Characterization of the c.190T>C missense mutation in BRCA1 codon 64 (Cys64Arg).

In the Milan area (Northern Italy), we identified a family characterized by a high prevalence of ovarian and breast cancer cases (5 out of 6 subjects, over 3 generations), and a predominant prevalence of ovarian lesions (4 out of 5 patients). Analysis of BRCA1 and BRCA2 genes allowed the identification of the missense c.190T>C mutation in codon 64 (Cys64Arg) of BRCA1. The aims of the present investigation were to characterize the functional implications of the c.190T>C mutation at the molecular level, and to search whether additional polymorphisms might be linked to the peculiar phenotypic features observed in the Italian pedigree. Molecular modelling studies suggested that substitution of the cysteine 64 with an arginine likely disrupts the architecture of the BRCA1 RING finger domain, responsible for the interaction with BARD1, essential for the tumor-suppressor activity of the BRCA1-BARD1 complex. By splicing site information analysis, exonic splicing enhancer site characterization, and analysis of transcript fragment length and sequence, we showed that the c.190T>C mutation was able to modulate the splicing of exon 5 in a fashion opposite to the c.190T>G transversion, responsible for the functionally-related Cys64Gly amino acid substitution. Genotyping of BRCA1 and BRCA2 in the Italian family revealed the presence of two significant polymorphisms: the cancer-associated c.2612C>T SNP in BRCA1, and the c.-26G>A SNP in the BRCA2 gene, acting as an ovarian cancer risk modifier in carriers of deleterious BRCA1 mutations. Analysis of these SNPs in a genotypically-unrelated Polish family, characterized by prevalent breast neoplasms in carriers of the c.190T>C mutation, revealed a genetic profile consistent with the hypothetic role of both polymorphisms

Dietary Patterns, Abdominal Visceral Adipose Tissue and Cardiometabolic Risk Factors in African Americans: the Jackson Heart Study

Dietary behavior is an important lifestyle factor to impact an individual’s risk of developing cardiovascular disease (CVD). However, the influence of specific dietary factors on CVD risk for African Americans remains unclear. We conducted a cross-sectional study of 1775 participants from Jackson Heart Study (JHS) Exam 2 (between 2006 and 2009) who were free of hypertension, diabetes and CVD at the baseline (between 2001 and 2004). Dietary intakes were documented using a validated food-frequency questionnaire (FFQ) and dietary patterns were generated by factor analysis. Three major dietary patterns were identified: a “southern”, a “fast food” and a “prudent” pattern. After adjustment for age, sex, smoking and alcohol status, education level and physical activity, high “southern” pattern score was associated with an increased odds ratio (OR) for high abdominal visceral adipose tissue (VAT) (OR:1.80, 95%CI:1.1–3.0, p=0.02), hypertension (OR:1.42, 95%CI:1.1–1.9, p=0.02), diabetes (OR:2.03, 95%CI:1.1–3.9, p=0.03) and metabolic syndrome (OR:2.16, 95%CI:1.3–3.6, p=0.004). Similar associations were also observed in the “fast food” pattern (p ranges 0.03–0.0001). The “prudent” pattern was significantly associated, in a protective direction, with hypertension (OR 0.69, 95%CI 0.5–0.9, p=0.02). In conclusion, dietary patterns, especially the “southern” pattern, identified from a regional specific FFQ in this Deep South African Americans, are correlated with abdominal VAT and cardiometabolic risk factors

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: a pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk of major cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regression models to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10−8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genome-wide association studies (Pinteraction ≥ 0.01). Our results suggest that there are no major pharmacogenetic influences of common SNPs on the relationship between blood pressure medications and the risk of incident CVD

Multi-ancestry study of blood lipid levels identifies four loci interacting with physical activity.

Many genetic loci affect circulating lipid levels, but it remains unknown whether lifestyle factors, such as physical activity, modify these genetic effects. To identify lipid loci interacting with physical activity, we performed genome-wide analyses of circulating HDL cholesterol, LDL cholesterol, and triglyceride levels in up to 120,979 individuals of European, African, Asian, Hispanic, and Brazilian ancestry, with follow-up of suggestive associations in an additional 131,012 individuals. We find four loci, in/near CLASP1, LHX1, SNTA1, and CNTNAP2, that are associated with circulating lipid levels through interaction with physical activity; higher levels of physical activity enhance the HDL cholesterol-increasing effects of the CLASP1, LHX1, and SNTA1 loci and attenuate the LDL cholesterol-increasing effect of the CNTNAP2 locus. The CLASP1, LHX1, and SNTA1 regions harbor genes linked to muscle function and lipid metabolism. Our results elucidate the role of physical activity interactions in the genetic contribution to blood lipid levels

Drug-gene interactions of antihypertensive medications and risk of incident cardiovascular disease: A pharmacogenomics study from the CHARGE consortium

Background Hypertension is a major risk factor for a spectrum of cardiovascular diseases (CVD), including myocardial infarction, sudden death, and stroke. In the US, over 65 million people have high blood pressure and a large proportion of these individuals are prescribed antihypertensive medications. Although large long-term clinical trials conducted in the last several decades have identified a number of effective antihypertensive treatments that reduce the risk of future clinical complications, responses to therapy and protection from cardiovascular events vary among individuals. Methods Using a genome-wide association study among 21,267 participants with pharmaceutically treated hypertension, we explored the hypothesis that genetic variants might influence or modify the effectiveness of common antihypertensive therapies on the risk ofmajor cardiovascular outcomes. The classes of drug treatments included angiotensin-converting enzyme inhibitors, beta-blockers, calcium channel blockers, and diuretics. In the setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, each study performed array-based genome-wide genotyping, imputed to HapMap Phase II reference panels, and used additive genetic models in proportional hazards or logistic regressionmodels to evaluate drug-gene interactions for each of four therapeutic drug classes. We used meta-analysis to combine study-specific interaction estimates for approximately 2 million single nucleotide polymorphisms (SNPs) in a discovery analysis among 15,375 European Ancestry participants (3,527 CVD cases) with targeted follow-up in a case-only study of 1,751 European Ancestry GenHAT participants as well as among 4,141 African-Americans (1,267 CVD cases). Results Although drug-SNP interactions were biologically plausible, exposures and outcomes were well measured, and power was sufficient to detect modest interactions, we did not identify any statistically significant interactions from the four antihypertensive therapy meta-analyses (Pinteraction > 5.0×10-8). Similarly, findings were null for meta-analyses restricted to 66 SNPs with significant main effects on coronary artery disease or blood pressure from large published genom

A new strategy for enhancing imputation quality of rare variants from next-generation sequencing data via combining SNP and exome chip data

Background: Rare variants have gathered increasing attention as a possible alternative source of missing heritability. Since next generation sequencing technology is not yet cost-effective for large-scale genomic studies, a widely used alternative approach is imputation. However, the imputation approach may be limited by the low accuracy of the imputed rare variants. To improve imputation accuracy of rare variants, various approaches have been suggested, including increasing the sample size of the reference panel, using sequencing data from study-specific samples (i.e., specific populations), and using local reference panels by genotyping or sequencing a subset of study samples. While these approaches mainly utilize reference panels, imputation accuracy of rare variants can also be increased by using exome chips containing rare variants. The exome chip contains 250 K rare variants selected from the discovered variants of about 12,000 sequenced samples. If exome chip data are available for previously genotyped samples, the combined approach using a genotype panel of merged data, including exome chips and SNP chips, should increase the imputation accuracy of rare variants. Results: In this study, we describe a combined imputation which uses both exome chip and SNP chip data simultaneously as a genotype panel. The effectiveness and performance of the combined approach was demonstrated using a reference panel of 848 samples constructed using exome sequencing data from the T2D-GENES consortium and 5,349 sample genotype panels consisting of an exome chip and SNP chip. As a result, the combined approach increased imputation quality up to 11 %, and genomic coverage for rare variants up to 117.7 % (MAF < 1 %), compared to imputation using the SNP chip alone. Also, we investigated the systematic effect of reference panels on imputation quality using five reference panels and three genotype panels. The best performing approach was the combination of the study specific reference panel and the genotype panel of combined data. Conclusions: Our study demonstrates that combined datasets, including SNP chips and exome chips, enhances both the imputation quality and genomic coverage of rare variants

TEAM: efficient two-locus epistasis tests in human genome-wide association study

As a promising tool for identifying genetic markers underlying phenotypic differences, genome-wide association study (GWAS) has been extensively investigated in recent years. In GWAS, detecting epistasis (or gene–gene interaction) is preferable over single locus study since many diseases are known to be complex traits. A brute force search is infeasible for epistasis detection in the genome-wide scale because of the intensive computational burden. Existing epistasis detection algorithms are designed for dataset consisting of homozygous markers and small sample size. In human study, however, the genotype may be heterozygous, and number of individuals can be up to thousands. Thus, existing methods are not readily applicable to human datasets. In this article, we propose an efficient algorithm, TEAM, which significantly speeds up epistasis detection for human GWAS. Our algorithm is exhaustive, i.e. it does not ignore any epistatic interaction. Utilizing the minimum spanning tree structure, the algorithm incrementally updates the contingency tables for epistatic tests without scanning all individuals. Our algorithm has broader applicability and is more efficient than existing methods for large sample study. It supports any statistical test that is based on contingency tables, and enables both family-wise error rate and false discovery rate controlling. Extensive experiments show that our algorithm only needs to examine a small portion of the individuals to update the contingency tables, and it achieves at least an order of magnitude speed up over the brute force approach

Association of genetic variation with systolic and diastolic blood pressure among African Americans: the Candidate Gene Association Resource study

The prevalence of hypertension in African Americans (AAs) is higher than in other US groups; yet, few have performed genome-wide association studies (GWASs) in AA. Among people of European descent, GWASs have identified genetic variants at 13 loci that are associated with blood pressure. It is unknown if these variants confer susceptibility in people of African ancestry. Here, we examined genome-wide and candidate gene associations with systolic blood pressure (SBP) and diastolic blood pressure (DBP) using the Candidate Gene Association Resource (CARe) consortium consisting of 8591 AAs. Genotypes included genome-wide single-nucleotide polymorphism (SNP) data utilizing the Affymetrix 6.0 array with imputation to 2.5 million HapMap SNPs and candidate gene SNP data utilizing a 50K cardiovascular gene-centric array (ITMAT-Broad-CARe [IBC] array). For Affymetrix data, the strongest signal for DBP was rs10474346 (P= 3.6 × 10−8) located near GPR98 and ARRDC3. For SBP, the strongest signal was rs2258119 in C21orf91 (P= 4.7 × 10−8). The top IBC association for SBP was rs2012318 (P= 6.4 × 10−6) near SLC25A42 and for DBP was rs2523586 (P= 1.3 × 10−6) near HLA-B. None of the top variants replicated in additional AA (n = 11 882) or European-American (n = 69 899) cohorts. We replicated previously reported European-American blood pressure SNPs in our AA samples (SH2B3, P= 0.009; TBX3-TBX5, P= 0.03; and CSK-ULK3, P= 0.0004). These genetic loci represent the best evidence of genetic influences on SBP and DBP in AAs to date. More broadly, this work supports that notion that blood pressure among AAs is a trait with genetic underpinnings but also with significant complexit

Epidemiology of Heart Failure Stages in Middle‐Aged Black People in the Community: Prevalence and Prognosis in the Atherosclerosis Risk in Communities Study

Background Black individuals have a higher burden of risk factors for heart failure (HF) and subclinical left ventricular remodeling. Methods and Results We evaluated 1871 Black participants in the Atherosclerosis Risk in Communities Study cohort who attended a routine examination (1993-1996, median age 58 years) when they underwent echocardiography. We estimated the prevalences of 4 HF stages: (1) Stage 0: no risk factors; (2) Stage A: presence of HF risk factors (hypertension, diabetes mellitus, obesity, smoking, dyslipidemia, coronary artery disease without clinical myocardial infarction), no cardiac structural/functional abnormality; (3) Stage B: presence of prior myocardial infarction, systolic dysfunction, left ventricular hypertrophy, regional wall motion abnormality, or left ventricular enlargement; and (4) Stage C/D: prevalent HF. We assessed the incidence of clinical HF, atherosclerotic cardiovascular disease events, and all-cause mortality on follow-up according to HF stage. The prevalence of HF Stages 0, A, B, and C/D were 3.8%, 20.6%, 67.0%, and 8.6%, respectively, at baseline. On follow-up (median 19.0 years), 309 participants developed overt HF, 390 incurred new-onset cardiovascular disease events, and 651 individuals died. Incidence rates per 1000 person-years for overt HF, cardiovascular disease events, and death, respectively, were Stage 0, 2.4, 0.8, and 7.6; Stage A, 7.4, 9.7, and 13.5; Stage B 13.6, 15.9, and 22.0. Stage B HF was associated with a 1.5- to 2-fold increased adjusted risk of HF, cardiovascular disease events and death compared with Stages 0/A. Conclusions In our large community-based sample of Black individuals, we observed a strikingly high prevalence of Stage B HF in middle age that was a marker of high cardiovascular morbidity and mortality