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Article: Neural variability in three major psychiatric disorders

TitleNeural variability in three major psychiatric disorders
Authors
Issue Date13-Jul-2023
PublisherSpringer Nature
Citation
Molecular Psychiatry, 2023, v. 28, n. 12, p. 5217-5227 How to Cite?
AbstractAcross 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 (SDBOLD) obtained from resting-state fMRI was used to characterize neural variability. Transdiagnostic disruptions in SDBOLD 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 SDBOLD disruption and postmortem gene expressions, Neurosynth meta-analytic cognitive functions, and neurotransmitter receptor profiles were estimated. Two transdiagnostic patterns of disrupted SDBOLD were discovered. Pattern 1 is exhibited in all diagnostic groups and is most pronounced in schizophrenia, characterized by higher SDBOLD in the language/auditory networks but lower SDBOLD in the default mode/sensorimotor networks. In comparison, pattern 2 is only exhibited in unipolar and bipolar depression, characterized by higher SDBOLD in the default mode/salience networks but lower SDBOLD 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.
Persistent Identifierhttp://hdl.handle.net/10722/345860
ISSN
2023 Impact Factor: 9.6
2023 SCImago Journal Rankings: 3.895

 

DC FieldValueLanguage
dc.contributor.authorWei, Wei-
dc.contributor.authorDeng, Lihong-
dc.contributor.authorQiao, Chunxia-
dc.contributor.authorYin, Yubing-
dc.contributor.authorZhang, Yamin-
dc.contributor.authorLi, Xiaojing-
dc.contributor.authorYu, Hua-
dc.contributor.authorJian, Lingqi-
dc.contributor.authorLi, Mingli-
dc.contributor.authorGuo, Wanjun-
dc.contributor.authorWang, Qiang-
dc.contributor.authorDeng, Wei-
dc.contributor.authorMa, Xiaohong-
dc.contributor.authorZhao, Liansheng-
dc.contributor.authorSham, Pak C-
dc.contributor.authorPalaniyappan, Lena-
dc.contributor.authorLi, Tao-
dc.date.accessioned2024-09-04T07:06:00Z-
dc.date.available2024-09-04T07:06:00Z-
dc.date.issued2023-07-13-
dc.identifier.citationMolecular Psychiatry, 2023, v. 28, n. 12, p. 5217-5227-
dc.identifier.issn1359-4184-
dc.identifier.urihttp://hdl.handle.net/10722/345860-
dc.description.abstractAcross 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 (SDBOLD) obtained from resting-state fMRI was used to characterize neural variability. Transdiagnostic disruptions in SDBOLD 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 SDBOLD disruption and postmortem gene expressions, Neurosynth meta-analytic cognitive functions, and neurotransmitter receptor profiles were estimated. Two transdiagnostic patterns of disrupted SDBOLD were discovered. Pattern 1 is exhibited in all diagnostic groups and is most pronounced in schizophrenia, characterized by higher SDBOLD in the language/auditory networks but lower SDBOLD in the default mode/sensorimotor networks. In comparison, pattern 2 is only exhibited in unipolar and bipolar depression, characterized by higher SDBOLD in the default mode/salience networks but lower SDBOLD 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.-
dc.languageeng-
dc.publisherSpringer Nature-
dc.relation.ispartofMolecular Psychiatry-
dc.titleNeural variability in three major psychiatric disorders-
dc.typeArticle-
dc.identifier.doi10.1038/s41380-023-02164-2-
dc.identifier.pmid37443193-
dc.identifier.scopuseid_2-s2.0-85164730753-
dc.identifier.volume28-
dc.identifier.issue12-
dc.identifier.spage5217-
dc.identifier.epage5227-
dc.identifier.eissn1476-5578-
dc.identifier.issnl1359-4184-

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