Allergy Asthma Immunol Res.  2014 Jul;6(4):333-340. 10.4168/aair.2014.6.4.333.

Gene - Gene Interactions Among MCP Genes Polymorphisms in Asthma

Affiliations
  • 1Respiratory and Allergy Medicine, Interanl Medicine, Soonchunhyang University Bucheon Hospital, Bucheon, Korea. mdcspark@unitel.co.kr

Abstract

PURPOSE
Monocyte chemoattractant proteins (MCPs) are important cytokines that involved in cellular activation and releasing of inflammatoy mediators by basophils and eosinophils in allergic disease. Some MCP gene variants implicate in asthma and monoclonal antibody for MCP-3 blocks allergic inflammations in the patients with asthma. Detection of interactions between gene and environment or between genes for complex disease such as asthma is important. We searched for an evidence of genetic effect of single nucleotide polymorphisms (SNPs) of MCP genes as well as gene - gene interactions involved in asthma.
METHODS
Four hundreds asthmatics and four hundreds normal controls were enrolled. Asthma was defined as a positive bronchodilator response or positive methacholine provocation test with compatible clinical symptoms. Seven MCP gene SNPs (2 SNPs in MCP-1, 1 in MCP-2, and 4 in MCP-3) were included. Association analyses between SNP and asthma, and the tests for gene - gene interaction were performed.
RESULTS
Strong linkage disequilibria were found among 7 MCP gene polymorphisms. There was no SNP that showed a significant association with asthma among 7 SNPs of 3 MCP genes. No haplotype was associated with asthma, either. The combination of MCP1-2518G>A, MCP2+46A>C, and MCP3+563C>T was the best predictive model for asthma as compared to the control in tests for gene - gene interaction. The MCP1-2518G>A and MCP2+46A>C was the second best predictive combination and this had the highest synergistic interaction effect on the subject's status than any other combination of polymorphisms. Complete linkages were not associated with the gene - gene interactions models.
CONCLUSIONS
MCP gene polymorphisms probably interact with each other; thus, these findings may help in developing a possible genetic marker to predict asthma.

Keyword

Asthma; epistasis; polymorphism; monocyte chemoattractant proteins

MeSH Terms

Asthma*
Basophils
Cytokines
Eosinophils
Genetic Markers
Haplotypes
Humans
Inflammation
Methacholine Chloride
Monocyte Chemoattractant Proteins
Polymorphism, Single Nucleotide
Cytokines
Genetic Markers
Methacholine Chloride
Monocyte Chemoattractant Proteins

Figure

  • Fig. 1 The best model composed of MCP1-2518G>A, MCP2+46A>C and MCP3+563C>T; In each cell, the left bar (orange) represents an asthma, and right bar (blue) a normal control. High-risk genotype combinations are shaded dark grey, while low-risk are shaded light grey; OR of each genotype combination was designated in each cell; P value was validated based on 1,000 permutation test. CVC, cross-validation consistency; OR, odds ratio.

  • Fig. 2 The 2-loci model composed of MCP1-2518G>A and MCP2+46A>C; In each cell, the left bar (orange) represents an asthma, and right bar (blue) a normal control; High-risk genotype combinations are shaded dark grey, while low-risk are shaded light grey; OR of each genotype combination was designated in each cell; P value was validated based on 1,000 permutation test. CVC, cross-validation consistency; OR, odds ratio.

  • Fig. 3 Interaction graph among seven SNPs of MCP-1, -2 and -3 genes; Boxes indicate the main effect of each locus on subject's status, and connections indicate the interactions effect between two loci on subject's status; Main effect means individual attribute to asthma-control status; Interaction effect means pairwise combination of attributes to asthma-control status; Solid lines indicate synergistic effect between two SNPs to asthma-control status. Dotted lines indicate independence effect of two SNPs to asthma-control status.


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