QTLs of factors of the metabolic syndrome and echocardiographic phenotypes: the hypertension genetic epidemiology network study

<p>Abstract</p> <p>Background</p> <p>In a previous study of the Hypertension Genetic Epidemiology Network (HyperGEN) we have shown that metabolic syndrome (MetS) risk factors were moderately and significantly associated with echocardiographic (ECHO) left ventricular (LV) phenotypes.</p> <p>Methods</p> <p>The study included 1,393 African Americans and 1,133 whites, stratified by type 2 diabetes mellitus (DM) status. Heritabilities of seven factor scores based on the analysis of 15 traits were sufficiently high to pursue QTL discovery in this follow-up study.</p> <p>Results</p> <p>Three of the QTLs discovered relate to combined MetS-ECHO factors of "blood pressure (BP)-LV wall thickness" on chromosome 3 at 225 cM with a 2.8 LOD score, on chromosome 20 at 2.1 cM with a 2.6 LOD score; and for "LV wall thickness" factor on chromosome 16 at 113.5 with a 2.6 LOD score in whites. The remaining QTLs include one for a "body mass index-insulin (BMI-INS)" factor with a LOD score of 3.9 on chromosome 2 located at 64.8 cM; one for the same factor on chromosome 12 at 91.4 cM with a 3.3 LOD score; one for a "BP" factor on chromosome 19 located at 67.8 cM with a 3.0 LOD score. A suggestive linkage was also found for "Lipids-INS" with a 2.7 LOD score located on chromosome 11 at 113.1 cM in African Americans. Of the above QTLs, the one on chromosome 12 for "BMI-INS" is replicated in both ethnicities, (with highest LOD scores in African Americans). In addition, the QTL for "LV wall thickness" on chromosome 16q24.2-q24.3 reached its local maximum LOD score at marker D16S402, which is positioned within the 5th intron of the <it>cadherin 13 </it>gene, implicated in heart and vascular remodeling.</p> <p>Conclusion</p> <p>Our previous study and this follow-up suggest gene loci for some crucial MetS and cardiac geometry risk factors that contribute to the risk of developing heart disease.</p

Heritability of cardiovascular risk factors in a Brazilian population: Baependi Heart Study

<p>Abstract</p> <p>Background</p> <p>The heritability of cardiovascular risk factors is expected to differ between populations because of the different distribution of environmental risk factors, as well as the genetic make-up of different human populations.</p> <p>Methods</p> <p>The purpose of this analysis was to evaluate genetic and environmental influences on cardiovascular risk factor traits, using a variance component approach, by estimating the heritability of these traits in a sample of 1,666 individuals in 81 families ascertained randomly from a highly admixed population of a city in a rural area in Brazil.</p> <p>Results</p> <p>Before adjustment for sex, age, age², and age × sex interaction, polygenic heritability of systolic (SBP) and diastolic (DBP) blood pressure were 15.0% and 16.4%, waist circumference 26.1%, triglycerides 25.7%, fasting glucose 32.8%, HDL-c 31.2%, total cholesterol 28.6%, LDL-c 26.3%, BMI 39.1%. Adjustment for covariates increased polygenic heritability estimates for all traits mainly systolic and diastolic blood pressure (25.9 and 26.2%, respectively), waist circumference (40.1%), and BMI (51.0%).</p> <p>Conclusion</p> <p>Heritability estimates for cardiovascular traits in the Brazilian population are high and not significantly different from other studied worldwide populations. Mapping efforts to identify genetic loci associated with variability of these traits are warranted.</p

Weight change over five-year periods and number of components of the metabolic syndrome in a Dutch cohort

Overweight and obesity are associated with the metabolic syndrome (MetS). We studied the association of weight change over three consecutive 5-year periods with the number of MetS components in people aged 20–59 years. 5735 participants from the Doetinchem Cohort Study were included. Weight was measured in round 1 and at each 5-year interval follow-up (round 2, 3 and 4). Weight change was defined as the absolute weight change between two consecutive measurements. The number of MetS components (assessed in round 2, 3 and 4) was based on the presence of the following components of the MetS: central obesity, raised blood pressure, reduced high density lipoprotein cholesterol and elevated glucose. Associations of weight change and the number of components of the MetS were analyzed with Generalized Estimating Equations for Poisson regression, stratified for 10-year age groups. For each age group, 1 kg weight gain was positively associated with the number of components of the MetS, independent of sex and measurement round. The association was stronger in 30–39 years (adjusted rate ratio: 1.044; 95%CI: 1.040–1.049) and smaller in older age groups. Compared to stable weight (>−2.5 kg and < 2.5 kg), weight loss (≤−2.5 kg) and weight gain (≥2.5 kg) was associated with a lower and higher rate ratio respectively, for the number of components of the MetS. Our results support the independent association of weight change with the number of MetS components with a more pronounced association in younger people

Properties of local interactions and their potential value in complementing genome-wide association studies

Local interactions between neighbouring SNPs are hypothesized to be able to capture variants missing from genome-wide association studies (GWAS) via haplotype effects but have not been thoroughly explored. We have used a new high-throughput analysis tool to probe this underexplored area through full pair-wise genome scans and conventional GWAS in diastolic and systolic blood pressure and six metabolic traits in the Northern Finland Birth Cohort 1966 (NFBC1966) and the Atherosclerosis Risk in Communities study cohort (ARIC). Genome-wide significant interactions were detected in ARIC for systolic blood pressure between PLEKHA7 (a known GWAS locus for blood pressure) and GPR180 (which plays a role in vascular remodelling), and also for triglycerides as local interactions within the 11q23.3 region (replicated significantly in NFBC1966), which notably harbours several loci (BUD13, ZNF259 and APOA5) contributing to triglyceride levels. Tests of the local interactions within the 11q23.3 region conditional on the top GWAS signal suggested the presence of two independent functional variants, each with supportive evidence for their roles in gene regulation. Local interactions captured 9 additional GWAS loci identified in this study (3 significantly replicated) and 73 from previous GWAS (24 in the eight traits and 49 in related traits). We conclude that the detection of local interactions requires adequate SNP coverage of the genome and that such interactions are only likely to be detectable between SNPs in low linkage disequilibrium. Analysing local interactions is a potentially valuable complement to GWAS and can provide new insights into the biology underlying variation in complex traits

Novel quantitative trait locus is mapped to chromosome 12p11 for left ventricular mass in Dominican families: the Family Study of Stroke Risk and Carotid Atherosclerosis

<p>Abstract</p> <p>Background</p> <p>Left ventricular mass (LVM) is an important risk factor for stroke and vascular disease. The genetic basis of LVM is unclear although a high heritability has been suggested. We sought to map quantitative trait loci (QTL) for LVM using large Dominican families.</p> <p>Methods</p> <p>Probands were selected from Dominican subjects of the population-based Northern Manhattan Study (NOMAS). LVM was measured by transthoracic echocardiography. A set of 405 microsatellite markers was used to screen the whole genome among 1360 subjects from 100 Dominican families who had complete phenotype data and DNA available. A polygenic covariate screening was run to identify the significant covariates. Variance components analysis was used to estimate heritability and to detect evidence for linkage, after adjusting for significant risk factors. Ordered-subset Analysis (OSA) was conducted to identify a more homogeneous subset for stratification analysis.</p> <p>Results</p> <p>LVM had a heritability of 0.58 in the studied population (p < 0.0001). The most significant evidence for linkage was found at chromosome 12p11 (MLOD = 3.11, empirical p = 0.0003) with peak marker at D12S1042. This linkage was significantly increased in a subset of families with the high average waist circumference (MLOD = 4.45, p = 0.0045 for increase in evidence for linkage).</p> <p>Conclusion</p> <p>We mapped a novel QTL near D12S1042 for LVM in Dominicans. Enhanced linkage evidence in families with larger waist circumference suggests that gene(s) residing within the QTL interact(s) with abdominal obesity to contribute to phenotypic variation of LVM. Suggestive evidence for linkage (LOD = 1.99) has been reported at the same peak marker for left ventricular geometry in a White population from the HyperGEN study, underscoring the importance of this QTL for left ventricular phenotype. Further fine mapping and validation studies are warranted to identify the underpinning genes.</p

Pleiotropic genes for metabolic syndrome and inflammation

Metabolic syndrome (MetS) has become a health and financial burden worldwide. The MetS definition captures clustering of risk factors that predict higher risk for diabetes mellitus and cardiovascular disease. Our study hypothesis is that additional to genes influencing individual MetS risk factors, genetic variants exist that influence MetS and inflammatory markers forming a predisposing MetS genetic network. To test this hypothesis a staged approach was undertaken. (a) We analyzed 17 metabolic and inflammatory traits in more than 85,500 participants from 14 large epidemiological studies within the Cross Consortia Pleiotropy Group. Individuals classified with MetS (NCEP definition), versus those without, showed on average significantly different levels for most inflammatory markers studied. (b) Paired average correlations between 8 metabolic traits and 9 inflammatory markers from the same studies as above, estimated with two methods, and factor analyses on large simulated data, helped in identifying 8 combinations of traits for follow-up in meta-analyses, out of 130,305 possible combinations between metabolic traits and inflammatory markers studied. (c) We performed correlated meta-analyses for 8 metabolic traits and 6 inflammatory markers by using existing GWAS published genetic summary results, with about 2.5 million SNPs from twelve predominantly largest GWAS consortia. These analyses yielded 130 unique SNPs/genes with pleiotropic associations (a SNP/gene associating at least one metabolic trait and one inflammatory marker). Of them twenty-five variants (seven loci newly reported) are proposed as MetS candidates. They map to genes MACF1, KIAA0754, GCKR, GRB14, COBLL1, LOC646736-IRS1, SLC39A8, NELFE, SKIV2L, STK19, TFAP2B, BAZ1B, BCL7B, TBL2, MLXIPL, LPL, TRIB1, ATXN2, HECTD4, PTPN11, ZNF664, PDXDC1, FTO, MC4R and TOMM40. Based on large data evidence, we conclude that inflammation is a feature of MetS and several gene variants show pleiotropic genetic associations across phenotypes and might explain a part of MetS correlated genetic architecture. These findings warrant further functional investigation. (C) 2014 Elsevier Inc. All rights reserved