| Literature DB >> 35205434 |
Lisa Geertjens1,2, Torben W van Voorst3, Arianne Bouman4, Maaike A van Boven3, Tjitske Kleefstra4, Matthijs Verhage3,5, Klaus Linkenkaer-Hansen6, Nael Nadif Kasri4, L Niels Cornelisse3,5, Hilgo Bruining1,2,7.
Abstract
Pharmacological options for neurodevelopmental disorders are limited to symptom suppressing agents that do not target underlying pathophysiological mechanisms. Studies on specific genetic disorders causing neurodevelopmental disorders have elucidated pathophysiological mechanisms to develop more rational treatments. Here, we present our concerted multi-level strategy 'BRAINMODEL', focusing on excitation/inhibition ratio homeostasis across different levels of neuroscientific interrogation. The aim is to develop personalized treatment strategies by linking iPSC-based models and novel EEG measurements to patient report outcome measures in individual patients. We focus our strategy on chromatin- and SNAREopathies as examples of severe genetic neurodevelopmental disorders with an unmet need for rational interventions.Entities:
Keywords: EEG; SNAREopathies; chromatinopathies; iPSC-based models; neurodevelopmental disorders
Mesh:
Year: 2022 PMID: 35205434 PMCID: PMC8872324 DOI: 10.3390/genes13020390
Source DB: PubMed Journal: Genes (Basel) ISSN: 2073-4425 Impact factor: 4.096
Figure 1BRAINMODEL’s multi-level strategy.
Figure 2Transcription regulation is controlled by histone modifications. Schematic representation of the deposition of histone methylation, performed by histone methyltransferases and histone demethylases on histone 3 (H3), which have been linked to neurodevelopmental disorders.
Figure 3Schematic Representation of the eight SNAREopathy genes with their orientation relative to the synaptic vesicle and the plasma membrane and their interaction.
Figure 4E/I estimation—from model to human EEG measurements: (A) The critical oscillations model simulates excitatory (red) and inhibitory (blue) neurons situated in a network. The E/I ratio can be regulated by changing the percentages of excitatory and inhibitory neurons that a neuron connects to within a local range (dashed lines). (B) Increasing excitatory connectivity in model networks (red bars, top row) leads to increasing amplitude of oscillations (bottom row). (C) The amplitude of oscillations (purple line) increases with increasing excitation, whereas the temporal complexity as quantified by the detrended fluctuation analysis (DFA, black line) peaks when excitation and inhibition is balanced. This relationship implies that a windowed analysis of oscillations reveals either positive, zero, or negative correlations (top inserts). (D) Hence, we defined a biomarker of E/I ratios as 1 minus the correlation, r, between windowed power and DFA (E/I = 1 – r), and showed that the structural E/I is well estimated by the E/I biomarker (fE/I) in simulated oscillations in networks with different structural E/I ratios. (E) Thus measuring EEG and (F) performing a joint analysis of the power and temporal structure of oscillations allows estimating individual differences in cortical E/I ratios or how these are pharmacologically modulated (Adjusted summary Figure of Bruining et al., 2020) [12].