Korea Association Resource Research Articles

Association of BUD13-ZNF259-APOA5-APOA1-SIK3 cluster polymorphism in 11q23.3 and structure of APOA5 with increased plasma triglyceride levels in a Korean population

In this association study on chromosome 11, the data from 12,537 Korean individuals within the Health Examinee (HEXA) and the Korea Association Resource (KARE) projects were analysed to identify genetic loci correlating with increased and decreased plasma triglyceride (TG) levels. We identified a locus in chromosomal region 11q23.3 that harbours genes BUD13, ZNF259, APOA5, APOA1, and SIK3, which may be associated with plasma TG levels. In this locus, 13 relevant single-nucleotide polymorphisms (SNPs) were found: rs184616707, rs118175510, rs60954647, rs79408961, and rs180373 (near BUD13); rs11604424 (in ZNF259); rs2075291, rs651821, and rs7123666 (in or near APOA5); rs525028 (near APOA1), and rs645258, rs10160754, and rs142395187 (in or near SIK3). All 13 SNPs satisfied the genome-wide significance level (P < 5.0 × 10−8) in both meta-analysis and conditional analysis. Haplotype analysis of six SNPs (rs79408961, rs180373, rs2075291, rs651821, rs525028, and rs10160754) that were selected based on the β coefficient and conditional P values, revealed nine common haplotypes (with frequency 0.02–0.34) associated with both increased and reduced TG levels. Furthermore, to shed light on possible structural implications, we modelled and simulated the G185C variant of APOA5 (corresponding to rs2075291), which showed the strongest association. Molecular dynamics simulation results showed that this polymorphic variant of APOA5 has a different hydrogen bond network, increased average distance between chains, and an ability to form distinct clusters. Owing to the orientation of cysteine, the possibility of disulphide bond formation with other proteins is evident. In summary, our association and modelling analyses provided evidence that genetic variations in chromosomal region 11q23.3 are associated with elevated TG levels.

Association of Habitual Coffee Consumption and HECTD4 Polymorphism with Risk of Prediabetes and Type 2 Diabetes (P18-071-19)

ObjectivesEpidemiological studies suggested the evidence that coffee consumption decreased risk of type 2 diabetes. Recently, Japanese genome-wide association studies (GWAS) of coffee consumption has identified rs2074356 (G > A) at 12q24.12–13 in HECTD4. This study aims to examine the associations of habitual coffee consumption with prediabetes and type 2 diabetes, and whether this association is modified by rs2074356 variant in Korean adults. MethodsA total of 4010 participants (1890 men and 2120 women) who had genetic information from Korea Association REsource (KARE) study were included. Habitual coffee consumption was assessed through a food frequency questionnaire and categorized into five categories (non-consumers, <1 cup/day and ≥1 cups/day of black coffee, and <1 cup/day and ≥1 cups/day of sugared coffee). Incident prediabetes or type 2 diabetes were defined according to the self-report of physician-diagnosis, oral glucose tolerance test (OGTT) or hemoglobin A1c (HbA1c) test. Multivariable logistic regression models were used to calculate odds ratio (OR)s and 95% confidence interval (CI)s. ResultsA total of 2916 participants (72.7%) have developed prediabetes during a follow-up of 15 years. We found that black coffee consumption lowered risk of prediabetes and type 2 diabetes combined among men and women combined (OR = 0.63; 95% CI = 0.44–0.91 for ≥1 cups/day black coffee vs. non-consumers). When we separated men and women, compared with non-consumers, ORs (95% CIs) for ≥1 cups/day of black coffee were 0.50 (0.27–0.93) among men and 0.72 (0.45–1.14) among women and ORs (95% CIs) for ≥1 cups/day of sugared coffee were 1.41 (0.91–2.18) among men and 1.12 (0.80–1.58) among women. We observed a suggestive difference by rs2074356 (GG vs. AG + AA). Compared with non-consumers, participants with AG + AA genotypes consumed ≥ 1 cups/day of black coffee had a 60% lower risk of prediabetes and type 2 diabetes combined (95% CI 0.20–0.78), but we found a weaker association among those with GG genotype (OR = 0.81; 95% CI = 0.51–1.28). ConclusionsWe observed an inverse association between black coffee consumption and prediabetes and type 2 diabetes combined in Korean population. This association was more pronounced among carriers of minor allele of HECTD4 rs2074356 (AG/AA). Funding SourcesNone.

245-LB: Association between the Risk of T2D Incidence and the Genetic Variants of GCK and HDAC4 Genes Interacting with Alcohol Consumption in Korea

Chronic alcohol consumption is well-known as an independent risk factor for type 2 diabetes (T2D), which is related with impaired glucose homeostasis and insulin resistance. The identification of genetic variants and the association with diseases may help to explain the genetic etiology of type 2 diabetes. In this study, we aimed to search for the single nucleotide polymorphisms (SNPs) associated with T2D risk, which also interact with alcohol consumption. We conducted genome-wide interaction study using the Korea Association Resource (KARE) data. We found that two SNPs, HDAC4 (rs3791370) and GCK (rs758989) are associated with T2D and also interact with alcohol consumption (odds ratio [OR] 1.74, and OR 1.37, respectively). We further investigated the association between these SNPs and response to alcohol consumption in risk of T2D incidence. In alcohol consumption group, these SNPs significantly increased the risk of T2D incidence compared with nonalcohol consumption group (HDAC4; hazard ratio [HR] 1.29, GCK; HR 1.34). Moreover, genotype association analysis showed that the presence of the risky allele (hetero risky allele [CR] + minor homo risky allele [RR]) in GCK SNP significantly increased the risk of T2D incidence (1.47, p = 0.032) compared with major homo C allele [CC] in alcohol consumption group after adjustment with age, BMI, smoking, physical activity, and history of diabetes. However, presence of the risky allele in HDAC4 SNP marginally increased the risk of T2D incidence (1.47, p = 0.0652). Based on our data, we suggest that HDAC4 and GCK SNPs could be a potential factor for increase of T2D incidence risk, which may be helpful to better understand the genetic basis of T2D in association with alcohol consumption. Disclosure J. Yun: None. H. Jang: None. M. Yoo: None. H. Lee: None. S. Park: None. Funding Korea National Institute of Health (2019-NI088-00)

Metabolic Markers Predictive of Prediabetes in the Korean Population

Background: Prediabetes (PD) is a high-risk state for type 2 diabetes (T2D), but the risk of progression from PD to T2D can be prevented by early diagnosis and intervention. Metabolomics studies suggest that metabolic biomarkers can shed insight into etiological mechanisms and improve the accuracy of prediction of disease onset. Objectives: We aimed to identify serum metabolic biomarkers and verify their predictive performance for PD in the Korean population, as compared to the performance of known clinical risk factor (CRF) as well as previously reported metabolites (PRM) in other population studies. Methods: A targeted metabolomics was carried out to quantify serum metabolites for 1,723 participants from the Korea Association REsource (KARE) cohort from which 500 individuals were followed-up to 6-years. PD-related metabolites were identified at baseline by statistical methods including multivariable regression analysis, and tested their association to incidence of PD during follow-up. Results: The 12 metabolites were significantly altered in PD (adjusted P&amp;lt;4.07E-04). These metabolites predicted incidence of PD with an area under curve (AUC) of 0.71. The AUC of the metabolic markers was significantly higher than that of the two PRM models (0.56 and 0.64, P&amp;lt;0.005) and the CRF (0.64, P&amp;lt;0.01). The performance of the metabolic markers compared to glucose model was significantly higher among the obese (BMI &amp;gt;= 25 kg/m2, 0.79 vs. 0.58, P&amp;lt;0.001), significantly lower among the female (0.73 vs. 0.85, P&amp;lt;0.002) and the lean (BMI&amp;lt;25 kg/m2, 0.68 vs. 0.78, P&amp;lt;0.01), and not significantly different among the age and the male. The full model with metabolic markers, CRF, glucose yielded the best prediction (AUC=0.84). Conclusion: Our results revealed that the novel metabolic markers are not only associated with the risk of PD, but also improve the prediction performance in combination with classical approaches. These findings may help understanding causality of diabetes progression and developing preventive strategies for T2D. Disclosure H. Lee: None. T. Park: None. B. Kim: None.

Genome-wide assessment of gene-by-smoking interactions in COPD

Cigarette smoke exposure is a major risk factor in chronic obstructive pulmonary disease (COPD) and its interactions with genetic variants could affect lung function. However, few gene-smoking interactions have been reported. In this report, we evaluated the effects of gene-smoking interactions on lung function using Korea Associated Resource (KARE) data with the spirometric variables—forced expiratory volume in 1 s (FEV1). We found that variations in FEV1 were different among smoking status. Thus, we considered a linear mixed model for association analysis under heteroscedasticity according to smoking status. We found a previously identified locus near SOX9 on chromosome 17 to be the most significant based on a joint test of the main and interaction effects of smoking. Smoking interactions were replicated with Gene-Environment of Interaction and phenotype (GENIE), Multi-Ethnic Study of Atherosclerosis-Lung (MESA-Lung), and COPDGene studies. We found that individuals with minor alleles, rs17765644, rs17178251, rs11870732, and rs4793541, tended to have lower FEV1 values, and lung function decreased much faster with age for smokers. There have been very few reports to replicate a common variant gene-smoking interaction, and our results revealed that statistical models for gene-smoking interaction analyses should be carefully selected.

Prediction of cholesterol ratios within a Korean population.

Cholesterol ratios (total cholesterol (TC)/high-density lipoprotein cholesterol (HDL-c) and triglyceride (TG)/HDL-c) have been suggested as better indicators to predict various clinical features such as insulin resistance and heart disease. Therefore, we aimed to build a single nucleotide polymorphism (SNP) set to predict constitutional lipid metabolism. The genotype data of 7795 samples were obtained from the Korea Association Resource. Among the total of 7795 samples, 7016 subjects were used to perform 10-fold cross-validation. We selected the SNPs that showed significance constantly throughout all 10 cross-validation sets; another 779 samples were used as the final validation set. After performing the 10-fold cross-validation, the six SNPs (rs4420638 (APOC1), rs12421652 (BUD13), rs17411126 (LPL), rs6589566 (ZPR1), rs16940212 (LOC101928635) and rs10852765 (ABCA8)) were finally selected for predicting cholesterol ratios. The weighted genetic risk scores (wGRS) were calculated based on the regression slopes of the six selected SNPs. Our results showed upward trends of wGRS for both the TC/HDL-c and TG/HDL-c ratios within the 10-fold cross-validation. Similarly, the wGRS of the six SNPs also showed upward trends in analyses using the SNP selection set and final validation set. The selected six SNPs can be used to explain both the TC/HDL-c and TG/HDL-c ratios. Our results may be useful for the prospective predictions of cholesterol-related diseases.

BMI prediction within a Korean population.

BackgroundBody Mass Index (BMI) is widely regarded as an important clinical trait for obesity and other diseases such as Type 2 diabetes, coronary heart disease, and osteoarthritis.MethodsThis study uses 6,011 samples of genotype data from ethnic Korean subjects. The data was retrieved from the Korea Association Resource. To identify the BMI-related markers within the Korean population, we collected genome-wide association study (GWAS) markers using a GWAS catalog and also obtained other markers from nearby regions. Of the total 6,011 samples, 5,410 subjects were used as part of a single nucleotide polymorphism (SNP) selection set in order to identify the overlapping BMI-associated SNPs within a 10-fold cross validation.ResultsWe selected nine SNPs (rs12566985 (FPGT-TNNI3K), rs6545809 (ADCY3), rs2943634 (located near LOC646736), rs734597 (located near TFAP2B), rs11030104 (BDNF), rs7988412 (GTF3A), rs2241423 (MAP2K5), rs7202116 (FTO), and rs6567160 (located near LOC105372152) to assist in BMI prediction. The calculated weighted genetic risk scores based on the selected 9 SNPs within the SNP selection set were applied to the final validation set consisting of 601 samples. Our results showed upward trends in the BMI values (P < 0.0001) within the 10-fold cross validation process for R2 > 0.22. These trends were also observed within the validation set for all subjects, as well as within the validation sets divided by gender (P < 0.0001, R2 > 0.46).DiscussionThe set of nine SNPs identified in this study may be useful for prospective predictions of BMI.

ATP2B1 gene Silencing Increases Insulin Sensitivity through Facilitating Akt Activation via the Ca2+/calmodulin Signaling Pathway and Ca2+-associated eNOS Activation in Endothelial Cells.

Endothelial cell insulin resistance may be partially responsible for the higher risk of atherosclerosis and cardiovascular disease in populations with insulin resistance and type 2 diabetes mellitus (T2DM). A genome-wide association study revealed a significant association between the ATPase plasma membrane Ca2+ transporting 1 (ATP2B1) gene and T2DM in two community-based cohorts from the Korea Association Resource Project. However, little is known about the implication of the ATP2B1 gene on T2DM. In the present study, we investigated the role of the ATP2B1 gene in endothelial cell insulin sensitivity. ATP2B1 gene silencing resulted in enhanced intracellular calcium concentrations and increased insulin-induced Akt activation compared to that in the negative siRNA-transfected HUVECs (Human Umbilical Vein Endothelial Cells). The elevated insulin sensitivity mediated by ATP2B1 gene silencing was Ca2+/calmodulin-dependent, as verified by administration of the calcium chelator BAPTA-AM or the calmodulin-specific antagonist W7. Moreover, higher levels of phosphorylation of eNOS (Ser1177) were observed in ATP2B1-silenced HUVECs. In addition to BAPTA-AM and W7, L-NAME, an eNOS antagonist, abolished insulin-induced Akt phosphorylation at Ser473 in both si-Neg and si-ATP2B1-transfected endothelial cells. These results indicate that the enhanced insulin sensitivity in ATP2B1-silenced endothelial cells is alternatively dependent on an increase in intracellular Ca2+ and the subsequent activation of the Ca2+/calmodulin/eNOS/Akt signaling pathway. In summary, ATP2B1 gene silencing increased insulin sensitivity in endothelial cells by directly modulating the Ca2+/calmodulin signaling pathway and via the Ca2+/calmodulin/eNOS/Akt signaling pathway alternatively.

Identification of putative biomarkers for type 2 diabetes using metabolomics in the Korea Association REsource (KARE) cohort

Type 2 diabetes (T2D) is a multifactorial disease resulting from a complex interaction between environmental and genetic risk factors. Metabolomics provide a logical framework that reflects the functional endpoints of biological processes being triggered by genetic information and various external influences. Identification of metabolite biomarkers can shed insight into etiological pathways and improve the prediction of disease risk. Here, we aimed to identify serum metabolites as putative biomarkers for T2D and their association with genetic variants in the Korean population. A targeted metabolomics approach was employed to quantify serum metabolites for 2240 participants in the Korea Association REsource (KARE) cohort. T2D-related metabolites were identified by statistical methods including multivariable linear and logistic regression, and were independently replicated in the Cooperative Health Research in the Region of Augsburg (KORA) cohort. Additionally, by combining a genome wide association study (GWAS) with metabolomics, genetic variants associated with the identified T2D-related metabolites were uncovered. 123 metabolites were quantified from fasting serum samples and four metabolites, hexadecanoylcarnitine (C16), glycine, lysophosphatidylcholine acyl C18:2 (lysoPC a C18:2), and phosphatidylcholine acyl-alkyl C36:0 (PC ae C36:0), were significantly altered in T2D compared to non-T2D subjects (after the Bonferroni correction for multiple testing with P < 4.07E − 04, α = 0.05). Among them, C16, glycine, and lysoPC a C18:2 were independently replicated in the KORA cohort. Alterations of these metabolites were associated with ten genetic loci including six that were previously implicated in T2D or obesity. Using a targeted-metabolomics and in combination with GWAS approach, we identified three serum metabolites associated with risk of T2D in both the KARE and KORA cohort and discovered ten genetic variants in relation to the identified metabolites. These findings provide a better understanding to develop novel preventive strategies for T2D in the Korean population.

Multiple susceptibility loci at chromosome 11q23.3 are associated with plasma triglyceride in East Asians

Genetic studies of plasma TG levels have identified associations with multiple candidate loci on chromosome11q23.3, which harbors a number of genes, including BUD13, ZNF259, and APOA5-A4-C3-A1. This study aimed to examine whether these multiple candidate genes on the 11q23.3 regions exert independent effects on TG levels or whether their effects are confounded by linkage disequilibrium (LD). We performed a genome-wide association study and consequent fine-mapping analyses on TG levels in two Korean population-based cohorts: the Korea Association Resource study (n = 8,223) and the Healthy Twin study (n = 1,735). A total of 301 loci reached genome-wide significance level in pooled analysis, including 10 SNPs with weak LD (r(2) < 0.06) clustered on 11q23.3: ApoA5 (rs651821, rs2075291); ZNF259 (rs964184, rs603446); BUD13 (rs11216126); Apoa4 (rs7396851); SIK3 (rs12292858); PCSK7 (rs199890178); PAFAH1B2 (rs12420127), and SIDT2 (rs2269399). When the inter-dependence between alleles was examined using conditional models, five loci on BUD13, ZNF259, and ApoA5 showed possible independent associations. A haplotype analysis using five SNPs revealed both hyper- and hypotriglyceridemic haplotypes, which are relatively common in Koreans (haplotype frequency 0.08-0.22). Our findings suggest the presence of multiple functional loci on 11q23.3, which might exert their effects on plasma TG level independently or through complex interactions between functional loci.

Efficient Strategy to Identify Gene-Gene Interactions and Its Application to Type 2 Diabetes.

Over the past decade, the detection of gene-gene interactions has become more and more popular in the field of genome-wide association studies (GWASs). The goal of the GWAS is to identify genetic susceptibility to complex diseases by assaying and analyzing hundreds of thousands of single-nucleotide polymorphisms. However, such tests are computationally demanding and methodologically challenging. Recently, a simple but powerful method, named “BOolean Operation-based Screening and Testing” (BOOST), was proposed for genome-wide gene-gene interaction analyses. BOOST was designed with a Boolean representation of genotype data and is approximately equivalent to the log-linear model. It is extremely fast, and genome-wide gene-gene interaction analyses can be completed within a few hours. However, BOOST can not adjust for covariate effects, and its type-1 error control is not correct. Thus, we considered two-step approaches for gene-gene interaction analyses. First, we selected gene-gene interactions with BOOST and applied logistic regression with covariate adjustments to select gene-gene interactions. We applied the two-step approach to type 2 diabetes (T2D) in the Korea Association Resource (KARE) cohort and identified some promising pairs of single-nucleotide polymorphisms associated with T2D.

Prediction of Quantitative Traits Using Common Genetic Variants: Application to Body Mass Index.

With the success of the genome-wide association studies (GWASs), many candidate loci for complex human diseases have been reported in the GWAS catalog. Recently, many disease prediction models based on penalized regression or statistical learning methods were proposed using candidate causal variants from significant single-nucleotide polymorphisms of GWASs. However, there have been only a few systematic studies comparing existing methods. In this study, we first constructed risk prediction models, such as stepwise linear regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN), using a GWAS chip and GWAS catalog. We then compared the prediction accuracy by calculating the mean square error (MSE) value on data from the Korea Association Resource (KARE) with body mass index. Our results show that SLR provides a smaller MSE value than the other methods, while the numbers of selected variables in each model were similar.

GWAS identifies two susceptibility loci for lamotrigine-induced skin rash in patients with epilepsy

PurposeLamotrigine (LTG)-induced maculopapular eruption (MPE) often causes treatment discontinuation and rising burdens on current healthcare systems. We conducted a genome-wide association study to identify novel susceptibility loci associated with LTG-induced MPE in patients with epilepsy. Materials and methodsWe enrolled patients with LTG-induced MPE (n=34) and utilized the Korea Association Resource project cohort as a control group (n=1214). We explored associations between LTG-induced MPE and single nucleotide polymorphisms (SNPs) through imputation and replicated these associations in samples from 59 LTG-induced MPE cases and 98 LTG tolerant-controls. ResultsWe found two novel SNPs associated with LTG-induced MPE: rs12668095 near CRAMP1L/TMEM204/IFT140/HN1L (P=4.89×10−7) and rs79007183 near TNS3 (P=3.15×10−10), both of which were replicated in an independent cohort. ConclusionThese two validated SNPs may be good candidate markers for predicting LTG-induced MPE in epilepsy patients, although further experimental validation is needed.

Adjusting sampling bias in case-control genetic association studies

Genome-wide association studies (GWAS) are designed to discover genetic vari-ants such as single nucleotide polymorphisms (SNPs) that are associated with human complex traits. Although there is an increasing interest in the application of GWAS methodologies to population-based cohorts, many published GWAS have adopted a case-control design, which raise an issue related to a sampling bias of both case and control samples. Because of unequal selection probabilities between cases and controls, the samples are not representative of the population that they are purported to represent. Therefore, non-random sampling in case-control study can potentially lead to inconsistent and biased estimates of SNP-trait associations. In this paper, we proposed inverse-probability of sampling weights based on disease prevalence to eliminate a case-control sampling bias in estimation and testing for association between SNPs and quantitative traits. We apply the proposed method to a data from the Korea Association Resource project and show that the standard estimators applied to the weighted data yield unbiased estimates.

Identification of three novel genetic variations associated with electrocardiographic traits (QRS duration and PR interval) in East Asians.

The electrocardiogram has several advantages in detecting cardiac arrhythmia-it is readily available, noninvasive and cost-efficient. Recent genome-wide association studies have identified single-nucleotide polymorphisms that are associated with electrocardiogram measures. We performed a genome-wide association study using Korea Association Resource data for the discovery phase (Phase 1, n = 6805) and two consecutive replication studies in Japanese populations (Phase 2, n = 2285; Phase 3, n = 5010) for QRS duration and PR interval. Three novel loci were identified: rs2483280 (PRDM16 locus) and rs335206 (PRDM6 locus) were associated with QRS duration, and rs17026156 (SLC8A1 locus) correlated with PR interval. PRDM16 was recently identified as a causative gene of left ventricular non-compaction and dilated cardiomyopathy in 1p36 deletion syndrome, which is characterized by heart failure, arrhythmia and sudden cardiac death. Thus, our finding that a PRDM16 SNP is linked to QRS duration strongly implicates PRDM16 in cardiac function. In addition, C allele of rs17026156 increases PR interval (beta ± SE, 2.39 ± 0.40 ms) and exists far more frequently in East Asians (0.46) than in Europeans and Africans (0.05 and 0.08, respectively).

Genotype-environment interactions for quantitative traits in Korea Associated Resource (KARE) cohorts

BackgroundDue to the lack of statistical power and confounding effects of population structure in human population data, genotype-environment interaction studies have not yielded promising results and have provided only limited knowledge for exploring how genotype and environmental factors interact to in their influence onto risk.ResultsWe analyzed 49 human quantitative traits in 7,170 unrelated Korean individuals on 326,262 autosomal single nucleotide polymorphisms (SNPs) collected from the KARE (Korean Association Resource) project, and we estimated the statistically significant proportion of variance that could be explained by genotype-area interactions in the supra-iliac skinfold thickness trait ( = 0.269 and P = 0.00032), which is related to abdominal obesity. Data suggested that the genotypes could have different effects on the phenotype (supra-iliac skinfold thickness) in different environmental settings (rural vs. urban areas). We then defined the genotype groups of individuals with similar genetic profiles based on the additive genetic relationships among individuals using SNPs. We observed the norms of reaction, and the differential phenotypic response of a genotype to a change in environmental exposure. Interestingly, we also found that the gene clusters responsible for cell-cell and cell-extracellular matrix interactions were enriched significantly for genotype-area interaction.ConclusionsThis significant heritability estimate of genotype-environment interactions will lead to conceptual advances in our understanding of the mechanisms underlying genotype-environment interactions, and could be ultimately applied to personalized preventative treatments based on environmental exposures.

Epidemiological and genome-wide association study of gastritis or gastric ulcer in korean populations.

Gastritis is a major disease that has the potential to grow as gastric cancer. Gastric cancer is a very common cancer, and it is related to a very high mortality rate in Korea. This disease is known to have various reasons, including infection with Helicobacter pylori, dietary habits, tobacco, and alcohol. The incidence rate of gastritis has reported to differ between age, population, and gender. However, unlike other factors, there has been no analysis based on gender. So, we examined the high risk factors of gastritis in each gender in the Korean population by focusing on sex. We performed an analysis of 120 clinical characteristics and genome-wide association studies (GWAS) using 349,184 single-nucleotide polymorphisms from the results of Anseong and Ansan cohort study in the Korea Association Resource (KARE) project. As the result, we could not prove a strong relation with these factors and gastritis or gastric ulcer in the GWAS. However, we confirmed several already-known risk factors and also found some differences of clinical characteristics in each gender using logistic regression. As a result of the logistic regression, a relation with hyperlipidemia, coronary artery disease, myocardial infarction, hyperlipidemia therapy, hypotensive or antihypotensive drug, diastolic blood pressure, and gastritis was seen in males; the results of this study suggest that vascular disease has a potential association with gastritis in males.

Relevance Epistasis Network of Gastritis for Intra-chromosomes in the Korea Associated Resource (KARE) Cohort Study.

Gastritis is a common but a serious disease with a potential risk of developing carcinoma. Helicobacter pylori infection is reported as the most common cause of gastritis, but other genetic and genomic factors exist, especially single-nucleotide polymorphisms (SNPs). Association studies between SNPs and gastritis disease are important, but results on epistatic interactions from multiple SNPs are rarely found in previous genome-wide association (GWA) studies. In this study, we performed computational GWA case-control studies for gastritis in Korea Associated Resource (KARE) data. By transforming the resulting SNP epistasis network into a gene-gene epistasis network, we also identified potential gene-gene interaction factors that affect the susceptibility to gastritis.

Pathway Analysis of Metabolic Syndrome Using a Genome-Wide Association Study of Korea Associated Resource (KARE) Cohorts.

Metabolic syndrome (MetS) is a complex disorder related to insulin resistance, obesity, and inflammation. Genetic and environmental factors also contribute to the development of MetS, and through genome-wide association studies (GWASs), important susceptibility loci have been identified. However, GWASs focus more on individual single-nucleotide polymorphisms (SNPs), explaining only a small portion of genetic heritability. To overcome this limitation, pathway analyses are being applied to GWAS datasets. The aim of this study is to elucidate the biological pathways involved in the pathogenesis of MetS through pathway analysis. Cohort data from the Korea Associated Resource (KARE) was used for analysis, which include 8,842 individuals (age, 52.2 ± 8.9 years; body mass index, 24.6 ± 3.2 kg/m2). A total of 312,121 autosomal SNPs were obtained after quality control. Pathway analysis was conducted using Meta-analysis Gene-Set Enrichment of Variant Associations (MAGENTA) to discover the biological pathways associated with MetS. In the discovery phase, SNPs from chromosome 12, including rs11066280, rs2074356, and rs12229654, were associated with MetS (p < 5 × 10-6), and rs11066280 satisfied the Bonferroni-corrected cutoff (unadjusted p < 1.38 × 10-7, Bonferroni-adjusted p < 0.05). Through pathway analysis, biological pathways, including electron carrier activity, signaling by platelet-derived growth factor (PDGF), the mitogen-activated protein kinase kinase kinase cascade, PDGF binding, peroxisome proliferator-activated receptor (PPAR) signaling, and DNA repair, were associated with MetS. Through pathway analysis of MetS, pathways related with PDGF, mitogen-activated protein kinase, and PPAR signaling, as well as nucleic acid binding, protein secretion, and DNA repair, were identified. Further studies will be needed to clarify the genetic pathogenesis leading to MetS.

Understanding Epistatic Interactions between Genes Targeted by Non-coding Regulatory Elements in Complex Diseases.

Genome-wide association studies have proven the highly polygenic architecture of complex diseases or traits; therefore, single-locus-based methods are usually unable to detect all involved loci, especially when individual loci exert small effects. Moreover, the majority of associated single-nucleotide polymorphisms resides in non-coding regions, making it difficult to understand their phenotypic contribution. In this work, we studied epistatic interactions associated with three common diseases using Korea Association Resource (KARE) data: type 2 diabetes mellitus (DM), hypertension (HT), and coronary artery disease (CAD). We showed that epistatic single-nucleotide polymorphisms (SNPs) were enriched in enhancers, as well as in DNase I footprints (the Encyclopedia of DNA Elements [ENCODE] Project Consortium 2012), which suggested that the disruption of the regulatory regions where transcription factors bind may be involved in the disease mechanism. Accordingly, to identify the genes affected by the SNPs, we employed whole-genome multiple-cell-type enhancer data which discovered using DNase I profiles and Cap Analysis Gene Expression (CAGE). Assigned genes were significantly enriched in known disease associated gene sets, which were explored based on the literature, suggesting that this approach is useful for detecting relevant affected genes. In our knowledge-based epistatic network, the three diseases share many associated genes and are also closely related with each other through many epistatic interactions. These findings elucidate the genetic basis of the close relationship between DM, HT, and CAD.