Metabolite quantitative traits carry great promise for epidemiological studies, and their genetic background has been addressed using Genome-Wide Association Studies (GWAS). Thus far, the role of less common variants has not been exhaustively studied. Here, we set out a GWAS for metabolite quantitative traits in serum, followed by exome sequence analysis to zoom in on putative causal variants in the associated genes. 1H Nuclear Magnetic Resonance (1H-NMR) spectroscopy experiments yielded successful quantification of 42 unique metabolites in 2,482 individuals from The Erasmus Rucphen Family (ERF) study. Heritability of metabolites were estimated by SOLAR. GWAS was performed by linear mixed models, using HapMap imputations. Based on physical vicinity and pathway analyses, candidate genes were screened for coding region variation using exome sequence data. Heritability estimates for metabolites ranged between 10% and 52%. GWAS replicated three known loci in the metabolome wide significance: CPS1 with glycine (P-value  = 1.27×10-32), PRODH with proline (P-value  = 1.11×10-19), SLC16A9 with carnitine level (P-value  = 4.81×10-14) and uncovered a novel association between DMGDH and dimethyl-glycine (P-value  = 1.65×10-19) level. In addition, we found three novel, suggestively significant loci: TNP1 with pyruvate (P-value  = 1.26×10-8), KCNJ16 with 3-hydroxybutyrate (P-value  = 1.65×10-8) and 2p12 locus with valine (P-value  = 3.49×10-8). Exome sequence analysis identified potentially causal coding and regulatory variants located in the genes CPS1, KCNJ2 and PRODH, and revealed allelic heterogeneity for CPS1 and PRODH. Combined GWAS and exome analyses of metabolites detected by high-resolution 1H-NMR is a robust approach to uncover metabolite quantitative trait loci (mQTL), and the likely causative variants in these loci. It is anticipated that insight in the genetics of intermediate phenotypes will provide additional insight into the genetics of complex traits.

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.

Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.

Phospho- and sphingolipids are crucial cellular and intracellular compounds. These lipids are required for active transport, a number of enzymatic processes, membrane formation, and cell signalling. Disruption of their metabolism leads to several diseases, with diverse neurological, psychiatric, and metabolic consequences. A large number of phospholipid and sphingolipid species can be detected and measured in human plasma. We conducted a meta-analysis of five European family-based genome-wide association studies (N = 4034) on plasma levels of 24 sphingomyelins (SPM), 9 ceramides (CER), 57 phosphatidylcholines (PC), 20 lysophosphatidylcholines (LPC), 27 phosphatidylethanolamines (PE), and 16 PE-based plasmalogens (PLPE), as well as their proportions in each major class. This effort yielded 25 genome-wide significant loci for phospholipids (smallest P-value = 9.88×10(-204)) and 10 loci for sphingolipids (smallest P-value = 3.10×10(-57)). After a correction for multiple comparisons (P-value<2.2×10(-9)), we observed four novel loci significantly associated with phospholipids (PAQR9, AGPAT1, PKD2L1, PDXDC1) and two with sphingolipids (PLD2 and APOE) explaining up to 3.1% of the variance. Further analysis of the top findings with respect to within class molar proportions uncovered three additional loci for phospholipids (PNLIPRP2, PCDH20, and ABDH3) suggesting their involvement in either fatty acid elongation/saturation processes or fatty acid specific turnover mechanisms. Among those, 14 loci (KCNH7, AGPAT1, PNLIPRP2, SYT9, FADS1-2-3, DLG2, APOA1, ELOVL2, CDK17, LIPC, PDXDC1, PLD2, LASS4, and APOE) mapped into the glycerophospholipid and 12 loci (ILKAP, ITGA9, AGPAT1, FADS1-2-3, APOA1, PCDH20, LIPC, PDXDC1, SGPP1, APOE, LASS4, and PLD2) to the sphingolipid pathways. In large meta-analyses, associations between FADS1-2-3 and carotid intima media thickness, AGPAT1 and type 2 diabetes, and APOA1 and coronary artery disease were observed. In conclusion, our study identified nine novel phospho- and sphingolipid loci, substantially increasing our knowledge of the genetic basis for these traits.

Chronic kidney disease (CKD) is an important public health problem with a genetic component. We performed genome-wide association studies in up to 130,600 European ancestry participants overall, and stratified for key CKD risk factors. We uncovered 6 new loci in association with estimated glomerular filtration rate (eGFR), the primary clinical measure of CKD, in or near MPPED2, DDX1, SLC47A1, CDK12, CASP9, and INO80. Morpholino knockdown of mpped2 and casp9 in zebrafish embryos revealed podocyte and tubular abnormalities with altered dextran clearance, suggesting a role for these genes in renal function. By providing new insights into genes that regulate renal function, these results could further our understanding of the pathogenesis of CKD.

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Genome-wide association studies (GWAS) have identified 38 larger genetic regions affecting classical blood lipid levels without adjusting for important environmental influences. We modeled diet and physical activity in a GWAS in order to identify novel loci affecting total cholesterol, LDL cholesterol, HDL cholesterol, and triglyceride levels. The Swedish (SE) EUROSPAN cohort (N(SE) = 656) was screened for candidate genes and the non-Swedish (NS) EUROSPAN cohorts (N(NS) = 3,282) were used for replication. In total, 3 SNPs were associated in the Swedish sample and were replicated in the non-Swedish cohorts. While SNP rs1532624 was a replication of the previously published association between CETP and HDL cholesterol, the other two were novel findings. For the latter SNPs, the p-value for association was substantially improved by inclusion of environmental covariates: SNP rs5400 (p(SE,unadjusted) = 3.6 x 10(-5), p(SE,adjusted) = 2.2 x 10(-6), p(NS,unadjusted) = 0.047) in the SLC2A2 (Glucose transporter type 2) and rs2000999 (p(SE,unadjusted) = 1.1 x 10(-3), p(SE,adjusted) = 3.8 x 10(-4), p(NS,unadjusted) = 0.035) in the HP gene (Haptoglobin-related protein precursor). Both showed evidence of association with total cholesterol. These results demonstrate that inclusion of important environmental factors in the analysis model can reveal new genetic susceptibility loci.

The optic nerve head is involved in many ophthalmic disorders, including common diseases such as myopia and open-angle glaucoma. Two of the most important parameters are the size of the optic disc area and the vertical cup-disc ratio (VCDR). Both are highly heritable but genetically largely undetermined. We performed a meta-analysis of genome-wide association (GWA) data to identify genetic variants associated with optic disc area and VCDR. The gene discovery included 7,360 unrelated individuals from the population-based Rotterdam Study I and Rotterdam Study II cohorts. These cohorts revealed two genome-wide significant loci for optic disc area, rs1192415 on chromosome 1p22 (p = 6.72x10(-19)) within 117 kb of the CDC7 gene and rs1900004 on chromosome 10q21.3-q22.1 (p = 2.67x10(-33)) within 10 kb of the ATOH7 gene. They revealed two genome-wide significant loci for VCDR, rs1063192 on chromosome 9p21 (p = 6.15x10(-11)) in the CDKN2B gene and rs10483727 on chromosome 14q22.3-q23 (p = 2.93x10(-10)) within 40 kbp of the SIX1 gene. Findings were replicated in two independent Dutch cohorts (Rotterdam Study III and Erasmus Rucphen Family study; N = 3,612), and the TwinsUK cohort (N = 843). Meta-analysis with the replication cohorts confirmed the four loci and revealed a third locus at 16q12.1 associated with optic disc area, and four other loci at 11q13, 13q13, 17q23 (borderline significant), and 22q12.1 for VCDR. ATOH7 was also associated with VCDR independent of optic disc area. Three of the loci were marginally associated with open-angle glaucoma. The protein pathways in which the loci of optic disc area are involved overlap with those identified for VCDR, suggesting a common genetic origin.

Optical Coherence Tomography (OCT) enables non-invasive imaging of the retina and is used to diagnose and manage ophthalmic diseases including glaucoma. We present the first large-scale genome-wide association study of inner retinal morphology using phenotypes derived from OCT images of 31,434 UK Biobank participants. We identify 46 loci associated with thickness of the retinal nerve fibre layer or ganglion cell inner plexiform layer. Only one of these loci has been associated with glaucoma, and despite its clear role as a biomarker for the disease, Mendelian randomisation does not support inner retinal thickness being on the same genetic causal pathway as glaucoma. We extracted overall retinal thickness at the fovea, representative of foveal hypoplasia, with which three of the 46 SNPs were associated. We additionally associate these three loci with visual acuity. In contrast to the Mendelian causes of severe foveal hypoplasia, our results suggest a spectrum of foveal hypoplasia, in part genetically determined, with consequences on visual function.

We performed an exome-wide association analysis in 1393 late-onset Alzheimer's disease (LOAD) cases and 8141 controls from the CHARGE consortium. We found that a rare variant (P155L) in TM2D3 was enriched in Icelanders (~0.5% versus <0.05% in other European populations). In 433 LOAD cases and 3903 controls from the Icelandic AGES sub-study, P155L was associated with increased risk and earlier onset of LOAD [odds ratio (95% CI) = 7.5 (3.5-15.9), p = 6.6x10-9]. Mutation in the Drosophila TM2D3 homolog, almondex, causes a phenotype similar to loss of Notch/Presenilin signaling. Human TM2D3 is capable of rescuing these phenotypes, but this activity is abolished by P155L, establishing it as a functionally damaging allele. Our results establish a rare TM2D3 variant in association with LOAD susceptibility, and together with prior work suggests possible links to the β-amyloid cascade.

Bromodomain and Extra-terminal motif (BET) proteins play a central role in transcription regulation and chromatin signalling pathways. They are present in unicellular eukaryotes and in this study, the role of the BET protein Bdf1 has been explored in Saccharomyces cerevisiae. Mutation of Bdf1 bromodomains revealed defects on both the formation of spores and the meiotic progression, blocking cells at the exit from prophase, before the first meiotic division. This phenotype is associated with a massive deregulation of the transcription of meiotic genes and Bdf1 bromodomains are required for appropriate expression of the key meiotic transcription factor NDT80 and almost all the Ndt80-inducible genes, including APC complex components. Bdf1 notably accumulates on the promoter of Ndt80 and its recruitment is dependent on Bdf1 bromodomains. In addition, the ectopic expression of NDT80 during meiosis partially bypasses this dependency. Finally, purification of Bdf1 partners identified two independent complexes with Bdf2 or the SWR complex, neither of which was required to complete sporulation. Taken together, our results unveil a new role for Bdf1 -working independently from its predominant protein partners Bdf2 and the SWR1 complex-as a regulator of meiosis-specific genes.

The major histocompatibility complex (MHC) region is strongly associated with multiple sclerosis (MS) susceptibility. HLA-DRB1*15:01 has the strongest effect, and several other alleles have been reported at different levels of validation. Using SNP data from genome-wide studies, we imputed and tested classical alleles and amino acid polymorphisms in 8 classical human leukocyte antigen (HLA) genes in 5,091 cases and 9,595 controls. We identified 11 statistically independent effects overall: 6 HLA-DRB1 and one DPB1 alleles in class II, one HLA-A and two B alleles in class I, and one signal in a region spanning from MICB to LST1. This genomic segment does not contain any HLA class I or II genes and provides robust evidence for the involvement of a non-HLA risk allele within the MHC. Interestingly, this region contains the TNF gene, the cognate ligand of the well-validated TNFRSF1A MS susceptibility gene. The classical HLA effects can be explained to some extent by polymorphic amino acid positions in the peptide-binding grooves. This study dissects the independent effects in the MHC, a critical region for MS susceptibility that harbors multiple risk alleles.

There is increasing evidence that the microcirculation plays an important role in the pathogenesis of cardiovascular diseases. Changes in retinal vascular caliber reflect early microvascular disease and predict incident cardiovascular events. We performed a genome-wide association study to identify genetic variants associated with retinal vascular caliber. We analyzed data from four population-based discovery cohorts with 15,358 unrelated Caucasian individuals, who are members of the Cohort for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, and replicated findings in four independent Caucasian cohorts (n  =  6,652). All participants had retinal photography and retinal arteriolar and venular caliber measured from computer software. In the discovery cohorts, 179 single nucleotide polymorphisms (SNP) spread across five loci were significantly associated (p<5.0×10(-8)) with retinal venular caliber, but none showed association with arteriolar caliber. Collectively, these five loci explain 1.0%-3.2% of the variation in retinal venular caliber. Four out of these five loci were confirmed in independent replication samples. In the combined analyses, the top SNPs at each locus were: rs2287921 (19q13; p  =  1.61×10(-25), within the RASIP1 locus), rs225717 (6q24; p = 1.25×10(-16), adjacent to the VTA1 and NMBR loci), rs10774625 (12q24; p  =  2.15×10(-13), in the region of ATXN2,SH2B3 and PTPN11 loci), and rs17421627 (5q14; p = 7.32×10(-16), adjacent to the MEF2C locus). In two independent samples, locus 12q24 was also associated with coronary heart disease and hypertension. Our population-based genome-wide association study demonstrates four novel loci associated with retinal venular caliber, an endophenotype of the microcirculation associated with clinical cardiovascular disease. These data provide further insights into the contribution and biological mechanisms of microcirculatory changes that underlie cardiovascular disease.

Magnesium, potassium, and sodium, cations commonly measured in serum, are involved in many physiological processes including energy metabolism, nerve and muscle function, signal transduction, and fluid and blood pressure regulation. To evaluate the contribution of common genetic variation to normal physiologic variation in serum concentrations of these cations, we conducted genome-wide association studies of serum magnesium, potassium, and sodium concentrations using approximately 2.5 million genotyped and imputed common single nucleotide polymorphisms (SNPs) in 15,366 participants of European descent from the international CHARGE Consortium. Study-specific results were combined using fixed-effects inverse-variance weighted meta-analysis. SNPs demonstrating genome-wide significant (p<5 x 10(-8)) or suggestive associations (p<4 x 10(-7)) were evaluated for replication in an additional 8,463 subjects of European descent. The association of common variants at six genomic regions (in or near MUC1, ATP2B1, DCDC5, TRPM6, SHROOM3, and MDS1) with serum magnesium levels was genome-wide significant when meta-analyzed with the replication dataset. All initially significant SNPs from the CHARGE Consortium showed nominal association with clinically defined hypomagnesemia, two showed association with kidney function, two with bone mineral density, and one of these also associated with fasting glucose levels. Common variants in CNNM2, a magnesium transporter studied only in model systems to date, as well as in CNNM3 and CNNM4, were also associated with magnesium concentrations in this study. We observed no associations with serum sodium or potassium levels exceeding p<4 x 10(-7). Follow-up studies of newly implicated genomic loci may provide additional insights into the regulation and homeostasis of human serum magnesium levels.

Large-scale population sequencing studies provide a complete picture of human genetic variation within the studied populations. A key challenge is to identify, among the myriad alleles, those variants that have an effect on molecular function, phenotypes, and reproductive fitness. Most non-neutral variation consists of deleterious alleles segregating at low population frequency due to incessant mutation. To date, studies characterizing selection against deleterious alleles have been based on allele frequency (testing for a relative excess of rare alleles) or ratio of polymorphism to divergence (testing for a relative increase in the number of polymorphic alleles). Here, starting from Maruyama's theoretical prediction (Maruyama T (1974), Am J Hum Genet USA 6:669-673) that a (slightly) deleterious allele is, on average, younger than a neutral allele segregating at the same frequency, we devised an approach to characterize selection based on allelic age. Unlike existing methods, it compares sets of neutral and deleterious sequence variants at the same allele frequency. When applied to human sequence data from the Genome of the Netherlands Project, our approach distinguishes low-frequency coding non-synonymous variants from synonymous and non-coding variants at the same allele frequency and discriminates between sets of variants independently predicted to be benign or damaging for protein structure and function. The results confirm the abundance of slightly deleterious coding variation in humans.

Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.

Intraocular pressure (IOP) is a highly heritable risk factor for primary open-angle glaucoma and is the only target for current glaucoma therapy. The genetic factors which determine IOP are largely unknown. We performed a genome-wide association study for IOP in 11,972 participants from 4 independent population-based studies in The Netherlands. We replicated our findings in 7,482 participants from 4 additional cohorts from the UK, Australia, Canada, and the Wellcome Trust Case-Control Consortium 2/Blue Mountains Eye Study. IOP was significantly associated with rs11656696, located in GAS7 at 17p13.1 (p=1.4×10(-8)), and with rs7555523, located in TMCO1 at 1q24.1 (p=1.6×10(-8)). In a meta-analysis of 4 case-control studies (total N = 1,432 glaucoma cases), both variants also showed evidence for association with glaucoma (p=2.4×10(-2) for rs11656696 and p=9.1×10(-4) for rs7555523). GAS7 and TMCO1 are highly expressed in the ciliary body and trabecular meshwork as well as in the lamina cribrosa, optic nerve, and retina. Both genes functionally interact with known glaucoma disease genes. These data suggest that we have identified two clinically relevant genes involved in IOP regulation.

Physical activity (PA) may modify the genetic effects that give rise to increased risk of obesity. To identify adiposity loci whose effects are modified by PA, we performed genome-wide interaction meta-analyses of BMI and BMI-adjusted waist circumference and waist-hip ratio from up to 200,452 adults of European (n = 180,423) or other ancestry (n = 20,029). We standardized PA by categorizing it into a dichotomous variable where, on average, 23% of participants were categorized as inactive and 77% as physically active. While we replicate the interaction with PA for the strongest known obesity-risk locus in the FTO gene, of which the effect is attenuated by ~30% in physically active individuals compared to inactive individuals, we do not identify additional loci that are sensitive to PA. In additional genome-wide meta-analyses adjusting for PA and interaction with PA, we identify 11 novel adiposity loci, suggesting that accounting for PA or other environmental factors that contribute to variation in adiposity may facilitate gene discovery.

Rare variant association tests (RVAT) have been developed to study the contribution of rare variants widely accessible through high-throughput sequencing technologies. RVAT require to aggregate rare variants in testing units and to filter variants to retain only the most likely causal ones. In the exome, genes are natural testing units and variants are usually filtered based on their functional consequences. However, when dealing with whole-genome sequence (WGS) data, both steps are challenging. No natural biological unit is available for aggregating rare variants. Sliding windows procedures have been proposed to circumvent this difficulty, however they are blind to biological information and result in a large number of tests. We propose a new strategy to perform RVAT on WGS data: "RAVA-FIRST" (RAre Variant Association using Functionally-InfoRmed STeps) comprising three steps. (1) New testing units are defined genome-wide based on functionally-adjusted Combined Annotation Dependent Depletion (CADD) scores of variants observed in the gnomAD populations, which are referred to as "CADD regions". (2) A region-dependent filtering of rare variants is applied in each CADD region. (3) A functionally-informed burden test is performed with sub-scores computed for each genomic category within each CADD region. Both on simulations and real data, RAVA-FIRST was found to outperform other WGS-based RVAT. Applied to a WGS dataset of venous thromboembolism patients, we identified an intergenic region on chromosome 18 enriched for rare variants in early-onset patients. This region that was missed by standard sliding windows procedures is included in a TAD region that contains a strong candidate gene. RAVA-FIRST enables new investigations of rare non-coding variants in complex diseases, facilitated by its implementation in the R package Ravages.

White blood cell (WBC) count is a common clinical measure from complete blood count assays, and it varies widely among healthy individuals. Total WBC count and its constituent subtypes have been shown to be moderately heritable, with the heritability estimates varying across cell types. We studied 19,509 subjects from seven cohorts in a discovery analysis, and 11,823 subjects from ten cohorts for replication analyses, to determine genetic factors influencing variability within the normal hematological range for total WBC count and five WBC subtype measures. Cohort specific data was supplied by the CHARGE, HeamGen, and INGI consortia, as well as independent collaborative studies. We identified and replicated ten associations with total WBC count and five WBC subtypes at seven different genomic loci (total WBC count-6p21 in the HLA region, 17q21 near ORMDL3, and CSF3; neutrophil count-17q21; basophil count- 3p21 near RPN1 and C3orf27; lymphocyte count-6p21, 19p13 at EPS15L1; monocyte count-2q31 at ITGA4, 3q21, 8q24 an intergenic region, 9q31 near EDG2), including three previously reported associations and seven novel associations. To investigate functional relationships among variants contributing to variability in the six WBC traits, we utilized gene expression- and pathways-based analyses. We implemented gene-clustering algorithms to evaluate functional connectivity among implicated loci and showed functional relationships across cell types. Gene expression data from whole blood was utilized to show that significant biological consequences can be extracted from our genome-wide analyses, with effect estimates for significant loci from the meta-analyses being highly corellated with the proximal gene expression. In addition, collaborative efforts between the groups contributing to this study and related studies conducted by the COGENT and RIKEN groups allowed for the examination of effect homogeneity for genome-wide significant associations across populations of diverse ancestral backgrounds.