Background. Although importance of genetic factors in epilepsy is undisputable, genetic structure of epilepsies is largely unknown. Knowledge of etiological structure of monogenic diseases associated with epilepsy or seizures may aid in the choice of proper genetic testing methods and algorithms. Besides, it may enable further studies into etiopathophysiological studies of ictogenesis and epileptogenesis.
Materials and methods. By implementing bioinformatic databases OMIM, Pubmed, MINT, BIOGRID, Gene Ontology, Human Phenotype Ontology, we have analysed the etiological structure of monogenic diseases associated with epilepsy or seizures, investigated clinical characteristics of these disorders and performed gene functional annotation analysis.
Results. The most extensive to our knowledge database (EpiGene) of 880 monogenic dis eases as so ci ated with epilepsy or seizures have been comprised and a tool for search according to clinical symptoms has been created; a list of most frequent functional gene categories has been composed; clinical symptoms, most fre quently as so ci ated with these dis orders, have been analysed.
Conclusions. Monogenic diseases associated with epilepsy or seizures are characterised by vast genetic and phenotypic heterogeneity. The most extensive group of monogenic epilepsies comprise inborn errors of metabolism. The most extensive to our knowledge database of monogenic diseases associated with epilepsy or seizures may be beneficial both in clinical practice (aiding in clinical and etiological diagnostics, choice of diagnostic methods and algorithms) and research (insights into processes leading to ictogenesis/epileptogenesis, search for new treatment targets).
