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Transcriptomic Profiling of Medial Temporal Lobe Epilepsy.


ABSTRACT: Epilepsy is one of the most prevalent neurological disorders affecting ~1% of the population. Medial temporal lobe epilepsy (MTLE) is the most frequent type of epilepsy observed in adults who do not respond to pharmacological treatment. The reason for intractability in these patients has not been systematically studied. Further, no markers are available that can predict the subset of patients who will not respond to pharmacotherapy. To identify potential biomarkers of epileptogenicity, we compared the mRNA profiles of surgically resected tissue from seizure zones with non-seizure zones from cases of intractable MTLE. We identified 413 genes that exhibited ?2-fold change that were statistically significant across these two groups. Several of these differentially expressed genes have not been previously described in the context of MTLE including claudin 11 (CLDN11) and bone morphogenetic protein receptor, type IB (BMPR1B). In addition, we found significant downregulation of a subset of gamma-aminobutyric acid (GABA) associated genes. We also identified molecules such as BACH2 and ADAMTS15, which are already known to be associated with epilepsy. We validated one upregulated molecule, serine/threonine kinase 31 (STK31) and one downregulated molecule, SMARCA4, by immunohistochemical labeling of tissue sections. These molecules need to be further confirmed in large-scale studies to determine their potential use as diagnostic as well as prognostic markers in intractable MTLE.

SUBMITTER: Venugopal AK 

PROVIDER: S-EPMC3593120 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

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Epilepsy is one of the most prevalent neurological disorders affecting ~1% of the population. Medial temporal lobe epilepsy (MTLE) is the most frequent type of epilepsy observed in adults who do not respond to pharmacological treatment. The reason for intractability in these patients has not been systematically studied. Further, no markers are available that can predict the subset of patients who will not respond to pharmacotherapy. To identify potential biomarkers of epileptogenicity, we compar  ...[more]

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