Comparative cytokine signatures and cognitive deficits in early-onset schizophrenia and adolescent major depression: Toward refined diagnostic classification frameworks.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Comparative cytokine signatures and cognitive deficits in early-onset schizophrenia and adolescent major depression: Toward refined diagnostic classification frameworks.
Συγγραφείς: Luo X; Affiliated Mental Health Centre, Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, Hangzhou, Zhejiang 310013, China. Electronic address: 1369643803@qq.com., Dong J; Affiliated Mental Health Centre, Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, Hangzhou, Zhejiang 310013, China., Li T; Affiliated Mental Health Centre, Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, Hangzhou, Zhejiang 310013, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China; Nanhu Brain-computer Interface Institute, Hangzhou 311100, China. Electronic address: Xuntao26@hotmail.com.
Πηγή: Journal of affective disorders [J Affect Disord] 2025 Nov 15; Vol. 389, pp. 119667. Date of Electronic Publication: 2025 Jun 16.
Τύπος έκδοσης: Journal Article; Comparative Study
Γλώσσα: English
Στοιχεία περιοδικού: Publisher: Elsevier/North-Holland Biomedical Press Country of Publication: Netherlands NLM ID: 7906073 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-2517 (Electronic) Linking ISSN: 01650327 NLM ISO Abbreviation: J Affect Disord Subsets: MEDLINE
Imprint Name(s): Original Publication: Amsterdam, Elsevier/North-Holland Biomedical Press.
Ιατρικοί όροι (MeSH): Major Depressive Disorder*/blood , Major Depressive Disorder*/diagnosis , Major Depressive Disorder*/classification , Major Depressive Disorder*/psychology , Major Depressive Disorder*/complications , Schizophrenia*/blood , Schizophrenia*/diagnosis , Schizophrenia*/classification , Schizophrenia*/complications , Cytokines*/blood , Cognitive Dysfunction*/blood , Cognitive Dysfunction*/diagnosis, Biomarkers/blood ; Humans ; Male ; Adolescent ; Female ; Neuropsychological Tests ; Machine Learning
Περίληψη: Background: This study analyzed plasma cytokine patterns in individuals with schizophrenia (SCZ), major depressive disorder (MDD), and healthy controls, explored the link between cytokine levels and cognitive function, and created machine learning models to evaluate the diagnostic potential of cytokine and cognitive assessments.
Methods: This study involved 64 early-onset SCZ patients, 53 adolescents with MDD, and 33 healthy controls. The plasma concentrations of 44 cytokines were measured using the LUMINEX multiplex assay. Cognitive function was tested with the Cambridge Neuropsychological Test Automated Battery. Random Forest and Extreme Gradient Boosting models were used for classification, with their effectiveness evaluated via ROC curve analysis.
Results: SCZ patients exhibited significantly elevated levels of CCL11, IL-2 and IL-13, while MDD patients displayed increased CXCL2 and G-CSF levels but decreased CCL20 and CCL11 levels. SCZ patients showed significant cognitive impairments compared to healthy controls. Elevated CCL11 were associated with poorer memory accuracy, and higher G-CSF were linked to worse executive function. The XGBoost model was more sensitive in classifying MDD than the Random Forest model, but both struggled to differentiate SCZ patients from healthy controls due to low specificity.
Conclusion: Early-onset SCZ and adolescent MDD patients showed unique peripheral cytokine profiles, with SCZ patients experiencing significant cognitive deficits. The cytokine CCL11 was found to have a significant association with cognitive dysfunction. Cytokine levels and cognitive assessments may serve as potential biomarkers for the diagnosis of MDD.
(Copyright © 2025 Elsevier B.V. All rights reserved.)
Competing Interests: Declaration of competing interest The authors declare that there are no financial or other relationships that might lead to a conflict of interest of the present article. All authors have reviewed the final version of the manuscript and approved it for publication.
Contributed Indexing: Keywords: CCL11; Cognitive impairment; Cytokines; Depression; Schizophrenia
Substance Nomenclature: 0 (Cytokines)
0 (Biomarkers)
Entry Date(s): Date Created: 20250618 Date Completed: 20250812 Latest Revision: 20260127
Update Code: 20260130
DOI: 10.1016/j.jad.2025.119667
PMID: 40532880
Βάση Δεδομένων: MEDLINE
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  Data: Comparative cytokine signatures and cognitive deficits in early-onset schizophrenia and adolescent major depression: Toward refined diagnostic classification frameworks.
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  Data: <searchLink fieldCode="AU" term="%22Luo+X%22">Luo X</searchLink>; Affiliated Mental Health Centre, Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, Hangzhou, Zhejiang 310013, China. Electronic address: 1369643803@qq.com.<br /><searchLink fieldCode="AU" term="%22Dong+J%22">Dong J</searchLink>; Affiliated Mental Health Centre, Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, Hangzhou, Zhejiang 310013, China.<br /><searchLink fieldCode="AU" term="%22Li+T%22">Li T</searchLink>; Affiliated Mental Health Centre, Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, Hangzhou, Zhejiang 310013, China; Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-Machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou 311121, China; NHC and CAMS Key Laboratory of Medical Neurobiology, Zhejiang University, Hangzhou 310058, China; Nanhu Brain-computer Interface Institute, Hangzhou 311100, China. Electronic address: Xuntao26@hotmail.com.
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  Data: <searchLink fieldCode="JN" term="%227906073%22">Journal of affective disorders</searchLink> [J Affect Disord] 2025 Nov 15; Vol. 389, pp. 119667. <i>Date of Electronic Publication: </i>2025 Jun 16.
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  Data: Background: This study analyzed plasma cytokine patterns in individuals with schizophrenia (SCZ), major depressive disorder (MDD), and healthy controls, explored the link between cytokine levels and cognitive function, and created machine learning models to evaluate the diagnostic potential of cytokine and cognitive assessments.<br />Methods: This study involved 64 early-onset SCZ patients, 53 adolescents with MDD, and 33 healthy controls. The plasma concentrations of 44 cytokines were measured using the LUMINEX multiplex assay. Cognitive function was tested with the Cambridge Neuropsychological Test Automated Battery. Random Forest and Extreme Gradient Boosting models were used for classification, with their effectiveness evaluated via ROC curve analysis.<br />Results: SCZ patients exhibited significantly elevated levels of CCL11, IL-2 and IL-13, while MDD patients displayed increased CXCL2 and G-CSF levels but decreased CCL20 and CCL11 levels. SCZ patients showed significant cognitive impairments compared to healthy controls. Elevated CCL11 were associated with poorer memory accuracy, and higher G-CSF were linked to worse executive function. The XGBoost model was more sensitive in classifying MDD than the Random Forest model, but both struggled to differentiate SCZ patients from healthy controls due to low specificity.<br />Conclusion: Early-onset SCZ and adolescent MDD patients showed unique peripheral cytokine profiles, with SCZ patients experiencing significant cognitive deficits. The cytokine CCL11 was found to have a significant association with cognitive dysfunction. Cytokine levels and cognitive assessments may serve as potential biomarkers for the diagnosis of MDD.<br /> (Copyright © 2025 Elsevier B.V. All rights reserved.)
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  Data: Declaration of competing interest The authors declare that there are no financial or other relationships that might lead to a conflict of interest of the present article. All authors have reviewed the final version of the manuscript and approved it for publication.
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