We performed genome-wide meta-analysis of lipid traits on three samples of Mexican and Mexican American ancestry comprising 4,383 individuals, and followed up significant and highly suggestive associations in three additional Hispanic samples comprising 7,876 individuals. Genome-wide significant signals were observed in or near CELSR2, ZNF259/APOA5, KANK2/DOCK6 and NCAN/MAU2 for total cholesterol, LPL, ABCA1, ZNF259/APOA5, LIPC and CETP for HDL cholesterol, CELSR2, APOB and NCAN/MAU2 for LDL cholesterol, and GCKR, TRIB1, ZNF259/APOA5 and NCAN/MAU2 for triglycerides. Linkage disequilibrium and conditional analyses indicate that signals observed at ABCA1 and LIPC for HDL cholesterol and NCAN/MAU2 for triglycerides are independent of previously reported lead SNP associations. Analyses of lead SNPs from the European Global Lipids Genetics Consortium (GLGC) dataset in our Hispanic samples show remarkable concordance of direction of effects as well as strong correlation in effect sizes. A meta-analysis of the European GLGC and our Hispanic datasets identified five novel regions reaching genome-wide significance: two for total cholesterol (FN1 and SAMM50), two for HDL cholesterol (LOC100996634 and COPB1) and one for LDL cholesterol (LINC00324/CTC1/PFAS). The top meta-analysis signals were found to be enriched for SNPs associated with gene expression in a tissue-specific fashion, suggesting an enrichment of tissue-specific function in lipid-associated loci.

Circulating blood cell counts and indices are important indicators of hematopoietic function and a number of clinical parameters, such as blood oxygen-carrying capacity, inflammation, and hemostasis. By performing whole-exome sequence association analyses of hematologic quantitative traits in 15,459 community-dwelling individuals, followed by in silico replication in up to 52,024 independent samples, we identified two previously undescribed coding variants associated with lower platelet count: a common missense variant in CPS1 (rs1047891, MAF = 0.33, discovery + replication p = 6.38 × 10(-10)) and a rare synonymous variant in GFI1B (rs150813342, MAF = 0.009, discovery + replication p = 1.79 × 10(-27)). By performing CRISPR/Cas9 genome editing in hematopoietic cell lines and follow-up targeted knockdown experiments in primary human hematopoietic stem and progenitor cells, we demonstrate an alternative splicing mechanism by which the GFI1B rs150813342 variant suppresses formation of a GFI1B isoform that preferentially promotes megakaryocyte differentiation and platelet production. These results demonstrate how unbiased studies of natural variation in blood cell traits can provide insight into the regulation of human hematopoiesis.

Acculturation to the U.S. is associated with increased risk of cardiovascular disease, but the etiologic pathways are not fully understood. Plasma fatty acid levels exhibit ethnic differences and are emerging as biomarkers and predictors of cardiovascular disease risk. Thus, plasma fatty acids may represent one pathway underlying the association between acculturation and cardiovascular disease. We investigated the cross-sectional relationship between acculturation and plasma phospholipid fatty acids in a diverse sample of Hispanic- and Chinese-American adults.

Previously identified single nucleotide polymorphisms (SNPs) in genome wide association studies (GWAS) of cardiovascular disease (CVD) in participants of mostly European descent were tested for association with subclinical cardiovascular disease (sCVD), coronary artery calcium score (CAC) and carotid intima media thickness (CIMT) in the Multi-Ethnic Study of Atherosclerosis (MESA). The data in this data in brief article correspond to the article Common Genetic Variants and Subclinical Atherosclerosis: The Multi-Ethnic Study of Atherosclerosis [1]. This article includes the demographic information of the participants analyzed in the article as well as graphical displays and data tables of the association of the selected SNPs with CAC and of the meta-analysis across ethnicities of the association of CIMT-c (common carotid), CIMT-I (internal carotid), CAC-d (CAC as dichotomous variable with CAC>0) and CAC-c (CAC as continuous variable, the log of the raw CAC score plus one) and CVD. The data tables corresponding to the 9p21 fine mapping experiment as well as the power calculations referenced in the article are also included.

Copy number variants (CNVs) have been proposed as a possible source of 'missing heritability' in complex human diseases. Two studies of type 1 diabetes (T1D) found null associations with common copy number polymorphisms, but CNVs of low frequency and high penetrance could still play a role. We used the Log-R-ratio intensity data from a dense single nucleotide polymorphism (SNP) array, ImmunoChip, to detect rare CNV deletions (rDELs) and duplications (rDUPs) in 6808 T1D cases, 9954 controls and 2206 families with T1D-affected offspring. Initial analyses detected CNV associations. However, these were shown to be false-positive findings, failing replication with polymerase chain reaction. We developed a pipeline of quality control (QC) tests that were calibrated using systematic testing of sensitivity and specificity. The case-control odds ratios (OR) of CNV burden on T1D risk resulting from this QC pipeline converged on unity, suggesting no global frequency difference in rDELs or rDUPs. There was evidence that deletions could impact T1D risk for a small minority of cases, with enrichment for rDELs longer than 400 kb (OR = 1.57, P = 0.005). There were also 18 de novo rDELs detected in affected offspring but none for unaffected siblings (P = 0.03). No specific CNV regions showed robust evidence for association with T1D, although frequencies were lower than expected (most less than 0.1%), substantially reducing statistical power, which was examined in detail. We present an R-package, plumbCNV, which provides an automated approach for QC and detection of rare CNVs that can facilitate equivalent analyses of large-scale SNP array datasets.

The incidence of type 1 diabetes is rising worldwide, particularly in young children. Since type 1 diabetes is preceded by autoimmunity to islet antigens, there must be a consequent increase in the incidence of islet autoimmunity in young children or a more rapid rate of progression to diabetes once islet autoimmunity initiates. This study was to determine whether the incidence of islet autoimmunity or the rate of progression from autoimmunity to diabetes onset has changed over a 20-year period in children genetically predisposed to type 1 diabetes. Between 1989 and 2010, children who were first-degree relatives of patients with type 1 diabetes and who were born in Germany were prospectively followed from birth without intervention. A total of 324 children (BABYDIAB study) born between 1989 and 2000 and 216 children (TEDDY study) born between 2004 and 2010 with matched HLA genotypes were recruited before age 3 months and included for analysis. Children were followed for the development of autoantibodies to insulin, GAD, and IA-2, and for progression to diabetes. The cumulative frequency of diabetes by age 4 years was 2.5% (95% CI 0.8-4.2%) in BABYDIAB children and 6.2% (95% CI 2.3-10.1%) in TEDDY children (p = 0.03). The cumulative frequency of islet autoantibodies by age 4 years was similar in the children from both studies (11.3% vs 13.9%). Progression to diabetes from the development of islet autoantibodies was markedly increased in autoantibody-positive children from the more recently recruited TEDDY cohort (50% progression within 85.2 months for BABYDIAB children vs 9.6 months for TEDDY children; p = 0.009), also if children were further selected on the basis of high-risk HLA genotypes or the development of autoantibodies to multiple islet antigens (p = 0.01). The findings suggest that recent increasing incidence of type 1 diabetes in young children could be due to weakening of mechanisms that normally regulate autoimmune destruction of islet beta cells.

The National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK) Central Repositories, part of the National Institutes of Health (NIH), are an important resource available to researchers and the general public. The Central Repositories house samples, genetic data, phenotypic data, and study documentation from >100 NIDDK-funded clinical studies, in areas such as diabetes, digestive disease, and liver disease research. The Central Repositories also have an exceptionally rich collection of studies related to kidney disease, including the Modification of Diet in Renal Disease landmark study and recent data from the Chronic Renal Insufficiency Cohort and CKD in Children Cohort studies. The data are carefully curated and linked to the samples from the study. The NIDDK is working to make the materials and data accessible to researchers. The Data Repositories continue to improve flexible online searching tools that help researchers identify the samples or data of interest, and NIDDK has created several different paths to access the data and samples, including some funding initiatives. Over the past several years, the Central Repositories have seen steadily increasing interest and use of the stored materials. NIDDK plans to make more collections available and do more outreach and education about use of the datasets to the nephrology research community in the future to enhance the value of this resource.

Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of The Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10(-4)), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.

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.

Background: Over 90 regions of the genome have been associated with lung function to date, many of which have also been implicated in chronic obstructive pulmonary disease. Methods: We carried out meta-analyses of exome array data and three lung function measures: forced expiratory volume in one second (FEV 1), forced vital capacity (FVC) and the ratio of FEV 1 to FVC (FEV 1/FVC). These analyses by the SpiroMeta and CHARGE consortia included 60,749 individuals of European ancestry from 23 studies, and 7,721 individuals of African Ancestry from 5 studies in the discovery stage, with follow-up in up to 111,556 independent individuals. Results: We identified significant (P<2·8x10 -7) associations with six SNPs: a nonsynonymous variant in RPAP1, which is predicted to be damaging, three intronic SNPs ( SEC24C, CASC17 and UQCC1) and two intergenic SNPs near to LY86 and FGF10. Expression quantitative trait loci analyses found evidence for regulation of gene expression at three signals and implicated several genes, including TYRO3 and PLAU. Conclusions: Further interrogation of these loci could provide greater understanding of the determinants of lung function and pulmonary disease.

Using the Immunochip custom SNP array, which was designed for dense genotyping of 186 loci identified through genome-wide association studies (GWAS), we analyzed 11,475 individuals with rheumatoid arthritis (cases) of European ancestry and 15,870 controls for 129,464 markers. We combined these data in a meta-analysis with GWAS data from additional independent cases (n = 2,363) and controls (n = 17,872). We identified 14 new susceptibility loci, 9 of which were associated with rheumatoid arthritis overall and five of which were specifically associated with disease that was positive for anticitrullinated peptide antibodies, bringing the number of confirmed rheumatoid arthritis risk loci in individuals of European ancestry to 46. We refined the peak of association to a single gene for 19 loci, identified secondary independent effects at 6 loci and identified association to low-frequency variants at 4 loci. Bioinformatic analyses generated strong hypotheses for the causal SNP at seven loci. This study illustrates the advantages of dense SNP mapping analysis to inform subsequent functional investigations.

Body size is postulated to modulate type 1 diabetes as either a trigger of islet autoimmunity or an accelerator to clinical onset after seroconversion. As overweight and obesity continue to rise among children, the aim of this study was to determine whether human leukocyte antigen DQ (HLA-DQ) genotypes may be related to body size among children genetically at risk for type 1 diabetes.

Despite the substantial burden of hypertension in US minority populations, few genetic studies of blood pressure have been conducted in Hispanics and African Americans, and it is unclear whether many of the established loci identified in European-descent populations contribute to blood pressure variation in non-European descent populations. Using the Metabochip array, we sought to characterize the genetic architecture of previously identified blood pressure loci, and identify novel cardiometabolic variants related to systolic and diastolic blood pressure in a multi-ethnic US population including Hispanics (n = 19,706) and African Americans (n = 18,744). Several known blood pressure loci replicated in African Americans and Hispanics. Fourteen variants in three loci (KCNK3, FGF5, ATXN2-SH2B3) were significantly associated with blood pressure in Hispanics. The most significant diastolic blood pressure variant identified in our analysis, rs2586886/KCNK3 (P = 5.2 x 10-9), also replicated in independent Hispanic and European-descent samples. African American and trans-ethnic meta-analysis data identified novel variants in the FGF5, ULK4 and HOXA-EVX1 loci, which have not been previously associated with blood pressure traits. Our identification and independent replication of variants in KCNK3, a gene implicated in primary hyperaldosteronism, as well as a variant in HOTTIP (HOXA-EVX1) suggest that further work to clarify the roles of these genes may be warranted. Overall, our findings suggest that loci identified in European descent populations also contribute to blood pressure variation in diverse populations including Hispanics and African Americans-populations that are understudied for hypertension genetic risk factors.

Massively parallel whole-genome sequencing (WGS) data have ushered in a new era in human genetics. These data are now being used to understand the role of rare variants in complex traits and to advance the goals of precision medicine. The technological and computing advances that have enabled us to generate WGS data on thousands of individuals have also outpaced our ability to perform analyses in scientifically and statistically rigorous and thoughtful ways. The past several years have witnessed the application of whole-exome sequencing (WES) to complex traits and diseases. From our analysis of NHLBI Exome Sequencing Project (ESP) data, not only have a number of important disease and complex trait association findings emerged, but our collective experience offers some valuable lessons for WGS initiatives. These include caveats associated with generating automated pipelines for quality control and analysis of rare variants; the importance of studying minority populations; sample size requirements and efficient study designs for identifying rare-variant associations; and the significance of incidental findings in population-based genetic research. With the ESP as an example, we offer guidance and a framework on how to conduct a large-scale association study in the era of WGS.

Individuals with exceptional longevity and their offspring have significantly larger high-density lipoprotein concentrations (HDL-C) particle sizes due to the increased homozygosity for the I405V variant in the cholesteryl ester transfer protein (CETP) gene. In this study, we investigate the association of CETP and HDL-C further to identify novel, independent CETP variants associated with HDL-C in humans.

Glycated hemoglobin (HbA1c) is used to diagnose type 2 diabetes (T2D) and assess glycemic control in patients with diabetes. Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic variants. These variants proved to be classifiable by their likely biological action as erythrocytic (also associated with erythrocyte traits) or glycemic (associated with other glucose-related traits). In this study, we tested the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated with HbA1c and that HbA1c variants implicated in erythrocytic biology would affect the diagnostic accuracy of HbA1c. We therefore expanded the number of HbA1c-associated loci and tested the effect of genetic risk-scores comprised of erythrocytic or glycemic variants on incident diabetes prediction and on prevalent diabetes screening performance. Throughout this multiancestry study, we kept a focus on interancestry differences in HbA1c genetics performance that might influence race-ancestry differences in health outcomes.

Little is known regarding the epigenetic basis of atherosclerosis. Here we present the CD14+ blood monocyte transcriptome and epigenome signatures associated with human atherosclerosis. The transcriptome signature includes transcription coactivator, ARID5B, which is known to form a chromatin derepressor complex with a histone H3K9Me2-specific demethylase and promote adipogenesis and smooth muscle development. ARID5B CpG (cg25953130) methylation is inversely associated with both ARID5B expression and atherosclerosis, consistent with this CpG residing in an ARID5B enhancer region, based on chromatin capture and histone marks data. Mediation analysis supports assumptions that ARID5B expression mediates effects of cg25953130 methylation and several cardiovascular disease risk factors on atherosclerotic burden. In lipopolysaccharide-stimulated human THP1 monocytes, ARID5B knockdown reduced expression of genes involved in atherosclerosis-related inflammatory and lipid metabolism pathways, and inhibited cell migration and phagocytosis. These data suggest that ARID5B expression, possibly regulated by an epigenetically controlled enhancer, promotes atherosclerosis by dysregulating immunometabolism towards a chronic inflammatory phenotype.The molecular mechanisms mediating the impact of environmental factors in atherosclerosis are unclear. Here, the authors examine CD14+ blood monocyte's transcriptome and epigenome signatures to find differential methylation and expression of ARID5B to be associated with human atherosclerosis.

Genome-wide association studies have identified numerous genetic loci for spirometic measures of pulmonary function, forced expiratory volume in one second (FEV(1)), and its ratio to forced vital capacity (FEV(1)/FVC). Given that cigarette smoking adversely affects pulmonary function, we conducted genome-wide joint meta-analyses (JMA) of single nucleotide polymorphism (SNP) and SNP-by-smoking (ever-smoking or pack-years) associations on FEV(1) and FEV(1)/FVC across 19 studies (total N = 50,047). We identified three novel loci not previously associated with pulmonary function. SNPs in or near DNER (smallest P(JMA = )5.00×10(-11)), HLA-DQB1 and HLA-DQA2 (smallest P(JMA = )4.35×10(-9)), and KCNJ2 and SOX9 (smallest P(JMA = )1.28×10(-8)) were associated with FEV(1)/FVC or FEV(1) in meta-analysis models including SNP main effects, smoking main effects, and SNP-by-smoking (ever-smoking or pack-years) interaction. The HLA region has been widely implicated for autoimmune and lung phenotypes, unlike the other novel loci, which have not been widely implicated. We evaluated DNER, KCNJ2, and SOX9 and found them to be expressed in human lung tissue. DNER and SOX9 further showed evidence of differential expression in human airway epithelium in smokers compared to non-smokers. Our findings demonstrated that joint testing of SNP and SNP-by-environment interaction identified novel loci associated with complex traits that are missed when considering only the genetic main effects.

Genome-wide association studies (GWAS) have identified common variants of modest-effect size at hundreds of loci for common autoimmune diseases; however, a substantial fraction of heritability remains unexplained, to which rare variants may contribute. To discover rare variants and test them for association with a phenotype, most studies re-sequence a small initial sample size and then genotype the discovered variants in a larger sample set. This approach fails to analyse a large fraction of the rare variants present in the entire sample set. Here we perform simultaneous amplicon-sequencing-based variant discovery and genotyping for coding exons of 25 GWAS risk genes in 41,911 UK residents of white European origin, comprising 24,892 subjects with six autoimmune disease phenotypes and 17,019 controls, and show that rare coding-region variants at known loci have a negligible role in common autoimmune disease susceptibility. These results do not support the rare-variant synthetic genome-wide-association hypothesis (in which unobserved rare causal variants lead to association detected at common tag variants). Many known autoimmune disease risk loci contain multiple, independently associated, common and low-frequency variants, and so genes at these loci are a priori stronger candidates for harbouring rare coding-region variants than other genes. Our data indicate that the missing heritability for common autoimmune diseases may not be attributable to the rare coding-region variant portion of the allelic spectrum, but perhaps, as others have proposed, may be a result of many common-variant loci of weak effect.

A genome-wide association scan of the Genetics of Kidneys in Diabetes (GoKinD) collections identified four novel susceptibility loci, located on chromosomes 7p14.3, 9q21.32, 11p15.4, and 13q33.3 associated with type 1 diabetic nephropathy. A recent evaluation of these loci in Japanese patients with type 2 diabetes supported an association at the 13q33.3 locus. To follow up these findings, we determined whether single-nucleotide polymorphisms (SNPs) at these same four loci were associated with diabetic nephropathy in the Joslin Study of Genetics of Nephropathy in Type 2 Diabetes collection. A total of 6 SNPs across these loci were genotyped in 646 normoalbuminuric controls and in 743 nephropathy patients of European ancestry. A significant association was identified at the 13q33.3 locus (rs9521445: P = 4.4 × 10(-3)). At this same locus, rs1411766 was also significantly associated with type 2 diabetic nephropathy (P = 0.03). Meta-analysis of these data with those of the Japanese and GoKinD collections significantly improved the strength of the association (P = 9.7 × 10(-9)). In addition, there was a significant association at the 11p15.4 locus (rs451041: P = 0.02). Thus, associations identified in the GoKinD collections on chromosomes 11p15.4 (near the CARS gene) and 13q33.3 (within an intergenic region between MYO16 and IRS2) are susceptibility loci of kidney disease common to both type 1 and 2 diabetes.