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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...
Autores principales: | , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
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The Korean Academy of Medical Sciences
2009
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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. |
format | Text |
id | pubmed-2650995 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | The Korean Academy of Medical Sciences |
record_format | MEDLINE/PubMed |
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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