Epilepsy is a heterogeneous disorder, the symptoms of which are preventable and controllable to some extent. Significant inter- and intra-country differences in incidence and prevalence exist because multiple etiologic factors are implicated. Many past reviews have addressed sole etiologies. We considered a comprehensive view of all etiologies (genetic/structural/metabolic) to be significant for both the developing and the developed world as well as routine clinical/epidemiology practice. We therefore carried out a comprehensive search for peer-reviewed articles (irrespective of year, region and language; chosen based on novelty and importance) for each etiology. This article was felt to be essential since newer etiologic knowledge has emerged in recent years. Many new genetic links for rarer epilepsy forms have emerged. Epilepsy risk in limbic encephalitis, mechanisms of Alzheimer's-related epilepsy and the genetic basis of cortical malformations have been detailed. An etiological approach to epilepsy in combination with the conventional classification of epilepsy syndromes is required to gain knowledge.

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Background: Tuberous sclerosis complex (TSC)-associated neuropsychiatric disorders (TAND) have unique, individual patterns that pose significant challenges for diagnosis, psycho-education, and intervention planning. A recent study suggested that it may be feasible to use TAND Checklist data and data-driven methods to generate natural TAND clusters. However, the study had a small sample size and data from only two countries. Here, we investigated the replicability of identifying natural TAND clusters from a larger and more diverse sample from the TOSCA study. Methods: As part of the TOSCA international TSC registry study, this embedded research project collected TAND Checklist data from individuals with TSC. Correlation coefficients were calculated for TAND variables to generate a correlation matrix. Hierarchical cluster and factor analysis methods were used for data reduction and identification of natural TAND clusters.

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