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.

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.

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.

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.

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.

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.

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.

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 of serum lipids confirms previously reported associations as well as new associations of common SNPs within PCSK7 gene with triglyceride.

Previous reports including genome-wide association studies (GWASs) have described associations of serum lipids with genomic variations. In the present study, we examined the association of ∼2.5 million single-nucleotide polymorphisms (SNPs) from 3041 Japanese healthy volunteers obtained from the Japan Pharmacogenomics Data Science Consortium (JPDSC) database with serum lipids. We confirmed the previously reported associations of 14 SNPs in 5 regions for low-density lipoprotein (LDL) cholesterol, 23 SNPs in 12 regions for high-density lipoprotein (HDL) cholesterol, 16 SNPs in 6 regions for triglyceride and 5 SNPs in 1 region for phospholipid. Furthermore, we identified 16 possible novel candidate genes associated with LDL cholesterol, HDL cholesterol or triglycerides, where SNPs had P-values of <1 × 10(-5). Further replication analyses of these genes with Korean data revealed significant associations of SNPs located within the PCSK7 gene and triglyceride (Pmeta=7.98 × 10(-9) and 1.91 × 10(-8) for rs508487 and rs236911, respectively). These associations remained significant even by the conditional analysis adjusting for three neighboring variations associated with triglyceride. Our present data suggest that PCSK7 as well as PCSK9 may be associated with lipids, especially triglyceride, and may serve as a candidate for a new drug target to treat lipid abnormality syndromes.

Evaluation of pleiotropic effects among common genetic loci identified for cardio-metabolic traits in a Korean population.

BACKGROUND: The genetic contribution to complex diseases or traits, including cardio-metabolic traits, has been elucidated recently by large-scale genome-wide association studies. These genome-wide association studies have indicated that most pleiotropic loci contain genes associated with lipids. Clinically, lipid related abnormalities are strongly associated with other diseases such as type 2 diabetes, coronary artery disease and hypertension. The aim of this study was to evaluate the shared genetic background of lipids and other cardio-metabolic traits. METHODS: We conducted meta-analyses of the association between 157 published lipid-associated loci and 10 cardio-metabolic traits in 14,028 Korean individuals genotyped using the Exome chip (Illumina HumanExome BeadChip). We also examined whether the pleiotropic effects of such loci constituted independent (i.e., biological) pleiotropy or mediated pleiotropy in these metabolic pathways. RESULTS: Eighteen lipid-associated loci were significantly associated with one of six cardio-metabolic traits after correction for multiple testing (P < 3.70 × 10(-4)). Region 12q24.12 had pleiotropic effects on fasting plasma glucose, blood pressure and obesity-related traits (body mass index and waist-hip ratio) independent of its effects on the lipid profile. Lipid risk scores, calculated according to whether or not subjects carried the risk allele for lipid traits, were significantly associated with fasting plasma glucose, blood pressure and obesity-related traits. CONCLUSIONS: The 12q24.12 region showed ethnic-specific genetic pleiotropy among cardio-metabolic traits in this study. Our findings may help to account for molecular mechanisms based on shared genetic background underlying not only dyslipidemia, but also cardiovascular disease and type 2 diabetes.

Combinatorial approach to estimate copy number genotype using whole-exome sequencing data.

Copy number variations (CNVs) are known risk factors in complex diseases. Array-based approaches have been widely used to detect CNVs, but limitations of array-based CNV detection methods, such as noisy signal and low resolution, have hindered detection of small CNVs. Recently, the development of next-generation sequencing techniques has increased rapidly owing to declines in cost. Particularly, whole-exome sequencing has proved useful for finding causal genes and variants in complex diseases. Because gene copy number may affect expression, CNV genotyping can be very valuable in disease association studies. However, almost all current CNV detection tools consider only two types of CNV genotypes. In this study, we propose a CNV genotype estimation approach using a combination of existing methods. Our approach was comprehensively compared with the customized Agilent array-comparative genomic hybridization. We found that our genotyping approach proved to be accurate, and reproducible, suggesting that it can complement existing CNV genotyping methods.

A genome-wide association study of copy-number variation identifies putative loci associated with osteoarthritis in Koreans.

BACKGROUND: OA is a complex disease caused by environmental and genetic risk factors. The purpose of this study is to identify candidate copy number variations (CNVs) associated with OA. METHODS: We performed a genome-wide association study of CNV to identify potential loci that confer susceptibility to or protection from OA. CNV genotyping was conducted using NimbleGen HD2 3 × 720K comparative hybridization array and included samples from 371 OA patients and 467 healthy controls. The putative CNV regions identified were confirmed with a TaqMan assay. RESULTS: We identified six genomic regions associated with OA encompassing CNV loci. None of six loci had previously been reported in genome-wide association studies with OA, although a genetic analysis suggested that they have functional effects. The protein product of a candidate risk gene for obesity, TNKS, targets Wnt inhibition, and this gene was significantly associated with hand and knee OA. Copy number deletion on TNKS was associated with a 1.37-fold decreased risk for OA. In addition, CA10, which shows a strong association with osteoporosis, was also significant in our study. Copy number deletion on this gene was associated with a 1.69-fold decreased risk for OA. CONCLUSION: We identified several CNV loci that may contribute to OA susceptibility in Koreans. Further functional investigations of these genes are warranted to fully characterize their putative association.

Genome-wide copy number variation study reveals KCNIP1 as a modulator of insulin secretion.

Copy number variations (CNVs) have emerged as another important genetic marker in addition to SNP for understanding etiology of complex diseases. In light of this, we performed a genome-wide CNV study to identify type 2 diabetes (T2D)-associated CNV using an array comparative genomic hybridization from 3180 subjects for T2D cases (n=863) and controls (n=2,317). Thus, five CNV regions having a p-value threshold ≤0.05 were identified and evaluated by validation with quantitative PCR and comparison with previously reported CNV regions in the Database of Genomic Variants. Furthermore, we performed a functional experiment to assess the biological significance of a gene encompassing a CNV region. The inhibition of KCNIP1 led to increased insulin secretion in a glucose-dependent manner, but had no effect on insulin gene transcription as well as cell apoptosis. Taken together, these data indicate that KCNIP1 from CNV study might function as a T2D-susceptibility gene whose dysregulation alters insulin production.

KGVDB: a population-based genomic map of CNVs tagged by SNPs in Koreans.

SUMMARY: Despite a growing interest in a correlation between copy number variations (CNVs) and flanking single nucleotide polymorphisms, few databases provide such information. In particular, most information on CNV available so far was obtained in Caucasian and Yoruba populations, and little is known about CNV in Asian populations. This article presents a database that provides CNV regions tagged by single nucleotide polymorphisms in about 4700 Koreans, which were detected under strict quality control, manually curated and experimentally validated. AVAILABILITY: KGVDB is freely available for non-commercial use at http://biomi.cdc.go.kr/KGVDB. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Meta-analysis identifies a MECOM gene as a novel predisposing factor of osteoporotic fracture.

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.

Gene-based copy number variation study reveals a microdeletion at 12q24 that influences height in the Korean population.

Height is a classic polygenic trait with high heritability (h(2)=0.8). Recent genome-wide association studies have revealed many independent loci associated with human height. In addition, although many studies have reported an association between copy number variation (CNV) and complex diseases, few have explored the relationship between CNV and height. Recent studies reported that single nucleotide polymorphisms (SNPs) are highly correlated with common CNVs, suggesting that it is warranted to survey CNVs to identify additional genetic factors affecting heritable traits such as height. This study tested the hypothesis that there would be CNV regions (CNVRs) associated with height nearby genes from the GWASs known to affect height. We identified regions containing >1% copy number deletion frequency from 3667 population-based cohort samples using the Illumina HumanOmni1-Quad BeadChip. Among the identified CNVRs, we selected 15 candidate regions that were located within 1Mb of 283 previously reported genes. To assess the effect of these CNVRs on height, statistical analyses were conducted with samples from a case group of 370 taller (upper 10%) individuals and a control group of 1828 individuals (lower 50%). We found that a newly identified 17.7 kb deletion at chromosomal position 12q24.33, approximately 171.6 kb downstream of GPR133, significantly correlated with height; this finding was validated using quantitative PCR. These results suggest that CNVs are potentially important in determining height and may contribute to height variation in human populations.

Genotype instability during long-term subculture of lymphoblastoid cell lines.

Epstein-Barr virus (EBV)-transformed lymphoblastoid cell lines (LCLs) promise to address the challenge posed by the limited availability of primary cells needed as a source of genomic DNA for genetic studies. However, the genetic stability of LCLs following prolonged culture has never been rigorously investigated. To evaluate genotypic errors caused by EBV integration into human chromosomes, we isolated genomic DNA from human peripheral blood mononuclear cells and LCLs collected from 20 individuals and genotyped the DNA samples using the Affymetrix 500K SNP array set. Genotype concordance measurements between two sources of DNA from the same individual indicated that genotypic discordance is negligible in early-passage LCLs (<20 passages) but substantial in late-passage LCLs (>50 passages). Analysis of concordance on a chromosome-by-chromosome basis identified genomic regions with a high frequency of genotypic errors resulting from the loss of heterozygosity observed in late-passage LCLs. Our findings suggest that, although LCLs harvested during early stages of propagation are a reliable source of genomic DNA for genetic studies, investigations that involve genotyping of the entire genome should not use DNA from late-passage LCLs.

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.

Genovar: a detection and visualization tool for genomic variants.

BACKGROUND: Along with single nucleotide polymorphisms (SNPs), copy number variation (CNV) is considered an important source of genetic variation associated with disease susceptibility. Despite the importance of CNV, the tools currently available for its analysis often produce false positive results due to limitations such as low resolution of array platforms, platform specificity, and the type of CNV. To resolve this problem, spurious signals must be separated from true signals by visual inspection. None of the previously reported CNV analysis tools support this function and the simultaneous visualization of comparative genomic hybridization arrays (aCGH) and sequence alignment. The purpose of the present study was to develop a useful program for the efficient detection and visualization of CNV regions that enables the manual exclusion of erroneous signals. RESULTS: A JAVA-based stand-alone program called Genovar was developed. To ascertain whether a detected CNV region is a novel variant, Genovar compares the detected CNV regions with previously reported CNV regions using the Database of Genomic Variants (DGV, http://projects.tcag.ca/variation) and the Single Nucleotide Polymorphism Database (dbSNP). The current version of Genovar is capable of visualizing genomic data from sources such as the aCGH data file and sequence alignment format files. CONCLUSIONS: Genovar is freely accessible and provides a user-friendly graphic user interface (GUI) to facilitate the detection of CNV regions. The program also provides comprehensive information to help in the elimination of spurious signals by visual inspection, making Genovar a valuable tool for reducing false positive CNV results. AVAILABILITY: http://genovar.sourceforge.net/.

Association between the ABO locus and hematological traits in Korean.

BACKGROUND: Recently, genome-wide association studies identified a pleiotropic gene locus, ABO, as being significantly associated with hematological traits. To confirm the effects of ABO on hematological traits, we examined the link between the ABO locus and hematological traits in Korean population-based cohorts. RESULTS: Six tagging SNPs for ABO were analyzed with regard to their effects on hematological traits [white blood cell count (WBC), red blood cell count (RBC), platelet (Plat), mean corpuscular volume (MCV), and mean corpuscular haemoglobin concentration (MCHC)]. Linear regression analyses were performed, controlling for recruitment center, sex, and age as covariates. Of the 6 tagging SNPs, 3 (rs2073823, rs8176720, and rs495828) and 3 (rs2073823, rs8176717, and rs687289) were significantly associated with RBC and MCV, respectively (Bonferroni correction p-value criteria < 0.05/6 = 0.008). rs2073823 and a reported SNP (rs8176746), as well as rs495828 and a reported SNP (rs651007), showed perfect linkage disequilibrium status (r2s = 0.99). Of the remaining 3 SNPs (rs8176720, rs8176717 and rs687289), rs8176717 generated an independent signal with moderate p-value (= 0.045) when it was adjusted for by rs2073823 (the most significant SNP). We also identified a copy number variation (CNV) that was tagged by the SNP rs8176717, the minor allele of which correlated with the deletion allele of CNV. Our haplotype analysis indicated that the haplotype that contained the CNV deletion was significantly associated with MCV (ß ± se = 0.363 ± 0.118, p =2.09 × 10-3). CONCLUSIONS: Our findings confirm that ABO is one of the genetic factors that are associated with hematological traits in the Korean population. This result is notable, because GWASs fail to evaluate the link between a CNV and phenotype traits.