Taxonomia. Malformations of cortical development (MCD) are a group of disorders, with many branches, generally manifesting with developmental delays and seizures. However, the genetic and clinic heterogeneity of this group has challenged us to properly classify the disorders and predict their neurological outcomes. Here, the authors compared two animal models of MCD with close aetiologies. The two models presented common but also specific neuronal features, from an early developmental stage. This finding calls for a refined, cell-based, classification method. (IB)
The scientific abstract: Grey matter heterotopia (GMH) are neurodevelopmental disorders associated with abnormal cortical function and epilepsy. Subcortical band heterotopia (SBH) and periventricular nodular heterotopia (PVNH) are two well-recognized GMH subtypes in which neurons are misplaced, either forming nodules lining the ventricles in PVNH, or forming bands in the white matter in SBH. Although both PVNH and SBH are commonly associated with epilepsy, it is unclear whether these two GMH subtypes differ in terms of pathological consequences or, on the contrary, share common altered mechanisms. Here, we studied two robust preclinical models of SBH and PVNH, and performed a systematic comparative assessment of the physiological and morphological diversity of heterotopia neurons, as well as the dynamics of epileptiform activity and input connectivity. We uncovered a complex set of altered properties, including both common and distinct physiological and morphological features across heterotopia subtypes, and associated with specific dynamics of epileptiform activity. Taken together, these results suggest that pro-epileptic circuits in GMH are, at least in part, composed of neurons with distinct, subtype-specific, physiological and morphological properties depending on the heterotopia subtype. Our work supports the notion that GMH represent a complex set of disorders, associating both shared and diverging pathological consequences, and contributing to forming epileptogenic networks with specific properties. A deeper understanding of these properties may help to refine current GMH classification schemes by identifying morpho-electric signatures of GMH subtypes, to potentially inform new treatment strategies.
Paru dans Brain, 2023