An integrative in silico system for predicting dysregulated genes in the human epileptic focus: Application to SLC transporters.

OBJECTIVE: Many different gene families are currently being investigated for their potential role in epilepsy and in the response to antiepileptic drugs. A common research challenge is identifying the members of a gene family that are most significantly dysregulated within the human epileptic focus, before taking them forward for resource-intensive functional studies. Published data about transcriptomic changes within the human epileptic focus remains incomplete. A need exists for an accurate in silico system for the prediction of dysregulated genes within the epileptic focus. We present such a bioinformatic system. We demonstrate the validity of our approach by applying it to the solute carrier (SLC) gene family. There are >400 known SLCs. SLCs have never been systematically studied in epilepsy. METHODS: Using our in silico system, we predicted the SLCs likely to be dysregulated in the epileptic focus. We validated our in silico predictions by identifying ex vivo the SLCs dysregulated in epileptic foci, and determining the overlap between our in silico and ex vivo results. For the ex vivo analysis, we used a custom oligonucleotide microarray containing exon probes for all known SLCs to analyze 24 hippocampal samples obtained from surgery for pharmacoresistant mesial temporal lobe epilepsy and 24 hippocampal samples from normal postmortem controls. RESULTS: There was a highly significant (p < 9.99 × 10(-7) ) overlap between the genes identified by our in silico and ex vivo strategies. The SLCs identified were either metal ion exchangers or neurotransmitter transporters, which are likely to play a part in epilepsy by influencing neuronal excitability. SIGNIFICANCE: The identified SLCs are most likely to mediate pharmacoresistance in epilepsy by enhancing the intrinsic severity of epilepsy, but further functional work will be needed to fully evaluate their role. Our successful in silico strategy can be adapted in order to prioritize genes relevant to epilepsy from other gene families.