• Asian Pacific Journal of Cancer Prevention
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• 제16권15호
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• pp.6645-6650
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• 2015

Background: Gastric cancer (GC) is the third most common cancer regarding mortality in the world. The cag pathogenicity island (PAI) of Helicobacter pylori which contains genes associated with a more aggressive phenotype may involve in the pathogenesis of gastrointestinal disease. We here aimed to examine the associations of cagH, cagL, orf17, and cagG genotypes of H. pylori cag PAI with severe gastrointestinal disease. Materials and Methods: A total of 242 H. pylori strains were genotyped. Histopathological examination and classification of subjects were performed. Results: The frequencies of the cagH, cagL, cagG, and orf17 genotypes were 40/54 (74.1%), 53/54 (98.1%), 38/54 (70.4%), and 43/54 (79.6%), respectively, in patients with peptidic ulceration (PU),while in the control group, the frequencies were 87/147 (59.6%) for cagH, 121/146 (82.9%) for cagL, 109/146 (74.7%) for cagG, and 89/146 (61.0%) for orf17. The results of simple logistic regression analysis showed that the cagL and orf17 genotypes were significantly associated with an increased risk of PU not GC; the ORs (95% CI) were 10.950 (1.446-82.935), and 2.504 (1.193-5.253), respectively. No significant association was found between the cagH and cagG genotypes and the risk of both the PU and the GC in Iran (P>0.05). Finally, multiple logistic regression analysis showed that the cagL genotype was independently and significantly associated with the age-and sex-adjusted risk for PU; the OR (95% CI) was 9.557 (1.219-17.185). Conclusions: We conclude that the orf17 and especially cagL genotypes of H. pylori cag PAI could be factors for risk prediction of PU, but not GC in Iran.

• Asian Pacific Journal of Cancer Prevention
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• 제13권10호
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• pp.5007-5010
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• 2012

Objective: We conducted a prospective study to test the association between three amino acid substitution polymorphismic variants of DNA repair genes, XRCC1 (Arg194Trp), XRCC1(Arg280His) and XRCC1 (Arg399Gln), and clinical outcome of ovarian cancer patients undergoing adjuvant chemotherapy. Methods: 195 patients with primary advanced ovarian cancer and treated by adjuvant chemotherapy were included in our study. All were followed-up from Jan. 2007 to Jan. 2012. Genotyping of XRCC1 polymorphisms was conducted by TaqMan Gene Expression assays. Results: The XRCC1 194 Trp/Trp genotype conferred a significant risk of death from ovarian cancer when compared with Arg/Arg (HR=1.56, 95%CI=1.04-3.15). Similarly, those carrying the XRCC1 399 Gln/Gln genotype had a increased risk of death as compared to the XRCC1 399Arg/Arg genotype with an HR (95% CI) of 1.98 (1.09-3.93). Conclusion: This study is the first to provide evidence that XRCC1 gene polymorphisms would well be useful as surrogate markers of clinical outcome in ovarian cancer cases undergoing adjuvant chemotherapy.

• Journal of Gastric Cancer
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• 제22권4호
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• pp.348-368
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• 2022

Purpose: Chromosomal instability is a hallmark of gastric cancer (GC). It can be driven by single nucleotide variants (SNVs) in cell cycle genes. We investigated the associations between SNVs in candidate genes, PLK2, PLK3, and ATM, and GC risk and clinicopathological features. Materials and Methods: The genotyping study included 542 patients with GC and healthy controls. Generalized linear models were used for the risk and clinicopathological association analyses. Survival analysis was performed using the Kaplan-Meier method. The binding of candidate miRs was analyzed using a luciferase reporter assay. Results: The PLK2 C_rs15009-C_rs963615 haplotype was under-represented in the GC group compared to that in the control group (P_corr=0.050). Male patients with the PLK2 rs963615 CT genotype had a lower risk of GC, whereas female patients had a higher risk (P=0.023; P=0.026). The PLK2 rs963615 CT genotype was associated with the absence of vascular invasion (P=0.012). The PLK3 rs12404160 AA genotype was associated with a higher risk of GC in the male population (P=0.015). The ATM T_rs228589-A_rs189037-G_rs4585 haplotype was associated with a higher risk of GC (P<0.001). The ATM rs228589, rs189037, and rs4585 genotypes TA+AA, AG+GG, and TG+GG were associated with the absence of perineural invasion (P=0.034). In vitro analysis showed that the cancer-associated miR-23b-5p mimic specifically bound to the PLK2 rs15009 G allele (P=0.0097). Moreover, low miR-23b expression predicted longer 10-year survival (P=0.0066) in patients with GC. Conclusions: PLK2, PLK3, and ATM SNVs could potentially be helpful for the prediction of GC risk and clinicopathological features. PLK2 rs15009 affects the binding of miR-23b-5p. MiR-23b-5p expression status could serve as a prognostic marker for survival in patients with GC.

• 한국통계학회:학술대회논문집
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• 한국통계학회 2005년도 추계 학술발표회 논문집
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• pp.31-36
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• 2005

An identification and characterization of susceptibility genes for common complex multifactorial diseases is a challengeable task, in which the effect of single genetic variation will be likely dependent on other genetic variations(gene-gene interaction) and environmental factors (gene-environment interaction). To address is issue, the multifactor dimensionality reduction (MDR) has been proposed and implemented by Ritchie et al. (2001), Moore et al. (2002), Hahn et al.(2003) and Ritchie et al. (2003). With MDR, multilocus genotypes effectively reduce the dimension of genotype predictors from n to one, which improves the identification of polymorphism combinations associated with disease risk. However, MDR cannot handle missing observations appropriately, in which missing observation is treated as an additional genotype category. This approach may suffer from a sparseness problem since when high-order interactions are considered, an additional missing category would make the contingency table cells more sparse. We propose a new MDR approach with minimum loss of sample sizes by considering missing data over all possible multifactor classes. We evaluate the proposed MDR by using the prediction errors and cross validation consistency.

• Asian-Australasian Journal of Animal Sciences
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• 제21권5호
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• pp.677-684
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• 2008

Accurate estimation of dry matter intake (DMI) is a prerequisite to meet animal performance targets without penalizing animal health and the environment. The objective of the current study was to evaluate some of the existing models in order to predict DMI when lactating dairy cows were offered a total mixed ration containing a high level of concentrates and locally produced agricultural by-products. Six popular models were chosen for DMI prediction (Brown et al., 1977; Rayburn and Fox, 1993; Agriculture Forestry and Fisheries Research Council Secretariat, 1999; National Research Council (NRC), 2001; Cornell Net Carbohydrate and Protein System (CNCPS), Fox et al., 2003; Fuentes-Pila et al., 2003). Databases for DMI comparison were constructed from two different sources: i) 12 commercial farm investigations and ii) a controlled dairy cow experiment. The model evaluation was performed using two different methods: i) linear regression analysis and ii) mean square error prediction analysis. In the commercial farm investigation, DMI predicted by Fuentes-Pila et al. (2003) was the most accurate when compared with the actual mean DMI, whilst the CNCPS prediction showed larger mean bias (difference between mean predicted and mean observed values). Similar results were observed in the controlled dairy cow experiment where the mean bias by Fuentes-Pila et al. (2003) was the smallest of all six chosen models. The more accurate prediction by Fuentes-Pila et al. (2003) could be attributed to the inclusion of dietary factors, particularly fiber as these factors were not considered in some models (i.e. NRC, 2001; CNCPS (Fox et al., 2003)). Linear regression analysis had little meaningful biological significance when evaluating models for prediction of DMI in this study. Further research is required to improve the accuracy of the models, and may recommend more mechanistic approaches to investigate feedstuffs (common to the Asian region), animal genotype, environmental conditions and their interaction, as the majority of the models employed are based on empirical approaches.

• 전기전자학회논문지
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• 제26권3호
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• pp.494-499
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• 2022

본 논문에서는 인간의 피부섬유모세포(Human dermal fibroblasts)로부터 확보한 전사체 정보를 활용하여 나이를 예측하는 방법을 소개한다. 제안 방법에서는 훈련을 통해 확보한 분류기 및 회귀 모델을 이용하여 샘플이 속한 적합한 연령 그룹을 선택한 후, 선택된 연령 그룹에 속하는 훈련 데이터의 관측값을 활용하여 구체적인 연령을 예측한다. 연령을 예측하려는 샘플이 입력되면 복수 개의 판별 규칙이 순서대로 실행되는데, 개별 판별 규칙에서는 분류기와 회귀 모델을 동시에 실행하여 해당 판별 규칙에 대한 선택조건이 만족되는지 여부를 확인한다. 선택 조건이 만족될 경우 판별 규칙의 타겟 연령 그룹에 속하는 데이터를 이용하여 훈련된 회귀 모델로 연령을 예측하며, 선택 조건이 만족되지 않으면 후속 판별 규칙을 실행한다. 공개 데이터에 대하여 실험한 결과 기존 연구에서 달성한 7.7년의 평균 예측 오차보다 우수한 5.7년이라는 평균 예측 오차를 달성함을 확인하였다.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2017년도 9th Asian Crop Science Association conference
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• pp.14-14
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• 2017

The discipline of plant breeding is experiencing a renaissance impacting crop improvement as a result of new technologies, however fundamental questions remain for predicting the phenotype and how the environment and genetics shape it. Inexpensive DNA sequencing, genotyping, new statistical methods, high throughput phenotyping and gene-editing are revolutionizing breeding methods and strategies for improving both quantitative and qualitative traits. Genomic selection (GS) models use genome-wide markers to predict performance for both phenotyped and non-phenotyped individuals. Aerial and ground imaging systems generate data on correlated traits such as canopy temperature and normalized difference vegetative index that can be combined with genotypes in multivariate models to further increase prediction accuracy and reduce the cost of advanced trials with limited replication in time and space. Design of a GS training population is crucial to the accuracy of prediction models and can be affected by many factors including population structure and composition. Prediction models can incorporate performance over multiple environments and assess GxE effects to identify a highly predictive subset of environments. We have developed a methodology for analyzing unbalanced datasets using genome-wide marker effects to group environments and identify outlier environments. Environmental covariates can be identified using a crop model and used in a GS model to predict GxE in unobserved environments and to predict performance in climate change scenarios. These new tools and knowledge challenge the plant breeder to ask the right questions and choose the tools that are appropriate for their crop and target traits. Contemporary plant breeding requires teams of people with expertise in genetics, phenotyping and statistics to improve efficiency and increase prediction accuracy in terms of genotypes, experimental design and environment sampling.

• 생물정신의학
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• 제13권4호
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• pp.299-304
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• 2006

Objectives : The purpose of the present study was to investigate whether the TaqI A polymorphism of dopamine receptor D2 gene(DRD2) is associated with Tourette syndrome(TS) and chronic motor tic disorder(CMT) in Korean population. Methods : DRD2 TaqI A RFLP genotyping was carried out with DNA extracted from blood samples of 75 patients with tic disorders(47 with TS and 28 with CMT) and 90 healthy subjects. Genotype and allelic frequencies for the DRD2 gene polymorphisms of the tic disorder group as a whole were compared to those of the control group. Separating the TS group, thereafter, the frequency of genotypes and alleles were compared to those of the controls. Results : The results demonstrated that genotype and allele distributions for the DRD2 gene polymorphism in the tic disorder as a whole, TS, and control groups were not significantly different. Conclusion : No association was found for DRD2 gene, TS and CMT. The data suggest that DRD2 gene may not be a useful marker for the prediction of the susceptibility of tic disorder.

• Genomics & Informatics
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• 제19권4호
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• pp.44.1-44.9
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• 2021

Autism is a complex neurodevelopmental disorder, the prevalence of which has increased drastically in India in recent years. Neuroligin is a type I transmembrane protein that plays a crucial role in synaptogenesis. Alterations in synaptic genes are most commonly implicated in autism and other cognitive disorders. The present study investigated the neuroligin 3 gene in the Indian autistic population by sequencing and in silico pathogenicity prediction of molecular changes. In total, 108 clinically described individuals with autism were included from the North Karnataka region of India, along with 150 age-, sex-, and ethnicity-matched healthy controls. Genomic DNA was extracted from peripheral blood, and exonic regions were sequenced. The functional and structural effects of variants of the neuroligin 3 protein were predicted. One coding sequence variant (a missense variant) and four non-coding variants (two 5'-untranslated region [UTR] variants and two 3'-UTR variants) were recorded. The novel missense variant was found in 25% of the autistic population. The C/C genotype of c.551T>C was significantly more common in autistic children than in controls (p = 0.001), and a significantly increased risk of autism (24.7-fold) was associated with this genotype (p = 0.001). The missense variant showed pathogenic effects and high evolutionary conservation over the functions of the neuroligin 3 protein. In the present study, we reported a novel missense variant, V184A, which causes abnormal neuroligin 3 and was found with high frequency in the Indian autistic population. Therefore, neuroligin is a candidate gene for future molecular investigations and functional analysis in the Indian autistic population.

• Genomics & Informatics
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• 제20권4호
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• pp.42.1-42.11
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• 2022

Breast cancer (BC) is a significant threat to female health, with both modifiable and non-modifiable risk factors. It is essential to monitor patients regularly and to raise population awareness. Increasing research also suggests that E-selectin (SELE) may increase tumor angiogenesis and the development of cancer. This study investigated SELE single-nucleotide polymorphisms (SNPs) in the following positions: rs5367T/C, rs5368C/T, rs5362T/G, and rs5362T/C. Using polymerase chain reaction, significant differences in allele and genotype frequencies were found between BC patients and controls. Position rs5368 was associated with an increased risk of BC for the CT and TT genotypes, with odds ratios (ORs) of 16.3 and 6.90 (Fisher probability = 0.0001, p = 0.005). Women with the T allele had a 19.3-fold higher incidence of BC, while allele C may be a protective allele against BC (OR, 0.05). Heterozygous genotypes at rs5367, rs5362, and rs5362 were significantly more common in BC patients, with ORs of 5.70, 4.50, and 3.80, respectively. These SNPs may be associated with the risk of BC, because the frequency of mutant alleles was significantly higher in patients (OR: 4.26, 3.83, and 4.30, respectively) than in controls (OR: 0.23, 0.30, and 0.20, respectively). These SNPs may be considered a common genotype in the Iraqi population, with the wild-type allele having a protective fraction and the mutant allele having an environmental fraction. The results also revealed a 2-fold increase in gene expression in BC patients compared to controls, with a significant effect (p = 0.017). This study's findings confirm the importance of SELE polymorphisms in cancer risk prediction.