Functional Effects of Schizophrenia-Linked Genetic Variants on Intrinsic Single-Neuron Excitability: A Modeling Study

doi:10.1016/j.bpsc.2015.09.002

Biological Psychiatry: Cognitive Neuroscience and Neuroimaging

Volume 1, Issue 1, January 2016, Pages 49-59

https://doi.org/10.1016/j.bpsc.2015.09.002 Get rights and content

Abstract

Background

Recent genome-wide association studies have identified a large number of genetic risk factors for schizophrenia (SCZ) featuring ion channels and calcium transporters. For some of these risk factors, independent prior investigations have examined the effects of genetic alterations on the cellular electrical excitability and calcium homeostasis. In the present proof-of-concept study, we harnessed these experimental results for modeling of computational properties on layer V cortical pyramidal cells and identified possible common alterations in behavior across SCZ-related genes.

Methods

We applied a biophysically detailed multicompartmental model to study the excitability of a layer V pyramidal cell. We reviewed the literature on functional genomics for variants of genes associated with SCZ and used changes in neuron model parameters to represent the effects of these variants.

Results

We present and apply a framework for examining the effects of subtle single nucleotide polymorphisms in ion channel and calcium transporter-encoding genes on neuron excitability. Our analysis indicates that most of the considered SCZ-related genetic variants affect the spiking behavior and intracellular calcium dynamics resulting from summation of inputs across the dendritic tree.

ConclusionS

Our results suggest that alteration in the ability of a single neuron to integrate the inputs and scale its excitability may constitute a fundamental mechanistic contributor to mental disease, alongside the previously proposed deficits in synaptic communication and network behavior.

Section snippets

The L5PC Model

The multicompartmental neuron model used in this work was based on a reconstructed morphology of a layer V thick-tufted pyramidal neuron [cell #1 in (11)]. The model includes the following ionic currents: fast inactivating Na⁺ current, persistent Na⁺ current, nonspecific cation current, muscarinic K⁺ current, slow inactivating K⁺ current (I_Kp), fast inactivating K⁺ current, fast noninactivating K⁺ current, high-voltage activated Ca²⁺ current, low-voltage activated Ca²⁺ current,

A New Framework for Bridging the Gap Between GWASs of SCZ and Computational Neuroscience

In this work, we reviewed the literature on effects of variants in SCZ-related genes on ion channel behavior and intracellular Ca²⁺ dynamics and interpreted the reported effects in the context of our neuron model parameters. An overview of the relevant studies is given in Table 1, while the effects of each variant on the L5PC model parameters are given in Table 2. These data gave us a direct interface for linking a change in the genomic data, such as an SNP or an alternative splicing, into a

Discussion

We presented a framework for studying the effects of genetic variants in genes related to SCZ on layer V pyramidal cell excitability. Our results indicate that most of the studied variants predicted an observable change in the neuron behavior (Figure 2, Figure 3, Figure 4, Figure 5, Figure 6). Taken together, these data provide support for using neuronal modeling to study the functional implications of SCZ-related genes on neuronal excitability. Although the analyses presented in this article

Acknowledgments and Disclosures

Norwegian Metacenter for Computational Science (NOTUR) resources were used for heavy simulations. This work was supported by National Institutes of Health Grant No. 5 R01 EB000790-10, EC-FP7 Grant No. 604102 (“Human Brain Project”), Research Council of Norway (Grant Nos. 216699, 213837, and 223273), South East Norway Health Authority (Grant No. 2013-123), and KG Jebsen Foundation.

The authors report no biomedical financial interests or potential conflicts of interest.

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Citation Excerpt :
As for our study, we generated the data by simulating the Hay model (Hay et al., 2011), which contains a large SK conductance not only in the apical dendrite but also in the soma – the mutual expression of these channels and their distinct roles are also backed by recent experiments (Rudolph and Thanawala, 2015). Therefore, applying the third step of the approach of Bahl et al. (2012) to our data would imply a major change to the second step fits (for reference, see the effect of SK blockade in the network experiment of Fig. S26 and our earlier analysis on the contribution of SK currents to the single-cell dynamics (Mäki-Marttunen et al., 2016)). Secondly, our model included a slightly larger set of ion channels but (in the default fitting task) smaller number of functionally different compartments.
Recent progress in electrophysiological and optical methods for neuronal recordings provides vast amounts of high-resolution data. In parallel, the development of computer technology has allowed simulation of ever-larger neuronal circuits. A challenge in taking advantage of these developments is the construction of single-cell and network models in a way that faithfully reproduces neuronal biophysics with subcellular level of details while keeping the simulation costs at an acceptable level.
In this work, we develop and apply an automated, stepwise method for fitting a neuron model to data with fine spatial resolution, such as that achievable with voltage sensitive dyes (VSDs) and Ca²⁺ imaging.
We apply our method to simulated data from layer 5 pyramidal cells (L5PCs) and construct a model with reduced neuronal morphology. We connect the reduced-morphology neurons into a network and validate against simulated data from a high-resolution L5PC network model.
Our approach combines features from several previously applied model-fitting strategies. The reduced-morphology neuron model obtained using our approach reliably reproduces the membrane-potential dynamics across the dendrites as predicted by the full-morphology model.
The network models produced using our method are cost-efficient and predict that interconnected L5PCs are able to amplify delta-range oscillatory inputs across a large range of network sizes and topologies, largely due to the medium after hyperpolarization mediated by the Ca²⁺-activated SK current.
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Archival ReportFunctional Effects of Schizophrenia-Linked Genetic Variants on Intrinsic Single-Neuron Excitability: A Modeling Study

Abstract

Background

Methods

Results

ConclusionS

Section snippets

The L5PC Model

A New Framework for Bridging the Gap Between GWASs of SCZ and Computational Neuroscience

Discussion

Acknowledgments and Disclosures

Neuron

Neuron

Neuron

Trends Neurosci

Biophys J

J Neurosci Methods

Arch Biochem Biophys

Dev Biol

Curr Biol

Lancet Psychiatry

J Mol Cell Cardiol

J Biol Chem

J Mol Cell Cardiol

J Biol Chem

J Biol Chem

J Biol Chem

J Biol Chem

Mol Cell Neurosci

Genome-wide association analysis identifies 13 new risk loci for schizophrenia

Nat Genet

Biological insights from 108 schizophrenia- associated genetic loci

Nature

Schizophrenia

Lancet

Large-scale genome-wide association analysis of bipolar disorder identifies a new susceptibility locus near ODZ4

Nat Genet

Genome-wide association study identifies five new schizophrenia loci

Nat Genet

Identification of risk loci with shared effects on five major psychiatric disorders: A genome-wide analysis

Lancet

Models of neocortical layer 5b pyramidal cells capturing a wide range of dendritic and perisomatic active properties

PLoS Comput Biol

A polygenic theory of schizophrenia

Proc Natl Acad Sci U S A

Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Nature

Common variants conferring risk of schizophrenia

Nature

De novo mutations in schizophrenia implicate synaptic networks

Nature

Synaptic dysregulation in a human iPS cell model of mental disorders

Nature

Archival Report
Functional Effects of Schizophrenia-Linked Genetic Variants on Intrinsic Single-Neuron Excitability: A Modeling Study