• Toxicological Research
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• v.20 no.1
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• pp.49-53
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• 2004

The genetic basis of hypertension is complex, and has been considered to be associated with the dopamine D2 receptor gene (DD2R). Because association studies using the candidate gene approach may provide important clues regarding the pathogenesis of hypertension and establish basis for further study, we performed the association study on the relationship between genetic polymorphisms in the DD2R gene and hypertension in Koreans. Eighty nine patients with hypertension and 86 age-matched subjects with normal blood pressure were enrolled. Genomic DNA was extracted from peripheral blood leukocytes. PCR-RFLP analysis was performed to detect the three polymorphic Taq I sites in the DD2R gene. There were no significant differences in genotype, allele and haplotype distributions of any polymorphisms in the DD2R gene between two groups, respectively (P>0.05), although significant linkage disequilibriums among these polymorphic sites were detected by pair-wise analysis (P<0.05). Therefore, our negative result suggest that the three Taq I RFLPs in the DD2R gene were not significantly associated with hypertension in Koreans.

• Genomics & Informatics
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• v.21 no.3
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• pp.28.1-28.13
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• 2023

Mild cognitive impairment (MCI) is a clinical syndrome characterized by the onset and evolution of cognitive impairments, often considered a transitional stage to Alzheimer's disease (AD). The genetic traits of MCI patients who experience a rapid progression to AD can enhance early diagnosis capabilities and facilitate drug discovery for AD. While a genome-wide association study (GWAS) is a standard tool for identifying single nucleotide polymorphisms (SNPs) related to a disease, it fails to detect SNPs with small effect sizes due to stringent control for multiple testing. Additionally, the method does not consider the group structures of SNPs, such as genes or linkage disequilibrium blocks, which can provide valuable insights into the genetic architecture. To address the limitations, we propose a Bayesian bi-level variable selection method that detects SNPs associated with time of conversion from MCI to AD. Our approach integrates group inclusion indicators into an accelerated failure time model to identify important SNP groups. Additionally, we employ data augmentation techniques to impute censored time values using a predictive posterior. We adapt Dirichlet-Laplace shrinkage priors to incorporate the group structure for SNP-level variable selection. In the simulation study, our method outperformed other competing methods regarding variable selection. The analysis of Alzheimer's Disease Neuroimaging Initiative (ADNI) data revealed several genes directly or indirectly related to AD, whereas a classical GWAS did not identify any significant SNPs.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.9
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• pp.4305-4309
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• 2012

Background: Previous studies on the association between the TP53 Arg72Pro polymorphism and hepatocellular carcinoma (HCC) risk obtained controversial findings. This study aimed to quantify the strength of the association by meta-analysis. Methods: We searched PubMed and Wangfang databases for published studies on the association between the TP53 Arg72Pro polymorphism and HCC risk, using the pooled odds ratio (OR) with its 95% confidence intervals (95% CI) for assessment. Results: 10 studies with a total of 2,026 cases and 2,733 controls were finally included into this meta-analysis. Overall, the TP53 Arg72Pro polymorphism was not associated with HCC risk (all P values greaterth HCC risk in Caucasians in three genetic models (For Pro versus Arg, OR = 1.20, 95%CI 1.03-1.41; For ProPro versus ArgArg, OR = 1.74, 95%CI 1.23-2.47; For ProPro versus ArgPro/ArgArg, OR = 1.85, 95%CI 1.33-2.57). However, there was no significant association between the TP53 Arg72Pro polymorphism and HCC risk in East Asians (all P values greater than 0.10). No evidence of publication bias was observed. Conclusion: Meta-analyses of available data suggest an obvious association between the TP53 Arg72Pro and HCC risk in Caucasians. However, the TP53 Arg72Pro polymorphism may have a race-specific effect on HCC risk and further studies are needed to elucidate this possible effect.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.3
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• pp.1937-1943
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• 2013

Altered expression or function of manganese superoxide dismutase (MnSOD) has been shown to be associated with cancer risk but assessment of gene polymorphisms has resulted in inconclusive data. Here a search of published data was made and 22 studies were recruited, covering 20,025 case and control subjects, for meta-analyses of the association of MnSOD polymorphisms with the risk of prostate, esophageal, and lung cancers. The data on 12 studies of prostate cancer (including 4,182 cases and 6,885 controls) showed a statistically significant association with the risk of development in co-dominant models and dominant models, but not in the recessive model. Subgroup analysis showed there was no statistically significant association of MnSOD polymorphisms with aggressive or nonaggressive prostate cancer in different genetic models. In addition, the data on four studies of esophageal cancer containing 620 cases and 909 controls showed a statistically significant association between MnSOD polymorphisms and risk in all comparison models. In contrast, the data on six studies of lung cancer with 3,375 cases and 4,050 controls showed that MnSOD polymorphisms were significantly associated with the decreased risk of lung cancer in the homozygote and dominant models, but not the heterozygote model. A subgroup analysis of the combination of MnSOD polymorphisms with tobacco smokers did not show any significant association with lung cancer risk, histological type, or clinical stage of lung cancer. The data from the current study indicated that the Ala allele MnSOD polymorphism is associated with increased risk of prostate and esophageal cancers, but with decreased risk of lung cancer. The underlying molecular mechanisms warrant further investigation.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.5
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• pp.3275-3279
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• 2013

Background: Tumor necrosis factor-${\alpha}$ (TNF-${\alpha}$) plays a very important role in the development and progression of cancer. Many epidemiological studies have evaluated associations between the TNF-${\alpha}$ 238 G/A polymorphism and hepatocellular carcinoma (HCC) risk, but the published data are inconclusive. Therefore, we performed the present meta-analysis. Methods: Electronic searches of several databases were conducted for all publications on the association between TNF-${\alpha}$ 238 G/A polymorphism and HCC through July 2012. Asummary odds ratio (OR) with its 95% confidence interval (CI) were calculated to evaluate the strength of this association. Results: Eleven case-control studies with a total of 1,572 HCC cases and 1,875 controls were finally included in this meta-analysis. Overall, the TNF-${\alpha}$ 238 G/A polymorphism was significantly associated with increased risk of hepatocellular carcinoma in three genetic comparison models (For A versus G: OR 1.32, 95%CI 1.04-1.69, P = 0.02, $I_2$ = 40%; for AG versus GG: OR 1.32, 95%CI 1.02-1.71, P = 0.03, $I_2$ = 40%; for AA/AG versus GG: OR 1.33, 95%CI 1.03-1.72, P = 0.03, $I_2$ = 41%) when all studies were pooled. Subgroup analysis by ethnicity further showed that there was a significant association between the TNF-${\alpha}$ 238 G/A polymorphism and risk of HCC in Asians under three genetic comparison models (For A versus G: OR 1.30, 95%CI 1.00-1.68, P = 0.05, $I_2$ = 45% for AA/AG versus GG: OR 1.31, 95%CI 1.00-1.71, P = 0.05, $I_2$ = 46%). Conclusions: This meta-analysis provided convincing evidence that the TNF-${\alpha}$ 238 G/A polymorphism is associated with increased susceptibility to HCC. However, more well-designed studies with large sample size are needed to validate this association in Caucasians.

• Genomics & Informatics
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• v.6 no.1
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• pp.18-28
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• 2008

Single nucleotide polymorphisms (SNPs) are the most abundant forms of human genetic variations and resources for mapping complex genetic traits and disease association studies. We have constructed a linkage disequilibrium (LD) map of chromosome 22 in Korean samples and compared it with those of other populations, including Yorubans in Ibadan, Nigeria (YRI), Centre d'Etude du Polymorphisme Humain (CEPH) reference families (CEU), Japanese in Tokyo (JPT) and Han Chinese in Beijing (CHB) in the HapMap database. We genotyped 4681 of 111,448 publicly available SNPs in 90 unrelated Koreans. Among genotyped SNPs, 4167 were polymorphic. Three hundred and five LD blocks were constructed to make up 18.6% (6.4 of 34.5 Mb) of chromosome 22 with 757 tagSNPs and 815 haplotypes (frequency $\geq$ 5.0%). Of 3430 common SNPs genotyped in all five populations, 514 were monomorphic in Koreans. The CHB + JPT samples have more than a 72% overlap with the monomorphic SNPs in Koreans, while the CEU + YRI samples have less than a 38% overlap. The patterns of hot spots and LD blocks were dispersed throughout chromosome 22, with some common blocks among populations, highly concordant between the three Asian samples. Analysis of the distribution of chimpanzee-derived allele frequency (DAF), a measure of genetic differentiation, Fst levels, and allele frequency difference (AFD) among Koreans and the HapMap samples showed a strong correlation between the Asians, while the CEU and YRI samples showed a very weak correlation with Korean samples. Relative distance as a quantitative measurement based upon DAF, Fst, and AFD indicated that all three Asian samples are very proximate, while CEU and YRI are significantly remote from the Asian samples. Comparative genome-wide LD studies provide useful information on the association studies of complex diseases.

• Asian-Australasian Journal of Animal Sciences
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• v.30 no.12
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• pp.1684-1688
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• 2017

Objective: From a review of published information on genetic association studies, a meta-analysis was conducted to determine the influence of the genes ${\kappa}-casein$ (CSN3) and ${\beta}-lactoglobulin$ (LGB) on milk yield traits in Holstein, Jersey, Brown Swiss, and Fleckvieh. Methods: The GLIMMIX procedure was used to analyze milk production and percentage of protein and fat in milk. Models included the main effects and all their possible two-way interactions; not estimable effects and non-significant (p>0.05) two-way interactions were dropped from the models. The three traits analyzed used Poisson distribution and a log link function and were determined with the Interactive Data Analysis of SAS software. Least square means and multiple mean comparisons were obtained and performed for significant main effects and their interactions (p<0.0255). Results: Interaction of breed by gene showed that Holstein and Fleckvieh were the breeds on which CSN3 ($6.01%{\pm}0.19%$ and $5.98%{\pm}0.22%$), and LGB ($6.02%{\pm}0.19%$ and $5.70%{\pm}0.22%$) have the greatest influence. Interaction of breed by genotype nested in the analyzed gene indicated that Holstein and Jersey showed greater influence of the CSN3 AA genotype, $6.04%{\pm}0.22%$ and $5.59%{\pm}0.31%$ than the other genotypes, while LGB AA genotype had the largest influence on the traits analyzed, $6.05%{\pm}0.20%$ and $5.60%{\pm}0.19%$, respectively. Furthermore, interaction of type of statistical model by genotype nested in the analyzed gene indicated that CSN3 and LGB genes had similar behavior, maintaining a difference of more than 7% across analyzed genotypes. These results could indicate that both Holstein and Jersey have had lower substitution allele effect in selection programs that include CSN3 and LGB genes than Brown Swiss and Fleckvieh. Conclusion: Breed determined which genotypes had the greatest association with analyzed traits. The mixed model based in Bayesian or Ridge Regression was the best alternative to analyze CSN3 and LGB gene effects on milk yield and protein and fat percentages.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3937-3942
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• 2012

Background: Many studies have investigated possible association between the methylenetetrahydrofolate reductase (MTHFR) C677T polymorphism and ovarian cancer risk, but the impact is still unclear owing to the obvious inconsistencies. This study was performed to quantify the strength of the association with a metaanalysis. Methods: We searched the PubMed, Embase, and CNKI databases for studies relating the association between MTHFR C677T polymorphism and ovarian cancer risk and estimated summary odds ratios (ORs) with confidence intervals (CIs) for assessment. Results: Finally, eight studies with a total of 3,379 ovarian cancer cases and 4,078 controls were included into this meta-analysis. Overall the showed that MTHFR C677T polymorphism was not associated with ovarian cancer risk under all genetic models ($OR_{T\;versus\;C}$ = 1.03, 95%CI 0.90-1.18; $OR_{TT\;versus\;CC}$ = 1.08, 95%CI 0.79-1.47; $OR_{TT\;versus\;TC+CC}$ = 1.05, 95%CI 0.80-1.37; $OR_{TT+TC\;versus\;CC}$ = 1.05, 95%CI 0.86-1.21). Meta-analyses of studies with confirmation of HWE also showed no significant association. Subgroup analyses by ethnicity showed there was no significant association in the Caucasians but MTHFR C677T polymorphic variant T contributed to increased risk of ovarian cancer in East Asians. No evidence of publication bias was observed. Conclusion: Meta-analyses of available data show that MTHFR C677T polymorphism is not associated with ovarian cancer risk in Caucasians, but the MTHFR polymorphic variant T may contribute to increased risk in East Asians.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.8
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• pp.3763-3766
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• 2012

Background: Methylenetetrahydrofolate reductase (MTHFR) is a key enzyme in the metabolism of folate, and the role of the MTHFR C677T polymorphism in pancreatic carcinogenesis is still controversial. Methods: A literature search was performed using Pubmed and CNKI databases for published studies through May 2012. We performed a meta-analysis of all relevant case-control studies that examined the association between MTHFR C677T polymorphism and pancreatic cancer risk. Results: Finally, 9 individual case-control studies with a total of 1,299 pancreatic cancer cases and 2,473 controls were included into this meta-analysis. Results: This metaanalysis showed there was an obvious association between MTHFR C677T polymorphism and pancreatic cancer risk in East Asians (for allele model, OR = 1.67, 95%CI 1.11-2.51; For homozygote model, OR = 2.77, 95%CI 1.40-5.48; for recessive model, OR = 1.96, 95%CI 1.54-2.50; for dominant model, OR = 2.11, 95%CI 1.01-4.41). However, no significant association was found in Caucasians. Conclusions: The MTHFR C677T polymorphism is associated with pancreatic cancer risk, and a race-specific effect may exist in this association. More studies with a larger sample size are needed to further clarify this association.

• Genomics & Informatics
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• v.14 no.4
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• pp.138-148
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• 2016

The success of genome-wide association studies (GWASs) has enabled us to improve risk assessment and provide novel genetic variants for diagnosis, prevention, and treatment. However, most variants discovered by GWASs have been reported to have very small effect sizes on complex human diseases, which has been a big hurdle in building risk prediction models. Recently, many statistical approaches based on penalized regression have been developed to solve the "large p and small n" problem. In this report, we evaluated the performance of several statistical methods for predicting a binary trait: stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and Elastic-Net (EN). We first built a prediction model by combining variable selection and prediction methods for type 2 diabetes using Affymetrix Genome-Wide Human SNP Array 5.0 from the Korean Association Resource project. We assessed the risk prediction performance using area under the receiver operating characteristic curve (AUC) for the internal and external validation datasets. In the internal validation, SLR-LASSO and SLR-EN tended to yield more accurate predictions than other combinations. During the external validation, the SLR-SLR and SLR-EN combinations achieved the highest AUC of 0.726. We propose these combinations as a potentially powerful risk prediction model for type 2 diabetes.