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 the heritability of this disease. Here, 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 European individuals with and without diabetes, and exome sequencing in 12,940 individuals from five ancestry groups. To increase statistical power, we expanded the 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 the idea that lower-frequency variants have a major role in predisposition to type 2 diabetes.

To investigate the genetic basis of type 2 diabetes (T2D) to high resolution, the GoT2D and T2D-GENES consortia catalogued variation from whole-genome sequencing of 2,657 European individuals and exome sequencing of 12,940 individuals of multiple ancestries. Over 27M SNPs, indels, and structural variants were identified, including 99% of low-frequency (minor allele frequency [MAF] 0.1-5%) non-coding variants in the whole-genome sequenced individuals and 99.7% of low-frequency coding variants in the whole-exome sequenced individuals. Each variant was tested for association with T2D in the sequenced individuals, and, to increase power, most were tested in larger numbers of individuals (>80% of low-frequency coding variants in ~82 K Europeans via the exome chip, and ~90% of low-frequency non-coding variants in ~44 K Europeans via genotype imputation). The variants, genotypes, and association statistics from these analyses provide the largest reference to date of human genetic information relevant to T2D, for use in activities such as T2D-focused genotype imputation, functional characterization of variants or genes, and other novel analyses to detect associations between sequence variation and T2D.

Pulse rate is known to be related to diverse phenotypes, such as cardiovascular diseases, lifespan, arrhythmia, hypertension, lipids, diabetes, and menopause. We have reported two genomewide significant genetic loci responsible for the variation in pulse rate as a part of the Korea Association Resource (KARE) project, the genomewide association study (GWAS) that was conducted with 352,228 single nucleoride polymorphisms typed in 8,842 subjects in the Korean population. GJA1 was implied as a functionally causal gene for pulse rate from the KARE study, but lacked evidence of replication. To re-evaluate the association of a locus near GJA1 with pulse rate, we looked up this signal in another GWAS conducted in a Health Examinee-shared cohort of 3,703 samples. Not only we were able to confirm two pulse rate loci (1q32.2a near CD46 and 6q22.13c near LOCL644502) identified in the KARE GWAS, we also replicated a locus (6q22.31c) near GJA1 by the lookup in the Health Examinee GWAS. Considering that the GJA1-encoded protein is a major component of cardiac gap junctions, a functional study might be necessary to validate its genuine molecular biological role in the synchronized contraction of the heart.

To identify novel coding association signals and facilitate characterization of mechanisms influencing glycemic traits and type 2 diabetes risk, we analyzed 109,215 variants derived from exome array genotyping together with an additional 390,225 variants from exome sequence in up to 39,339 normoglycemic individuals from five ancestry groups. We identified a novel association between the coding variant (p.Pro50Thr) in AKT2 and fasting plasma insulin (FI), a gene in which rare fully penetrant mutations are causal for monogenic glycemic disorders. The low-frequency allele is associated with a 12% increase in FI levels. This variant is present at 1.1% frequency in Finns but virtually absent in individuals from other ancestries. Carriers of the FI-increasing allele had increased 2-h insulin values, decreased insulin sensitivity, and increased risk of type 2 diabetes (odds ratio 1.05). In cellular studies, the AKT2-Thr50 protein exhibited a partial loss of function. We extend the allelic spectrum for coding variants in AKT2 associated with disorders of glucose homeostasis and demonstrate bidirectional effects of variants within the pleckstrin homology domain of AKT2.

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.

Although approximately 25 common genetic susceptibility loci have been identified to be independently associated with breast cancer risk through genome-wide association studies (GWAS), the genetic risk variants reported to date only explain a small fraction of the heritability of breast cancer. Furthermore, GWAS-identified loci were primarily identified in women of European descent.

Recent genome-wide association studies have identified six novel genes for type 2 diabetes and obesity and confirmed TCF7L2 as the major type 2 diabetes gene to date in Europeans. However, the implications of these genes in Asians are unclear.

Observational studies have demonstrated an increased risk of polycystic ovarian syndrome (PCOS) in obese women. This study aimed to identify genetic variants influencing obesity in females and to evaluate the causal association between genetically defined obesity and PCOS in Korean women.

Lipoprotein lipase (LPL) plays an essential role in the regulation of high-density lipoprotein cholesterol (HDLC) and triglyceride levels, which have been closely associated with cardiovascular diseases. Genetic studies in European have shown that LPL single-nucleotide polymorphisms (SNPs) are strongly associated with lipid levels. However, studies about the influence of interactions between LPL SNPs and lifestyle factors have not been sufficiently performed. Here, we examine if LPL polymorphisms, as well as their interaction with lifestyle factors, influence lipid concentrations in a Korean population. A two-stage association study was performed using genotype data for SNPs on the LPL gene, including the 3' flanking region from 7,536 (stage 1) and 3,703 (stage 2) individuals. The association study showed that 15 SNPs and 4 haplotypes were strongly associated with HDLC (lowest p = 2.86 × 10(-22)) and triglyceride levels (lowest p = 3.0 × 10(-15)). Interactions between LPL polymorphisms and lifestyle factors (lowest p = 9.6 × 10(-4)) were also observed on lipid concentrations. These findings suggest that there are interaction effects of LPL polymorphisms with lifestyle variables, including energy intake, fat intake, smoking, and alcohol consumption, as well as effects of LPL polymorphisms themselves, on lipid concentrations in a Korean population.

Although more than 20 genetic susceptibility loci have been reported for type 2 diabetes (T2D), most reported variants have small to moderate effects and account for only a small proportion of the heritability of T2D, suggesting that the majority of inter-person genetic variation in this disease remains to be determined. We conducted a multistage, genome-wide association study (GWAS) within the Asian Consortium of Diabetes to search for T2D susceptibility markers. From 590,887 SNPs genotyped in 1,019 T2D cases and 1,710 controls selected from Chinese women in Shanghai, we selected the top 2,100 SNPs that were not in linkage disequilibrium (r(2)<0.2) with known T2D loci for in silico replication in three T2D GWAS conducted among European Americans, Koreans, and Singapore Chinese. The 5 most promising SNPs were genotyped in an independent set of 1,645 cases and 1,649 controls from Shanghai, and 4 of them were further genotyped in 1,487 cases and 3,316 controls from 2 additional Chinese studies. Consistent associations across all studies were found for rs1359790 (13q31.1), rs10906115 (10p13), and rs1436955 (15q22.2) with P-values (per allele OR, 95%CI) of 6.49 × 10(-9) (1.15, 1.10-1.20), 1.45 × 10(-8) (1.13, 1.08-1.18), and 7.14 × 10(-7) (1.13, 1.08-1.19), respectively, in combined analyses of 9,794 cases and 14,615 controls. Our study provides strong evidence for a novel T2D susceptibility locus at 13q31.1 and the presence of new independent risk variants near regions (10p13 and 15q22.2) reported by previous GWAS.

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

Colorectal cancer (CRC) is the third most common cancer worldwide and is influenced by environmental and genetic factors. Although numerous genetic loci for CRC have been identified, the overall understanding of the genetic factors is yet to be elucidated. We sought to discover new genes involved in CRC applying genetic association analysis and functional study.

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes1. Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel2) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.

Genistein, a phyto-estrogen, can potentially replace endogenous estrogens in postmenopausal women, but the underlying molecular mechanisms remain incompletely understood. To obtain insight into the effect of genistein on bone differentiation, RNA sequencing (RNA-seq) analysis was used to detect differentially expressed genes (DEGs) in genistein-treated vs. untreated MC3T3-E1 mouse osteoblastic cells. Osteoblastic cell differentiation was monitored by measuring osteoblast differentiation factors (ALP production, bone mineralization, and expression of osteoblast differentiation markers). From RNA-seq analysis, a total of 132 DEGs (including 52 up-regulated and 80 down-regulated genes) were identified in genistein-treated cells (FDR q-value < 0.05 and fold change > 1.5). KEGG pathway and Gene Ontology (GO) enrichment analyses were performed to estimate the biological functions of DEGs and demonstrated that these DEGs were highly enriched in functions related to chemotactic cytokines. The functional relevance of DEGs to genistein-induced osteoblastic cell differentiation was further evaluated by siRNA-mediated knockdown in MC3T3-E1 cells. These siRNA knockdown experiments (of the DEGs validated by real-time qPCR) demonstrated that two up-regulated genes (Ereg and Efcab2) enhance osteoblastic cell differentiation, while three down-regulated genes (Hrc, Gli, and Ifitm5) suppress the differentiation. These results imply their major functional roles in bone differentiation regulated by genistein.

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 a significant excess in the 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 new T2D susceptibility loci. Furthermore, we observed considerable improvements in the 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 characterization 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.

Oxidative stress-induced reactive oxygen species (ROS) are responsible for various neuronal diseases. Antioxidant 1 (Atox1) regulates copper homoeostasis and promotes cellular antioxidant defence against toxins generated by ROS. The roles of Atox1 protein in ischaemia, however, remain unclear. In this study, we generated a protein transduction domain fused Tat-Atox1 and examined the roles of Tat-Atox1 in oxidative stress-induced hippocampal HT-22 cell death and an ischaemic injury animal model. Tat-Atox1 effectively transduced into HT-22 cells and it protected cells against the effects of hydrogen peroxide (H2O2)-induced toxicity including increasing of ROS levels and DNA fragmentation. At the same time, Tat-Atox1 regulated cellular survival signalling such as p53, Bad/Bcl-2, Akt and mitogen-activate protein kinases (MAPKs). In the animal ischaemia model, transduced Tat-Atox1 protected against neuronal cell death in the hippocampal CA1 region. In addition, Tat-Atox1 significantly decreased the activation of astrocytes and microglia as well as lipid peroxidation in the CA1 region after ischaemic insult. Taken together, these results indicate that transduced Tat-Atox1 protects against oxidative stress-induced HT-22 cell death and against neuronal damage in animal ischaemia model. Therefore, we suggest that Tat-Atox1 has potential as a therapeutic agent for the treatment of oxidative stress-induced ischaemic damage.

Plasma concentrations of total cholesterol, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol and triglycerides are among the most important risk factors for coronary artery disease (CAD) and are targets for therapeutic intervention. We screened the genome for common variants associated with plasma lipids in >100,000 individuals of European ancestry. Here we report 95 significantly associated loci (P < 5 x 10(-8)), with 59 showing genome-wide significant association with lipid traits for the first time. The newly reported associations include single nucleotide polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken together, our findings provide the foundation to develop a broader biological understanding of lipoprotein metabolism and to identify new therapeutic opportunities for the prevention of CAD.

Knowledge regarding the genetic risk loci for gestational diabetes mellitus (GDM) is still limited. In this study, we performed a two-stage genome-wide association analysis in Korean women. In the stage 1 genome scan, 468 women with GDM and 1,242 nondiabetic control women were compared using 2.19 million genotyped or imputed markers. We selected 11 loci for further genotyping in stage 2 samples of 931 case and 783 control subjects. The joint effect of stage 1 plus stage 2 studies was analyzed by meta-analysis. We also investigated the effect of known type 2 diabetes variants in GDM. Two loci known to be associated with type 2 diabetes had a genome-wide significant association with GDM in the joint analysis. rs7754840, a variant in CDKAL1, had the strongest association with GDM (odds ratio 1.518; P=6.65×10(-16)). A variant near MTNR1B, rs10830962, was also significantly associated with the risk of GDM (1.454; P=2.49×10(-13)). We found that there is an excess of association between known type 2 diabetes variants and GDM above what is expected under the null hypothesis. In conclusion, we have confirmed that genetic variants in CDKAL1 and near MTNR1B are strongly associated with GDM in Korean women. There seems to be a shared genetic basis between GDM and type 2 diabetes.

Prolongation of the electrocardiographic QT interval, a measure of cardiac repolarization, predisposes one to ventricular arrhythmias and sudden cardiac death. Since NOS1AP, a regulator of neuronal nitric oxide synthase, was discovered in a genome-wide association study (GWAS) as a novel target that modulates cardiac repolarization, several loci have been linked to the QT interval in studies (QTGEN and QTSCD) of European descendents. However, there has been no GWAS of the QT interval in Asian populations. We conducted a GWAS with regard to the QT interval in Korea Association Resource (KARE [n = 6,805]) cohorts. Replication studies in independent populations of Korean (n = 4,686) and Japanese (n = 2,687) groups validated the association between a SNP, rs13017846, which maps to near SLC8A1 (sodium/calcium exchanger 1 precursor, overall p = 8.0 × 10(-14)), and the QT interval. The minor allele frequency (MAF) of rs13017846 varies widely between ethnicities-0.053 in Europeans (HapMap CEU [Utah residents with ancestry from northern and western Europe from the Centre d'Étude du Polymorphisme Humain collection] samples) versus 0.080 in Africans (HapMap YRI [Yoruba in Ibadan, Nigeria] samples)-whereas a MAF of 0.500 has been reported in Asians (HapMap HCB [Han Chinese in Beijing, China] and JPT [Japanese in Tokyo, Japan] samples). This might explain why this locus has not been identified in Europeans in previous studies.

We aggregated coding variant data for 81,412 type 2 diabetes cases and 370,832 controls of diverse ancestry, identifying 40 coding variant association signals (P < 2.2 × 10-7); of these, 16 map outside known risk-associated loci. We make two important observations. First, only five of these signals are driven by low-frequency variants: even for these, effect sizes are modest (odds ratio ≤1.29). Second, when we used large-scale genome-wide association data to fine-map the associated variants in their regional context, accounting for the global enrichment of complex trait associations in coding sequence, compelling evidence for coding variant causality was obtained for only 16 signals. At 13 others, the associated coding variants clearly represent 'false leads' with potential to generate erroneous mechanistic inference. Coding variant associations offer a direct route to biological insight for complex diseases and identification of validated therapeutic targets; however, appropriate mechanistic inference requires careful specification of their causal contribution to disease predisposition.