In-silico testing of new pharmacology for restoring inhibition and human cortical function in depression

Guet-McCreight, Alexandre; Moradi-Chameh, Homeira; Mazza, Frank; Prevot, Thomas D.; Valiante, Taufik A.; Sibille, Etienne; Hay, Etay

doi:10.1101/2023.02.22.529541

Cited by 3 publications

(15 citation statements)

References 92 publications

(147 reference statements)

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“…the possible altered levels of SST interneuron inhibition indicated by our study and recent gene-expression studies [3,23,89]. Moreover, the computational models that we developed can provide a powerful tool to identify potential EEG biomarkers of novel therapeutic compounds and treatments for schizophrenia via in-silico testing to improve monitoring treatment efficacy and dose prediction [90]. The simulated EEG that our models provide can also be related to that of recorded EEG, by scaling to account for the difference between the number of neurons in our models compared to the amount of neurons that generate the recorded EEG at a given electrode, which would be about a factor of 10,000 to 100,000 [91,92].…”

Section: Discussionmentioning

confidence: 87%

Linking reduced prefrontal microcircuit inhibition in schizophrenia to EEG biomarkers in silico

Rosanally,

Mazza,

Yao

et al. 2023

Preprint

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Reduced cortical inhibition by parvalbumin-expressing (PV) interneurons has been associated with impaired cortical processing in the prefrontal cortex (PFC) and altered EEG signals such as oddball mismatch negativity (MMN) in schizophrenia. However, establishing the link between reduced PV interneuron inhibition and reduced MMN experimentally in humans is currently not possible. To overcome these challenges, we used detailed computational models of human PFC microcircuits, and modeled schizophrenia microcircuits by integrating gene-expression data from schizophrenia patients indicating reduced PV interneuron inhibition output and NMDA input. We simulated spiking activity and EEG in microcircuits with different levels of reduced PV interneuron mechanisms and showed that a double effect of the reduction indicated by gene-expression led to a significantly reduced MMN amplitude as seen in Schizophrenia patients, whereas a single effect produced a smaller reduction in MMN that matched the magnitude seen in patients at high-risk of schizophrenia. In addition, we showed that simulated resting EEG of schizophrenia microcircuits exhibited a right shift from alpha to beta frequencies. Our study thus links the level of reduced PV interneuron inhibition to distinct EEG biomarkers that can serve to better stratify different severities of schizophrenia and improve the early detection using non-invasive brain signals.

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Section: Discussionmentioning

confidence: 87%

Linking reduced prefrontal microcircuit inhibition in schizophrenia to EEG biomarkers in silico

Rosanally,

Mazza,

Yao

et al. 2023

Preprint

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“…We constrained the models with the effect of 3 μM of the α5-PAM compound, GL-II-73 (i.e., the reference 100% dose) as previously 11 , which is in the range for selectively targeting α5 subunit receptors without substantially activating other subunits 9,10 . In rodents, this dose was also within the range that yielded anxiolytic, antidepressant, and pro-cognitive effects without sedation 10 .…”

Section: Discussionmentioning

confidence: 99%

“…Detailed biophysical models can capture key properties of EEG 29–31 , and thus provide powerful tools for linking cellular and circuit mechanisms to brain activity and clinically-relevant signals. We previously showed in silico that α5-PAM would recover cortical activity, function and EEG spectral profile in detailed models of human depression microcircuits with reduced SST interneuron inhibition, and we highlighted EEG biomarkers that can monitor α5-PAM efficacy 11 . However, the study utilized an average reduced SST interneuron inhibition as a model of depression microcircuits 28 and EEG effects 30 , and did not consider varying depression severity level.…”

Section: Introductionmentioning

confidence: 88%

“…We simulated a reference dose of α5-PAM application corresponding to experimentally-measured effects of a 3 μM dose of GL-II-73 on human Pyr neurons, modelled as a 60% boost of synaptic and tonic inhibition to Pyr neuron apical dendrites 11 . We simulated the application of different doses of α5-PAM relative to this reference dose (25% to 150%, where 100% is the reference dose).…”

Section: Methodsmentioning

confidence: 99%

“…Along with the baseline activity, we simulated resting-state EEG from the microcircuit models in LFPy 2.0.2 (Python 3.7.6) using a four-sphere volume conductor model (representing grey matter, cerebrospinal fluid, skull, and scalp with radii of 79 mm, 80 mm, 85 mm, and 90 mm, respectively) that assumed homogeneous, isotropic, and linear (frequency-independent) conductivity 11,30 . The conductivity for each sphere was 0.047 S m −1 , 1.71 S m −1 , 0.02 S m −1 , and 0.41 S m −1 , respectively 11,30,62 . We computed EEG power spectral density (PSD) using Welch’s method 63 from the Scipy python module with 2s time windows.…”

Section: Methodsmentioning

confidence: 99%

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

Guet-McCreight,

Mazza,

Prevot

et al. 2024

Preprint

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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 α5-GABAA receptors (α5-PAM) offers a promising effective treatment. However, testing the effect of α5-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 α5-PAM effects, to simulate EEG of virtual subjects across depression severity and α5-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 α5-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 α5-PAM treatment to clinical use.

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Spine loss in depression impairs dendritic signal integration in human cortical microcircuit models

Yao,

Mazza,

Prevot

et al. 2024

Preprint

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Major depressive disorder (depression) is associated with altered dendritic structure and function in excitatory cortical pyramidal neurons, due to decreased inhibition from somatostatin interneurons and loss of spines and associated synapses, as indicated in postmortem human studies. Dendrites play an important role in signal processing as they receive the majority of synaptic inputs and exhibit nonlinear properties including backpropagating action potentials and dendritic Na+spikes that enhance the computational power of the neuron. However, it is currently unclear how depression-related dendritic changes impact the integration of signals. Here, we expanded our previous data-driven detailed computational models of human cortical microcircuits in health and depression to include active dendritic properties that enable backpropagating action potentials as measured in human neurons, and spine loss in depression in terms of synapse loss and altered intrinsic property. We show that spine loss dampens signal response and thus results in a larger impairment of cortical function such as signal detection than due to reduced somatostatin interneuron inhibition alone. We further show that the altered intrinsic properties due to spine loss abolish nonlinear dendritic integration of signals and impair recurrent microcircuit activity. Our study thus mechanistically links cellular changes in depression to impaired dendritic processing in human cortical microcircuits.

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In-silico testing of new pharmacology for restoring inhibition and human cortical function in depression

Cited by 3 publications

References 92 publications

Linking reduced prefrontal microcircuit inhibition in schizophrenia to EEG biomarkers in silico

Linking reduced prefrontal microcircuit inhibition in schizophrenia to EEG biomarkers in silico

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

Spine loss in depression impairs dendritic signal integration in human cortical microcircuit models

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