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Pavlidis, E.

Publications and source records attributed to Pavlidis, E..

2 recordsLinked to original sources

Comprehensive classification of HCN1 variants linked to neurodevelopmental disorders with and without epilepsy

Hyperpolarization-activated cyclic nucleotide-gated 1 channels (HCN1) mediate the Ih cationic current and play a central role in regulating neuronal excitability and synaptic integration. HCN1 is predominantly expressed in the neocortex and hippocampus. Pathogenic variants in HCN1 have been increasingly identified in individuals presenting with a broad spectrum of epileptic disorders, ranging from severe developmental and epileptic encephalopathy (DEE) to milder epilepsies. Here, we used patch-clamp electrophysiology in combination with confocal imaging in HEK293 cells to functionally characterize 43 HCN1 variants found in patients presenting with neurodevelopmental disorders, with or without epilepsy. Based on their biophysical properties, we defined four functional classes: (I) low or no current, (II) hyperpolarizing (i.e. left) shift in voltage dependence, (III) depolarizing (i.e. right) shift in voltage dependence, and (IV) generation of an instantaneous current. Integration of this functional classification with detailed clinical data from a cohort of 49 patients revealed a striking genotype-phenotype correlation. Loss-of-function variants were strongly enriched among individuals without epilepsy or with milder generalized phenotypes, whereas gain-of-function and mixed variants were predominantly associated with epilepsy, including all cases of DEE. Notably, non-epileptic cases clustered within a subgroup of loss-of-function variants affecting the selectivity filter. We further show that allosteric modulators, including the peptides NB6 and TRIP8bnano and the small molecule J&J12e, normalize the functional properties of mutant HCN1 channels in three classes. These findings establish a clinically relevant framework for interpreting HCN1 gain- and loss-of-function variants suggesting that the direction of channel dysfunction is a major determinant of epilepsy risk and severity.

pathology↗

Multiple-timescale dynamics, mixed mode oscillations and mixed affective states in a model of Bipolar Disorder

Mixed affective states in bipolar disorder (BD) is a common psychiatric condition that occurs when symptoms of the two opposite poles coexist during an episode of mania or depression. A four-dimensional model by A. Goldbeter [27, 28] rests upon the notion that manic and depressive symptoms are produced by two competing and auto-inhibited neural networks. Some of the rich dynamics that this model can produce, include complex rhythms formed by both small-amplitude (subthreshold) and large-amplitude (suprathreshold) oscillations and could correspond to mixed bipolar states. These rhythms are commonly referred to as mixed mode oscillations (MMOs) and they have already been studied in many different contexts [7, 50]. In order to accurately explain these dynamics one has to apply a mathematical apparatus that makes full use of the timescale separation between variables. Here we apply the framework of multiple-timescale dynamics to the model of BD in order to understand the mathematical mechanisms underpinning the observed dynamics of changing mood. We show that the observed complex oscillations can be understood as MMOs due to a so-called folded-node singularity. Moreover, we explore the bifurcation structure of the system and we provide possible biological interpretations of our findings. Finally, we show the robustness of the MMOs regime to stochastic noise and we propose a minimal three-dimensional model which, with the addition of noise, exhibits similar yet purely noise-driven dynamics. The broader significance of this work is to introduce mathematical tools that could be used to analyse and potentially control future, more biologically grounded models of BD.

neuroscience↗