The angiotensin-converting enzyme insertion/deletion polymorphism and its associations with carotid artery wall thickness and coronary heart disease: The atherosclerosis risk in communities study

Coronary heart disease (CHD) is the leading cause of death in the United States. Recently, renin-angiotensin system (RAS) was found associated with atherosclerosis formation, with angiotensin II inducing vascular smooth muscle cell growth and migration, platelet activation and aggregation, and stimulation of plasminogen activator inhibitor-1. Angiotensin II is converted from angiotensin I by angiotensin I-converting enzyme (ACE) and this enzyme is mainly genetically determined. The ACE gene has been assigned to chromosome 17q23 and an insertion/deletion (I/D)polymorphism has been characterized by the presence/absence of a 287 bp fragment in intron 16 of the gene. The two alleles form three genotypes, namely, DD, ID and II and the DD genotype has been linked to higher plasma ACE levels and cell ACE activity.^ In this study, the association between the ACE I/D polymorphism and carotid artery wall thickness measured by B-mode ultrasound was investigated in a biracial sample, and the association between the gene and incident CHD was investigated in whites and if the gene-CHD association in whites, if any, was due to the gene effect on atherosclerosis. The study participants are from the prospective Atherosclerosis Risk in Communities (ARIC) Study, including adults aged 45 to 65 years. The present dissertation used a matched case-control design for studying the associations of the ACE gene with carotid artery atherosclerosis and an unmatched case-control design for the association of the gene with CHD. A significant recessive effect of the D allele on carotid artery thickness was found in blacks (OR = 3.06, 95% C.I: 1.11-8.47, DD vs. ID and II) adjusting for age, gender, cigarette smoking, LDL-cholesterol and diabetes. No similar associations were found in whites. The ACE I/D polymorphism is significantly associated with coronary heart disease in whites, and while stratifying data by carotid artery wall thickness, the significant associations were only observed in thin-walled subgroups. Assuming a recessive effect of the D allele, odds ratio was 2.84 (95% C.I:1.17-6.90, DD vs. ID and II) and it was 2.30 (95% C.I:1.22-4.35, DD vs. ID vs. II) assuming a codominant effect of the D allele. No significant associations were observed while comparing thick-walled CHD cases with thin-walled controls. Following conclusions could be drawn: (1) The ACE I/D polymorphism is unlikely to confer appreciable increase in the risk of carotid atherosclerosis in US whites, but may increases the risk of carotid atherosclerosis in blacks. (2) ACE I/D polymorphism is a genetic risk factor for incident CHD in US whites and this effect is separate from the chronic process of atherosclerosis development. Finally, the associations observed here are not causal, since the I/D polymorphism is in an intron, where no ACE proteins are encoded. ^

Global patterns of DNA polymorphism in noncoding regions in human populations

DNA sequence variation is currently a major source of data for studying human origins, evolution, and demographic history, and for detecting linkage association of complex diseases. In this dissertation, I investigated DNA variation in worldwide populations from two ∼10 kb autosomal regions on 22q11.2 (noncoding) and 1q24 (introns). A total of 75 variant sites were found among 128 human sequences in the 22q11.2 region, yielding an estimate of 0.088% for nucleotide diversity (π), and a total of 52 variant sites were found among 122 human sequences in the 1q24 region with an estimated π value of 0.057%. The data from these two regions and a 10 kb noncoding region on Xq13.3 all show a strong excess of low-frequency variants in comparison to that expected from an equilibrium population, indicating a relatively recent population expansion. The effective population sizes estimated from the three regions were 11,000, 12,700, and 8,600, respectively, which are close to the commonly used value of 10,000. In each of the two autosomal regions, the age of the most recent common ancestor (MRCA) was estimated to be older than 1 million years among all the sequences and ∼600,000 years among non-African sequences, providing first evidence from autosomal noncoding or intronic regions for a genetic history of humans much more ancient than the emergence of modern humans. The ancient genetic history of humans indicates no severe bottleneck during the evolution of humans in the last half million years; otherwise, much of the ancient genetic history would have been lost during a severe bottleneck. This study strongly suggests that both the “out of Africa” and the multiregional models are too simple for explaining the evolution of modern humans. A compilation of genome-wide data revealed that nucleotide diversity is highest in autosomal regions, intermediate in X-linked regions, and lowest in Y-linked regions. The data suggest the existence of background selection or selective sweep on Y-linked loci. In general, the nucleotide diversity in humans is low compared to that in chimpanzee and Drosophila populations. ^

Familial aggregation, candidate genes and genome scans: Analyzing the role of genetics in stroke

The genetic etiology of stroke likely reflects the influence of multiple loci with small effects, each modulating different pathophysiological processes. This research project utilized three analytical strategies to address the paucity of information related to the identification and characterization of genetic variation associated with stroke in the general population. ^ First, the general contribution of familial factors to stroke susceptibility was evaluated in a population-based sample of unrelated individuals. Increased risk of subclinical cerebral infarction was observed among individuals with a positive parental history of stroke. This association did not appear to be mediated by established stroke risk factors, specifically blood pressure levels or hypertension status. ^ The need to identify specific gene variation associated with stroke in the general population was addressed by evaluating seven candidate gene polymorphisms in a population-based sample of unrelated individuals. Three polymorphisms were significantly associated with increased subclinical cerebral infarction or incident clinical ischemic stroke risk. These relationships include the G-protein β3 subunit 825C/T polymorphism and clinical stroke in Whites, the lipoprotein lipase S/X447 polymorphism and subclinical and clinical stroke in men, and the angiotensin I-converting enzyme Ins/Del polymorphism and subclinical stroke in White men. These associations did not appear to be obfuscated by the stroke risk factors adjusted for in the analysis models specifically blood pressure levels or anti-hypertensive medication use. ^ The final research strategy considered, on a genome-wide scale, the idea that genetic variation may contribute to the occurrence of hypertension or stroke through a common etiologic pathway. Genomic regions were identified for which significant evidence of heterogeneity was observed among hypertensive sibpairs stratified by family history of stroke information. Regions identified on chromosome 15 in African Americans, and chromosome 13 in Whites and African Americans, suggest the presence of genes influencing hypertension and stroke susceptibility. ^ Insight into the role of genetics in stroke is useful for the potential early identification of individuals at increased risk for stroke and improved understanding of the etiology of the disease. The ultimate goal of these endeavors is to guide the development of therapeutic intervention and informed prevention to provide a lasting and positive impact on public health. ^

Single nucleotide polymorphism (SNP) selection for genotype-phenotype association studies

With hundreds of single nucleotide polymorphisms (SNPs) in a candidate gene and millions of SNPs across the genome, selecting an informative subset of SNPs to maximize the ability to detect genotype-phenotype association is of great interest and importance. In addition, with a large number of SNPs, analytic methods are needed that allow investigators to control the false positive rate resulting from large numbers of SNP genotype-phenotype analyses. This dissertation uses simulated data to explore methods for selecting SNPs for genotype-phenotype association studies. I examined the pattern of linkage disequilibrium (LD) across a candidate gene region and used this pattern to aid in localizing a disease-influencing mutation. The results indicate that the r2 measure of linkage disequilibrium is preferred over the common D′ measure for use in genotype-phenotype association studies. Using step-wise linear regression, the best predictor of the quantitative trait was not usually the single functional mutation. Rather it was a SNP that was in high linkage disequilibrium with the functional mutation. Next, I compared three strategies for selecting SNPs for application to phenotype association studies: based on measures of linkage disequilibrium, based on a measure of haplotype diversity, and random selection. The results demonstrate that SNPs selected based on maximum haplotype diversity are more informative and yield higher power than randomly selected SNPs or SNPs selected based on low pair-wise LD. The data also indicate that for genes with small contribution to the phenotype, it is more prudent for investigators to increase their sample size than to continuously increase the number of SNPs in order to improve statistical power. When typing large numbers of SNPs, researchers are faced with the challenge of utilizing an appropriate statistical method that controls the type I error rate while maintaining adequate power. We show that an empirical genotype based multi-locus global test that uses permutation testing to investigate the null distribution of the maximum test statistic maintains a desired overall type I error rate while not overly sacrificing statistical power. The results also show that when the penetrance model is simple the multi-locus global test does as well or better than the haplotype analysis. However, for more complex models, haplotype analyses offer advantages. The results of this dissertation will be of utility to human geneticists designing large-scale multi-locus genotype-phenotype association studies. ^