An in silico and in vitro human neuronal network model reveals cellular mechanisms beyond NaV1.1 underlying Dravet syndrome

Nina Doorn* (Corresponding Author), Eline J.H. van Hugte, Ummi Ciptasari, Annika Mordelt, Hil G.E. Meijer, Dirk Schubert, Monica Frega, Nael Nadif Kasri, Michel J.A.M. van Putten

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Human induced pluripotent stem cell (hiPSC)-derived neuronal networks on multi-electrode arrays (MEAs) provide a unique phenotyping tool to study neurological disorders. However, it is difficult to infer cellular mechanisms underlying these phenotypes. Computational modeling can utilize the rich dataset generated by MEAs, and advance understanding of disease mechanisms. However, existing models lack biophysical detail, or validation and calibration to relevant experimental data. We developed a biophysical in silico model that accurately simulates healthy neuronal networks on MEAs. To demonstrate the potential of our model, we studied neuronal networks derived from a Dravet syndrome (DS) patient with a missense mutation in SCN1A, encoding sodium channel NaV1.1. Our in silico model revealed that sodium channel dysfunctions were insufficient to replicate the in vitro DS phenotype, and predicted decreased slow afterhyperpolarization and synaptic strengths. We verified these changes in DS patient-derived neurons, demonstrating the utility of our in silico model to predict disease mechanisms.
Original languageEnglish
Pages (from-to)1686-1700
Number of pages15
JournalStem cell reports
Volume18
Issue number8
Early online date6 Jul 2023
DOIs
Publication statusPublished - 8 Aug 2023

Keywords

  • UT-Gold-D

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