Journal article
Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modeling
Proceedings of the National Academy of Sciences - PNAS, Vol.121(34), e2312511121
08/20/2024
DOI: 10.1073/pnas.2312511121
PMCID: PMC11348150
PMID: 39141354
Abstract
Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modeling of postsynaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from postmortem RNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in the anterior cingulate cortex, lead to impaired protein kinase A (PKA)-pathway-mediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped electroencephalogram (EEG) dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder.Schizophrenia phenotypes are suggestive of impaired cortical plasticity in the disease, but the mechanisms of these deficits are unknown. Genomic association studies have implicated a large number of genes that regulate neuromodulation and plasticity, indicating that the plasticity deficits have a genetic origin. Here, we used biochemically detailed computational modeling of postsynaptic plasticity to investigate how schizophrenia-associated genes regulate long-term potentiation (LTP) and depression (LTD). We combined our model with data from postmortem RNA expression studies (CommonMind gene-expression datasets) to assess the consequences of altered expression of plasticity-regulating genes for the amplitude of LTP and LTD. Our results show that the expression alterations observed post mortem, especially those in the anterior cingulate cortex, lead to impaired protein kinase A (PKA)-pathway-mediated LTP in synapses containing GluR1 receptors. We validated these findings using a genotyped electroencephalogram (EEG) dataset where polygenic risk scores for synaptic and ion channel-encoding genes as well as modulation of visual evoked potentials were determined for 286 healthy controls. Our results provide a possible genetic mechanism for plasticity impairments in schizophrenia, which can lead to improved understanding and, ultimately, treatment of the disorder.
Details
- Title: Subtitle
- Genetic mechanisms for impaired synaptic plasticity in schizophrenia revealed by computational modeling
- Creators
- Tuomo Mäki-Marttunen - Tampere UniversityKim T Blackwell - University of IowaIbrahim Akkouh - Oslo University HospitalAlexey Shadrin - Oslo University HospitalMathias Valstad - Norwegian Institute of Public HealthTorbjørn Elvsåshagen - Oslo University HospitalMarja-Leena Linne - Tampere UniversitySrdjan Djurovic - Oslo University HospitalGaute T Einevoll - Norwegian University of Life SciencesOle A Andreassen - University of Oslo
- Resource Type
- Journal article
- Publication Details
- Proceedings of the National Academy of Sciences - PNAS, Vol.121(34), e2312511121
- Publisher
- NATL ACAD SCIENCES
- DOI
- 10.1073/pnas.2312511121
- PMID
- 39141354
- PMCID
- PMC11348150
- ISSN
- 1091-6490
- eISSN
- 1091-6490
- Grant note
- Academy of Finland: 330776, 336376, 318879 University of Oslo Convergence Environment (4MENT)ERA-NET NEURON project SYNSCHIZ (Research Council of Norway): 283798 Takeda Pharmaceuticals Company LimitedNIH: R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881, AG02219, AG05138, MH06692, R01MH110921, R01MH109677, R01MH109897, U01MH103392 IRP National Institute of Mental Health (NIMH): HHSN271201300031C NIMH Human Brain Collection CoreCSC Finland: 2003397 Sigma2 Norway: NN9529K/NS9529K F. Hoffmann-La Roche Ltd.
Academy of Finland (330776, 336376, and 318879) , University of Oslo Convergence Environment (4MENT) , and ERA-NET NEURON project SYNSCHIZ (Research Council of Norway, grant number 283798) . CommonMind: Data were generated as part of the CommonMind Consortium supported by funding from Takeda Pharmaceuticals Company Limited, F. Hoffmann-La Roche Ltd. and NIH grants R01MH085542, R01MH093725, P50MH066392, P50MH080405, R01MH097276, RO1-MH-075916, P50M096891, P50MH084053S1, R37MH057881, AG02219, AG05138, MH06692, R01MH110921, R01MH109677, R01MH109897, U01MH103392, and contract HHSN271201300031C through IRP National Institute of Mental Health (NIMH) . Brain tissue for the study was obtained from the following brain bank collections: the Mount Sinai NIH Brain and Tissue Repository, the University of Pennsylvania Alzheimer's Disease Core Center, the University of Pittsburgh NeuroBioBank and Brain and Tissue Repositories, and the NIMH Human Brain Collection Core. CMC Leadership: Panos Roussos, Joseph Buxbaum, Andrew Chess, Schahram Akbarian, Vahram Haroutunian (Icahn School of Medicine at Mount Sinai) , Bernie Devlin, David Lewis (University of Pittsburgh) , Raquel Gur, Chang-Gyu Hahn (University of Pennsylvania) , Enrico Domenici (University of Trento) , Mette A. Peters, Solveig Sieberts (Sage Bionetworks) , Thomas Lehner, Stefano Marenco, and Barbara K. Lipska (NIMH) . The authors wish to acknowledge CSC Finland (project 2003397) and Sigma2 Norway (project NN9529K/NS9529K) for computational resources.
- Language
- English
- Date published
- 08/20/2024
- Academic Unit
- Roy J. Carver Department of Biomedical Engineering; Iowa Neuroscience Institute
- Record Identifier
- 9984697060102771
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