Gene-gene and gene-environment interactions: new insights into the prevention, detection and management of coronary artery disease

Despite the recent success of genome-wide association studies (GWASs) in identifying loci consistently associated with coronary artery disease (CAD), a large proportion of the genetic components of CAD and its metabolic risk factors, including plasma lipids, type 2 diabetes and body mass index, remain unattributed. Gene-gene and gene-environment interactions might produce a meaningful improvement in quantification of the genetic determinants of CAD. Testing for gene-gene and gene-environment interactions is thus a new frontier for large-scale GWASs of CAD. There are several anecdotal examples of monogenic susceptibility to CAD in which the phenotype was worsened by an adverse environment. In addition, small-scale candidate gene association studies with functional hypotheses have identified gene-environment interactions. For future evaluation of gene-gene and gene-environment interactions to achieve the same success as the single gene associations reported in recent GWASs, it will be important to pre-specify agreed standards of study design and statistical power, environmental exposure measurement, phenomic characterization and analytical strategies. Here we discuss these issues, particularly in relation to the investigation and potential clinical utility of gene-gene and gene-environment interactions in CAD

BRCA2 variants and cardiovascular disease in a multi-ethnic study.

BACKGROUND: Germline mutations of BRCA1/2 are associated with hereditary breast and ovarian cancer. Recent data suggests excess mortality in mutation carriers beyond that conferred by neoplasia, and recent in vivo and in vitro studies suggest a modulatory role for BRCA proteins in endothelial and cardiomyocyte function. We therefore tested the association of BRCA2 variants with clinical cardiovascular disease (CVD). METHODS: Using data from 1,170 individuals included in two multi-ethnic population-based studies (SHARE and SHARE-AP), the association between BRCA2 variants and CVD was evaluated. 15 SNPs in BRCA2 with minor allele frequencies (MAF) > 0.01 had been previously genotyped using the cardiovascular gene-centric 50 k SNP array. 115 individuals (9.8%) reported a CVD event, defined as myocardial infarction (MI), angina, silent MI, stroke, and angioplasty or coronary artery bypass surgery. Analyses were adjusted for age and sex. The SNPs rs11571836 and rs1799943 were subsequently genotyped using the MassARRAY platform in 1,045 cases of incident MI and 1,135 controls from the South Asian subset of an international case-control study of acute MI (INTERHEART), and rs11571836 was imputed in 4,686 cases and 4500 controls from the Pakistan Risk of Myocardial Infarction Study (PROMIS). RESULTS: Two BRCA2 SNPs, rs11571836 and rs1799943, both located in untranslated regions, were associated with lower risk of CVD (OR 0.47 p = 0.01 and OR 0.56 p = 0.03 respectively) in the SHARE studies. Analysis by specific ethnicities demonstrated an association with CVD for both SNPs in Aboriginal People, and for rs11571836 only in South Asians. No association was observed in the European and Chinese subgroups. A non-significant trend towards an association between rs11571836 and lower risk of MI was observed in South Asians from INTERHEART [OR = 0.87 (95% CI: 0.75-1.01) p = 0.068], but was not evident in PROMIS [OR = 0.96 (95% CI: 0.90-1.03) p = 0.230]. Meta-analysis of both case-control studies resulted in a combined OR of 0.94 (95% CI: 0.89-1.004, p = 0.06). CONCLUSIONS: Although there was an association between two SNPs in BRCA2 and CVD in a multi-ethnic population, these results were not replicated in two South Asian case-control studies of incident MI. Future studies exploring the association between BRCA variants and cardiovascular disorders are needed to clarify the role, if any, for BRCA variants in CVD pathogenesis.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Структурно-семантичний аналіз еврісемантів української мови (на матеріалі лексико-семантичного поля "річ")

В статье рассматриваются лексико-семантические особенности эврисемантов в украинском языке, осуществляется их семантическая классификация, методом компонентного анализа проводится структурный анализ. Представлен фрагмент иерархично упорядоченной парадигмы широкозначных имен существительных, состоящий из ЛСГ "Предмет" и "Дело".У статті розглядаються лексико-семантичні особливості еврісемантів української мови, здійснюється їх семантична класифікація, за допомогою компонентного аналізу проводиться структурний аналіз. Подається фрагмент ієрархічно впорядкованої парадигми широкозначних іменників, представлений ЛСГ "Предмет" та "Справа".In this article lexica-semantic peculiarities of everysemantical nouns in Ukrainian are considered. It was made semantic distinguishing and structural analysis of those elements. The everysemants of a lexica-semantic field "Thing", represented by two groups "Subject" and "Work", are disposed in specific hierarchy

Gene-centric meta-analyses of 108,912 individuals confirm known body mass index loci and reveal three novel signals

Recent genetic association studies have made progress in uncovering components of the genetic architecture of body mass index (BMI). We used the ITMAT-Broad-CARe (IBC) array comprising up to 49,320 single nucleotide polymorphisms (SNPs) across ~2,100 metabolic and cardiovascular-related loci to genotype up to 108,912 individuals of European ancestry (EA), African Americans, Hispanics, and East Asians, from 46 studies, to provide additional insight into SNPs underpinning BMI. We used a five-phase study design: Phase I focused on meta-analysis of EA studies providing individual level genotype data; Phase II performed a replication of cohorts providing summary level EA data; Phase III meta-analyzed results from the first two phases; associated SNPs from Phase III were used for replication in Phase IV; finally in Phase V, a multi-ethnic meta-analysis of all samples from four ethnicities was performed. At an array-wide significance (P<2.40E-06), we identify novel BMI associations in loci TOMM40-APOE-APOC1 (rs2075650, P=2.95E-10), SREBF2 (a sterol regulatory element binding transcription factor gene, rs5996074, P=9.43E-07) and NTRK2 (a BDNF receptor, rs1211166, P=1.04E-06) in the Phase IV meta-analysis. Of ten loci with previous evidence for BMI association represented on IBC array, eight were replicated, with the remaining two showing nominal significance. Conditional analyses revealed two independent BMI associated signals in BDNF and MC4R regions. Of the 11 array-wide significant SNPs, three are associated with gene expression levels in both primary B-cells and monocytes; with rs4788099 in SH2B1 notably being associated with the expression of multiple genes in cis. These multi-ethnic meta-analyses expand our knowledge of BMI genetics

Gene-Centric Meta-Analysis of Lipid Traits in African, East Asian and Hispanic Populations

Meta-analyses of European populations has successfully identified genetic variants in over 100 loci associated with lipid levels, but our knowledge in other ethnicities remains limited. To address this, we performed dense genotyping of ∼2,000 candidate genes in 7,657 African Americans, 1,315 Hispanics and 841 East Asians, using the IBC array, a custom ∼50,000 SNP genotyping array. Meta-analyses confirmed 16 lipid loci previously established in European populations at genome-wide significance level, and found multiple independent association signals within these lipid loci. Initial discovery and in silico follow-up in 7,000 additional African American samples, confirmed two novel loci: rs5030359 within ICAM1 is associated with total cholesterol (TC) and low-density lipoprotein cholesterol (LDL-C) $(p = 8.8×10^{−7} and p = 1.5×10^{−6}$ respectively) and a nonsense mutation rs3211938 within CD36 is associated with high-density lipoprotein cholesterol (HDL-C) levels $(p = 13.5×10^{−12})$. The rs3211938-G allele, which is nearly absent in European and Asian populations, has been previously found to be associated with CD36 deficiency and shows a signature of selection in Africans and African Americans. Finally, we have evaluated the effect of SNPs established in European populations on lipid levels in multi-ethnic populations and show that most known lipid association signals span across ethnicities. However, differences between populations, especially differences in allele frequency, can be leveraged to identify novel signals, as shown by the discovery of ICAM1 and CD36 in the current report

Gene-centric meta-analyses of 108 912 individuals confirm known body mass index loci and reveal three novel signals

Recent genetic association studies have made progress in uncovering components of the genetic architecture of the body mass index (BMI). We used the ITMAT-Broad-Candidate Gene Association Resource (CARe) (IBC) array comprising up to 49 320 single nucleotide polymorphisms (SNPs) across ∼2100 metabolic and cardiovascular-related loci to genotype up to 108 912 individuals of European ancestry (EA), African-Americans, Hispanics and East Asians, from 46 studies, to provide additional insight into SNPs underpinning BMI. We used a five-phase study design: Phase I focused on meta-analysis of EA studies providing individual level genotype data; Phase II performed a replication of cohorts providing summary level EA data; Phase III meta-analyzed results from the first two phases; associated SNPs from Phase III were used for replication in Phase IV; finally in Phase V, a multi-ethnic meta-analysis of all samples from four ethnicities was performed. At an array-wide significance (P &lt; 2.40E-06), we identify novel BMI associations in loci translocase of outer mitochondrial membrane 40 homolog (yeast) - apolipoprotein E - apolipoprotein C-I (TOMM40-APOE-APOC1) (rs2075650, P = 2.95E-10), sterol regulatory element binding transcription factor 2 (SREBF2, rs5996074, P = 9.43E-07) and neurotrophic tyrosine kinase, receptor, type 2 [NTRK2, a brain-derived neurotrophic factor (BDNF) receptor gene, rs1211166, P = 1.04E-06] in the Phase IV meta-analysis. Of 10 loci with previous evidence for BMI association represented on the IBC array, eight were replicated, with the remaining two showing nominal significance. Conditional analyses revealed two independent BMI-associated signals in BDNF and melanocortin 4 receptor (MC4R) regions. Of the 11 array-wide significant SNPs, three are associated with gene expression levels in both primary B-cells and monocytes; with rs4788099 in SH2B adaptor protein 1 (SH2B1) notably being associated with the expression of multiple genes in cis. These multi-ethnic meta-analyses expand our knowledge of BMI genetics

Genome-Wide Study Updates in the International Genetics and Translational Research in Transplantation Network (iGeneTRAiN)

The prevalence of end-stage renal disease (ESRD) and the number of kidney transplants performed continues to rise every year, straining the procurement of deceased and living kidney allografts and health systems. Genome-wide genotyping and sequencing of diseased populations have uncovered genetic contributors in substantial proportions of ESRD patients. A number of these discoveries are beginning to be utilized in risk stratification and clinical management of patients. Specifically, genetics can provide insight into the primary cause of chronic kidney disease (CKD), the risk of progression to ESRD, and post-transplant outcomes, including various forms of allograft rejection. The International Genetics & Translational Research in Transplantation Network (iGeneTRAiN), is a multi-site consortium that encompasses >45 genetic studies with genome-wide genotyping from over 51,000 transplant samples, including genome-wide data from >30 kidney transplant cohorts (n = 28,015). iGeneTRAiN is statistically powered to capture both rare and common genetic contributions to ESRD and post-transplant outcomes. The primary cause of ESRD is often difficult to ascertain, especially where formal biopsy diagnosis is not performed, and is unavailable in ∼2% to >20% of kidney transplant recipients in iGeneTRAiN studies. We overview our current copy number variant (CNV) screening approaches from genome-wide genotyping datasets in iGeneTRAiN, in attempts to discover and validate genetic contributors to CKD and ESRD. Greater aggregation and analyses of well phenotyped patients with genome-wide datasets will undoubtedly yield insights into the underlying pathophysiological mechanisms of CKD, leading the way to improved diagnostic precision in nephrology