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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 (GWAS), haplotype analysis, and a gene-based association test were conducted using the Korea Biobank Array or targeted sequencing for 114 pharmacogenes. Results GWAS verified that CYP3A5*3 is the only common variant associated with TAC PK variability in Koreans. We detected several CYP3A5 and CYP3A4 rare variants which 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 (ADME) 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 which needs to be further investigated.Supplemental Visual Abstract; http://links.lww.com/TP/C134.

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

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. Keywords: genome editing, TALEN, safe harbor, copy number variation region

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. Electronic supplementary material The online version of this article (10.1186/s40246-018-0180-4) contains supplementary material, which is available to authorized users.

Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.A trans-ancestry meta-analysis of GWAS of glycemic traits in up to 281,416 individuals identifies 99 novel loci, of which one quarter was found due to the multi-ancestry approach, which also improves fine-mapping of credible variant sets.

We assembled an ancestrally diverse collection of genome-wide association studies of type 2 diabetes (T2D) in 180,834 cases and 1,159,055 controls (48.9% non-European descent). We identified 277 loci at genome-wide significance (p-8), including 237 attaining a more stringent trans-ancestry threshold (p-9), which were delineated to 338 distinct association signals. Trans-ancestry meta-regression offered substantial enhancements to fine-mapping, with 58.6% of associations more precisely localised due to population diversity, and 54.4% of signals resolved 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 foundations for functional investigations. Trans-ancestry genetic risk scores enhanced transferability across diverse populations, providing a step towards more effective clinical translation to improve global health.

Glycaemic traits are used to diagnose and monitor type 2 diabetes, and cardiometabolic health. To date, most genetic studies of glycaemic traits have focused on individuals of European ancestry. Here, we aggregated genome-wide association studies in up to 281,416 individuals without diabetes (30% non-European ancestry) with fasting glucose, 2h-glucose post-challenge, glycated haemoglobin, and fasting insulin data. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P-8), 80% with no significant evidence of between-ancestry heterogeneity. Analyses restricted to European ancestry individuals with equivalent sample size would have led to 24 fewer new loci. Compared to single-ancestry, equivalent sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase understanding of diabetes pathophysiology by use of trans-ancestry studies for improved power and resolution.

IntroductionObesity 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 methodsWe 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).ResultsSeven 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.ConclusionsOur finding prioritizes influential genes in obesity and provides new evidence for the role of CPA3 linking obesity, T2D, and asthma.

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

Osteoporotic fractures (OFs) are critical hard outcomes of osteoporosis and are characterized by decreased bone strength induced by low bone density and microarchitectural deterioration in bone tissue. Most OFs cause acute pain, hospitalization, immobilization, and slow recovery in patients and are associated with increased mortality. A variety of genetic studies have suggested associations of genetic variants with the risk of OF. Genome-wide association studies have reported various single-nucleotide polymorphisms and copy number variations (CNVs) in European and Asian populations. To identify CNV regions associated with OF risk, we conducted a genome-wide CNV study in a Korean population. We performed logistic regression analyses in 1,537 Korean subjects (299 OF cases and 1,238 healthy controls) and identified a total of 8 CNV regions significantly associated with OF (p < 0.05). Then, one CNV region located on chromosome 20q13.12 was selected for experimental validation. The selected CNV region was experimentally validated by quantitative polymerase chain reaction. The CNV region of chromosome 20q13.12 is positioned upstream of a family of long non-coding RNAs, LINC01260. Our findings could provide new information on the genetic factors associated with the risk of OF.

SUMMARYMeta-analyses of genome-wide association studies (GWAS) have identified >240 loci associated with type 2 diabetes (T2D), however most loci have been identified in analyses of European-ancestry individuals. To examine T2D risk in East Asian individuals, we meta-analyzed GWAS data in 77,418 cases and 356,122 controls. In the main analysis, we identified 298 distinct association signals at 178 loci, and across T2D association models with and without consideration of body mass index and sex, we identified 56 loci newly implicated in T2D predisposition. Common variants associated with T2D in both East Asian and European populations exhibited strongly correlated effect sizes. New associations include signals in/near GDAP1, PTF1A, SIX3, ALDH2, a microRNA cluster, and genes that affect muscle and adipose differentiation. At another locus, eQTLs at two overlapping T2D signals act through two genes, NKX6-3 and ANK1, in different tissues. Association studies in diverse populations identify additional loci and elucidate disease genes, biology, and pathways.Type 2 diabetes (T2D) is a common metabolic disease primarily caused by insufficient insulin production and/or secretion by the pancreatic β cells and insulin resistance in peripheral tissues1. Most genetic loci associated with T2D have been identified in populations of European (EUR) ancestry, including a recent meta-analysis of genome-wide association studies (GWAS) of nearly 900,000 individuals of European ancestry that identified >240 loci influencing the risk of T2D2. Differences in allele frequency between ancestries affect the power to detect associations within a population, particularly among variants rare or monomorphic in one population but more frequent in another3,4. Although smaller than studies in European populations, a recent T2D meta-analysis in almost 200,000 Japanese individuals identified 28 additional loci4. The relative contributions of different pathways to the pathophysiology of T2D may also differ between ancestry groups. For example, in East Asian (EAS) populations, T2D prevalence is greater than in European populations among people of similar body mass index (BMI) or waist circumference5. We performed the largest meta-analysis of East Asian individuals to identify new genetic associations and provide insight into T2D pathogenesis.

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.

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

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&ndash, 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&rsquo, 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.

Low levels of HDL are known to be associated with increased risk of type 2 diabetes. It has been suggested as a new therapeutic approach that increase HDL levels in plasma. Previously, to identify lipids traits associated loci, we performed large-scale genome-wide meta-analyses comprising 25,923 East Asian individuals from 11 studies from Korea, Japan, Philippines, China, Singapore, and Taiwan in the discovery stage. With subsequent replication study, we have revealed seven novel loci associated with HDL including loci at CD163-APOBEC1, NCOA2, and NID2-PTGDR. However, previous study was limited in sample size in the discovery stage and low association mapping resolution due to HapMap based imputation analysis. In this study, we performed genome-wide association analyses (GWAS) on HDL using about 35,000 Korean samples and imputed based on 1,000 Genomes project phase 3 and Korean Reference Genome. We focused on imputed (imputation quality score >0.4) and genotyped common variants with minor allele frequency >= 1%. In this discovery study, 17 known loci were replicated at the genome-wide significance level (P In summary, we performed a GWAS on HDL using about 35,000 Korean samples. The GWAS confirmed 28 known loci and discovered 10 possible novel candidate loci responsible for variation of HDL level. However, a replication study in an independent cohort is warranted for validating the results. Taken together, the possible novel candidates discovered from this study may provide potential novel therapeutic targets for diseases associated with HDL. Disclosure B. Kim: None. Y. Kim: None. M. Hwang: None. S. Moon: None.

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

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 in MI 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.

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., Blood pressure (BP) is a major risk factor for cardiovascular disease and more than 200 genetic loci associated with BP are known. Here, the authors perform discovery GWAS for BP in East Asians and meta-analysis in East Asians and Europeans and report ancestry-specific BP SNPs and selection signals.

Supplementary information. Figure S1. Screenshot of GTEx database for significant SNP pair rs7107152 and rs1242229. Figure S2. Screenshot of NESDA NTR Conditional eQTL Catalog for rs7107152 and rs1242229. Figure S3. Screenshot of RegulomeDB for rs1242229. Figure S4. Radar chart showing the result of the rs7107152 and rs1242229 SNP pairâ single trait (metabolic syndrome-component trait) association analysis. Figure S5. Screenshot from the GTEx database of the eQTL SNP-enriched region around SIDT2 and TAGLN (chr11:117,000,000-117,100,000). Figure S6 Model for how significant SNP pair rs7107152/rs1242229 may affect metabolic syndrome risk. Table S1. Characteristics of gene-based SNPs set. Table S2. Minor allele frequency of identified SNPs. (PDF 975 kb)

Copy number variation is a well-known genetic variation. microRNAs (miRNAs/miRs) are non-coding RNAs that mediate gene expression by regulating target mRNAs. In the present study, copy number deletions encompassing miRNA coding regions were investigated to determine the association between the deletion of miRNA and its phenotypic effects. A total of 38 human miRNAs in copy number variants were identified and miR-650, which is functional in the human osteosarcoma MG-63 cell line, was selected. Overexpression of miR-650 decreased the expression of inhibitor of growth family member 4 (ING4) in the MG-63 cells and increased interleukin (IL)6 transcription, as well as IL6 secretion in IL1B-stimulated cells. Furthermore, miR-650 downregulated the amount of nuclear factor of κ light polypeptide gene enhancer in B cells inhibitor α and increased the transcriptional activity of nuclear factor (NF)κB. Downregulation of ING4 also increased the production of IL6, similar to miR-650 overexpression. Taken together, these data indicate that miR-650 plays a significant role in the production of IL6 by regulating ING4 expression and NFκB signaling in IL1B-stimulated MG-63 osteosarcoma cells.

Platelets are derived from the fragments that are formed from the cytoplasm of bone marrow megakaryocytes-small irregularly shaped anuclear cells. Platelets respond to vascular damage, contracts blood vessels, and attaches to the damaged region, thereby stopping bleeding, together with the action of blood coagulation factors. Platelet activation is known to affect genes associated with vascular risk factors, as well as with arteriosclerosis and myocardial infarction. Here, we performed a genome-wide association study with 352,228 single-nucleotide polymorphisms typed in 8,842 subjects of the Korea Association Resource (KARE) project and replicated the results in 7,861 subjects from an independent population. We identified genetic associations between platelet count and common variants nearby chromosome 4p16.1 (p = 1.46 × 10(-10), in the KIAA0232 gene), 6p21 (p = 1.36 × 10(-7), in the BAK1 gene), and 12q24.12 (p = 1.11 × 10(-15), in the SH2B3 gene). Our results illustrate the value of large-scale discovery and a focus for several novel research avenues.

Longitudinal data enables detecting the effect of aging/time, and as a repeated measures design is statistically more efficient compared to cross-sectional data if the correlations between repeated measurements are not large. In particular, when genotyping cost is more expensive than phenotyping cost, the collection of longitudinal data can be an efficient strategy for genetic association analysis. However, in spite of these advantages, genome-wide association studies (GWAS) with longitudinal data have rarely been analyzed taking this into account. In this report, we calculate the required sample size to achieve 80% power at the genome-wide significance level for both longitudinal and cross-sectional data, and compare their statistical efficiency. Furthermore, we analyzed the GWAS of eight phenotypes with three observations on each individual in the Korean Association Resource (KARE). A linear mixed model allowing for the correlations between observations for each individual was applied to analyze the longitudinal data, and linear regression was used to analyze the first observation on each individual as cross-sectional data. We found 12 novel genome-wide significant disease susceptibility loci that were then confirmed in the Health Examination cohort, as well as some significant interactions between age/sex and SNPs.

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 −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.

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. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1622-z) contains supplementary material, which is available to authorized users.

A complete report for all experiments performed for this work. Text 1. Rao’s score test statistic with the expected copy number. Text 2. Rao’s score test statistic with the probe intensity measurements. Figure S1. Results of the clustering analysis with family samples (A) and cohort samples (B). Figure S2. Schematic representation of the strategy for the CNV analysis. Figure S3. Validation results. Figure S4. Validation results of replication samples by TaqMan qPCR experiment. Table S1. Specification of parameters for the signal model used in the simulation studies. Table S2. Primer information for CNV validation. Table S3. Accuracy of copy number clusters identified with PedCNV. Table S4. Accuracy of copy number clusters identified with CNVtools. Table S5. Accuracy of copy number estimated with silhouette score. Table S6. Empirical type 1 error estimates when M = 6. Table S7. Empirical power estimates when M = 6. Table S8. Empirical power estimates of T 1 and T 1 * which use the expected copy number and the most probable copy number respectively. Table S9. Estimated parameters of T 1 and T 1 * which use the expected copy number and the most probable copy number respectively. (PDF 814 kb)

Background Osteoporotic fracture (OF) as a clinical endpoint is a major complication of osteoporosis. To screen for OF susceptibility genes, we performed a genome-wide association study and carried out de novo replication analysis of an East Asian population. Methods Association was tested using a logistic regression analysis. A meta-analysis was performed on the combined results using effect size and standard errors estimated for each study. Results In a combined meta-analysis of a discovery cohort (288 cases and 1139 controls), three hospital based sets in replication stage I (462 cases and 1745 controls), and an independent ethnic group in replication stage II (369 cases and 560 for controls), we identified a new locus associated with OF ( rs784288 in the MECOM gene) that showed genome-wide significance (p=3.59×10 −8 ; OR 1.39). RNA interference revealed that a MECOM knockdown suppresses osteoclastogenesis. Conclusions Our findings provide new insights into the genetic architecture underlying OF in East Asians.

Genome-wide association studies (GWAS) have identified more than 80 susceptibility loci for type 2 diabetes (T2D), but most of its heritability still remains to be elucidated. In this study, we conducted a meta-analysis of GWAS for T2D in the Japanese population. Combined data from discovery and subsequent validation analyses (23,399 T2D cases and 31,722 controls) identify 7 new loci with genome-wide significance (P), rs1116357 near CCDC85A, rs147538848 in FAM60A, rs1575972 near DMRTA1, rs9309245 near ASB3, rs67156297 near ATP8B2, rs7107784 near MIR4686 and rs67839313 near INAFM2. Of these, the association of 4 loci with T2D is replicated in multi-ethnic populations other than Japanese (up to 65,936 T2Ds and 158,030 controls, P, 論文