Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10-8) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.

The contribution of common and rare genetic variants to variation in metabolic traits in 288,137 East Asians.

Metabolic traits are heritable phenotypes widely-used in assessing the risk of various diseases. We conduct a genome-wide association analysis (GWAS) of nine metabolic traits (including glycemic, lipid, liver enzyme levels) in 125,872 Korean subjects genotyped with the Korea Biobank Array. Following meta-analysis with GWAS from Biobank Japan identify 144 novel signals (MAF ≥ 1%), of which 57.0% are replicated in UK Biobank. Additionally, we discover 66 rare (MAF < 1%) variants, 94.4% of them co-incident to common loci, adding to allelic series. Although rare variants have limited contribution to overall trait variance, these lead, in carriers, substantial loss of predictive accuracy from polygenic predictions of disease risk from common variant alone. We capture groups with up to 16-fold variation in type 2 diabetes (T2D) prevalence by integration of genetic risk scores of fasting plasma glucose and T2D and the I349F rare protective variant. This study highlights the need to consider the joint contribution of both common and rare variants on inherited risk of metabolic traits and related diseases.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.

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.

Unraveling the Genomic Architecture of the CYP3A Locus and ADME Genes for Personalized Tacrolimus Dosing.

BACKGROUND: Tacrolimus (TAC) is an immunosuppressant widely prescribed following an allogenic organ transplant. Due to wide interindividual pharmacokinetic (PK) variability, optimizing TAC dosing based on genetic factors is required to minimize nephrotoxicity and acute rejections. METHODS: We enrolled 1133 participants receiving TAC from 4 cohorts, consisting of 3 with kidney transplant recipients and 1 with healthy males from clinical trials. The effects of clinical factors were estimated to appropriately control confounding variables. A genome-wide association study, haplotype analysis, and a gene-based association test were conducted using the Korea Biobank Array or targeted sequencing for 114 pharmacogenes. RESULTS: Genome-wide association study verified that CYP3A5*3 is the only common variant associated with TAC PK variability in Koreans. We detected several CYP3A5 and CYP3A4 rare variants that could potentially affect TAC metabolism. The haplotype structure of CYP3A5 stratified by CYP3A5*3 was a significant factor for CYP3A5 rare variant interpretation. CYP3A4 rare variant carriers among CYP3A5 intermediate metabolizers displayed higher TAC trough levels. Gene-based association tests in the 61 absorption, distribution, metabolism, and excretion genes revealed that CYP1A1 are associated with additional TAC PK variability: CYP1A1 rare variant carriers among CYP3A5 poor metabolizers showed lower TAC trough levels than the noncarrier controls. CONCLUSIONS: Our study demonstrates that rare variant profiling of CYP3A5 and CYP3A4, combined with the haplotype structures of CYP3A locus, provide additive value for personalized TAC dosing. We also identified a novel association between CYP1A1 rare variants and TAC PK variability in the CYP3A5 nonexpressers that needs to be further investigated.

Genome-wide association studies identify two novel loci conferring susceptibility to diabetic retinopathy in Japanese patients with type 2 diabetes.

Several reports have suggested that genetic susceptibility contributes to the development and progression of diabetic retinopathy. We aimed to identify genetic loci that confer susceptibility to diabetic retinopathy in Japanese patients with type 2 diabetes. We analysed 5 790 508 single nucleotide polymorphisms (SNPs) in 8880 Japanese patients with type 2 diabetes, 4839 retinopathy cases and 4041 controls, as well as 2217 independent Japanese patients with type 2 diabetes, 693 retinopathy cases and 1524 controls. The results of these two genome-wide association studies (GWAS) were combined with an inverse variance meta-analysis (Stage-1), followed by de novo genotyping for the candidate SNP loci (P < 1.0 × 10-4) in an independent case-control study (Stage-2, 2260 cases and 723 controls). After combining the association data (Stages 1 and 2) using meta-analysis, the associations of two loci reached a genome-wide significance level: rs12630354 near STT3B on chromosome 3, P = 1.62 × 10-9, odds ratio (OR) = 1.17, 95% confidence interval (CI) 1.11-1.23, and rs140508424 within PALM2 on chromosome 9, P = 4.19 × 10-8, OR = 1.61, 95% CI 1.36-1.91. However, the association of these two loci was not replicated in Korean, European or African American populations. Gene-based analysis using Stage-1 GWAS data identified a gene-level association of EHD3 with susceptibility to diabetic retinopathy (P = 2.17 × 10-6). In conclusion, we identified two novel SNP loci, STT3B and PALM2, and a novel gene, EHD3, that confers susceptibility to diabetic retinopathy; however, further replication studies are required to validate these associations.

Obesity susceptible novel DNA methylation marker on regulatory region of inflammation gene: results from the Korea Epigenome Study (KES).

INTRODUCTION: Obesity is growing global health concern and highly associated with increased risk of metabolic diseases including type 2 diabetes. We aimed to discover new differential DNA methylation patterns predisposing obesity and prioritize surrogate epigenetic markers in Koreans. RESEARCH DESIGN AND METHODS: We performed multistage epigenome-wide analyses to identify differentially expressed CpGs in obesity using the Illumina HumanMethylationEPIC array (EPIC). Forty-eight CpGs showed significant differences across three phases: 902 whole blood DNAs from two cohorts (phase 1: n=450, phase 2: n=377) and a hospital-based sample (phase 3: n=75). Samples from phase III participants were used to examine whether the 48 CpGs are significant in the fat tissue and influenced gene expression. Furthermore, we investigated the epigenetic effect of CpG loci in childhood obesity (n=94). RESULTS: Seven of the 48 CpGs exhibited similar changes in the fat tissue along with gene expression changes. In particular, hypomethylated CpG (cg13424229) on the GATA1 transcription factor cluster of CPA3 promoter was related to its increased gene expression and showed consistent effect in childhood obesity. Interestingly, subsequent analysis using RNA sequencing data from 21 preadipocytes and 26 adipocytes suggested CPA3 as a potential obesity-related gene. Moreover, expression patterns from RNA sequencing and public Gene Expression Omnibus showed the correlation between CPA3 and type 2 diabetes (T2D) and asthma. CONCLUSIONS: Our finding prioritizes influential genes in obesity and provides new evidence for the role of CPA3 linking obesity, T2D, and asthma.

Integrated Analysis of Tissue-Specific Promoter Methylation and Gene Expression Profile in Complex Diseases.

This study investigated whether the promoter region of DNA methylation positively or negatively regulates tissue-specific genes (TSGs) and if it correlates with disease pathophysiology. We assessed tissue specificity metrics in five human tissues, using sequencing-based approaches, including 52 whole genome bisulfite sequencing (WGBS), 52 RNA-seq, and 144 chromatin immunoprecipitation sequencing (ChIP-seq) data. A correlation analysis was performed between the gene expression and DNA methylation levels of the TSG promoter region. The TSG enrichment analyses were conducted in the gene-disease association network (DisGeNET). The epigenomic association analyses of CpGs in enriched TSG promoters were performed using 1986 Infinium MethylationEPIC array data. A correlation analysis showed significant associations between the promoter methylation and 449 TSGs' expression. A disease enrichment analysis showed that diabetes- and obesity-related diseases were high-ranked. In an epigenomic association analysis based on obesity, 62 CpGs showed statistical significance. Among them, three obesity-related CpGs were newly identified and replicated with statistical significance in independent data. In particular, a CpG (cg17075888 of PDK4), considered as potential therapeutic targets, were associated with complex diseases, including obesity and type 2 diabetes. The methylation changes in a substantial number of the TSG promoters showed a significant association with metabolic diseases. Collectively, our findings provided strong evidence of the relationship between tissue-specific patterns of epigenetic changes and metabolic diseases.

Identification of type 2 diabetes loci in 433,540 East Asian individuals.

Meta-analyses of genome-wide association studies (GWAS) have identified more than 240 loci that are associated with type 2 diabetes (T2D)1,2; however, most of these loci have been identified in analyses of individuals with European ancestry. Here, to examine T2D risk in East Asian individuals, we carried out a meta-analysis of GWAS data from 77,418 individuals with T2D and 356,122 healthy control individuals. In the main analysis, we identified 301 distinct association signals at 183 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 61 loci that are newly implicated in predisposition to T2D. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. Previously undescribed associations include signals in or near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect the differentiation of muscle and adipose cells3. At another locus, expression quantitative trait loci at two overlapping T2D signals affect two genes-NKX6-3 and ANK1-in different tissues4-6. Association studies in diverse populations identify additional loci and elucidate disease-associated genes, biology, and pathways.

Programmable Nuclease-Based Integration into Novel Extragenic Genomic Safe Harbor Identified from Korean Population-Based CNV Analysis.

Here, we found two genomic safe harbor (GSH) candidates from chromosomes 3 and 8, based on large-scale population-based cohort data from 4,694 Koreans by CNV analysis. Furthermore, estimated genotype of these CNVRs was validated by quantitative real-time PCR, and epidemiological data examined no significant genetic association between diseases or traits and two CNVRs. After screening the GSH candidates by in silico approaches, we designed TALEN pairs to integrate EGFP expression cassette into human cell lines in order to confirm the functionality of GSH candidates in an in vitro setting. As a result, transgene insertion into one of the two loci using TALEN showed robust transgene expression comparable to that with an AAVS1 site without significantly perturbing neighboring genes. Changing the promoter or cell type did not noticeably disturb this trend. Thus, we could validate two CNVRs as a site for effective and safe transgene insertion in human cells.

Exome chip-driven association study of lipidemia in >14,000 Koreans and evaluation of genetic effect on identified variants between different ethnic groups.

Lipid levels in blood are widely used to diagnose and monitor chronic diseases. It is essential to identify the genetic traits involved in lipid metabolism for understanding chronic diseases. However, the influence of genetic traits varies depending on race, sex, age, and ethnicity. Therefore, research focusing on populations of individual countries is required, and the results can be used as a basis for comparison of results of other studies at the cross-racial and cross-country levels. In the present study, we selected lipid-related variants and evaluated their effects on lipid-related diseases in more than 14,000 subjects of three cohorts using the Illumina Human Exome Beadchip. A genome-wide association study was conducted using EPACTs after adjusting for age, sex, and recruitment area. A genome-wide significance cutoff was defined as p < 5E-08 in all the three cohorts. Sixteen variants represented the lipid traits and were classified as vulnerable to borderline hypertriglyceridemia, hyper-LDL-cholesterolemia, or hypo-HDL-cholesterolemia. Moreover, we compared the genetic effects of the 16 variants between ethnic groups and identified the missense variants in apolipoprotein A-V, cholesterol ester transfer protein, and apolipoprotein E as Asian-specific. Our study provides candidate genes as markers for chronic diseases through the evaluation of genetic effects.

The Korea Biobank Array: Design and Identification of Coding Variants Associated with Blood Biochemical Traits.

We introduce the design and implementation of a new array, the Korea Biobank Array (referred to as KoreanChip), optimized for the Korean population and demonstrate findings from GWAS of blood biochemical traits. KoreanChip comprised >833,000 markers including >247,000 rare-frequency or functional variants estimated from >2,500 sequencing data in Koreans. Of the 833 K markers, 208 K functional markers were directly genotyped. Particularly, >89 K markers were presented in East Asians. KoreanChip achieved higher imputation performance owing to the excellent genomic coverage of 95.38% for common and 73.65% for low-frequency variants. From GWAS (Genome-wide association study) using 6,949 individuals, 28 associations were successfully recapitulated. Moreover, 9 missense variants were newly identified, of which we identified new associations between a common population-specific missense variant, rs671 (p.Glu457Lys) of ALDH2, and two traits including aspartate aminotransferase (P = 5.20 × 10-13) and alanine aminotransferase (P = 4.98 × 10-8). Furthermore, two novel missense variants of GPT with rare frequency in East Asians but extreme rarity in other populations were associated with alanine aminotransferase (rs200088103; p.Arg133Trp, P = 2.02 × 10-9 and rs748547625; p.Arg143Cys, P = 1.41 × 10-6). These variants were successfully replicated in 6,000 individuals (P = 5.30 × 10-8 and P = 1.24 × 10-6). GWAS results suggest the promising utility of KoreanChip with a substantial number of damaging variants to identify new population-specific disease-associated rare/functional variants.

Interethnic analyses of blood pressure loci in populations of East Asian and European descent.

Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, we perform a multi-stage genome-wide association study for BP (max N = 289,038) principally in East Asians and meta-analysis in East Asians and Europeans. We report 19 new genetic loci and ancestry-specific BP variants, conforming to a common ancestry-specific variant association model. At 10 unique loci, distinct non-rare ancestry-specific variants colocalize within the same linkage disequilibrium block despite the significantly discordant effects for the proxy shared variants between the ethnic groups. The genome-wide transethnic correlation of causal-variant effect-sizes is 0.898 and 0.851 for systolic and diastolic BP, respectively. Some of the ancestry-specific association signals are also influenced by a selective sweep. Our results provide new evidence for the role of common ancestry-specific variants and natural selection in ethnic differences in complex traits such as BP.

Multiple genotype-phenotype association study reveals intronic variant pair on SIDT2 associated with metabolic syndrome in a Korean population.

BACKGROUND: Metabolic syndrome is a risk factor for type 2 diabetes and cardiovascular disease. We identified common genetic variants that alter the risk for metabolic syndrome in the Korean population. To isolate these variants, we conducted a multiple-genotype and multiple-phenotype genome-wide association analysis using the family-based quasi-likelihood score (MFQLS) test. For this analysis, we used 7211 and 2838 genotyped study subjects for discovery and replication, respectively. We also performed a multiple-genotype and multiple-phenotype analysis of a gene-based single-nucleotide polymorphism (SNP) set. RESULTS: We found an association between metabolic syndrome and an intronic SNP pair, rs7107152 and rs1242229, in SIDT2 gene at 11q23.3. Both SNPs correlate with the expression of SIDT2 and TAGLN, whose products promote insulin secretion and lipid metabolism, respectively. This SNP pair showed statistical significance at the replication stage. CONCLUSIONS: Our findings provide insight into an underlying mechanism that contributes to metabolic syndrome.

Analysis of a survey on orthopaedic residency training for fracture treatment in Korea.

INTRODUCTION: Fracture surgery is the most frequently performed orthopaedic procedure and is considered an essential surgical procedure for orthopaedic surgeons in general. Although the approach and circumstances of orthopaedic residency training for fracture treatment may differ between countries, the goals of training, which is to educate the residents regarding the principles of the fracture treatment and foster conscientious orthopaedic specialists, remain unchanged. Thus, the aim of the this study was to determine a desirable course of orthopaedic residency training by investigating and analysing the reality of training associated with fracture surgery and treatment during the orthopaedic residency of 4th year orthopaedic residents in Korea. METHODS: Using a questionnaire survey, a one-on-one interview was proposed to 266 applicants following the secondary board examination of residents who had completed the orthopaedic residency training course; the survey was conducted on January 19, 2016. Responses from 152 applicants (response rate: 57%) who accepted to participate in the survey were statistically analysed. RESULTS: During residency training, clinicians underwent fracture-related training for 3.5 h on average per month. Training consisted of various approaches and included lectures by professors, case briefings, textbook reading, and field training in an operating room. The residents largely differed in terms of experience in conducting fracture surgery: 47 (31%) responded that they had never performed fracture surgery during the training period, whereas 21 (14%) answered that they had conducted fracture surgery over 20 times. Experience in performing the surgical procedure was the most valuable in fracture training. CONCLUSION: To optimize fracture education among orthopaedic residents, the professors at teaching hospitals should understand the realities of fracture education, dedicate sufficient time for internal and external fracture teachings, and allow residents to perform fracture surgeries hands-on under their supervision, and also attempt to foster a social atmosphere that encourages all three factors.

Nonsynonymous Variants in PAX4 and GLP1R Are Associated With Type 2 Diabetes in an East Asian Population.

We investigated ethnicity-specific exonic variants of type 2 diabetes (T2D) and its related clinical phenotypes in an East Asian population. We performed whole-exome sequencing in 917 T2D case and control subjects, and the findings were validated by exome array genotyping in 3,026 participants. In silico replication was conducted for seven nonsynonymous variants in an additional 13,122 participants. Single-variant and gene-based association tests for T2D were analyzed. A total of 728,838 variants were identified by whole-exome sequencing. Among nonsynonymous variants, PAX4 Arg192His increased risk of T2D and GLP1R Arg131Gln decreased risk of T2D in genome-wide significance (odds ratio [OR] 1.48, P = 4.47 × 10-16 and OR 0.84, P = 3.55 × 10-8, respectively). Another variant at PAX4 192 codon Arg192Ser was nominally associated with T2D (OR 1.62, P = 5.18 × 10-4). In T2D patients, PAX4 Arg192His was associated with earlier age at diagnosis, and GLP1R Arg131Gln was associated with decreased risk of cardiovascular disease. In control subjects without diabetes, the PAX4 Arg192His was associated with higher fasting glucose and GLP1R Arg131Gln was associated with lower fasting glucose and HbA1c level. Gene-based analysis revealed that SLC30A8 was most significantly associated with decreased risk of T2D (P = 1.0 × 10-4). In summary, we have identified nonsynonymous variants associated with risk of T2D and related phenotypes in Koreans.

On the association analysis of CNV data: a fast and robust family-based association method.

BACKGROUND: Copy number variation (CNV) is known to play an important role in the genetics of complex diseases and several methods have been proposed to detect association of CNV with phenotypes of interest. Statistical methods for CNV association analysis can be categorized into two different strategies. First, the copy number is estimated by maximum likelihood and association of the expected copy number with the phenotype is tested. Second, the observed probe intensity measurements can be directly used to detect association of CNV with the phenotypes of interest. RESULTS: For each strategy we provide a statistic that can be applied to extended families. The computational efficiency of the proposed methods enables genome-wide association analysis and we show with simulation studies that the proposed methods outperform other existing approaches. In particular, we found that the first strategy is always more efficient than the second strategy no matter whether copy numbers for each individual are well identified or not. With the proposed methods, we performed genome-wide CNV association analyses of hematological trait, hematocrit, on 521 Korean family samples. CONCLUSIONS: We found that statistical analysis with the expected copy number is more powerful than the statistic with the probe intensity measurements regardless of the accuracy of the estimation of copy numbers.

Genome-Wide Association Study Meta-Analysis of Long-Term Average Blood Pressure in East Asians.

BACKGROUND: Genome-wide single marker and gene-based meta-analyses of long-term average (LTA) blood pressure (BP) phenotypes may reveal novel findings for BP. METHODS AND RESULTS: We conducted genome-wide analysis among 18 422 East Asian participants (stage 1) followed by replication study of ≤46 629 participants of European ancestry (stage 2). Significant single-nucleotide polymorphisms and genes were determined by a P<5.0×10-8 and 2.5×10-6, respectively, in joint analyses of stage-1 and stage-2 data. We identified 1 novel ARL3 variant, rs4919669 at 10q24.32, influencing LTA systolic BP (stage-1 P=5.03×10-8, stage-2 P=8.64×10-3, joint P=2.63×10-8) and mean arterial pressure (stage-1 P=3.59×10-9, stage-2 P=2.35×10-2, joint P=2.64×10-8). Three previously reported BP loci (WBP1L, NT5C2, and ATP2B1) were also identified for all BP phenotypes. Gene-based analysis provided the first robust evidence for association of KCNJ11 with LTA systolic BP (stage-1 P=8.55×10-6, stage-2 P=1.62×10-5, joint P=3.28×10-9) and mean arterial pressure (stage-1 P=9.19×10-7, stage-2 P=9.69×10-5, joint P=2.15×10-9) phenotypes. Fourteen genes (TMEM180, ACTR1A, SUFU, ARL3, SFXN2, WBP1L, CYP17A1, C10orf32, C10orf32-ASMT, AS3MT, CNNM2, and NT5C2 at 10q24.32; ATP2B1 at 12q21.33; and NCR3LG1 at 11p15.1) implicated by previous genome-wide association study meta-analyses were also identified. Among the loci identified by the previous genome-wide association study meta-analysis of LTA BP, we transethnically replicated associations of the KCNK3 marker rs1275988 at 2p23.3 with LTA systolic BP and mean arterial pressure phenotypes (P=1.27×10-4 and 3.30×10-4, respectively). CONCLUSIONS: We identified 1 novel variant and 1 novel gene and present the first direct evidence of relevance of the KCNK3 locus for LTA BP among East Asians.

Association analyses of East Asian individuals and trans-ancestry analyses with European individuals reveal new loci associated with cholesterol and triglyceride levels.

Large-scale meta-analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting cholesterol levels, including total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), and triglycerides (TG). With differences in linkage disequilibrium (LD) structure and allele frequencies between ancestry groups, studies in additional large samples may detect new associations. We conducted staged GWAS meta-analyses in up to 69,414 East Asian individuals from 24 studies with participants from Japan, the Philippines, Korea, China, Singapore, and Taiwan. These meta-analyses identified (P < 5 × 10-8) three novel loci associated with HDL-C near CD163-APOBEC1 (P = 7.4 × 10-9), NCOA2 (P = 1.6 × 10-8), and NID2-PTGDR (P = 4.2 × 10-8), and one novel locus associated with TG near WDR11-FGFR2 (P = 2.7 × 10-10). Conditional analyses identified a second signal near CD163-APOBEC1. We then combined results from the East Asian meta-analysis with association results from up to 187,365 European individuals from the Global Lipids Genetics Consortium in a trans-ancestry meta-analysis. This analysis identified (log10Bayes Factor ≥6.1) eight additional novel lipid loci. Among the twelve total loci identified, the index variants at eight loci have demonstrated at least nominal significance with other metabolic traits in prior studies, and two loci exhibited coincident eQTLs (P < 1 × 10-5) in subcutaneous adipose tissue for BPTF and PDGFC. Taken together, these analyses identified multiple novel lipid loci, providing new potential therapeutic targets.

Genome-based exome sequencing analysis identifies GYG1, DIS3L and DDRGK1 are associated with myocardial infarction in Koreans.

Myocardial infarction (MI) is a complex disease caused by combination of genetic and environmental factors. Although genome-wide association studies (GWAS) identified more than 46 risk loci which are associated with coronary artery disease and MI, most of the genetic variability inMI still remains undefined. Here, we screened the susceptibility loci for MI using exome sequencing and validated candidate variants in replication sets. We identified that three genes (GYG1, DIS3L and DDRGK1) were associated with MI at the discovery and replication stages. Further research will be required to determine the functional association of these genes with MI risk, and these associations have to be confirmed in other ethnic populations.