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Gene-to-Gene Interaction between Sodium Channel-Related Genes in Determining the Risk of Antiepileptic Drug Resistance

The pathogenesis of antiepileptic drug (AED) resistance is multifactorial. However, most candidate gene association studies typically assess the effects of candidate genes independently of each other, which is partly because of the limitations of the parametric-statistical methods for detecting the...

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Autores principales: Jang, Sin-Young, Kim, Myeong-Kyu, Lee, Kee-Ra, Park, Man-Seok, Kim, Byeong-Chae, Cho, Ki-Hyun, Lee, Min-Cheol, Kim, Yo-Sik
Formato: Texto
Lenguaje:English
Publicado: The Korean Academy of Medical Sciences 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2650995/
https://www.ncbi.nlm.nih.gov/pubmed/19270815
http://dx.doi.org/10.3346/jkms.2009.24.1.62
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author Jang, Sin-Young
Kim, Myeong-Kyu
Lee, Kee-Ra
Park, Man-Seok
Kim, Byeong-Chae
Cho, Ki-Hyun
Lee, Min-Cheol
Kim, Yo-Sik
author_facet Jang, Sin-Young
Kim, Myeong-Kyu
Lee, Kee-Ra
Park, Man-Seok
Kim, Byeong-Chae
Cho, Ki-Hyun
Lee, Min-Cheol
Kim, Yo-Sik
author_sort Jang, Sin-Young
collection PubMed
description The pathogenesis of antiepileptic drug (AED) resistance is multifactorial. However, most candidate gene association studies typically assess the effects of candidate genes independently of each other, which is partly because of the limitations of the parametric-statistical methods for detecting the gene-to-gene interactions. A total of 200 patients with drug-resistant epilepsy and 200 patients with drug-responsive epilepsy were genotyped for 3 representative the single nucleotide polymorphisms (SNPs) of the voltage-gated sodium channel genes (SCN1A, SCN1B, and SCN2A) by polymerase chain reaction and direct sequencing analysis. Besides the typical parametric statistical method, a new statistical method (multifactor dimensionality reduction [MDR]) was used to determine whether gene-to-gene interactions increase the risk of AED resistance. None of the individual genotypes or alleles tested in the present study showed a significant association with AED resistance, regardless of their theoretical functional value. With the MDR method, of three possible 2-locus genotype combinations, the combination of SCN2A-PM with SCN1B-PM was the best model for predicting susceptibility to AED resistance, with a p value of 0.0547. MDR, as an analysis paradigm for investigating multi-locus effects in complex disorders, may be a useful statistical method for determining the role of gene-to-gene interactions in the pathogenesis of AED resistance.
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spelling pubmed-26509952009-03-06 Gene-to-Gene Interaction between Sodium Channel-Related Genes in Determining the Risk of Antiepileptic Drug Resistance Jang, Sin-Young Kim, Myeong-Kyu Lee, Kee-Ra Park, Man-Seok Kim, Byeong-Chae Cho, Ki-Hyun Lee, Min-Cheol Kim, Yo-Sik J Korean Med Sci Original Article The pathogenesis of antiepileptic drug (AED) resistance is multifactorial. However, most candidate gene association studies typically assess the effects of candidate genes independently of each other, which is partly because of the limitations of the parametric-statistical methods for detecting the gene-to-gene interactions. A total of 200 patients with drug-resistant epilepsy and 200 patients with drug-responsive epilepsy were genotyped for 3 representative the single nucleotide polymorphisms (SNPs) of the voltage-gated sodium channel genes (SCN1A, SCN1B, and SCN2A) by polymerase chain reaction and direct sequencing analysis. Besides the typical parametric statistical method, a new statistical method (multifactor dimensionality reduction [MDR]) was used to determine whether gene-to-gene interactions increase the risk of AED resistance. None of the individual genotypes or alleles tested in the present study showed a significant association with AED resistance, regardless of their theoretical functional value. With the MDR method, of three possible 2-locus genotype combinations, the combination of SCN2A-PM with SCN1B-PM was the best model for predicting susceptibility to AED resistance, with a p value of 0.0547. MDR, as an analysis paradigm for investigating multi-locus effects in complex disorders, may be a useful statistical method for determining the role of gene-to-gene interactions in the pathogenesis of AED resistance. The Korean Academy of Medical Sciences 2009-02 2009-02-28 /pmc/articles/PMC2650995/ /pubmed/19270815 http://dx.doi.org/10.3346/jkms.2009.24.1.62 Text en Copyright © 2009 The Korean Academy of Medical Sciences http://creativecommons.org/licenses/by-nc/3.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Jang, Sin-Young
Kim, Myeong-Kyu
Lee, Kee-Ra
Park, Man-Seok
Kim, Byeong-Chae
Cho, Ki-Hyun
Lee, Min-Cheol
Kim, Yo-Sik
Gene-to-Gene Interaction between Sodium Channel-Related Genes in Determining the Risk of Antiepileptic Drug Resistance
title Gene-to-Gene Interaction between Sodium Channel-Related Genes in Determining the Risk of Antiepileptic Drug Resistance
title_full Gene-to-Gene Interaction between Sodium Channel-Related Genes in Determining the Risk of Antiepileptic Drug Resistance
title_fullStr Gene-to-Gene Interaction between Sodium Channel-Related Genes in Determining the Risk of Antiepileptic Drug Resistance
title_full_unstemmed Gene-to-Gene Interaction between Sodium Channel-Related Genes in Determining the Risk of Antiepileptic Drug Resistance
title_short Gene-to-Gene Interaction between Sodium Channel-Related Genes in Determining the Risk of Antiepileptic Drug Resistance
title_sort gene-to-gene interaction between sodium channel-related genes in determining the risk of antiepileptic drug resistance
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2650995/
https://www.ncbi.nlm.nih.gov/pubmed/19270815
http://dx.doi.org/10.3346/jkms.2009.24.1.62
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