Neural variability in three major psychiatric disorders
Across the major psychiatric disorders (MPDs), a shared disruption in brain physiology is suspected. Here we investigate the neural variability at rest, a well-established behavior-relevant marker of brain function, and probe its basis in gene expression and neurotransmitter receptor profiles across...
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| Veröffentlicht in: | Molecular psychiatry 2023-12, Vol.28 (12), p.5217-5227 |
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| creator | Wei, Wei Deng, Lihong Qiao, Chunxia Yin, Yubing Zhang, Yamin Li, Xiaojing Yu, Hua Jian, Lingqi Li, Mingli Guo, Wanjun Wang, Qiang Deng, Wei Ma, Xiaohong Zhao, Liansheng Sham, Pak C. Palaniyappan, Lena Li, Tao |
| description | Across the major psychiatric disorders (MPDs), a shared disruption in brain physiology is suspected. Here we investigate the neural variability at rest, a well-established behavior-relevant marker of brain function, and probe its basis in gene expression and neurotransmitter receptor profiles across the MPDs. We recruited 219 healthy controls and 279 patients with schizophrenia, major depressive disorder, or bipolar disorders (manic or depressive state). The standard deviation of blood oxygenation level-dependent signal (SD
BOLD
) obtained from resting-state fMRI was used to characterize neural variability. Transdiagnostic disruptions in SD
BOLD
patterns and their relationships with clinical symptoms and cognitive functions were tested by partial least-squares correlation. Moving beyond the clinical sample, spatial correlations between the observed patterns of SD
BOLD
disruption and postmortem gene expressions, Neurosynth meta-analytic cognitive functions, and neurotransmitter receptor profiles were estimated. Two transdiagnostic patterns of disrupted SD
BOLD
were discovered. Pattern 1 is exhibited in all diagnostic groups and is most pronounced in schizophrenia, characterized by higher SD
BOLD
in the language/auditory networks but lower SD
BOLD
in the default mode/sensorimotor networks. In comparison, pattern 2 is only exhibited in unipolar and bipolar depression, characterized by higher SD
BOLD
in the default mode/salience networks but lower SD
BOLD
in the sensorimotor network. The expression of pattern 1 related to the severity of clinical symptoms and cognitive deficits across MPDs. The two disrupted patterns had distinct spatial correlations with gene expressions (e.g., neuronal projections/cellular processes), meta-analytic cognitive functions (e.g., language/memory), and neurotransmitter receptor expression profiles (e.g., D2/serotonin/opioid receptors). In conclusion, neural variability is a potential transdiagnostic biomarker of MPDs with a substantial amount of its spatial distribution explained by gene expressions and neurotransmitter receptor profiles. The pathophysiology of MPDs can be traced through the measures of neural variability at rest, with varying clinical-cognitive profiles arising from differential spatial patterns of aberrant variability. |
| doi_str_mv | 10.1038/s41380-023-02164-2 |
| format | Article |
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BOLD
) obtained from resting-state fMRI was used to characterize neural variability. Transdiagnostic disruptions in SD
BOLD
patterns and their relationships with clinical symptoms and cognitive functions were tested by partial least-squares correlation. Moving beyond the clinical sample, spatial correlations between the observed patterns of SD
BOLD
disruption and postmortem gene expressions, Neurosynth meta-analytic cognitive functions, and neurotransmitter receptor profiles were estimated. Two transdiagnostic patterns of disrupted SD
BOLD
were discovered. Pattern 1 is exhibited in all diagnostic groups and is most pronounced in schizophrenia, characterized by higher SD
BOLD
in the language/auditory networks but lower SD
BOLD
in the default mode/sensorimotor networks. In comparison, pattern 2 is only exhibited in unipolar and bipolar depression, characterized by higher SD
BOLD
in the default mode/salience networks but lower SD
BOLD
in the sensorimotor network. The expression of pattern 1 related to the severity of clinical symptoms and cognitive deficits across MPDs. The two disrupted patterns had distinct spatial correlations with gene expressions (e.g., neuronal projections/cellular processes), meta-analytic cognitive functions (e.g., language/memory), and neurotransmitter receptor expression profiles (e.g., D2/serotonin/opioid receptors). In conclusion, neural variability is a potential transdiagnostic biomarker of MPDs with a substantial amount of its spatial distribution explained by gene expressions and neurotransmitter receptor profiles. The pathophysiology of MPDs can be traced through the measures of neural variability at rest, with varying clinical-cognitive profiles arising from differential spatial patterns of aberrant variability.</description><identifier>ISSN: 1359-4184</identifier><identifier>EISSN: 1476-5578</identifier><identifier>DOI: 10.1038/s41380-023-02164-2</identifier><identifier>PMID: 37443193</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>38/39 ; 59/57 ; 59/78 ; 692/53/2421 ; 692/699/476/1333 ; 692/699/476/1414 ; 692/699/476/1799 ; Adult ; Behavioral Sciences ; Biological Psychology ; Bipolar Disorder - genetics ; Bipolar Disorder - metabolism ; Bipolar Disorder - physiopathology ; Blood levels ; Brain - metabolism ; Brain - physiopathology ; Brain mapping ; Cognition - physiology ; Cognitive ability ; Depressive Disorder, Major - genetics ; Depressive Disorder, Major - metabolism ; Depressive Disorder, Major - physiopathology ; Female ; Functional magnetic resonance imaging ; Gene expression ; Humans ; Magnetic Resonance Imaging - methods ; Male ; Medicine ; Medicine & Public Health ; Mental disorders ; Mental Disorders - genetics ; Mental Disorders - metabolism ; Mental Disorders - physiopathology ; Meta-analysis ; Middle Aged ; Neurosciences ; Neurotransmitters ; Opioid receptors ; Oxygen - blood ; Oxygen - metabolism ; Pharmacotherapy ; Psychiatry ; Schizophrenia ; Schizophrenia - genetics ; Schizophrenia - metabolism ; Schizophrenia - physiopathology ; Sensorimotor system ; Spatial distribution</subject><ispartof>Molecular psychiatry, 2023-12, Vol.28 (12), p.5217-5227</ispartof><rights>The Author(s), under exclusive licence to Springer Nature Limited 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><rights>2023. The Author(s), under exclusive licence to Springer Nature Limited.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c375t-428037989d3c5331c53117e9dc1648342af5672501df6654b1a900a3f550b6ce3</citedby><cites>FETCH-LOGICAL-c375t-428037989d3c5331c53117e9dc1648342af5672501df6654b1a900a3f550b6ce3</cites><orcidid>0000-0002-3008-5135 ; 0009-0002-1756-4497 ; 0000-0002-0517-3352 ; 0000-0002-4109-3878 ; 0000-0003-3831-901X ; 0000-0003-1640-7182</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1038/s41380-023-02164-2$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1038/s41380-023-02164-2$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/37443193$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Wei, Wei</creatorcontrib><creatorcontrib>Deng, Lihong</creatorcontrib><creatorcontrib>Qiao, Chunxia</creatorcontrib><creatorcontrib>Yin, Yubing</creatorcontrib><creatorcontrib>Zhang, Yamin</creatorcontrib><creatorcontrib>Li, Xiaojing</creatorcontrib><creatorcontrib>Yu, Hua</creatorcontrib><creatorcontrib>Jian, Lingqi</creatorcontrib><creatorcontrib>Li, Mingli</creatorcontrib><creatorcontrib>Guo, Wanjun</creatorcontrib><creatorcontrib>Wang, Qiang</creatorcontrib><creatorcontrib>Deng, Wei</creatorcontrib><creatorcontrib>Ma, Xiaohong</creatorcontrib><creatorcontrib>Zhao, Liansheng</creatorcontrib><creatorcontrib>Sham, Pak C.</creatorcontrib><creatorcontrib>Palaniyappan, Lena</creatorcontrib><creatorcontrib>Li, Tao</creatorcontrib><title>Neural variability in three major psychiatric disorders</title><title>Molecular psychiatry</title><addtitle>Mol Psychiatry</addtitle><addtitle>Mol Psychiatry</addtitle><description>Across the major psychiatric disorders (MPDs), a shared disruption in brain physiology is suspected. Here we investigate the neural variability at rest, a well-established behavior-relevant marker of brain function, and probe its basis in gene expression and neurotransmitter receptor profiles across the MPDs. We recruited 219 healthy controls and 279 patients with schizophrenia, major depressive disorder, or bipolar disorders (manic or depressive state). The standard deviation of blood oxygenation level-dependent signal (SD
BOLD
) obtained from resting-state fMRI was used to characterize neural variability. Transdiagnostic disruptions in SD
BOLD
patterns and their relationships with clinical symptoms and cognitive functions were tested by partial least-squares correlation. Moving beyond the clinical sample, spatial correlations between the observed patterns of SD
BOLD
disruption and postmortem gene expressions, Neurosynth meta-analytic cognitive functions, and neurotransmitter receptor profiles were estimated. Two transdiagnostic patterns of disrupted SD
BOLD
were discovered. Pattern 1 is exhibited in all diagnostic groups and is most pronounced in schizophrenia, characterized by higher SD
BOLD
in the language/auditory networks but lower SD
BOLD
in the default mode/sensorimotor networks. In comparison, pattern 2 is only exhibited in unipolar and bipolar depression, characterized by higher SD
BOLD
in the default mode/salience networks but lower SD
BOLD
in the sensorimotor network. The expression of pattern 1 related to the severity of clinical symptoms and cognitive deficits across MPDs. The two disrupted patterns had distinct spatial correlations with gene expressions (e.g., neuronal projections/cellular processes), meta-analytic cognitive functions (e.g., language/memory), and neurotransmitter receptor expression profiles (e.g., D2/serotonin/opioid receptors). In conclusion, neural variability is a potential transdiagnostic biomarker of MPDs with a substantial amount of its spatial distribution explained by gene expressions and neurotransmitter receptor profiles. The pathophysiology of MPDs can be traced through the measures of neural variability at rest, with varying clinical-cognitive profiles arising from differential spatial patterns of aberrant variability.</description><subject>38/39</subject><subject>59/57</subject><subject>59/78</subject><subject>692/53/2421</subject><subject>692/699/476/1333</subject><subject>692/699/476/1414</subject><subject>692/699/476/1799</subject><subject>Adult</subject><subject>Behavioral Sciences</subject><subject>Biological Psychology</subject><subject>Bipolar Disorder - genetics</subject><subject>Bipolar Disorder - metabolism</subject><subject>Bipolar Disorder - physiopathology</subject><subject>Blood levels</subject><subject>Brain - metabolism</subject><subject>Brain - physiopathology</subject><subject>Brain mapping</subject><subject>Cognition - physiology</subject><subject>Cognitive ability</subject><subject>Depressive Disorder, Major - genetics</subject><subject>Depressive Disorder, Major - metabolism</subject><subject>Depressive Disorder, Major - 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Academic</collection><jtitle>Molecular psychiatry</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wei, Wei</au><au>Deng, Lihong</au><au>Qiao, Chunxia</au><au>Yin, Yubing</au><au>Zhang, Yamin</au><au>Li, Xiaojing</au><au>Yu, Hua</au><au>Jian, Lingqi</au><au>Li, Mingli</au><au>Guo, Wanjun</au><au>Wang, Qiang</au><au>Deng, Wei</au><au>Ma, Xiaohong</au><au>Zhao, Liansheng</au><au>Sham, Pak C.</au><au>Palaniyappan, Lena</au><au>Li, Tao</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Neural variability in three major psychiatric disorders</atitle><jtitle>Molecular psychiatry</jtitle><stitle>Mol Psychiatry</stitle><addtitle>Mol Psychiatry</addtitle><date>2023-12-01</date><risdate>2023</risdate><volume>28</volume><issue>12</issue><spage>5217</spage><epage>5227</epage><pages>5217-5227</pages><issn>1359-4184</issn><eissn>1476-5578</eissn><abstract>Across the major psychiatric disorders (MPDs), a shared disruption in brain physiology is suspected. Here we investigate the neural variability at rest, a well-established behavior-relevant marker of brain function, and probe its basis in gene expression and neurotransmitter receptor profiles across the MPDs. We recruited 219 healthy controls and 279 patients with schizophrenia, major depressive disorder, or bipolar disorders (manic or depressive state). The standard deviation of blood oxygenation level-dependent signal (SD
BOLD
) obtained from resting-state fMRI was used to characterize neural variability. Transdiagnostic disruptions in SD
BOLD
patterns and their relationships with clinical symptoms and cognitive functions were tested by partial least-squares correlation. Moving beyond the clinical sample, spatial correlations between the observed patterns of SD
BOLD
disruption and postmortem gene expressions, Neurosynth meta-analytic cognitive functions, and neurotransmitter receptor profiles were estimated. Two transdiagnostic patterns of disrupted SD
BOLD
were discovered. Pattern 1 is exhibited in all diagnostic groups and is most pronounced in schizophrenia, characterized by higher SD
BOLD
in the language/auditory networks but lower SD
BOLD
in the default mode/sensorimotor networks. In comparison, pattern 2 is only exhibited in unipolar and bipolar depression, characterized by higher SD
BOLD
in the default mode/salience networks but lower SD
BOLD
in the sensorimotor network. The expression of pattern 1 related to the severity of clinical symptoms and cognitive deficits across MPDs. The two disrupted patterns had distinct spatial correlations with gene expressions (e.g., neuronal projections/cellular processes), meta-analytic cognitive functions (e.g., language/memory), and neurotransmitter receptor expression profiles (e.g., D2/serotonin/opioid receptors). In conclusion, neural variability is a potential transdiagnostic biomarker of MPDs with a substantial amount of its spatial distribution explained by gene expressions and neurotransmitter receptor profiles. The pathophysiology of MPDs can be traced through the measures of neural variability at rest, with varying clinical-cognitive profiles arising from differential spatial patterns of aberrant variability.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>37443193</pmid><doi>10.1038/s41380-023-02164-2</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0002-3008-5135</orcidid><orcidid>https://orcid.org/0009-0002-1756-4497</orcidid><orcidid>https://orcid.org/0000-0002-0517-3352</orcidid><orcidid>https://orcid.org/0000-0002-4109-3878</orcidid><orcidid>https://orcid.org/0000-0003-3831-901X</orcidid><orcidid>https://orcid.org/0000-0003-1640-7182</orcidid></addata></record> |
| fulltext | fulltext |
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| ispartof | Molecular psychiatry, 2023-12, Vol.28 (12), p.5217-5227 |
| issn | 1359-4184 1476-5578 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_2838251584 |
| source | MEDLINE; Springer Nature - Complete Springer Journals |
| subjects | 38/39 59/57 59/78 692/53/2421 692/699/476/1333 692/699/476/1414 692/699/476/1799 Adult Behavioral Sciences Biological Psychology Bipolar Disorder - genetics Bipolar Disorder - metabolism Bipolar Disorder - physiopathology Blood levels Brain - metabolism Brain - physiopathology Brain mapping Cognition - physiology Cognitive ability Depressive Disorder, Major - genetics Depressive Disorder, Major - metabolism Depressive Disorder, Major - physiopathology Female Functional magnetic resonance imaging Gene expression Humans Magnetic Resonance Imaging - methods Male Medicine Medicine & Public Health Mental disorders Mental Disorders - genetics Mental Disorders - metabolism Mental Disorders - physiopathology Meta-analysis Middle Aged Neurosciences Neurotransmitters Opioid receptors Oxygen - blood Oxygen - metabolism Pharmacotherapy Psychiatry Schizophrenia Schizophrenia - genetics Schizophrenia - metabolism Schizophrenia - physiopathology Sensorimotor system Spatial distribution |
| title | Neural variability in three major psychiatric disorders |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-11T18%3A01%3A45IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Neural%20variability%20in%20three%20major%20psychiatric%20disorders&rft.jtitle=Molecular%20psychiatry&rft.au=Wei,%20Wei&rft.date=2023-12-01&rft.volume=28&rft.issue=12&rft.spage=5217&rft.epage=5227&rft.pages=5217-5227&rft.issn=1359-4184&rft.eissn=1476-5578&rft_id=info:doi/10.1038/s41380-023-02164-2&rft_dat=%3Cproquest_cross%3E2838251584%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=3046693784&rft_id=info:pmid/37443193&rfr_iscdi=true |