• Genomics & Informatics
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• v.12 no.3
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• pp.127-133
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• 2014

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.

• Genomics & Informatics
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• v.14 no.4
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• pp.160-165
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• 2016

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.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.8
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• pp.3699-3704
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• 2014

Background: This study aimed to determine knowledge, attitudes and believes about cervical cancer and human papilloma virus (HPV) vaccination with related factors in Turkish university students. Materials and Methods: This descriptive and cross sectional study was conducted between June-July 2013 in Hitit University located in Corum, a rural area to the East of Ankara. The population consisted of 550 university students who were training in first and last year from Faculties of Economics, Theology and Health. We reached 463 volunteer students without selection. The study of data was collected with a 44 item questionaire covering socio-demographic features, knowledge, attitudes and beliefs about cervical cancer, HPV and vaccination. Also for this study ethic committee report was taken from Bozok University. Data were evaluated with the SPSS 17.0 programme using the Ki kare test with P<0.05 accepted as statistically significant. Results: It was seen that there was a statistically significant variation between classrooms and departments of students with knowledge about cervical cancer and human papilloma virus and vaccine (p<0.001; p<0.01; p<0.05). Also we found low attitudes to thinking about taking HPV vaccination of girls and their children in the future. Conclusions: In light of the study findings; it was concluded that knowledge levels, beliefs and attitudes of the university students about cervical cancer, HPV infection and HPV vaccination were low.

• Genomics & Informatics
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• v.12 no.4
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• pp.225-230
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• 2014

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 ($p=1.46{\times}10^{10}$, in the KIAA0232 gene), 6p21 ($p=1.36{\times}10^{-7}$, in the BAK1 gene), and 12q24.12 ($p=1.11{\times}10^{-15}$, in the SH2B3 gene). Our results illustrate the value of large-scale discovery and a focus for several novel research avenues.

• Biomedical Science Letters
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• v.18 no.3
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• pp.244-253
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• 2012

Bone mineral density (BMD) is used in the clinical diagnosis of osteoporosis and the assessment of fracture risk. Osteoporosis, characterized mainly by decreased BMD, is a highly heritable complex disorder and a major public health concern to hundreds of millions of elderly persons worldwide. However, the specific genetic variants determining risk for low bone density are still largely unknown. Here, we performed association analysis to elucidate the possible relations of genetic polymorphisms in ESR1 gene with low bone density. By examining genotype data of a total of 1813 women in the Korean Association REsource (KARE) study, we discovered the ESR1 gene polymorphisms are associated with decreased BMD and osteoporosis. The results on the BD-RT (bone density estimated by T-score at distal radius), three SNPs (rs2248586, rs9371557, and rs1569788) within the ESR1 gene were significantly associated with bone density. The results on the BD-TT (bone density estimated by T-score at midshaft tibia), five SNPs (rs9371552, rs2248586, rs712221, rs7772475, and rs3798577) were significantly associated with bone density. The SNP rs2248586 within the ESR1 gene had commonly significance in both BD-RT (${\beta}$=-0.151, dominant P=0.049) and BD-TT (${\beta}$=-0.156, dominant P=0.039). In the SNP rs2248586, their ${\beta}$-values in BD-RT and/or BD-TT showed consistent trends with the odds ratios (ORs) of osteoporosis. In summary, we found statistically significant SNPs in ESR1 gene that are associated with both decreased BMD and osteoporosis traits. Therefore, our findings suggest ESR1 gene could be related to pathogenesis of osteoporosis.

• Genomics & Informatics
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• v.14 no.4
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• pp.181-186
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• 2016

Glucose tolerance tests have been devised to determine the speed of blood glucose clearance. Diabetes is often tested with the standard oral glucose tolerance test (OGTT), along with fasting glucose level. However, no single test may be sufficient for the diagnosis, and the World Health Organization (WHO)/International Diabetes Federation (IDF) has suggested composite criteria. Accordingly, a single multi-class trait was constructed with three of the fasting phenotypes and 1- and 2-hour OGTT phenotypes from the Korean Association Resource (KARE) project, and the genetic association was investigated. All of the 18 possible combinations made out of the 3 sets of classification for the individual phenotypes were taken into our analysis. These were possible due to a method that was recently developed by us for estimating genomic associations using a generalized index of dissimilarity. Eight single-nucleotide polymorphisms (SNPs) that were found to have the strongest main effect are reported with the corresponding genes. Four of them conform to previous reports, located in the CDKAL1 gene, while the other 4 SNPs are new findings. Two-order interacting SNP pairs of are also presented. One pair (rs2328549 and rs6486740) has a prominent association, where the two single-nucleotide polymorphism locations are CDKAL1 and GLT1D1. The latter has not been found to have a strong main effect. New findings may result from the proper construction and analysis of a composite trait.

• Biomedical Science Letters
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• v.18 no.2
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• pp.87-95
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• 2012

Hypertension is a complex disease that results from the interaction of genetic and environmental influences and heritability is influenced by about one-third to one-half. However, the specific genetic variants determining risk for hypertension are still largely unknown. Here, we performed association analysis to elucidate the possible relations of genetic polymorphisms in ESR1 gene with blood pressure traits. By examining genotype data of a total of 3,804 women in the Korean Association REsource (KARE) study, we discovered the ESR1 gene polymorphisms are associated with blood pressure and hypertension. The highest significant polymorphisms were rs2982571 (${\beta}=-1.56$, $P=6.8{\times}10^{-3}$) with systolic blood pressure (SBP), rs9322335 (${\beta}=-0.61$, P=0.013) with diastolic blood pressure (DBP), and rs851985 (OR=0.78, CI: 0.65~0.94, $P=8.6{\times}10^{-3}$) with hypertension. In the 5 SNPs (rs2982571, rs851985, rs851983, rs851981, and rs851980), their ${\beta}$-values in SBP and/or DBP showed consistent trends with the odds ratios (ORs) of hypertension, and these 5 SNPs were composed with one LD block. Consequently, we found statistically significant SNPs in ESR1 gene that are associated with both blood pressure and hypertension traits. These results suggested that the individuals with the minor alleles of the 5 SNPs in the ESR1 gene may be less susceptible to the development of hypertension in the Korean women.

• Genomics & Informatics
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• v.10 no.4
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• pp.256-262
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• 2012

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene ($G{\times}G$) interactions. However, the biological interpretation of $G{\times}G$ interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified $G{\times}G$ interactions. The proposed network graph analysis consists of three steps. The first step is for performing $G{\times}G$ interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified $G{\times}G$ interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform $G{\times}G$ interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified $G{\times}G$ interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of $G{\times}G$ interactions.

• Biomedical Science Letters
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• v.18 no.4
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• pp.377-383
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• 2012

Recent genome-wide association studies (GWAS) have identified a number of common variants associated with blood pressure homeostasis and hypertension in population. In the previous study, single nucleotide polymorphisms (SNPs) in the SLC4A4 gene have been reported to be associated with hypertension in Han Chinese population. We aimed to confirm whether the genetic variation of SLC4A4 gene influence the susceptibility to blood pressure and hypertension in Korean population. We genotyped variants in or near SLC4A4 in a population-based cohort including 7,551 unrelated Korean from Ansan and Ansung. Here, we performed association analysis to elucidate the possible relations of genetic polymorphisms in SLC4A4 gene with blood pressure traits. By examining genotype data of a total of 7,551 subjects in the Korean Association REsource (KARE) study, we discovered the SLC4A4 gene polymorphisms are associated with blood pressure and hypertension. The common and highest significant polymorphism was rs6846301 (${\beta}$=0.839, additive P=0.032) with systolic blood pressure (SBP), rs6846301 (${\beta}$=0.588, additive P=0.027) with diastolic blood pressure (DBP), and rs6846301 (OR=1.23, CI: 1.09~1.40, additive $P=1.2{\times}10^{-3}$) with hypertension. Furthermore, the SNP rs6846301 was consistently associated with both blood pressure and hypertension. Consequently, we found statistically significant SNPs in SLC4A4 gene that are associated with both blood pressure and hypertension traits. In addition, these results suggest that the individuals with the minor alleles of the SNP in the SLC4A4 gene may be more susceptible to the development of hypertension in the Korean population.

• Genomics & Informatics
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• v.12 no.4
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• pp.181-186
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• 2014

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.