Alterations in Schizophrenia-Associated Genes Can Lead to Increased Power in Delta Oscillations

Mäki‐Marttunen, Tuomo; Krull, Florian; Bettella, Francesco; Hagen, Espen; Næss, Solveig; Ness, Torbjørn V.; Moberget, Torgeir; Elvsåshagen, Torbjørn; Metzner, Christoph; Devor, Anna; Edwards, Andrew G.; Fyhn, Marianne; Djurovic, Srdjan; Dale, Anders M.; Andreassen, Ole A.; Einevoll, Gaute T.

doi:10.1093/cercor/bhy291

Cited by 31 publications

(72 citation statements)

References 117 publications

(172 reference statements)

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“…Finally, the theta neuron model is a simple and abstract neuron model and does not capture electrophysiological differences between BCs and ChCs found experimentally [30]. Interestingly, genetic variants of risk genes for schizophrenia include a variety of genes coding for ion channels or ion transporters, which have been shown to alter cell excitability [24,26] and network oscillations [25]. Such variants might potentially amplify electrophysiological differences between BCs and ChCs and thereby change their relative roles in the generation of gamma/beta oscillations.…”

Section: Discussionmentioning

confidence: 99%

The Role of Parvalbumin-positive Interneurons in Auditory Steady-State Response Deficits in Schizophrenia

Metzner

Zurowski

Steuber

2019

Preprint

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Despite an increasing body of evidence demonstrating subcellular alterations in parvalbumin-positive (PV + ) interneurons in schizophrenia, their functional consequences remain elusive. Since PV + interneurons are involved in the generation of fast cortical rhythms, these changes have been hypothesized to contribute to well-established alterations of beta and gamma range oscillations in patients suffering from schizophrenia. However, the precise role of these alterations and the role of different subtypes of PV + interneurons is still unclear. Here we used a computational model of auditory steady-state response (ASSR) deficits in schizophrenia. We investigated the differential effects of decelerated synaptic dynamics, caused by subcellular alterations at two subtypes of PV + interneurons: basket cells and chandelier cells. Our simulations suggest that subcellular alterations at basket cell synapses rather than chandelier cell synapses are the main contributor to these deficits Particularly, basket cells might serve as target for innovative therapeutic interventions aiming at reversing the oscillatory deficits.

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Section: Discussionmentioning

confidence: 99%

The Role of Parvalbumin-positive Interneurons in Auditory Steady-State Response Deficits in Schizophrenia

Metzner

Zurowski

Steuber

2019

Preprint

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“…Multiple studies in animals, iPSCs, and humans have noted increased potassium and sodium channel expression and activity in the prefrontal cortex. These changes were associated with abnormal neuronal activity, diminished synaptic plasticity, and impaired white matter integrity, all of which are characteristic of SCZ [17][18][19][20][21][22]. Additionally, antipsychotics can reverse these ion channel alterations, suggesting that this is a key mechanism in SCZ pathology [23][24][25].…”

Section: Discussionmentioning

confidence: 99%

“…These results are encouraging that persistence is a meaningful measure because these pathways have been implicated in SCZ in prior studies. For example, ion homeostasis was the most commonly altered category in our high persistent pathways [17][18][19][20][21][22].…”

Section: Discussionmentioning

confidence: 99%

Persistence: Using Protein Turnover to Expand the Applications of Transcriptomics

Smail

Reigle

McCullumsmith

2020

Preprint

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ABSTRACTOne of the major issues with RNA sequencing is the lack of reproducibility between RNA and protein expression. Transcriptomics offers a holistic view of the molecular landscape of a tissue at an RNA level. However, RNA and protein expression are often at odds when measured in the same sample, raising the question whether or not changes in RNA expression translate to functional differences. This problem creates a need to devise a way to approximate protein abundance from transcriptomics data, in order to create a more complete picture of the functional landscape of a tissue. One additional measure that could be useful here is protein turnover or half-life. Once RNA is transcribed into protein, that protein can either be quickly degraded or remain in the cell for an extended period of time. The longer a protein’s half-life, the more influence it can have on its surroundings. Recently, a study used stable isotope labeling in mammals (SILAM) in combination with mass spectrometry to determine the turnover ratio of ∼2200 protein in mouse synaptosomes. This data offers a valuable opportunity to integrate protein turnover with RNA expression to gain deeper insight into the functional meaning of RNA expression changes. Here, we present the concept of this combination of protein turnover and RNA expression, which we coined as persistence. We then demonstrate the application of persistence using schizophrenia (SCZ) transcriptomics datasets. Calculating persistence for these datasets greatly improved our ability to predict protein expression from RNA expression. Furthermore, this approach successfully identified persistent genes and pathways known to have impactful changes in SCZ. These results suggest that persistence is a valuable metric for improving the functional insight that can be gained from transcriptomics data.

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“…The presented formalism is well suited for modeling EEG/MEG contributions from various potential neural origins, including different cell types, different ion channels and different synaptic pathways. For example, to study the effect of calcium spikes [Suzuki and Larkum, 2017], I h currents [Ness et al, 2016[Ness et al, , 2018Kalmbach et al, 2018], or gene expression on EEG signals [Mäki-Marttunen et al, 2019b], one only needs to know how the z-component of the resulting population current dipole is affected. This decoupling of the current dipole moment and head model allows for easier investigation and improved understanding of the origin of the EEG/MEG signal.…”

Section: Discussionmentioning

confidence: 99%

Biophysical modeling of the neural origin of EEG and MEG signals

Næss

Halnes

Hagen

et al. 2020

Preprint

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AbstractElectroencephalography (EEG) and magnetoencephalography (MEG) are among the most important techniques for non-invasively studying cognition and disease in the human brain. These signals are known to originate from cortical neural activity, typically described in terms of current dipoles. While the link between cortical current dipoles and EEG/MEG signals is relatively well understood, surprisingly little is known about the link between different kinds of neural activity and the current dipoles themselves. Detailed biophysical modeling has played an important role in exploring the neural origin of intracranial electric signals, like extracellular spikes and local field potentials. However, this approach has not yet been taken full advantage of in the context of exploring the neural origin of the cortical current dipoles that are causing EEG/MEG signals.Here, we present a method for reducing arbitrary simulated neural activity to single current dipoles. We find that the method is applicable for calculating extracranial signals, but less suited for calculating intracranial electrocorticography (ECoG) signals. We demonstrate that this approach can serve as a powerful tool for investigating the neural origin of EEG/MEG signals. This is done through example studies of the single-neuron EEG contribution, the putative EEG contribution from calcium spikes, and from calculating EEG signals from large-scale neural network simulations. We also demonstrate how the simulated current dipoles can be used directly in combination with detailed head models, allowing for simulated EEG signals with an unprecedented level of biophysical details.In conclusion, this paper presents a framework for biophysically detailed modeling of EEG and MEG signals, which can be used to better our understanding of non-inasively measured neural activity in humans.Graphical abstractHighlightsCurrent dipoles are computed from biophysically detailed simulated neuron and network activityExtracted current dipoles allow for accurate computation of EEG and MEG signals in simplified and detailed head modelsCurrent-diplole approximation generally not suitable for accurate calculations of ECoG signalsMethod provides biophysics-based link between detailed neural activity and systems-level signals

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Alterations in Schizophrenia-Associated Genes Can Lead to Increased Power in Delta Oscillations

Cited by 31 publications

References 117 publications

The Role of Parvalbumin-positive Interneurons in Auditory Steady-State Response Deficits in Schizophrenia

The Role of Parvalbumin-positive Interneurons in Auditory Steady-State Response Deficits in Schizophrenia

Persistence: Using Protein Turnover to Expand the Applications of Transcriptomics

Biophysical modeling of the neural origin of EEG and MEG signals

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