Literature DB >> 18712274

Genetic interactions model among Eotaxin gene polymorphisms in asthma.

June-Hyuk Lee1, Jason H Moore2, Sung-Woo Park1, An-Soo Jang1, Soo-Taek Uh1, Yong Hoon Kim1, Choon-Sik Park3, Byung Lae Park4, Hyoung Doo Shin4.   

Abstract

Eotaxin family (Eotaxin 1,2 and 3) recruits and activates CCR3-bearing cells such as eosinophil, mast cells, and Th2 lymphocytes that play a major role in allergic disorders. We examined the polygenetic effects of the Eotaxin gene family in a Korean population. Gene-gene interactions were tested using a multistep approach with multifactor dimensionality reduction (MDR) method between asthmatics and normal controls. The overall best MDR model of the main effect single nucleotide polymorphisms (SNPs) included EOT2 + 1272A > G and EOT3 + 77C > T (model 1) [testing accuracy 0.597, cross-validation consistency (CVC) 10/10, P < 0.001]. The overall best MDR model of the SNPs with no main effects included EOT2 + 304C > A, EOT3 + 716A > G, and EOT3 + 1579G > A (model 2) (testing accuracy 0.616, CVC 10/10, P < 0.001). Model 3 was obtained by including the MDR variables for models 1 and 2. This new composite model predicted asthma with better accuracy than either model 1 or model 2 (testing accuracy 0.643, CVC 10/10, P < 0.001). The detection of statistical interaction models is one evidence of gene-gene interactions among Eotaxin genes, and this interaction is thought to influence the development of asthma. Although the models are limited to determining statistical interactions within a population, they may be useful for identifying groups at high risk of developing asthma.

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Year:  2008        PMID: 18712274     DOI: 10.1007/s10038-008-0314-y

Source DB:  PubMed          Journal:  J Hum Genet        ISSN: 1434-5161            Impact factor:   3.172


  32 in total

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3.  A flexible computational framework for detecting, characterizing, and interpreting statistical patterns of epistasis in genetic studies of human disease susceptibility.

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4.  Odds ratio based multifactor-dimensionality reduction method for detecting gene-gene interactions.

Authors:  Yujin Chung; Seung Yeoun Lee; Robert C Elston; Taesung Park
Journal:  Bioinformatics       Date:  2006-11-08       Impact factor: 6.937

Review 5.  Non-replication and inconsistency in the genome-wide association setting.

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9.  Oncostatin M regulates eotaxin expression in fibroblasts and eosinophilic inflammation in C57BL/6 mice.

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10.  Association of Eotaxin gene family with asthma and serum total IgE.

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Journal:  Hum Mol Genet       Date:  2003-06-01       Impact factor: 6.150

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  9 in total

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Journal:  Allergy Asthma Immunol Res       Date:  2010-06-11       Impact factor: 5.764

3.  Association of three-gene interaction among MTHFR, ALOX5AP and NOTCH3 with thrombotic stroke: a multicenter case-control study.

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5.  Expression analysis of asthma candidate genes during human and murine lung development.

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6.  Gene set based association analyses for the WSSV resistance of Pacific white shrimp Litopenaeus vannamei.

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7.  Genetic polymorphisms and associated susceptibility to asthma.

Authors:  Michael E March; Patrick Ma Sleiman; Hakon Hakonarson
Journal:  Int J Gen Med       Date:  2013-04-17

8.  Clinical Significance of the Dynamic Changes in Serum Eotaxin, Interleukin 13 and Total IgE in Children with Bronchial Asthma.

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9.  Gene - Gene Interactions Among MCP Genes Polymorphisms in Asthma.

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  9 in total

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