SummaryEducational attainment (EA) is strongly influenced by social and other environmental factors, but genetic factors are also estimated to account for at least 20% of the variation across individuals1. We report the results of a genome-wide association study (GWAS) for EA that extends our earlier discovery sample1,2 of 101,069 individuals to 293,723 individuals, and a replication in an independent sample of 111,349 individuals from the UK Biobank. We now identify 74 genome-wide significant loci associated with number of years of schooling completed. Single-nucleotide polymorphisms (SNPs) associated with educational attainment are disproportionately found in genomic regions regulating gene expression in the fetal brain. Candidate genes are preferentially expressed in neural tissue, especially during the prenatal period, and enriched for biological pathways involved in neural development. Our findings demonstrate that, even for a behavioral phenotype that is mostly environmentally determined, a well-powered GWAS identifies replicable associated genetic variants that suggest biologically relevant pathways. Because EA is measured in large numbers of individuals, it will continue to be useful as a proxy phenotype in efforts to characterize the genetic influences of related phenotypes, including cognition and neuropsychiatric disease.

The genetic architecture of common traits, including the number, frequency, and effect sizes of inherited variants that contribute to individual risk, has been long debated. Genome-wide association studies have identified scores of common variants associated with type 2 diabetes, but in aggregate, these explain only a fraction of heritability. To test the hypothesis that lower-frequency variants explain much of the remainder, the GoT2D and T2D-GENES consortia performed whole genome sequencing in 2,657 Europeans with and without diabetes, and exome sequencing in a total of 12,940 subjects from five ancestral groups. To increase statistical power, we expanded sample size via genotyping and imputation in a further 111,548 subjects. Variants associated with type 2 diabetes after sequencing were overwhelmingly common and most fell within regions previously identified by genome-wide association studies. Comprehensive enumeration of sequence variation is necessary to identify functional alleles that provide important clues to disease pathophysiology, but large-scale sequencing does not support a major role for lower-frequency variants in predisposition to type 2 diabetes.

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q < 0.05). Loci influencing fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control.

To further understanding of the genetic basis of type 2 diabetes (T2D) susceptibility, we aggregated published meta-analyses of genome-wide association studies (GWAS) including 26,488 cases and 83,964 controls of European, East Asian, South Asian, and Mexican and Mexican American ancestry. We observed significant excess in directional consistency of T2D risk alleles across ancestry groups, even at SNPs demonstrating only weak evidence of association. By following up the strongest signals of association from the trans-ethnic meta-analysis in an additional 21,491 cases and 55,647 controls of European ancestry, we identified seven novel T2D susceptibility loci. Furthermore, we observed considerable improvements in fine-mapping resolution of common variant association signals at several T2D susceptibility loci. These observations highlight the benefits of trans-ethnic GWAS for the discovery and characterisation of complex trait loci, and emphasize an exciting opportunity to extend insight into the genetic architecture and pathogenesis of human diseases across populations of diverse ancestry.

Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n=321,223) and offspring birth weight (n=230,069 mothers), we identified 190 independent association signals (129 novel). We used structural equation modelling to decompose the contributions of direct fetal and indirect maternal genetic effects, and then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of those alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.

We conducted a genome-wide association study using 207,097 SNP markers in Japanese individuals with type 2 diabetes and unrelated controls, and identified KCNQ1 (potassium voltage-gated channel, KQT-like subfamily, member 1) to be a strong candidate for conferring susceptibility to type 2 diabetes. We detected consistent association of a SNP in KCNQ1 (rs2283228) with the disease in several independent case-control studies (additive model P = 3.1 x 10(-12); OR = 1.26, 95% CI = 1.18-1.34). Several other SNPs in the same linkage disequilibrium (LD) block were strongly associated with type 2 diabetes (additive model: rs2237895, P = 7.3 x 10(-9); OR = 1.32, 95% CI = 1.20-1.45, rs2237897, P = 6.8 x 10(-13); OR = 1.41, 95% CI = 1.29-1.55). The association of these SNPs with type 2 diabetes was replicated in samples from Singaporean (additive model: rs2237895, P = 8.5 x 10(-3); OR = 1.14, rs2237897, P = 2.4 x 10(-4); OR = 1.22) and Danish populations (additive model: rs2237895, P = 3.7 x 10(-11); OR = 1.24, rs2237897, P = 1.2 x 10(-4); OR = 1.36).

Birth weight (BW) is influenced by both foetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease1. These lifecourse associations have often been attributed to the impact of an adverse early life environment. We performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where foetal genotype was associated with BW (P <5x10-8). Overall, ˜15% of variance in BW could be captured by assays of foetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (rg=-0.22, P =5.5x10-13), T2D (rg=-0.27, P =1.1x10-6) and coronary artery disease (rg=-0.30, P =6.5x10-9) and, in large cohort data sets, demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P =1.9x10-4). We have demonstrated that lifecourse associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and have highlighted some of the pathways through which these causal genetic effects are mediated.

OBJECTIVE -The high-molecular weight (HMW) form of adiponectin, an adipocytederived insulin-sensitizing hormone, has been reported to be the most active form of this hormone. We investigated whether measurement of plasma HMW adiponectin levels, using our newly developed enzyme-linked immunosorbent assay system for selective measurement of human HMW adiponectin level, may be useful for the prediction of insulin resistance and metabolic syndrome.RESEARCH DESIGN AND METHODS -A total of 298 patients admitted for diabetes treatment or coronary angiography served as study subjects. Receiver operator characteristic (ROC) curves for the HMW ratio (HMWR; ratio of plasma level of HMW adiponectin to that of total adiponectin) and plasma total adiponectin levels were plotted to predict the presence of insulin resistance and metabolic syndrome. CONCLUSIONS -The HMWR value has better predictive power for the prediction of insulin resistance and metabolic syndrome than plasma total adiponectin level. RESULTS Diabetes Care 29:1357-1362, 2006A diponectin (also known as ACRP30, GBP28, and AdipoQ) is a hormone secreted exclusively by adipocytes (1-4). Adiponectin replenishment has been found to ameliorate the abnormalities of metabolic syndrome, including insulin resistance, hyperglycemia, and dyslipidemia, in a murine model of obesity-linked metabolic syndrome associated with decreased adiponectin levels (5). Adiponectin-deficient mice (6,7) have been demonstrated to show features of metabolic syndrome, such as insulin resistance, glucose intolerance, dyslipidemia, and hypertension. In humans, decreased plasma adiponectin levels have been demonstrated in patients with obesity, diabetes, and coronary artery disease (8 -10), all of which are linked to insulin resistance. Moreover, the degree of hypoadiponectinemia has been reported to be correlated with the degree of insulin resistance (11,12), and hypoadiponectinemia has been shown to be closely associated with the clinical phenotype of metabolic syndrome (13,14). The gene encoding adiponectin (APM1) has been mapped to chromosome 3q27, which has been reported to be linked to type 2 diabetes and metabolic syndrome by genome-wide scans in Japanese (15), American, (16), and French-Caucasian (17) populations. A single nucleotide polymorphism in the adiponectin gene was shown to be associated with hypoadiponectinemia, insulin resistance, and increased risk of type 2 diabetes (18,19), indicating that adiponectin may play a crucial role in the regulation of insulin sensitivity and glucose and lipid metabolism and that reduced plasma adiponectin levels caused by genetic and environmental factors may lead to the development of insulin resistance, type 2 diabetes, and metabolic syndrome (20). Indeed, a recent study demonstrated that individuals with high plasma adiponectin levels had a substantially lower relative risk of developing type 2 diabetes, even after adjustment for conventional risk factors, such as BMI (21,22).We have reported that adiponectin forms multimers and is present in th...