• Genomics & Informatics
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• v.7 no.1
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• pp.20-25
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• 2009

Rheumatoid arthritis (RA) is a chronic autoimmune disorder that is characterized by inflammation of the synovial tissue and deterioration of the joint and bone. A recent study reported a potential gene-environment interaction between HLA-DR and smoking. The present study investigated whether a specific gene was related to the association between smoking and the severity of RA (rheumatoid factor levels > 20 IU/ml). We used the resources of the NARAC family collection of GAW 15 databases, and 1139 subjects with RF>20 IU/ml were included in the current analysis. The linkage panel contained 5858 SNP markers, and 5744 SNPs passed quality control criteria. Linear regression analyses, using PLINK software and generalized estimating equation regression models, were used to test for associations between the SNPs and the severity of RA according to smoking groups. Two major findings were established. First, the severity of RA in smokers was associated with rs703618 (p=$6{\times}10^{-5}$), which lies in the intronic region of the stabilin 2 (STAB2) gene on chromosome 12. Second, there were significant differences in the levels of RF between 'ever smokers' and 'never smokers' according to the rs703618 genotype (G/G, A/G, A/A). We investigated whether a specific gene acts as a mediator between smoking and the severity of RA and found that the STAB2 gene could affect this relationship. Our finding indicates that smoking may mediate RA severity by affecting the expression level of a specific gene.

• 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.

• BMB Reports
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• v.35 no.6
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• pp.562-567
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• 2002

In order to find the cellular interaction factors of the Heliothis armigera nuclear polyhedrosis virus capsid protein VP39, a Heliothis armigera cell cDNA library was constructed. Then VP39 was used as bait. The host actin gene was isolated from the cDNA library with the yeast two-hybrid system. This demonstrated that VP39 could interact with its host actin in yeast. In order to corroborate this interaction in vivo, the vp39 gene was fused with the green fluorescent protein gene in plasmid pEGFP39. The fusion protein was expressed in the Hz-AM1 cells under the control of the Autographa californica multiple nucleopolyhedrovirus immediate early gene promoter. The host actin was labeled specifically by the red fluorescence substance, tetramethy rhodamine isothicyanete-phalloidin. Observation under a fluorescence microscopy showed that VP39, which was indicated by green fluorescence, began to appear in the cells 6 h after being transfected with pEGFP39. Red actin cables were also formed in the cytoplasm at the same time. Actin was aggregated in the nucleus 9 h after the transfection. The green and red fluorescence always appeared in the same location of the cells, which demonstrated that VP39 could combine with the host actin. Such a combination would result in the actin skeleton rearrangement.

• Korean Journal of Biological Psychiatry
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• v.20 no.4
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• pp.129-135
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• 2013

Aggression can be defined as 'behavior intended to harm another' which can be seen both from humans and animals. However, trying to understand aggression in a simplistic view may make it difficult to develop an integrated approach. So, we tried to explain aggression in a multidisciplinary approach, affected by various factors such as neuroanatomical structures, neurotransmitter, genes, and sex hormone. Parallel with animal models, human aggression can be understood with two phenomena, offensive aggression and defensive aggression. Neurobiological model of aggression give a chance to explain aggression with an imbalance between prefrontal regulatory influences and hyper-reactivity of the subcortical areas involved in affective evaluation, finally in an aspect of brain organization. Serotonin and GABA usually inhibit aggression and norepinephrine while glutamate and dopamine precipitate aggressive behavior. As there is no one gene which has been identified as a cause of aggression, functions between gene to gene interaction and gene to environment interaction are being magnified. Contributions of sex hormone to aggression, especially molecular biologic interaction of testosterone and regulation of estrogen receptor have been emphasized during the research on aggression. This multidisciplinary approach on aggression with types, neurochemical bases, and animal models can bring integrated interpretation on aggression.

• ETRI Journal
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• v.38 no.1
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• pp.206-215
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• 2016

The detection of gene-gene interactions during genetic studies of common human diseases is important, and the technique of multifactor dimensionality reduction (MDR) has been widely applied to this end. However, this technique is not free from the "curse of dimensionality" -that is, it works well for two- or three-way interactions but requires a long execution time and extensive computing resources to detect, for example, a 10-way interaction. Here, we propose a boosting method to reduce MDR execution time. With the use of pre-evaluation measurements, gene sets with low levels of interaction can be removed prior to the application of MDR. Thus, the problem space is decreased and considerable time can be saved in the execution of MDR.

• Journal of Preventive Medicine and Public Health
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• v.40 no.2
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• pp.108-113
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• 2007

When conducting large-scale cohort studies, numerous statistical issues arise from the range of study design, data collection, data analysis and interpretation. In genomic cohort studies, these statistical problems become more complicated, which need to be carefully dealt with. Rapid technical advances in genomic studies produce enormous amount of data to be analyzed and traditional statistical methods are no longer sufficient to handle these data. In this paper, we reviewed several important statistical issues that occur frequently in large-scale genomic cohort studies, including measurement error and its relevant correction methods, cost-efficient design strategy for main cohort and validation studies, inflated Type I error, gene-gene and gene-environment interaction and time-varying hazard ratios. It is very important to employ appropriate statistical methods in order to make the best use of valuable cohort data and produce valid and reliable study results.

• The Plant Pathology Journal
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• v.17 no.2
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• pp.83-87
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• 2001

Disease resistance in plants is often controlled by gene-for-gene mechanism in which avirulence (avr) gene products encoding by pathogens are specifically recognized, either directly or indirectly by plant disease resistance (R) gene products. Recent studies arising from molecular cloning of a number of R genes from various plant species that confer resistance to different pathogens and corresponding avr genes from various pathogens resulted in the accumulation of a wealth of knowledge on mode of action of gene-for-gene interaction. Specially, members of the NBS-LRR class of R genes encoding proteins containing a nucleotide binding site (NBS) and carboxyl-terminal leucine-rich repeats (LRRs) confer resistance to very different types of phytopathogens, such as bacteria, fungi, oomycetes, viruses, nematodes and aphids. This article reviewed the molecular events that occur up-stream of defense response pathway, specially, bacterial avr gene protein recognition mediated by NBS-LRR type R gene product in plant based on current research results of well studied model plants.

• Asian Pacific Journal of Cancer Prevention
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• v.13 no.5
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• pp.2031-2037
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• 2012

Background: Analysis of gene-gene and gene-environment interactions for complex multifactorial human disease faces challenges regarding statistical methodology. One major difficulty is partly due to the limitations of parametric-statistical methods for detection of gene effects that are dependent solely or partially on interactions with other genes or environmental exposures. Based on our previous case-control study in Chongqing of China, we have found increased risk of colorectal cancer exists in individuals carrying a novel homozygous TT at locus rs1329149 and known homozygous AA at locus rs671. Methods: In this study, we proposed statistical method-crossover analysis in combination with logistic regression model, to further analyze our data and focus on assessing gene-environmental interactions for colorectal cancer. Results: The results of the crossover analysis showed that there are possible multiplicative interactions between loci rs671 and rs1329149 with alcohol consumption. Multifactorial logistic regression analysis also validated that loci rs671 and rs1329149 both exhibited a multiplicative interaction with alcohol consumption. Moreover, we also found additive interactions between any pair of two factors (among the four risk factors: gene loci rs671, rs1329149, age and alcohol consumption) through the crossover analysis, which was not evident on logistic regression. Conclusions: In conclusion, the method based on crossover analysis-logistic regression is successful in assessing additive and multiplicative gene-environment interactions, and in revealing synergistic effects of gene loci rs671 and rs1329149 with alcohol consumption in the pathogenesis and development of colorectal cancer.

• Journal of the Korean Data and Information Science Society
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• v.20 no.1
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• pp.171-178
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• 2009

In order to make the high quality Korean cattle, it has been identified the gene which influence to various economic characters. In this paper, we introduce Restricted Partition Method for gene-gene interaction analysis. Further, economic traits, longissimus muscle dorsi area (LMA), carcass cold weight (CWT) and average daily gain (ADG) are applied with Restricted Partition Method (RPM). The SNP (19_1)$^*$SNP (28_2) was selected and was best marker on Single nucleotide polymorphisms (SNPs). It also influenced SNP (19_1)$^*$SNP (28_2) was an very important marker for economic character and to make the thing know it became.

• Proceedings of the Korean Statistical Society Conference
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• 2005.11a
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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.