Genome-wide association scan meta-analysis identifies three Loci influencing adiposity and fat distribution.

To identify genetic loci influencing central obesity and fat distribution, we performed a meta-analysis of 16 genome-wide association studies (GWAS, N = 38,580) informative for adult waist circumference (WC) and waist-hip ratio (WHR). We selected 26 SNPs for follow-up, for which the evidence of association with measures of central adiposity (WC and/or WHR) was strong and disproportionate to that for overall adiposity or height. Follow-up studies in a maximum of 70,689 individuals identified two loci strongly associated with measures of central adiposity; these map near TFAP2B (WC, P = 1.9x10(-11)) and MSRA (WC, P = 8.9x10(-9)). A third locus, near LYPLAL1, was associated with WHR in women only (P = 2.6x10(-8)). The variants near TFAP2B appear to influence central adiposity through an effect on overall obesity/fat-mass, whereas LYPLAL1 displays a strong female-only association with fat distribution. By focusing on anthropometric measures of central obesity and fat distribution, we have identified three loci implicated in the regulation of human adiposity

Common Variants at 10 Genomic Loci Influence Hemoglobin A(1C) Levels via Glycemic and Nonglycemic Pathways

OBJECTIVE Glycated hemoglobin (HbA1c), used to monitor and diagnose diabetes, is influenced by average glycemia over a 2- to 3-month period. Genetic factors affecting expression, turnover, and abnormal glycation of hemoglobin could also be associated with increased levels of HbA1c. We aimed to identify such genetic factors and investigate the extent to which they influence diabetes classification based on HbA1c levels. RESEARCH DESIGN AND METHODS We studied associations with HbA1c in up to 46,368 nondiabetic adults of European descent from 23 genome-wide association studies (GWAS) and 8 cohorts with de novo genotyped single nucleotide polymorphisms (SNPs). We combined studies using inverse-variance meta-analysis and tested mediation by glycemia using conditional analyses. We estimated the global effect of HbA1c loci using a multilocus risk score, and used net reclassification to estimate genetic effects on diabetes screening. RESULTS Ten loci reached genome-wide significant association with HbA1c, including six new loci near FN3K (lead SNP/P value, rs1046896/P = 1.6 × 10−26), HFE (rs1800562/P = 2.6 × 10−20), TMPRSS6 (rs855791/P = 2.7 × 10−14), ANK1 (rs4737009/P = 6.1 × 10−12), SPTA1 (rs2779116/P = 2.8 × 10−9) and ATP11A/TUBGCP3 (rs7998202/P = 5.2 × 10−9), and four known HbA1c loci: HK1 (rs16926246/P = 3.1 × 10−54), MTNR1B (rs1387153/P = 4.0 × 10−11), GCK (rs1799884/P = 1.5 × 10−20) and G6PC2/ABCB11 (rs552976/P = 8.2 × 10−18). We show that associations with HbA1c are partly a function of hyperglycemia associated with 3 of the 10 loci (GCK, G6PC2 and MTNR1B). The seven nonglycemic loci accounted for a 0.19 (% HbA1c) difference between the extreme 10% tails of the risk score, and would reclassify ∼2% of a general white population screened for diabetes with HbA1c. CONCLUSIONS GWAS identified 10 genetic loci reproducibly associated with HbA1c. Six are novel and seven map to loci where rarer variants cause hereditary anemias and iron storage disorders. Common variants at these loci likely influence HbA1c levels via erythrocyte biology, and confer a small but detectable reclassification of diabetes diagnosis by HbA1c

Genome-wide association analysis of total cholesterol and high-density lipoprotein cholesterol levels using the Framingham Heart Study data

<p>Abstract</p> <p>Background</p> <p>Cholesterol concentrations in blood are related to cardiovascular diseases. Recent genome-wide association studies (GWAS) of cholesterol levels identified a number of single-locus effects on total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C) levels. Here, we report single-locus and epistasis SNP effects on TC and HDL-C using the Framingham Heart Study (FHS) data.</p> <p>Results</p> <p>Single-locus effects and pairwise epistasis effects of 432,096 SNP markers were tested for their significance on log-transformed TC and HDL-C levels. Twenty nine additive SNP effects reached single-locus genome-wide significance (p < 7.2 × 10^-8) and no dominance effect reached genome-wide significance. Two new gene regions were detected, the <it>RAB3GAP1-R3HDM1-LCT-MCM6 </it>region of chr02 for TC identified by six new SNPs, and the <it>OSBPL8-ZDHHC17 </it>region (chr12) for HDL-C identified by one new SNP. The remaining 22 single-locus SNP effects confirmed previously reported genes or gene regions. For TC, three SNPs identified two gene regions that were tightly linked with previously reported genes associated with TC, including rs599839 that was 10 bases downstream <it>PSRC1 </it>and 3.498 kb downstream <it>CELSR2</it>, rs4970834 in <it>CELSR2</it>, and rs4245791 in <it>ABCG8 </it>that slightly overlapped with <it>ABCG5</it>. For HDL-C, <it>LPL </it>was confirmed by 12 SNPs 8-45 kb downstream, <it>CETP </it>by two SNPs 0.5-11 kb upstream, and the <it>LIPG-ACAA2 </it>region by five SNPs inside this region. Two epistasis effects on TC and thirteen epistasis effects on HDL-C reached the significance of "suggestive linkage". The most significant epistasis effect (p = 5.72 × 10^-13) was close to reaching "significant linkage" and was a dominance × dominance effect of HDL-C between <it>LMBRD1 </it>(chr06) and the <it>LRIG3 </it>region (chr12), and this pair of gene regions had six other D × D effects with "suggestive linkage".</p> <p>Conclusions</p> <p>Genome-wide association analysis of the FHS data detected two new gene regions with genome-wide significance, detected epistatic SNP effects on TC and HDL-C with the significance of suggestive linkage in seven pairs of gene regions, and confirmed some previously reported gene regions associated with TC and HDL-C.</p

Association between Urinary Excretion of Cortisol and Markers of Oxidatively Damaged DNA and RNA in Humans

Chronic psychological stress is associated with accelerated aging, but the underlying biological mechanisms are not known. Prolonged elevations of the stress hormone cortisol is suspected to play a critical role. Through its actions, cortisol may potentially induce oxidatively generated damage to cellular constituents such as DNA and RNA, a phenomenon which has been implicated in aging processes. We investigated the relationship between 24 h excretion of urinary cortisol and markers of oxidatively generated DNA and RNA damage, 8-oxo-7,8-dihydro-2′-deoxyguanosine and 8-oxo-7,8-dihydroguanosine, in a sample of 220 elderly men and women (age 65 – 83 years). We found a robust association between the excretion of cortisol and the oxidation markers (R2 = 0.15, P<0.001 for both markers). Individuals in the highest quartile of cortisol excretion had a 57% and 61% higher median excretion of the DNA and RNA oxidation marker, respectively, than individuals in the lowest quartile. The finding adds support to the hypothesis that cortisol-induced damage to DNA/RNA is an explanatory factor in the complex relation between stress, aging and disease

Sequential Use of Transcriptional Profiling, Expression Quantitative Trait Mapping, and Gene Association Implicates MMP20 in Human Kidney Aging

Kidneys age at different rates, such that some people show little or no effects of aging whereas others show rapid functional decline. We sequentially used transcriptional profiling and expression quantitative trait loci (eQTL) mapping to narrow down which genes to test for association with kidney aging. We first performed whole-genome transcriptional profiling to find 630 genes that change expression with age in the kidney. Using two methods to detect eQTLs, we found 101 of these age-regulated genes contain expression-associated SNPs. We tested the eQTLs for association with kidney aging, measured by glomerular filtration rate (GFR) using combined data from the Baltimore Longitudinal Study of Aging (BLSA) and the InCHIANTI study. We found a SNP association (rs1711437 in MMP20) with kidney aging (uncorrected p = 3.6×10−5, empirical p = 0.01) that explains 1%–2% of the variance in GFR among individuals. The results of this sequential analysis may provide the first evidence for a gene association with kidney aging in humans

Red Blood Cell Fatty Acid Patterns and Acute Coronary Syndrome

BACKGROUND:Assessment of coronary heart disease (CHD) risk is typically based on a weighted combination of standard risk factors. We sought to determine the extent to which a lipidomic approach based on red blood cell fatty acid (RBC-FA) profiles could discriminate acute coronary syndrome (ACS) cases from controls, and to compare RBC-FA discrimination with that based on standard risk factors. METHODOLOGY/PRINCIPAL FINDINGS:RBC-FA profiles were measured in 668 ACS cases and 680 age-, race- and gender-matched controls. Multivariable logistic regression models based on FA profiles (FA) and standard risk factors (SRF) were developed on a random 2/3(rds) derivation set and validated on the remaining 1/3(rd). The area under receiver operating characteristic (ROC) curves (c-statistics), misclassification rates, and model calibrations were used to evaluate the individual and combined models. The FA discriminated cases from controls better than the SRF (c = 0.85 vs. 0.77, p = 0.003) and the FA profile added significantly to the standard model (c = 0.88 vs. 0.77, p<0.0001). Hosmer-Lemeshow calibration was poor for the FA model alone (p = 0.01), but acceptable for both the SRF (p = 0.30) and combined models (p = 0.22). Misclassification rates were 23%, 29% and 20% for FA, the SRF, and the combined models, respectively. CONCLUSIONS/SIGNIFICANCE:RBC-FA profiles contribute significantly to the discrimination of ACS cases, especially when combined with standard risk factors. The utility of FA patterns in risk prediction warrants further investigation