• Title, Summary, Keyword: gene-environment interactions

Search Result 62, Processing Time 0.036 seconds

Application of Crossover Analysis-logistic Regression in the Assessment of Gene- environmental Interactions for Colorectal Cancer

  • Wu, Ya-Zhou;Yang, Huan;Zhang, Ling;Zhang, Yan-Qi;Liu, Ling;Yi, Dong;Cao, Jia
    • Asian Pacific Journal of Cancer Prevention
    • /
    • v.13 no.5
    • /
    • pp.2031-2037
    • /
    • 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.

Replication of Early B-cell Factor 1 (EBF1) Gene-by-psychosocial Stress Interaction Effects on Central Adiposity in a Korean Population

  • Kim, Hyun-Jin;Min, Jin-Young;Min, Kyoung-Bok
    • Journal of Preventive Medicine and Public Health
    • /
    • v.49 no.5
    • /
    • pp.253-259
    • /
    • 2016
  • Objectives: Central obesity plays a major role in the development of many chronic diseases, including cardiovascular disease and cancer. Chronic stress may be involved in the pathophysiology of central obesity. Although several large-scale genome-wide association studies have reported susceptibility genes for central adiposity, the effects of interactions between genes and psychosocial stress on central adiposity have rarely been examined. A recent study focusing on Caucasians discovered the novel gene early B-cell factor 1 (EBF1), which was associated with central obesity-related traits via interactions with stress levels. We aimed to evaluate EBF1 gene-by-stress interaction effects on central adiposity traits, including visceral adipose tissue (VAT), in Korean adults. Methods: A total of 1467 Korean adults were included in this study. We selected 22 single-nucleotide polymorphisms (SNPs) in the EBF1 gene and analyzed their interactions with stress on central adiposity using additive, dominant, and recessive genetic modeling. Results: The four SNPs that had strong linkage disequilibrium relationships (rs10061900, rs10070743, rs4704967, and rs10056564) demonstrated significant interactions with the waist-hip ratio in the dominant model ($p_{int}$<0.007). In addition, two other SNPs (rs6556377 and rs13180086) were associated with VAT by interactions with stress levels, especially in the recessive genetic model ($p_{int}$<0.007). As stress levels increased, the mean values of central adiposity traits according to SNP genotypes exhibited gradual but significant changes (p<0.05). Conclusions: These results suggest that the common genetic variants for EBF1 are associated with central adiposity through interactions with stress levels, emphasizing the importance of managing stress in the prevention of central obesity.

Discovering Gene-Environment Interactions in the Post-Genomic Era

  • Naidoo, Nirinjini;Chia, Kee-Seng
    • Journal of Preventive Medicine and Public Health
    • /
    • v.42 no.6
    • /
    • pp.356-359
    • /
    • 2009
  • In the more than 100 genome wide association studies (GWAS) conducted in the past 5 years, more than 250 genetic loci contributing to more than 40 common diseases and traits have been identified. Whilst many genes have been linked to a trait, both their individual and combined effects are small and unable to explain earlier estimates of heritability. Given the rapid changes in disease incidence that cannot be accounted for by changes in diagnostic practises, there is need to have well characterized exposure information in addition to genomic data for the study of gene-environment interactions. The case-control and cohort study designs are most suited for studying associations between risk factors and occurrence of an outcome. However, the case control study design is subject to several biases and hence the preferred choice of the prospective cohort study design in investigating geneenvironment interactions. A major limitation of utilising the prospective cohort study design is the long duration of follow-up of participants to accumulate adequate outcome data. The GWAS paradigm is a timely reminder for traditional epidemiologists who often perform one- or few-at-a-time hypothesis-testing studies with the main hallmarks of GWAS being the agnostic approach and the massive dataset derived through large-scale international collaborations.

Environment Adaptation using Evolutional Interactivity in a Swarm of Robots (진화적 상호작용을 이용한 군집로봇의 환경적응)

  • Moon, Woo-Sung;Jang, Jin-Won;Baek, Kwang-Ryul
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.16 no.3
    • /
    • pp.227-232
    • /
    • 2010
  • In this paper we consider the multi-robot system that collects target objects spread in an unexplored environment. The robots cooperate each other to improve the capability and the efficiency. The robots attract or intimidate each other as behaviors of bacterial swarms or particles with electrical moments. The interactions would increase the working efficiency in some environments but it would decrease the efficiency in some other environments. Therefore, the system needs to adapt to the working environment by adjusting the strengths of the interactions. The strengths of the interactions are expressed as sets of gene codes that mean the weights of each kind of attracting or intimidating vectors. The proposed system adjusts the gene codes using evolutional strategy. The proposed approach has been validated by computer simulation. The results of this paper show that our inter-swarm interacting strategy and optimizing algorithm improves the working efficiency, adaptively to the characteristics of environments.

Exploration of the Gene-Gene Interactions Using the Relative Risks in Distinct Genotypes (유전자형별 상대 위험도를 이용한 유전자-유전자간 상호작용 탐색)

  • Jung, Ji-Won;Yee, Jae-Yong;Lee, Suk-Hoon;Pa, Mi-Ra
    • The Korean Journal of Applied Statistics
    • /
    • v.24 no.5
    • /
    • pp.861-869
    • /
    • 2011
  • One of the main objects of recent genetic studies is to understand genetic factors that induce complex diseases. If there are interactions between loci, it is difficult to find such associations through a single-locus analysis strategy. Thus we need to consider the gene-gene interactions and/or gene-environment interactions. The MDR(multifactor dimensionality reduction) method is being used frequently; however, it is not appropriate to detect interactions caused by a small fraction of the possible genotype pairs. In this study, we propose a relative risk interaction explorer that detects interactions through the calculation of the relative risks between the control and disease groups from each genetic combinations. For illustration, we apply this method to MDR open source data. We also compare the MDR and the proposed method using the simulated data eight genetic models.

Suicide : Gene-Environment Interaction (자살 : 유전자-환경 상호작용)

  • Kim, Yong-Ku
    • Korean Journal of Biological Psychiatry
    • /
    • v.17 no.2
    • /
    • pp.65-69
    • /
    • 2010
  • Gene-environment interactions are important in pathogenesis of suicide or suicidal behavior. Twin and adoption studies and family studies show that genetic factors play a critical role in suicide or suicidal behavior. Given the strong association between serotonergic neurotransmission and suicide, recent molecular genetic studies have focused on polymorphisms of serotonin genes, especially on serotonin transporter and tryptophan hydroxylase genes. Some studies have revealed a significant interaction between s allele of the serotonin transporter gene and the risk of suicide attempt associated with childhood trauma. In addition, the polymorphism of brain-derived neurotrophic factor gene also may influence the effect of childhood trauma in relation to the risk of attempting suicide. Future studies should explore genetic and environmental factors in suicide or suicidal behavior and examine for gene and environment interaction.

Multifactor-Dimensionality Reduction in the Presence of Missing Observations

  • Chung, Yu-Jin;Lee, Seung-Yeoun;Park, Tae-Sung
    • Proceedings of the Korean Statistical Society Conference
    • /
    • /
    • pp.31-36
    • /
    • 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.

  • PDF

Statistical Analysis of Gene Expression in Innate Immune Responses: Dynamic Interactions between MicroRNA and Signaling Molecules

  • Piras, Vincent;Selvarajoo, Kumar;Fujikawa, Naoki;Choi, Sang-Dun;Tomita, Masaru;Giuliani, Alessandro;Tsuchiya, Masa
    • Genomics & Informatics
    • /
    • v.5 no.3
    • /
    • pp.107-112
    • /
    • 2007
  • MicroRNAs (miRNAs) are known to negatively control protein-coding genes by binding to messenger RNA (mRNA) in the cytoplasm. In innate immunity, the role of miRNA gene silencing is largely unknown. In this study, we performed microarray-based experiments using lipopolysaccharide (LPS)-stimulated macrophages derived from wild-type, MyD88 knockout (KO), TRIF KO, and MyD88/TRIF double KO mice. We employed a statistical approach to determine the importance of the commonality and specificity of miRNA binding sites among groups of temporally co-regulated genes. We demonstrate that both commonality and specificity are irrelevant to define a priori groups of co-down regulated genes. In addition, analyzing the various experimental conditions, we suggest that miRNA regulation may not only be a late-phase process (after transcription) but can also occur even early (1h) after stimulation in knockout conditions. This further indicates the existence of dynamic interactions between miRNA and signaling molecules/transcription factor regulation; this is another proof for the need of shifting from a 'hard-wired' paradigm of gene regulation to a dynamical one in which the gene co-regulation is established on a case-by-case basis.

Resistant spectrum of major genes including Pi-9 carried against Korean rice blast fungus. (oral)

  • Kim, Byung-Ryun;Han, Seong-Sook;Hwan, Roh-Jae;Park, Seong-Ho;Ryu, Jae-Dang
    • Proceedings of the Korean Society of Plant Pathology Conference
    • /
    • /
    • pp.64.2-64
    • /
    • 2003
  • Twenty-seven monogenic rice lines harboring major resistant gene for blast were screened to analyze their resistance spectrum to Korean blast fungus population using 190 isolates collected from 1985 to 2002. Especially, the monogenic line containing Pi-9 gene was screened using 320 isolates. Based on the monogenic lines-blast isolate interactions, the 27 rice lines were classified into 9 groups. The chinese rice cultivar LTH showed susceptible to all the tested isolates. Those lines IRBLz-Fu, ERBL5-M and IRBL9-W harboring Pi-z, Pi-5, and Pi-9, respectively showed broader spectrum of resistance than those rice lines having Pi-19, Pi-7 etc. Interestingly, the Pi-9 gene(IRBL9-W) showed resistance to most isolates collected before 2000, but it showed susceptible reactions to 5% and 20% of blast fungus population in 2001 and 2002, respectively. Population of virulent isolates to Pi-ta, Pi-b, and Pi-7 also were increased in 2002 compared to those before 2000.

  • PDF