AGT M235T genotype/anxiety interaction and gender in the HyperGEN study

Background

Both anxiety and elevated heart rate (HR) have been implicated in the development of hypertension. The HyperGen cohort, consisting of siblings with severe and mild hypertension, an age-matched random sample of persons from the same base populations, and unmedicated adult offspring of the hypertensive siblings (N = 1,002 men and 987 women), was analyzed for an association of the angiotenisinogen AGTM235T genotype (TT, MT, MM) with an endophenotype, heart rate (HR) in high and low anxious groups.

Methodology

The interaction of AGTM genotype with anxiety, which has been independently associated with hypertension, was investigated adjusting for age, hypertension status, smoking, alcohol consumption, beta blocker medication, body mass index, physical activity and hours of television viewing (sedentary life style).

Principal Findings

Although there was no main effect of genotype on HR in men or women, high anxious men with the TT genotype had high HR, whereas high anxious men with the MM genotype had low HR. In women, HR was inversely associated with anxiety but there was no interaction with genotype.

Conclusion/Significance

The results suggest that high anxiety in men with the TT genotype may increase risk for hypertension whereas the MM genotype may be protective in high anxious men. This type of gene x environment interaction may be one reason why genome wide association studies sometimes fail to replicate. The locus may be important only in combination with certain environmental factors.     

Haplotype association analysis of human disease traits using genotype data of unrelated individuals

Haplotype inference has become an important part of human genetic data analysis due to its functional and statistical advantages over the single-locus approach in linkage disequilibrium mapping. Different statistical methods have been proposed for detecting haplotype - disease associations using unphased multi-locus genotype data, ranging from the early approach by the simple gene-counting method to the recent work using the generalized linear model. However, these methods are either confined to case - control design or unable to yield unbiased point and interval estimates of haplotype effects. Based on the popular logistic regression model, we present a new approach for haplotype association analysis of human disease traits. Using haplotype-based parameterization, our model infers the effects of specific haplotypes (point estimation) and constructs confidence interval for the risks of haplotypes (interval estimation). Based on the estimated parameters, the model calculates haplotype frequency conditional on the trait value for both discrete and continuous traits. Moreover, our model provides an overall significance level for the association between the disease trait and a group or all of the haplotypes. Featured by the direct maximization in haplotype estimation, our method also facilitates a computer simulation approach for correcting the significance level of individual haplotype to adjust for multiple testing. We show, by applying the model to an empirical data set, that our method based on the well-known logistic regression model is a useful tool for haplotype association analysis of human disease traits.     

Haplotype combination of SREBP-1c gene sequence variants is associated with growth traits in cattle

The aim of this study was to examine the association of the SREBP-1c polymorphism with growth traits in cattle breeds. Five sequence variants (SVs) were identified within the bovine sterol regulatory element-binding protein-1c gene (SREBP-1c), using DNA sequencing, PCR, PCR–RFLP, and forced PCR–RFLP methods. These polymorphisms include three missense mutations (SV1, SV4, and SV5) in exons 7, 9, and 12, a silent mutation (SV3) in exon 9, and a large deletion (SV2) in intron 7. Overall, we report the validation of polymorphisms within the bovine SREBP-1c gene, and the haplotype variability and extent of linkage disequilibrium (LD) in 1061 individuals representing the five main cattle breeds from China. We also investigated haplotype frequencies and LD coefficients for five SVs in all study populations. LD and haplotype structure of SREBP-1c were different between breeds. The result of haplotype analysis of five SVs showed that 27 different haplotypes were identified by all breeds. Two haplotypes (Hap1 and Hap2) shared by all five populations accounted for 42.75%, 35.68%, 36.44%, 25.43%, and 96.26% of all haplotypes observed in the cattle breeds Nanyang, Qinchuan, Jiaxian, Jinnan, and Chinese Holstein, respectively. The statistical analyses indicated that one single SV and 38 combined haplotypes were significantly associated with growth traits in the Nanyang cattle population (P < 0.05 or P < 0.01). The results of this study suggest that the SREBP-1c gene possibly is a strong candidate gene that affects growth traits in the Chinese beef cattle breeding program.     

Genome-wide association study reveals five nucleotide sequence variants for carcass traits in beef cattle

Genetic associations of nucleotide sequence variants with carcass traits in beef cattle were investigated using a genome-wide single nucleotide polymorphism (SNP) assay. Three hundred and thirteen Korean cattle were genotyped with the Illumina BovineSNP50 BeadChip, and 39,129 SNPs from 311 animals were analysed for each carcass phenotype after filtering by quality assurance. Five sequence markers were associated with one of the meat quantity or quality traits; rs109593638 on chromosome 3 with marbling score, rs109821175 on chromosome 11 and rs110862496 on chromosome 13 with backfat thickness (BFT), and rs110228023 on chromosome 6 and rs110201414 on chromosome 16 with eye muscle area (EMA) (P < 1.27 × 10(-6) , Bonferonni P < 0.05). The ss96319521 SNP, located within a gene with functions of muscle development, dishevelled homolog 1 (DVL1), would be a desirable candidate marker. Individuals with genotype CC at this gene appeared to have increased both EMA and carcass weight. Fine-mapping would be required to refine each of the five association signals shown in the current study for future application in marker-assisted selection for genetic improvement of beef quality and quantity.     

Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits

Nonalcoholic fatty liver disease (NAFLD) clusters in families, but the only known common genetic variants influencing risk are near PNPLA3. We sought to identify additional genetic variants influencing NAFLD using genome-wide association (GWA) analysis of computed tomography (CT) measured hepatic steatosis, a non-invasive measure of NAFLD, in large population based samples. Using variance components methods, we show that CT hepatic steatosis is heritable (∼26%–27%) in family-based Amish, Family Heart, and Framingham Heart Studies (n = 880 to 3,070). By carrying out a fixed-effects meta-analysis of genome-wide association (GWA) results between CT hepatic steatosis and ∼2.4 million imputed or genotyped SNPs in 7,176 individuals from the Old Order Amish, Age, Gene/Environment Susceptibility-Reykjavik study (AGES), Family Heart, and Framingham Heart Studies, we identify variants associated at genome-wide significant levels (p<5×10⁻⁸) in or near PNPLA3, NCAN, and PPP1R3B. We genotype these and 42 other top CT hepatic steatosis-associated SNPs in 592 subjects with biopsy-proven NAFLD from the NASH Clinical Research Network (NASH CRN). In comparisons with 1,405 healthy controls from the Myocardial Genetics Consortium (MIGen), we observe significant associations with histologic NAFLD at variants in or near NCAN, GCKR, LYPLAL1, and PNPLA3, but not PPP1R3B. Variants at these five loci exhibit distinct patterns of association with serum lipids, as well as glycemic and anthropometric traits. We identify common genetic variants influencing CT–assessed steatosis and risk of NAFLD. Hepatic steatosis associated variants are not uniformly associated with NASH/fibrosis or result in abnormalities in serum lipids or glycemic and anthropometric traits, suggesting genetic heterogeneity in the pathways influencing these traits.     

Genome-wide association scan shows genetic variants in the FTO gene are associated with obesity-related traits

The obesity epidemic is responsible for a substantial economic burden in developed countries and is a major risk factor for type 2 diabetes and cardiovascular disease. The disease is the result not only of several environmental risk factors, but also of genetic predisposition. To take advantage of recent advances in gene-mapping technology, we executed a genome-wide association scan to identify genetic variants associated with obesity-related quantitative traits in the genetically isolated population of Sardinia. Initial analysis suggested that several SNPs in the FTO and PFKP genes were associated with increased BMI, hip circumference, and weight. Within the FTO gene, rs9930506 showed the strongest association with BMI (p = 8.6 ×10⁻⁷), hip circumference (p = 3.4 × 10⁻⁸), and weight (p = 9.1 × 10⁻⁷). In Sardinia, homozygotes for the rare “G” allele of this SNP (minor allele frequency = 0.46) were 1.3 BMI units heavier than homozygotes for the common “A” allele. Within the PFKP gene, rs6602024 showed very strong association with BMI (p = 4.9 × 10⁻⁶). Homozygotes for the rare “A” allele of this SNP (minor allele frequency = 0.12) were 1.8 BMI units heavier than homozygotes for the common “G” allele. To replicate our findings, we genotyped these two SNPs in the GenNet study. In European Americans (N = 1,496) and in Hispanic Americans (N = 839), we replicated significant association between rs9930506 in the FTO gene and BMI (p-value for meta-analysis of European American and Hispanic American follow-up samples, p = 0.001), weight (p = 0.001), and hip circumference (p = 0.0005). We did not replicate association between rs6602024 and obesity-related traits in the GenNet sample, although we found that in European Americans, Hispanic Americans, and African Americans, homozygotes for the rare “A” allele were, on average, 1.0–3.0 BMI units heavier than homozygotes for the more common “G” allele. In summary, we have completed a whole genome–association scan for three obesity-related quantitative traits and report that common genetic variants in the FTO gene are associated with substantial changes in BMI, hip circumference, and body weight. These changes could have a significant impact on the risk of obesity-related morbidity in the general population.     

Analysis of the association of interleukin 4 and interleukin 10 gene variants with basic personality traits

There is growing evidence that serum levels of various inflammation markers are associated with personality traits. However, only few studies investigated the link between genetic variants of cytokine encoding genes and psychological characteristics. In this study, we examined genotypes in 297 individuals to assess the association between common variants of interleukin 4 (IL-4) and interleukin 10 (IL-10) genes and basic personality traits of extraversion and neuroticism, measured using the Eysenck Personality Questionnaire (EPQ). We found that, in homozygous female carriers of high expression alleles Т (IL-4 C-589T) and G (IL-10 G-1082A), neuroticism scores were higher (p = 0.045 and p = 0.08, respectively). In turn, extraversion scores were significantly higher in both male and female carriers of heterozygous variants CT and GA (p = 0.01). Our results are in accordance with the behavioral immune system hypothesis, and the general paradigm on the role of personality traits in health and longevity.     

Comprehensive biochemical analysis of rare prostacyclin receptor variants: study of association of signaling with coronary artery obstruction

Currently, pharmacogenetic studies are at an impasse as the low prevalence (<2%) of most variants hinder their pharmacogenetic analysis with population sizes often inadequate for sufficiently powered studies. Grouping rare mutations by functional phenotype rather than mutation site can potentially increase sample size. Using human population-based studies (n = 1,761) to search for dysfunctional human prostacyclin receptor (hIP) variants, we recently discovered 18 non-synonymous mutations, all with frequencies less than 2% in our study cohort. Eight of the 18 had defects in binding, activation, and/or protein stability/folding. Mutations (M113T, L104R, and R279C) in three highly conserved positions demonstrated severe misfolding manifested by impaired binding and activation of cell surface receptors. To assess for association with coronary artery disease, we performed a case-control study comparing coronary angiographic results from patients with reduced cAMP production arising from the non-synonymous mutations (n = 23) with patients with non-synonymous mutations that had no reduction in cAMP (n = 17). Major coronary artery obstruction was significantly increased in the dysfunctional mutation group in comparison with the silent mutations. We then compared the 23 dysfunctional receptor patients with 69 age- and risk factor-matched controls (1:3). This verified the significantly increased coronary disease in the non-synonymous dysfunctional variant cohort. This study demonstrates the potential utility of in vitro functional characterization in predicting clinical phenotypes and represents the most comprehensive characterization of human prostacyclin receptor genetic variants to date.     

Haplotype diversity: the link between statistical and biological association

In the rapidly growing field of association mapping in plants, the use of (marker) haplotypes rather than single markers can be an effective way of improving detection power. Here, we highlight the information that can be obtained from deducing the historical relationships between haplotypes. The ordering of haplotype classes according to deduced historical relationships should further enhance association detection power, but can also be used to predict the genotypic and phenotypic values of unobserved germplasm.     

The statistical power of genome-wide association studies for threshold traits with different frequencies of causal variants

Genetica - This study aimed to investigate the effects of incidence rate, heritability, and polygenic variance on the statistical power of genome-wide association studies (GWAS) for threshold...     

Haplotype block structure and its applications to association studies: power and study designs

Recent studies have shown that the human genome has a haplotype block structure, such that it can be divided into discrete blocks of limited haplotype diversity. In each block, a small fraction of single-nucleotide polymorphisms (SNPs), referred to as "tag SNPs," can be used to distinguish a large fraction of the haplotypes. These tag SNPs can potentially be extremely useful for association studies, in that it may not be necessary to genotype all SNPs; however, this depends on how much power is lost. Here we develop a simulation study to quantitatively assess the power loss for a variety of study designs, including case-control designs and case-parental control designs. First, a number of data sets containing case-parental or case-control samples are generated on the basis of a disease model. Second, a small fraction of case and control individuals in each data set are genotyped at all the loci, and a dynamic programming algorithm is used to determine the haplotype blocks and the tag SNPs based on the genotypes of the sampled individuals. Third, the statistical power of tests was evaluated on the basis of three kinds of data: (1) all of the SNPs and the corresponding haplotypes, (2) the tag SNPs and the corresponding haplotypes, and (3) the same number of randomly chosen SNPs as the number of tag SNPs and the corresponding haplotypes. We study the power of different association tests with a variety of disease models and block-partitioning criteria. Our study indicates that the genotyping efforts can be significantly reduced by the tag SNPs, without much loss of power. Depending on the specific haplotype block-partitioning algorithm and the disease model, when the identified tag SNPs are only 25% of all the SNPs, the power is reduced by only 4%, on average, compared with a power loss of approximately 12% when the same number of randomly chosen SNPs is used in a two-locus haplotype analysis. When the identified tag SNPs are approximately 14% of all the SNPs, the power is reduced by approximately 9%, compared with a power loss of approximately 21% when the same number of randomly chosen SNPs is used in a two-locus haplotype analysis. Our study also indicates that haplotype-based analysis can be much more powerful than marker-by-marker analysis.     

Pharmacogenetic association of NOS3 variants with cardiovascular disease in patients with hypertension: the GenHAT study

Nitric oxide synthase 3 (NOS3) catalyzes production of NO in the endothelium and may play a role in cardiovascular disease (CVD). We assessed the pharmacogenetic associations of three NOS3 polymorphisms and three antihypertensive drugs with CVD outcomes. Hypertensive subjects (n = 30,280) from a multi-center, double-blind clinical trial were randomized to chlorthalidone, amlodipine, or lisinopril treatment (mean follow up, 4.9 years). Outcomes included coronary heart disease (CHD: fatal CHD and nonfatal myocardial infarction); stroke; heart failure (fatal, requiring hospitalization, or outpatient treatment); all-cause mortality; and end-stage renal disease (ESRD). Main effects of NOS3 variants on outcome and genotype-treatment interactions were tested. For NOS3 −690 C>T (rs3918226), a higher hazard ratio (HR) was found in minor allele carriers for CHD (CC = 1.00, CT+TT = 1.12 (95% confidence interval (CI) = 1.00–1.26), P = 0.048). For NOS3 −922 A>G (rs1800779), a higher HR was found in minor allele carriers for heart failure (AA = 1.00, AG+GG = 1.10 (CI = 1.00–1.21), P = 0.046). Significant pharmacogenetic findings were observed for stroke and all-cause mortality. For −690 C>T, a lower HR was observed for stroke in minor allele carriers when treated with amlodipine versus lisinopril (CC = 0.85 (CI = 0.73–0.99), CT+TT = 0.49 (CI = 0.31–0.80), P = 0.04). For glu298asp G>T (rs1799983), a lower HR was observed for all-cause mortality in minor allele carriers when treated with amlodipine versus lisinopril (GG = 1.01 (CI = 0.91–1.13), GT+TT = 0.85 (CI = 0.75–0.97), P = 0.04). We observed significant associations with NOS3 variants and CHD and heart failure and significant pharmacogenetic effects for stroke and all cause mortality. This suggests that NOS3 variants may potentially provide useful clinical information with respect to treatment decisions in the future.     

Regression association analysis of fruit traits with molecular markers in cherries

The use of molecular markers supports the study of genetic marker–trait association of biological and agronomic interest in diverse genetic material. In this research, association between simple sequence repeat (SSR) and random amplified polymorphic DNA (RAPD) markers with fruit traits were investigated in two collections of cherries by applying multiple regression analysis (MRA). Thirty-eight SSR alleles and 135 RAPD fragments were found associated with 14 of affecting fruit traits. Some of SSR and RAPD markers were associated with more than one fruit trait in MRA. Such an association may arise due to pleiotropic effect of the linked quantitative trait locus on different traits. For example, some SSR and RAPD markers were associated with all four traits including fruit cracking, fruit firmness, total soluble solid (TSS) and fruit shape. Also, some markers had correlations with all four characters of TSS, anthocyanin, fruit skin color and fruit flesh color, indicating a significant correlation among these traits. Therefore, it is possible to use these markers along with morphological traits in cherry breeding programs for identification of suitable parents to produce mapping populations and hybrid cultivars. Also, these results could be useful in marker-assisted breeding programs when no other genetic information is available.     

A genome scan for renal function among hypertensives: the HyperGEN study

Decreased renal function is often a complication of hypertension. Although it has been suggested that the response of the kidney to hypertension has an underlying genetic component, there is limited information suggesting that specific genetic regions or candidate genes contribute to the variability in creatinine clearance, a commonly used measure of kidney function. As part of the Hypertension Genetic Epidemiology Network (HyperGEN) study, creatinine clearance measurements were assessed in a large biracial sample of hypertensive siblings (466 African American subjects and 634 white subjects in 215 and 265 sibships, respectively). All participants were hypertensive before the age of 60 years, and the mean age of the siblings was 52 years among the African American subjects and 61 years among the white subjects. Two residual models were created for creatinine clearance: a minimally adjusted model (which included age and age(2)) and a fully adjusted model (which included age, age(2), lean body mass, pulse rate, pulse pressure, hormone-replacement therapy, educational status, and physical activity). Standardized residuals were calculated separately for men and women in both racial groups. The heritability of the residual creatinine clearance was 17% and 18% among the African American and white subjects, respectively. We conducted multipoint variance components linkage analysis using GENEHUNTER2 and 387 anonymous markers (Cooperative Human Linkage Center screening set 8). The best evidence for linkage in African American subjects was found on chromosome 3 (LOD = 3.61 at 214.6 cM, 3q27) with the fully adjusted model, and the best evidence in white subjects was found on chromosome 3 (LOD = 3.36 at 115.1 cM) with the minimally adjusted model. Positional candidate genes that are contained in and around the region on chromosome 3 (214.6 cM) that may contribute to renal function include enoyl-CoA hydratase/3-hydroxyacyl-CoA dehydrogenase (EHHADH) and apolipoprotein D (ApoD). These findings suggest there may be genetic regions related to the variability of creatinine clearance among hypertensive individuals.     

Genetic association studies of complex traits: design and analysis issues

Most common diseases and many important quantitative traits are complex genetic traits, with multiple genetic and environmental variables contributing to the observed phenotype. Because of the multi-factorial nature of complex traits, each individual genetic variant generally has only a modest effect, and the interaction of genetic variants with each other or with environmental factors can potentially be quite important in determining the observed phenotype. It remains largely unknown what sort of genetic variants explain inherited variation in complex traits, but recent evidence suggests that common genetic variants will explain at least some of the inherited variation in susceptibility to common disease. Genetic association studies, in which the allele or genotype frequencies at markers are determined in affected individuals and compared with those of controls (either population- or family-based), may be an effective approach to detecting the effects of common variants with modest effects. With the explosion in single nucleotide polymorphism (SNP) discovery and genotyping technologies, large-scale association studies have become feasible, and small-scale association studies have become plentiful. We review the different types of association studies and discuss issues that are important to consider when performing and interpreting association studies of complex genetic traits. Heritable and accurately measured phenotypes, carefully matched large samples, well-chosen genetic markers, and adequate standards in genotyping, analysis, and interpretation are all integral parts of a high-quality association study.     

Imputation-based analysis of association studies: candidate regions and quantitative traits

We introduce a new framework for the analysis of association studies, designed to allow untyped variants to be more effectively and directly tested for association with a phenotype. The idea is to combine knowledge on patterns of correlation among SNPs (e.g., from the International HapMap project or resequencing data in a candidate region of interest) with genotype data at tag SNPs collected on a phenotyped study sample, to estimate ("impute") unmeasured genotypes, and then assess association between the phenotype and these estimated genotypes. Compared with standard single-SNP tests, this approach results in increased power to detect association, even in cases in which the causal variant is typed, with the greatest gain occurring when multiple causal variants are present. It also provides more interpretable explanations for observed associations, including assessing, for each SNP, the strength of the evidence that it (rather than another correlated SNP) is causal. Although we focus on association studies with quantitative phenotype and a relatively restricted region (e.g., a candidate gene), the framework is applicable and computationally practical for whole genome association studies. Methods described here are implemented in a software package, Bim-Bam, available from the Stephens Lab website http://stephenslab.uchicago.edu/software.html.