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bioRxiv · 10.1101/2024.05.15.594433

Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity

Guet-McCreight, A.·Mazza, F.·Prevot, T. D.·Sibille, E.·Hay, E.
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Abstract

Treatment for major depressive disorder (depression) often has partial efficacy and a large portion of patients are treatment resistant. Recent studies implicate reduced somatostatin (SST) interneuron inhibition in depression, and new pharmacology boosting this inhibition via positive allosteric modulators of 5-GABAA receptors (5-PAM) offers a promising effective treatment. However, testing the effect of 5-PAM on human brain activity is limited, meriting the use of detailed simulations. We utilized our previous detailed computational models of human depression microcircuits with reduced SST interneuron inhibition and 5-PAM effects, to simulate EEG of virtual subjects across depression severity and 5-PAM doses. We developed machine learning models that predicted optimal dose from EEG with high accuracy and recovered microcircuit activity and EEG. This study provides dose prediction models for 5-PAM administration based on EEG biomarkers of depression severity. Given limitations in doing the above in the living human brain, the results and tools we developed will facilitate translation of 5-PAM treatment to clinical use.

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Guet-McCreight, A., Mazza, F., Prevot, T. D., Sibille, E., Hay, E.. 2024-05-16. Therapeutic dose prediction of α5-GABA receptor modulation from simulated EEG of depression severity. https://doi.org/10.1101/2024.05.15.594433

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