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Vitamin D is crucial for maintenance of musculoskeletal health, and might also have a role in extraskeletal tissues. Determinants of circulating 25-hydroxyvitamin D concentrations include sun exposure and diet, but high heritability suggests that genetic factors could also play a part. We aimed to identify common genetic variants affecting vitamin D concentrations and risk of insufficiency. We undertook a genome-wide association study of 25-hydroxyvitamin D concentrations in 33 996 individuals of European descent from 15 cohorts. Five epidemiological cohorts were designated as discovery cohorts (n=16 125), five as in-silico replication cohorts (n=9367), and five as de-novo replication cohorts (n=8504). 25-hydroxyvitamin D concentrations were measured by radioimmunoassay, chemiluminescent assay, ELISA, or mass spectrometry. Vitamin D insufficiency was defined as concentrations lower than 75 nmol/L or 50 nmol/L. We combined results of genome-wide analyses across cohorts using Z-score-weighted meta-analysis. Genotype scores were constructed for confirmed variants. Variants at three loci reached genome-wide significance in discovery cohorts for association with 25-hydroxyvitamin D concentrations, and were confirmed in replication cohorts: 4p12 (overall p=1·9×10 −109 for rs2282679, in GC); 11q12 (p=2·1×10 −27 for rs12785878, near DHCR7); and 11p15 (p=3·3×10 −20 for rs10741657, near CYP2R1). Variants at an additional locus (20q13, CYP24A1) were genome-wide significant in the pooled sample (p=6·0×10 −10 for rs6013897). Participants with a genotype score (combining the three confirmed variants) in the highest quartile were at increased risk of having 25-hydroxyvitamin D concentrations lower than 75 nmol/L (OR 2·47, 95% CI 2·20–2·78, p=2·3×10 −48) or lower than 50 nmol/L (1·92, 1·70–2·16, p=1·0×10 −26) compared with those in the lowest quartile. Variants near genes involved in cholesterol synthesis, hydroxylation, and vitamin D transport affect vitamin D status. Genetic variation at these loci identifies individuals who have substantially raised risk of vitamin D insufficiency. Full funding sources listed at end of paper (see Acknowledgments).

We carried out a genome-wide association study of serum aspartate aminotransferase (AST) activity in 866 Amish participants of the Heredity and Phenotype Intervention Heart Study and identified significant association of AST activity with a cluster of single nucleotide polymorphisms located on chromosome 10q24.1 (peak association was rs17109512; P =2.80E-14), in the vicinity of GOT1 , the gene encoding cytosolic AST (cAST). Sequencing of GOT1 revealed an in-frame deletion of three nucleic acids encoding asparagine at position 389 c.1165_1167delAAC (p.Asn389del) in the gene. Deletion carriers had significantly lower AST activity levels compared with homozygotes for the common allele (mean±s.d.: 10.0±2.8 versus 18.8±5.2 U l −1 ; P =2.80E-14). Further genotyping of the deletion in other Amish samples ( n =1932) identified an additional 20 carriers (minor allele frequency (MAF)=0.0052). The deletion was not detected in 647 outbred Caucasians. Asn at codon 389 is conserved among known mammalian cASTs. In vitro transient transfection of wild-type and mutant cAST indicated that mutant cAST protein was barely detectable in the cells. Furthermore, even after correction for cAST expression, mutant cAST had markedly diminished enzymatic activity. Remarkably, we did not find any association between the deletion and metabolic traits including serum fasting glucose or insulin, fasting and post-meal lipids, inflammatory markers, or sub-clinical markers of cardiovascular disease. In conclusion, we discovered a rare in-frame deletion in GOT1 gene, which inactivates cAST enzyme in the Old Order Amish. This finding will help us to understand structure and function of the enzyme and would be useful for predicting serum AST levels.

The genetics of human height A genome-wide association (GWA) study of more than 180,000 individuals has identified hundreds of genetic variants in at least 180 loci associated with adult human height. The loci are not clustered randomly but are enriched for genes involved in growth-related processes that influence adult height. This demonstrates that GWA studies of common human traits, and therefore of many diseases, can identify large numbers of loci that implicate potential causal genes. This very large genome-wide association study identifies hundreds of new genetic variants influencing adult height in at least 180 loci enriched for genes involved in skeletal growth defects. The results show that the likely causal gene is often located near the most strongly associated variant, that many loci have multiple independently associated variants and that associated variants are enriched for likely functional effects on genes. Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits 1 , but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait 2 , 3 . The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways ( P = 0.016) and that underlie skeletal growth defects ( P  < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Electrocardiographic PR interval measures atrio-ventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. Our genome-wide association study of over 92,000 European-descent individuals identifies 44 PR interval loci (34 novel). Examination of these loci reveals known and previously not-yet-reported biological processes involved in cardiac atrial electrical activity. Genes in these loci are over-represented in cardiac disease processes including heart block and atrial fibrillation. Variants in over half of the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with missense variants. Six additional loci were identified either by meta-analysis of ~105,000 African and European-descent individuals and/or by pleiotropic analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation. These findings implicate developmental pathways, and identify transcription factors, ion-channel genes, and cell-junction/cell-signaling proteins in atrio-ventricular conduction, identifying potential targets for drug development. Abnormal PR interval duration is associated with risk for atrial fibrillation and heart block. Here, van Setten et al. identify 44 PR interval loci in a genome-wide association study of over 92,000 individuals and find genetic overlap with QRS duration, heart rate and atrial fibrillation.

Pleiotropic genetic variants have independent effects on different phenotypes. C-reactive protein (CRP) is associated with several cardiometabolic phenotypes. Shared genetic backgrounds may partially underlie these associations. We conducted a genome-wide analysis to identify the shared genetic background of inflammation and cardiometabolic phenotypes using published genome-wide association studies (GWAS). We also evaluated whether the pleiotropic effects of such loci were biological or mediated in nature. First, we examined whether 283 common variants identified for 10 cardiometabolic phenotypes in GWAS are associated with CRP level. Second, we tested whether 18 variants identified for serum CRP are associated with 10 cardiometabolic phenotypes. We used a Bonferroni corrected p-value of 1.1×10-04 (0.05/463) as a threshold of significance. We evaluated the independent pleiotropic effect on both phenotypes using individual level data from the Women Genome Health Study. Evaluating the genetic overlap between inflammation and cardiometabolic phenotypes, we found 13 pleiotropic regions. Additional analyses showed that 6 regions (APOC1, HNF1A, IL6R, PPP1R3B, HNF4A and IL1F10) appeared to have a pleiotropic effect on CRP independent of the effects on the cardiometabolic phenotypes. These included loci where individuals carrying the risk allele for CRP encounter higher lipid levels and risk of type 2 diabetes. In addition, 5 regions (GCKR, PABPC4, BCL7B, FTO and TMEM18) had an effect on CRP largely mediated through the cardiometabolic phenotypes. In conclusion, our results show genetic pleiotropy among inflammation and cardiometabolic phenotypes. In addition to reverse causation, our data suggests that pleiotropic genetic variants partially underlie the association between CRP and cardiometabolic phenotypes.

Non-high-density lipoprotein cholesterol(NHDL) is an independent and superior predictor of CVD risk as compared to low-density lipoprotein alone. It represents a spectrum of atherogenic lipid fractions with possibly a distinct genomic signature. We performed genome-wide association studies (GWAS) to identify loci influencing baseline NHDL and its postprandial lipemic (PPL) response. We carried out GWAS in 4,241 participants of European descent. Our discovery cohort included 928 subjects from the Genetics of Lipid-Lowering Drugs and Diet Network Study. Our replication cohorts included 3,313 subjects from the Heredity and Phenotype Intervention Heart Study and Family Heart Study. A linear mixed model using the kinship matrix was used for association tests. The best association signal was found in a tri-genic region at RHOQ - PIGF - CRIPT for baseline NHDL (lead SNP rs6544903, discovery p  = 7e−7, MAF = 2 %; validation p  = 6e−4 at 0.1 kb upstream neighboring SNP rs3768725, and 5e−4 at 0.7 kb downstream neighboring SNP rs6733143, MAF = 10 %). The lead and neighboring SNPs were not perfect surrogate proxies to each other ( D ′ = 1, r 2  = 0.003) but they seemed to be partially dependent (likelihood ration test p  = 0.04). Other suggestive loci (discovery p  < 1e−6) included LOC100419812 and LOC100288337 for baseline NHDL, and LOC100420502 and CDH13 for NHDL PPL response that were not replicated ( p  > 0.01). The current and first GWAS of NHDL yielded an interesting common variant in RHOQ - PIGF - CRIPT influencing baseline NHDL levels. Another common variant in CDH13 for NHDL response to dietary high-fat intake challenge was also suggested. Further validations for both loci from large independent studies, especially interventional studies, are warranted.

Genome-Wide Association Scan Identifies Variants near Matrix Metalloproteinase ( MMP ) Genes on Chromosome 11q21–22 Strongly Associated With Serum MMP-1 Levels Yu-Ching Cheng, PhD ; Wen-Hong L. Kao, PhD ; Braxton D. Mitchell, PhD ; Jeffrey R. O'Connell, PhD ; Haiqing Shen, PhD ; Patrick F. McArdle, PhD ; Quince Gibson, MBA ; Kathleen A. Ryan, MPH ; Alan R. Shuldiner, MD and Toni I. Pollin, PhD From the Division of Endocrinology, Diabetes and Nutrition (Y.C.C., B.D.M., J.R.o.C., H.S., P.F.M.A., Q.G., K.A.R., A.R.S., T.I.P.), School of Medicine, University of Maryland, Baltimore, Md; Department of Epidemiology (W.H.L.K.), Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Md; and Geriatric Research and Education Clinical Center (A.R.S.), Baltimore, Veterans Administration Medical Center, Baltimore, Md. Correspondence to Yu-Ching Cheng, PhD, 660 W Redwood St, Room 478, Baltimore, MD 21201. E-mail ycheng{at}medicine.umaryland.edu Received November 12, 2008; accepted April 30, 2009. Background— Matrix metalloproteinase (MMP)-1 may play a role in cardiovascular disease susceptibility by influencing plaque rupture via its ability to degrade extracellular collagens. Methods and Results— We performed a genome-wide association analysis of circulating MMP-1 levels using 500 K single-nucleotide polymorphisms (SNPs) to identify genes influencing variation in serum MMP-1 levels in 778 healthy Amish adults. Serum MMP-1 levels, logarithm transformed, and adjusted for age and sex, were screened for association with SNPs using mixed-model variance components to account for familial relatedness. Median MMP-1 level was 3.05 ng/mL (interquartile range: 1.82 to 5.04 ng/mL) with an estimated heritability of 81% ( P <0.0001). Serum MMP-1 levels were strongly associated with a cluster of 179 SNPs extending over an 11.5-megabase region on chromosome 11q. The peak association was with rs495366 ( P =5.73 x 10 –34 ), located within the region between MMP-1 and MMP-3 and having a minor allele frequency of 0.36. Two other SNPs within the 11q region, rs12289128 and rs11226373, were strongly associated with MMP-1 levels after accounting for rs495366 ( P 10 –7 ). These 3 SNPs explained 31% of the variance in MMP-1 levels after adjusting for age and sex. Conclusions— This study provides strong evidence that the serum MMP-1 level is highly heritable and that SNPs near MMPs on chromosome 11q explain a significant portion of the variation in MMP-1 levels. Identification of the genetic variants that influence MMP-1 levels may provide insights into genetic mechanisms of cardiovascular disease. Key Words: epidemiology • genetics • metalloproteinases • population   CLINICAL PERSPECTIVE The online-only Data Supplement is available at http://circgenetics.ahajournals.org/cgi/content/full/CIRCGENETICS.108.834986/DC1. Home | Subscriptions | Archives | Feedback | Authors | Help | Circulation Journals Home | AHA Journals Home | Search Copyright © 2009 American Heart Association, Inc. All rights reserved. Unauthorized use prohibited. var _rsCI=\"us-lippincott\"; var _rsCG=\"0\"; var _rsDN=\"//secure-us.imrworldwide.com/\"; var _rsSE=1; var _rsSM=1.0;

Genome-wide association studies have had great success in identifying human genetic variants associated with disease, disease risk factors, and other biomedical phenotypes. Many variants are associated with multiple traits, even after correction for trait-trait correlation. Discovering subsets of variants associated with a shared subset of phenotypes could help reveal disease mechanisms, suggest new therapeutic options, and increase the power to detect additional variants with similar pattern of associations. Here we introduce two methods based on a Bayesian framework, SNP And Pleiotropic PHenotype Organization (SAPPHO), one modeling independent phenotypes (SAPPHO-I) and the other incorporating a full phenotype covariance structure (SAPPHO-C). These two methods learn patterns of pleiotropy from genotype and phenotype data, using identified associations to discover additional associations with shared patterns. The SAPPHO methods, along with other recent approaches for pleiotropic association tests, were assessed using data from the Atherosclerotic Risk in Communities (ARIC) study of 8,000 individuals, whose gold-standard associations were provided by meta-analysis of 40,000 to 100,000 individuals from the CHARGE consortium. Using power to detect gold-standard associations at genome-wide significance (0.05 family-wise error rate) as a metric, SAPPHO performed best. The SAPPHO methods were also uniquely able to select the most significant variants in a parsimonious model, excluding other less likely variants within a linkage disequilibrium block. For meta-analysis, the SAPPHO methods implement summary modes that use sufficient statistics rather than full phenotype and genotype data. Meta-analysis applied to CHARGE detected 16 additional associations to the gold-standard loci, as well as 124 novel loci, at 0.05 false discovery rate. Reasons for the superior performance were explored by performing simulations over a range of scenarios describing different genetic architectures. With SAPPHO we were able to learn genetic structures that were hidden using the traditional univariate tests.

Electrocardiographic PR interval measures atrial and atrioventricular depolarization and conduction, and abnormal PR interval is a risk factor for atrial fibrillation and heart block. We performed a genome-wide association study in over 92,000 individuals of European descent and identified 44 loci associated with PR interval (34 novel). Examination of the 44 loci revealed known and novel biological processes involved in cardiac atrial electrical activity, and genes in these loci were highly over-represented in several cardiac disease processes. Nearly half of the 61 independent index variants in the 44 loci were associated with atrial or blood transcript expression levels, or were in high linkage disequilibrium with one or more missense variants. Cardiac regulatory regions of the genome as measured by cardiac DNA hypersensitivity sites were enriched for variants associated with PR interval, compared to non-cardiac regulatory regions. Joint analyses combining PR interval with heart rate, QRS interval, and atrial fibrillation identified additional new pleiotropic loci. The majority of associations discovered in European-descent populations were also present in African-American populations. Meta-analysis examining over 105,000 individuals of African and European descent identified additional novel PR loci. These additional analyses identified another 13 novel loci. Together, these findings underscore the power of GWAS to extend knowledge of the molecular underpinnings of clinical processes.

Summary Improving the rate and extent of faecal decomposition in basic forms of sanitation such as pit latrines would benefit around 1.7 billion users worldwide, but to do so requires a major advance in our understanding of the biology of these systems. As a critical first step, bacterial diversity and composition was studied in 30 latrines in Tanzania and Vietnam using pyrosequencing of 16S rRNA genes, and correlated with a number of intrinsic environmental factors such as pH, temperature, organic matter content/composition and geographical factors. Clear differences were observed at the operational taxonomic unit, family and phylum level in terms of richness and community composition between latrines in Tanzania and Vietnam. The results also clearly show that environmental variables, particularly substrate type and availability, can exert a strong structuring influence on bacterial communities in latrines from both countries. The origins and significance of these environmental differences are discussed. This work describes the bacterial ecology of pit latrines in combination with inherent latrine characteristics at an unprecedented level of detail. As such, it provides useful baseline information for future studies that aim to understand the factors that affect decomposition rates in pit latrines. This work describes the bacterial ecology of pit latrines in combination with inherent latrine characteristics at an unprecedented level of detail. As such, it provides useful baseline information for future studies that aim to understand the factors that affect decomposition rates in pit latrines