Title

The effects of seizures on the brain: transcriptional profiling using a DNA microarray database.

Peer Reviewed

1

Document Type

Article

Publication Date

2008

Keywords

Seizures, Mice, Epilepsy, Microarray Analysis, Gene Expression

Abstract

Background: Epilepsy is one of the most common neurological disorders, affecting people of all ages. In recent years, important advances have been made in the study of mechanisms underlying the development of epilepsy using large-scale gene profiling. Changes in the expression of genes involved in neurogenesis, astrogliosis, and axonal and/or dendritic plasticity, and the loss of selective neuronal populations, are some of the significant findings made in previous microarray studies.

Aim: To categorise the biological function, cellular compartment localisation and molecular function of genes altered by seizures.

Methods: A mouse brain gene expression database containing the results of the effects of seizures on around 35,000 genes was investigated.

Results: Genes whose expression was altered at least two-fold as compared to controls, once corrected for multiple comparisons, were included in the analysis (929 genes in total). Gene ontology analysis revealed that cellular activity, immune system, biological adhesion and localisation were the most highly represented processes in the biological function category. Within the cellular component category, genes associated with intracellular organelles and the synapse were most abundant. Finally, within the molecular function category, genes involved in binding and transporter activities (particularly glutamatergic ion channels) were most highly represented.

Conclusion: This analysis provides a comprehensive ontology profile of gene expression changes in response to seizure activity in the brain, and may yield new insights into molecular mechanisms underlying the development of epilepsy.

Disciplines

Physics | Physiology

Citation

Kazmi F, Jimenez-Mateos EN, Henshall DC. The effects of seizures on the brain: transcriptional profiling using a DNA microarray database. RCSI Student Medical Journal 2008;2(1):16-21.

Creative Commons License

Creative Commons License
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