• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1247-1255
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• 2016

Kim and Lee (2015) identified a superior FABP4 gene that improves the grade and fatty acid of Korean cattle. This study selects a superior genotype by expanding genes that influence the economic traits of Korean cattle. Expanded genes are FABP4, SCD, FASN and SREBPs that are related to grade and fatty acid (Oh, 2014). We use the adjusted economic-trait values with environmental factors excluded. We also applied multifactor dimensionality reduction(MDR) method to data of the adjusted economic-trait values. As a result, we identified superior genes and genotypes which improved the grade and fatty acid of Korean cattle.

• Communications for Statistical Applications and Methods
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• v.16 no.4
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• pp.579-586
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• 2009

We have used multifactor dimensionality reduction(MDR) method to study interaction effect of statistical model in general. But MDR method cannot be applied in all cases. It can be applied to the only case-control data. So, two methods are suggested E-MDR and D-MDR method using regression tree algorithm and dummy variables. We applied the methods on the identify interaction effects of single nucleotide polymorphisms(SNPs) responsible for longissimus mulcle dorsi area(LMA), carcass cold weight(CWT) and average daily gain(ADG) in a Hanwoo beef cattle population. Finally, we compare the results using permutation test.

• Genomics & Informatics
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• v.20 no.2
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• pp.17.1-17.11
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• 2022

Genetic associations have been quantified using a number of statistical measures. Entropy-based mutual information may be one of the more direct ways of estimating the association, in the sense that it does not depend on the parametrization. For this purpose, both the entropy and conditional entropy of the phenotype distribution should be obtained. Quantitative traits, however, do not usually allow an exact evaluation of entropy. The estimation of entropy needs a probability density function, which can be approximated by kernel density estimation. We have investigated the proper sequence of procedures for combining the kernel density estimation and entropy estimation with a probability density function in order to calculate mutual information. Genotypes and their interactions were constructed to set the conditions for conditional entropy. Extensive simulation data created using three types of generating functions were analyzed using two different kernels as well as two types of multifactor dimensionality reduction and another probability density approximation method called m-spacing. The statistical power in terms of correct detection rates was compared. Using kernels was found to be most useful when the trait distributions were more complex than simple normal or gamma distributions. A full-scale genomic dataset was explored to identify associations using the 2-h oral glucose tolerance test results and γ-glutamyl transpeptidase levels as phenotypes. Clearly distinguishable single-nucleotide polymorphisms (SNPs) and interacting SNP pairs associated with these phenotypes were found and listed with empirical p-values.

• Asian-Australasian Journal of Animal Sciences
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• v.24 no.11
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• pp.1525-1528
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• 2011

The purpose of this study was to detect SNPs that were responsible for a carcass trait in Hanwoo populations. A non-parametric model applying a restricted partition method (RPM) was used, which exploited a partitioning algorithm considering statistical criteria for multiple comparison testing. Phenotypic and genotypic data were obtained from the Hanwoo Improvement Center, National Agricultural Cooperation Federation, Korea, in which the pedigree structure comprised 229 steers from 16 paternal half-sib proven sires that were born in Namwon or Daegwanryong livestock testing station between spring of 2002 and fall of 2003. A carcass trait, longissimus dorsi muscle area for each steer was measured after slaughter at approximately 722 days. Three SNPs (19_1, 18_4 and 28_2) near the microsatellite marker ILSTS035 on BTA6, around which the quantitative trait loci (QTL) for meat quality were previously detected, were used in this study. The RPM analyses resulted in two significant interaction effects between SNPs (19_1 and 18_4) and (19_1 and 28_2) at ${\alpha}$ = 0.05 level. However, under a general linear (parametric) model no interaction effect between any pair of the three SNPs was detected, while only one main effect for SNP19_1 was found for the trait. Also, under another non-parametric model using a multifactor dimensionality reduction (MDR) method, only one interaction effect of the two SNPs (19_1 and 28_2) explained the trait significantly better than the parametric model with the main effect of SNP19_1. Our results suggest that RPM is a good alternative to model choices that can find associations of the interaction effects of multiple SNPs for quantitative traits in livestock species.

• Asian Pacific Journal of Cancer Prevention
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• v.17 no.6
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• pp.2811-2819
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• 2016

Multiple genetic and environmental factors have been reported to play key role in the development of nasopharyngeal carcinoma (NPC). Here, we investigated interactions of XRCC1 Arg399Gln and XRCC2 Arg188His polymorphisms and environmental factors in modulating susceptibility to NPC in Northeast India. One-hundred NPC patients, 90 first-degree relatives of patients and 120 controls were enrolled in the study. XRCC1 Arg399Gln and XRCC2 Arg188His polymorphisms were determined using PCR-RFLP, and the results were confirmed by DNA sequencing. Logistic regression (LR) and multifactor dimensionality reduction (MDR) approaches were applied for statistical analysis. The XRCC1 Gln/Gln genotype showed increased risk (OR=2.76; P<0.024) of NPC. However, individuals with both XRCC1 and XRCC2 polymorphic variants had 3.2 fold elevated risk (P<0.041). An enhanced risk of NPC was also observed in smoked meat (OR=4.07; P=0.004) and fermented fish consumers (OR=4.34, P=0.001), and tobacco-betel quid chewers (OR=7.00; P=0.0001) carrying XRCC1 polymorphic variants. However, smokers carrying defective XRCC1 gene showed the highest risk (OR = 7.47; P<0.0001). On MDR analysis, the best model for NPC risk was the five-factor model combination of XRCC1 variant genotype, fermented fish, smoked meat, smoking and chewing (CVC=10/10; TBA=0.636; P<0.0001); whereas in interaction entropy graphs, smoked meat and tobacco chewing showed synergistic interactions with XRCC1. These findings suggest that interaction of genetic and environmental factors might increase susceptibility to NPC in Northeast Indian populations.

• Korean Journal of Biological Psychiatry
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• v.17 no.4
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• pp.218-225
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• 2010

Objectives : The potential association between choline acetyltransferase(CHAT) polymorphism and the risk of mild cognitive impairment(MCI) has not been investigated in Korea. We examined the main effect of CHAT polymorphism and its interaction with apolipoprotein E(APOE) polymorphism in the development of MCI in elderly Korean sample. Methods : We analyzed CHAT 2384G > A polymorphism and APOE polymorphism among 149 MCI subjects with MCI and 298 normal controls. We tested the association between MCI and CHAT A allele status using a logistic regression model. In addition, we employed generalized multifactor dimensionality reduction(GMDR) to investigate the interaction between CHAT and APOE with regard to the risk of MCI. Results : The CHAT A allele was associated with AD risk(OR = 1.59, 95% CI = 1.02-2.48, p = 0.042). No significant gene-gene interaction between CHAT and APOE was found in GMDR method(testing balanced accuracy = 0.540, p = 0.055). Conclusion : The CHAT A allele was associated with MCI risk in the Korean elderly. Its interaction with the APOE ${\varepsilon}4$ allele was not significant with regard to the development of MCI.

• The Korean Journal of Applied Statistics
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• v.28 no.5
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• pp.859-870
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• 2015

Economic-traits of livestock are affected by environmental and genetic factors. We are interested in genetic factors that influence the economic-traits of Korean cattle. It is necessary to adjust environmental factors in order to enhance the accuracy of the genetic effect analysis. In this paper, we propose a statistical model of Korean cattle that exclude environmental breeding farm and age factors. We formulated an adjusted economic-trait value, and applied multifactor dimensionality reduction (MDR) method to data of before-and-after adjustment to identify major FABP4 genes. We were able to increase the accuracy of the analysis after adjustment and identify superior FABP4 genes that influence grade and fatty acid.

• Asian Pacific Journal of Cancer Prevention
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• v.16 no.16
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• pp.6953-6961
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• 2015

Background: Tobacco and alcohol contain or may generate carcinogenic compounds related to cancers. CYP1A1 enzymes act upon these carcinogens before elimination from the body. The aim of this study was to investigate whether CYP1A1 T3801C polymorphism modulates the relationship between tobacco and alcohol-associated head and neck cancer (HNC) susceptibility among the northeast Indian population. Materials and Methods: One hundred and seventy histologically confirmed HNC cases and 230 controls were included within the study. The CYP1A1 T3801C polymorphism was determined using PCR-RFLP, and the results were confirmed by DNA sequencing. Logistic regression (LR) and multifactor dimensionality reduction (MDR) approaches were applied for statistical analysis. Results: The CYP1A1 CC genotype was significantly associated with HNC risk (P=0.045). A significantly increased risk of HNC (OR=6.09; P<0.0001) was observed in individuals with combined habits of smoking, alcohol drinking and tobacco-betel quid chewing. Further, gene-environment interactions revealed enhanced risks of HNC among smokers, alcohol drinkers and tobacco-betel quid chewers carrying CYP1A1 TC or CC genotypes. The highest risk of HNC was observed among smokers (OR=7.55; P=0.009) and chewers (OR=10.8; P<0.0001) carrying the CYP1A1 CC genotype. In MDR analysis, the best model for HNC risk was the three-factor model combination of smoking, tobacco-betel quid chewing and the CYP1A1 variant genotype (CVC=99/100; TBA=0.605; P<0.0001); whereas interaction entropy graphs showed synergistic interaction between tobacco habits and CYP1A1. Conclusions: Our results confirm that the CYP1A1 T3801C polymorphism modifies the risk of HNC and further demonstrated importance of gene-environment interaction.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.11
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• pp.6673-6680
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• 2013

Objective: Insulin resistance (IR) is an established risk factor for colorectal cancer (CRC). Given that CRC and IR physiologically overlap and the calpain-10 gene (CAPN10) is a candidate for IR, we explored the association between CAPN10 and CRC risk. Methods: Blood samples of 400 case-control pairs were genotyped, and the lifestyle and dietary habits of these pairs were recorded and collected. Unconditional logistic regression (LR) was used to assess the effects of CAPN10 SNP43 and SNP19, and environmental factors. Both generalized multifactor dimensionality reduction (GMDR) and the classification and regression tree (CART) were used to test gene-environment interactions for CRC risk. Results: The GA+AA genotype of SNP43 and the Del/Ins+Ins/Ins genotype of SNP19 were marginally related to CRC risk (GA+AA: OR = 1.35, 95% CI = 0.92-1.99; Del/Ins+Ins/Ins: OR = 1.31, 95% CI = 0.84-2.04). Notably, a high-order interaction was consistently identified by GMDR and CART analyses. In GMDR, the four-factor interaction model of SNP43, SNP19, red meat consumption, and smoked meat consumption was the best model, with a maximum cross-validation consistency of 10/10 and testing balance accuracy of 0.61 (P < 0.01). In LR, subjects with high red and smoked meat consumption and two risk genotypes had a 6.17-fold CRC risk (95% CI = 2.44-15.6) relative to that of subjects with low red and smoked meat consumption and null risk genotypes. In CART, individuals with high smoked and red meat consumption, SNP19 Del/Ins+Ins/Ins, and SNP43 GA+AA had higher CRC risk (OR = 4.56, 95%CI = 1.94-10.75) than those with low smoked and red meat consumption. Conclusions: Though the single loci of CAPN10 SNP43 and SNP19 are not enough to significantly increase the CRC susceptibility, the combination of SNP43, SNP19, red meat consumption, and smoked meat consumption is associated with elevated risk.