EXPLORING CANDIDATE GENES FOR EPILEPSY
BY COMPUTATIONAL DISEASE-GENE
IDENTIFICATION STRATEGY
Sha Y, Liu Q, Wang Y, Dong C, Song L
*Corresponding Author: Ying Sha, Department of Neurology, First Hospital of Jilin University,
Jilin Province, People’s Republic of China; Tel.: +86-1387-878-9232; Fax: +86-1387-778-7078;
E-mail: shaying2010@ 126.com
page: 35
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Abstract
Epilepsy is a complex disease with a strong
genetic component. So far, studies have focused on
experimental validation or genome-wide linkage
scans for epilepsy susceptibility genes in multiple
populations. We have used four bioinformatic
tools (SNPs3D, PROSPECTR and SUSPECTS,
GenWanderer, PosMed) to analyze 16 susceptibility
loci selected from a literature search. Pathways
and regulatory network analyses were performed
using the Ingenuity Pathways Analysis (IPA)
software. We identified a subset of 48 candidate
epilepsy susceptibility genes. Five significant
canonical pathways, in four typical networks, were
identified: GABA receptor signaling, interleukin-6
(IL-6) signaling, G-protein coupled receptor
signaling, type 2 diabetes mellitus signaling and
airway inflammation in asthma. We concluded that
online analytical tools provide a powerful way to
reveal candidate genes which can greatly reduce
experimental time. Our study contributes to further
experimental tests for epilepsy susceptibility genes.
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