The Type 1 Diabetes Genetics Consortium (T1DGC) has assembled and genotyped a large collection of multiplex families for the purpose of mapping genomic regions linked to type 1 diabetes. In the current study, we tested for evidence of loci associated with type 1 diabetes utilizing genome-wide linkage scan data and family-based association methods.

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.

To discover new rheumatoid arthritis (RA) risk loci, we systematically examined 370 SNPs from 179 independent loci with P < 0.001 in a published meta-analysis of RA genome-wide association studies (GWAS) of 3,393 cases and 12,462 controls. We used Gene Relationships Across Implicated Loci (GRAIL), a computational method that applies statistical text mining to PubMed abstracts, to score these 179 loci for functional relationships to genes in 16 established RA disease loci. We identified 22 loci with a significant degree of functional connectivity. We genotyped 22 representative SNPs in an independent set of 7,957 cases and 11,958 matched controls. Three were convincingly validated: CD2-CD58 (rs11586238, P = 1 x 10(-6) replication, P = 1 x 10(-9) overall), CD28 (rs1980422, P = 5 x 10(-6) replication, P = 1 x 10(-9) overall) and PRDM1 (rs548234, P = 1 x 10(-5) replication, P = 2 x 10(-8) overall). An additional four were replicated (P < 0.0023): TAGAP (rs394581, P = 0.0002 replication, P = 4 x 10(-7) overall), PTPRC (rs10919563, P = 0.0003 replication, P = 7 x 10(-7) overall), TRAF6-RAG1 (rs540386, P = 0.0008 replication, P = 4 x 10(-6) overall) and FCGR2A (rs12746613, P = 0.0022 replication, P = 2 x 10(-5) overall). Many of these loci are also associated to other immunologic diseases.

Case-control genetic studies of complex human diseases can be confounded by population stratification. This issue can be addressed using panels of ancestry informative markers (AIMs) that can provide substantial population substructure information. Previously, we described a panel of 128 SNP AIMs that were designed as a tool for ascertaining the origins of subjects from Europe, Sub-Saharan Africa, Americas, and East Asia.

Accounting for population genetic substructure is important in reducing type 1 errors in genetic studies of complex disease. As efforts to understand complex genetic disease are expanded to different continental populations the understanding of genetic substructure within these continents will be useful in design and execution of association tests. In this study, population differentiation (Fst) and Principal Components Analyses (PCA) are examined using >200 K genotypes from multiple populations of East Asian ancestry. The population groups included those from the Human Genome Diversity Panel [Cambodian, Yi, Daur, Mongolian, Lahu, Dai, Hezhen, Miaozu, Naxi, Oroqen, She, Tu, Tujia, Naxi, Xibo, and Yakut], HapMap [ Han Chinese (CHB) and Japanese (JPT)], and East Asian or East Asian American subjects of Vietnamese, Korean, Filipino and Chinese ancestry. Paired Fst (Wei and Cockerham) showed close relationships between CHB and several large East Asian population groups (CHB/Korean, 0.0019; CHB/JPT, 00651; CHB/Vietnamese, 0.0065) with larger separation with Filipino (CHB/Filipino, 0.014). Low levels of differentiation were also observed between Dai and Vietnamese (0.0045) and between Vietnamese and Cambodian (0.0062). Similarly, small Fst's were observed among different presumed Han Chinese populations originating in different regions of mainland of China and Taiwan (Fst's <0.0025 with CHB). For PCA, the first two PC's showed a pattern of relationships that closely followed the geographic distribution of the different East Asian populations. PCA showed substructure both between different East Asian groups and within the Han Chinese population. These studies have also identified a subset of East Asian substructure ancestry informative markers (EASTASAIMS) that may be useful for future complex genetic disease association studies in reducing type 1 errors and in identifying homogeneous groups that may increase the power of such studies.

A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a "cosmopolitan" tagging approach to capture the genetic diversity across approximately 2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.

Total white blood cell (WBC) and neutrophil counts are lower among individuals of African descent due to the common African-derived "null" variant of the Duffy Antigen Receptor for Chemokines (DARC) gene. Additional common genetic polymorphisms were recently associated with total WBC and WBC sub-type levels in European and Japanese populations. No additional loci that account for WBC variability have been identified in African Americans. In order to address this, we performed a large genome-wide association study (GWAS) of total WBC and cell subtype counts in 16,388 African-American participants from 7 population-based cohorts available in the Continental Origins and Genetic Epidemiology Network. In addition to the DARC locus on chromosome 1q23, we identified two other regions (chromosomes 4q13 and 16q22) associated with WBC in African Americans (P<2.5×10(-8)). The lead SNP (rs9131) on chromosome 4q13 is located in the CXCL2 gene, which encodes a chemotactic cytokine for polymorphonuclear leukocytes. Independent evidence of the novel CXCL2 association with WBC was present in 3,551 Hispanic Americans, 14,767 Japanese, and 19,509 European Americans. The index SNP (rs12149261) on chromosome 16q22 associated with WBC count is located in a large inter-chromosomal segmental duplication encompassing part of the hydrocephalus inducing homolog (HYDIN) gene. We demonstrate that the chromosome 16q22 association finding is most likely due to a genotyping artifact as a consequence of sequence similarity between duplicated regions on chromosomes 16q22 and 1q21. Among the WBC loci recently identified in European or Japanese populations, replication was observed in our African-American meta-analysis for rs445 of CDK6 on chromosome 7q21 and rs4065321 of PSMD3-CSF3 region on chromosome 17q21. In summary, the CXCL2, CDK6, and PSMD3-CSF3 regions are associated with WBC count in African American and other populations. We also demonstrate that large inter-chromosomal duplications can result in false positive associations in GWAS.

Recent genome-wide association studies (GWAS) have shown that single nucleotide polymorphisms (SNPs) in the Chr9p21 region are associated with coronary artery disease (CAD). Most of the SNPs identified in this region are non-coding SNPs, suggesting that they may influence gene expression by cis or trans mechanisms to affect disease susceptibility. Since all cells from an individual have the same DNA sequence variations, levels of gene expression in immortalized cell lines can reflect the functional effects of DNA sequence variations that influence or regulate gene expression. The objective of this study is to evaluate the functional consequences of the risk variants in the Chr9p21 region on gene expression.

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.

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.

Genome-wide association studies (GWASs) primarily performed in European-ancestry (EA) populations have identified numerous loci associated with body mass index (BMI). However, it is still unclear whether these GWAS loci can be generalized to other ethnic groups, such as African Americans (AAs). Furthermore, the putative functional variant or variants in these loci mostly remain under investigation. The overall lower linkage disequilibrium in AA compared to EA populations provides the opportunity to narrow in or fine-map these BMI-related loci. Therefore, we used the Metabochip to densely genotype and evaluate 21 BMI GWAS loci identified in EA studies in 29,151 AAs from the Population Architecture using Genomics and Epidemiology (PAGE) study. Eight of the 21 loci (SEC16B, TMEM18, ETV5, GNPDA2, TFAP2B, BDNF, FTO, and MC4R) were found to be associated with BMI in AAs at 5.8 × 10(-5). Within seven out of these eight loci, we found that, on average, a substantially smaller number of variants was correlated (r(2) > 0.5) with the most significant SNP in AA than in EA populations (16 versus 55). Conditional analyses revealed GNPDA2 harboring a potential additional independent signal. Moreover, Metabochip-wide discovery analyses revealed two BMI-related loci, BRE (rs116612809, p = 3.6 × 10(-8)) and DHX34 (rs4802349, p = 1.2 × 10(-7)), which were significant when adjustment was made for the total number of SNPs tested across the chip. These results demonstrate that fine mapping in AAs is a powerful approach for both narrowing in on the underlying causal variants in known loci and discovering BMI-related loci.

To perform a genome-wide association study (GWAS) using the Immunochip array in 3,420 cases of ischemic stroke and 6,821 controls, followed by a meta-analysis with data from more than 14,000 additional ischemic stroke cases.

For complex traits, most associated single nucleotide variants (SNV) discovered to date have a small effect, and detection of association is only possible with large sample sizes. Because of patient confidentiality concerns, it is often not possible to pool genetic data from multiple cohorts, and meta-analysis has emerged as the method of choice to combine results from multiple studies. Many meta-analysis methods are available for single SNV analyses. As new approaches allow the capture of low frequency and rare genetic variation, it is of interest to jointly consider multiple variants to improve power. However, for the analysis of haplotypes formed by multiple SNVs, meta-analysis remains a challenge, because different haplotypes may be observed across studies. We propose a two-stage meta-analysis approach to combine haplotype analysis results. In the first stage, each cohort estimate haplotype effect sizes in a regression framework, accounting for relatedness among observations if appropriate. For the second stage, we use a multivariate generalized least square meta-analysis approach to combine haplotype effect estimates from multiple cohorts. Haplotype-specific association tests and a global test of independence between haplotypes and traits are obtained within our framework. We demonstrate through simulation studies that we control the type-I error rate, and our approach is more powerful than inverse variance weighted meta-analysis of single SNV analysis when haplotype effects are present. We replicate a published haplotype association between fasting glucose-associated locus (G6PC2) and fasting glucose in seven studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and we provide more precise haplotype effect estimates.

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.

Genome-wide association studies (GWASs) have identified loci for erythrocyte traits in primarily European ancestry populations. We conducted GWAS meta-analyses of six erythrocyte traits in 71,638 individuals from European, East Asian, and African ancestries using a Bayesian approach to account for heterogeneity in allelic effects and variation in the structure of linkage disequilibrium between ethnicities. We identified seven loci for erythrocyte traits including a locus (RBPMS/GTF2E2) associated with mean corpuscular hemoglobin and mean corpuscular volume. Statistical fine-mapping at this locus pointed to RBPMS at this locus and excluded nearby GTF2E2. Using zebrafish morpholino to evaluate loss of function, we observed a strong in vivo erythropoietic effect for RBPMS but not for GTF2E2, supporting the statistical fine-mapping at this locus and demonstrating that RBPMS is a regulator of erythropoiesis. Our findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci influencing hematologic traits.

Statin treatment and variants in the gene encoding HMG-CoA reductase are associated with reductions in both the concentration of LDL cholesterol and the risk of coronary heart disease, but also with modest hyperglycaemia, increased bodyweight, and modestly increased risk of type 2 diabetes, which in no way offsets their substantial benefits. We sought to investigate the associations of LDL cholesterol-lowering PCSK9 variants with type 2 diabetes and related biomarkers to gauge the likely effects of PCSK9 inhibitors on diabetes risk.

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.

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.

High blood pressure (BP) is more prevalent and contributes to more severe manifestations of cardiovascular disease (CVD) in African Americans than in any other United States ethnic group. Several small African-ancestry (AA) BP genome-wide association studies (GWASs) have been published, but their findings have failed to replicate to date. We report on a large AA BP GWAS meta-analysis that includes 29,378 individuals from 19 discovery cohorts and subsequent replication in additional samples of AA (n = 10,386), European ancestry (EA) (n = 69,395), and East Asian ancestry (n = 19,601). Five loci (EVX1-HOXA, ULK4, RSPO3, PLEKHG1, and SOX6) reached genome-wide significance (p < 1.0 × 10(-8)) for either systolic or diastolic BP in a transethnic meta-analysis after correction for multiple testing. Three of these BP loci (EVX1-HOXA, RSPO3, and PLEKHG1) lack previous associations with BP. We also identified one independent signal in a known BP locus (SOX6) and provide evidence for fine mapping in four additional validated BP loci. We also demonstrate that validated EA BP GWAS loci, considered jointly, show significant effects in AA samples. Consequently, these findings suggest that BP loci might have universal effects across studied populations, demonstrating that multiethnic samples are an essential component in identifying, fine mapping, and understanding their trait variability.

Coronary heart disease (CHD) is the major cause of death in the United States. Coronary artery calcification (CAC) scores are independent predictors of CHD. African Americans (AA) have higher rates of CHD but are less well-studied in genomic studies. We assembled the largest AA data resource currently available with measured CAC to identify associated genetic variants.