ANALYSIS OF FACIAL ASYMMETRY AND DYSMORPHISM IN EPILEPSY

Purpose: There is variable clinical expressivity in each specific form of epilepsy. Genotype-phenotype correlations are very helpful to understand the origin and the mechanisms underlying the spectrum of clinical variability in epilepsy. In the current study, we use novel phenotyping 3D stereophotogrammetry and dense surface models, to evaluate facial asymmetry and dysmorphism in people with focal epilepsies aiming to generate new tools to explore the genetic contribution to these epilepsies. Method: We consecutively recruited 859 people with epilepsy attending the epilepsy clinics at the National Hospital for Neurology and Neurosurgery, London (UK). We used dense surface modeling of the full face and signature analyses of 3-dimensional facial photographs to discriminate between cases and 205 healthy controls and to determine agreement with epilepsy categorization. Results: Cases with focal cryptogenic and idiopathic generalised epilepsy showed more asymmetry compared to controls (p = 0.018 and p = 0.014, two-sample t-test, respectively). There was no significant difference between focal symptomatic cases and controls. The opposite pattern was observed when considering the signature analysis: no difference emerged when comparing focal cryptogenic or idiopathic generalised epilepsy cases with controls, whilst cases with focal symptomatic epilepsy associated with unilateral lesions showed higher signature weights than controls (p < 0.001, two-sample t-test). Conclusion: Facial structure development is driven by complex molecular interactions between surface ectoderm and underlying forebrain and neural crest cells. The increased level of facial asymmetry in cases with focal cryptogenic and idiopathic generalised epilepsy might be explained by a potential genetic cause, with underlying genetic pathways shared between face and brain development. 3D stereophotogrammetry and dense surface models could represent a powerful novel phenotyping process that will permit greater understanding of genetic data, improved discrimination between pathogenic and non-pathogenic variation, and further insight into genetics of facial and neural development.