the brain, referred to as leukoaraiosis, is associated with increased risk of stroke and dementia. Hypertension may contribute to leukoaraiosis by accelerating the process of arteriosclerosis involving penetrating small arteries and arterioles in the brain. Leukoaraiosis volume is highly heritable but shows significant inter-individual variability that is not predicted well by any clinical covariates (except for age) or by single SNPs.</p> <p>Methods</p> <p>As part of the Genetics of Microangiopathic Brain Injury (GMBI) Study, 777 individuals (74% hypertensive) underwent brain MRI and were genotyped for 1649 SNPs from genes known or hypothesized to be involved in arteriosclerosis and related pathways. We examined SNP main effects, epistatic (gene-gene) interactions, and context-dependent (gene-environment) interactions between these SNPs and covariates (including conventional and novel risk factors for arteriosclerosis) for association with leukoaraiosis volume. Three methods were used to reduce the chance of false positive associations: 1) false discovery rate (FDR) adjustment for multiple testing, 2) an internal replication design, and 3) a ten-iteration four-fold cross-validation scheme.</p> <p>Results</p> <p>Four SNP main effects (in <it>F3</it>, <it>KITLG</it>, <it>CAPN10</it>, and <it>MMP2</it>), 12 SNP-covariate interactions (including interactions between <it>KITLG </it>and homocysteine, and between <it>TGFB3 </it>and both physical activity and C-reactive protein), and 173 SNP-SNP interactions were significant, replicated, and cross-validated. While a model containing the top single SNPs with main effects predicted only 3.72% of variation in leukoaraiosis in independent test samples, a multiple variable model that included the four most highly predictive SNP-SNP and SNP-covariate interactions predicted 11.83%.</p> <p>Conclusion</p> <p>These results indicate that the genetic architecture of leukoaraiosis is complex, yet predictive, when the contributions of SNP main effects are considered in combination with effects of SNP interactions with other genes and covariates.</p

Interactions between the adducin 2 gene and antihypertensive drug therapies in determining blood pressure in people with hypertension

<p>Abstract</p> <p>Background</p> <p>As part of the NHLBI Family Blood Pressure Program, the Genetic Epidemiology Network of Arteriopathy (GENOA) recruited 575 sibships (n = 1583 individuals) from Rochester, MN who had at least two hypertensive siblings diagnosed before age 60. Linkage analysis identified a region on chromosome 2 that was investigated using 70 single nucleotide polymorphisms (SNPs) typed in 7 positional candidate genes, including adducin 2 (<it>ADD2</it>).</p> <p>Method</p> <p>To investigate whether blood pressure (BP) levels in these hypertensives (n = 1133) were influenced by gene-by-drug interactions, we used cross-validation statistical methods (i.e., estimating a model for predicting BP levels in one subgroup and testing it in a different subgroup). These methods greatly reduced the chance of false positive findings.</p> <p>Results</p> <p>Eight SNPs in <it>ADD2 </it>were significantly associated with systolic BP in untreated hypertensives (p-value < 0.05). Moreover, we also identified SNPs associated with gene-by-drug interactions on systolic BP in drug-treated hypertensives. The TT genotype at SNP rs1541582 was associated with an average systolic BP of 133 mmHg in the beta-blocker subgroup and 148 mmHg in the diuretic subgroup after adjusting for overall mean differences among drug classes.</p> <p>Conclusion</p> <p>Our findings suggest that hypertension candidate gene variation may influence BP responses to specific antihypertensive drug therapies and measurement of genetic variation may assist in identifying subgroups of hypertensive patients who will benefit most from particular antihypertensive drug therapies.</p