Ji Hee Oh

A large-scale genome-wide association study of Asian populations uncovers genetic factors influencing eight quantitative traits

To identify genetic factors influencing quantitative traits of biomedical importance, we conducted a genome-wide association study in 8,842 samples from population-based cohorts recruited in Korea. For height and body mass index, most variants detected overlapped those reported in European samples. For the other traits examined, replication of promising GWAS signals in 7,861 independent Korean samples identified six previously unknown loci. For pulse rate, signals reaching genome-wide significance mapped to chromosomes 1q32 (rs12731740, P = 2.9 × 10−9) and 6q22 (rs12110693, P = 1.6 × 10−9), with the latter ∼400 kb from the coding sequence of GJA1. For systolic blood pressure, the most compelling association involved chromosome 12q21 and variants near the ATP2B1 gene (rs17249754, P = 1.3 × 10−7). For waist-hip ratio, variants on chromosome 12q24 (rs2074356, P = 7.8 × 10−12) showed convincing associations, although no regional transcript has strong biological candidacy. Finally, we identified two loci influencing bone mineral density at multiple sites. On chromosome 7q31, rs7776725 (within the FAM3C gene) was associated with bone density at the radius (P = 1.0 × 10−11), tibia (P = 1.6 × 10−6) and heel (P = 1.9 × 10−10). On chromosome 7p14, rs1721400 (mapping close to SFRP4, a frizzled protein gene) showed consistent associations at the same three sites (P = 2.2 × 10−3, P = 1.4 × 10−7 and P = 6.0 × 10−4, respectively). This large-scale GWA analysis of well-characterized Korean population-based samples highlights previously unknown biological pathways.

Large-scale genome-wide association studies in east Asians identify new genetic loci influencing metabolic traits

To identify the genetic bases for nine metabolic traits, we conducted a meta-analysis combining Korean genome-wide association results from the KARE project (n = 8,842) and the HEXA shared control study (n = 3,703). We verified the associations of the loci selected from the discovery meta-analysis in the replication stage (30,395 individuals from the BioBank Japan genome-wide association study and individuals comprising the Health2 and Shanghai Jiao Tong University Diabetes cohorts). We identified ten genome-wide significant signals newly associated with traits from an overall meta-analysis. The most compelling associations involved 12q24.11 (near MYL2) and 12q24.13 (in C12orf51) for high-density lipoprotein cholesterol, 2p21 (near SIX2-SIX3) for fasting plasma glucose, 19q13.33 (in RPS11) and 6q22.33 (in RSPO3) for renal traits, and 12q24.11 (near MYL2), 12q24.13 (in C12orf51 and near OAS1), 4q31.22 (in ZNF827) and 7q11.23 (near TBL2-BCL7B) for hepatic traits. These findings highlight previously unknown biological pathways for metabolic traits investigated in this study.

Genome-Wide Association Study Identifies Two Novel Loci with Sex-Specific Effects for Type 2 Diabetes Mellitus and Glycemic Traits in a Korean Population

Background Until recently, genome-wide association study (GWAS)-based findings have provided a substantial genetic contribution to type 2 diabetes mellitus (T2DM) or related glycemic traits. However, identification of allelic heterogeneity and population-specific genetic variants under consideration of potential confounding factors will be very valuable for clinical applicability. To identify novel susceptibility loci for T2DM and glycemic traits, we performed a two-stage genetic association study in a Korean population. Methods We performed a logistic analysis for T2DM, and the first discovery GWAS was analyzed for 1,042 cases and 2,943 controls recruited from a population-based cohort (KARE, n=8,842). The second stage, de novo replication analysis, was performed in 1,216 cases and 1,352 controls selected from an independent population-based cohort (Health 2, n=8,500). A multiple linear regression analysis for glycemic traits was further performed in a total of 14,232 nondiabetic individuals consisting of 7,696 GWAS and 6,536 replication study participants. A meta-analysis was performed on the combined results using effect size and standard errors estimated for stage 1 and 2, respectively. Results A combined meta-analysis for T2DM identified two new (rs11065756 and rs2074356) loci reaching genome-wide significance in CCDC63 and C12orf51 on the 12q24 region. In addition, these variants were significantly associated with fasting plasma glucose and homeostasis model assessment of β-cell function. Interestingly, two independent single nucleotide polymorphisms were associated with sex-specific stratification in this study. Conclusion Our study showed a strong association between T2DM and glycemic traits. We further observed that two novel loci with multiple diverse effects were highly specific to males. Taken together, these findings may provide additional insights into the clinical assessment or subclassification of disease risk in a Korean population.

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.

New susceptibility loci in MYL2, C12orf51 and OAS1 associated with 1-h plasma glucose as predisposing risk factors for type 2 diabetes in the Korean population

Most recently, 1-h hyperglycemia has been recognized as an additional risk factor for type 2 diabetes. To date, previous genome-wide association studies for glycemic traits have a limited impact on the fasting state and 2-h plasma glucose level in an oral glucose challenge. To identify genetic susceptibility in different stages of glucose tolerance, we performed a meta-analysis for glycemic traits including 1-h plasma glucose (1-hPG) from 14 232 non-diabetic individuals in the Korean population. Newly implicated variants (MYL2, C12orf51 and OAS1) were found to be significantly associated with 1-hPG. We also demonstrated associations with gestational diabetes mellitus. Our results could provide additional insight into the genetic variation in the clinical range of glycemia.

Identification of a Systemic Lupus Erythematosus Risk Locus Spanning ATG16L2, FCHSD2, and P2RY2 in Koreans.

Systemic lupus erythematosus (SLE) is a chronic autoimmune disorder whose etiology is incompletely understood, but likely involves environmental triggers in genetically susceptible individuals. Using an unbiased genome‐wide association (GWA) scan and replication analysis, we sought to identify the genetic loci associated with SLE in a Korean population.

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.

Genome-Wide Association Study Identifies Candidate Loci Associated with Platelet Count in Koreans

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.

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.

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.