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Deconstructing Cognitive Impairment in Psychosis With a Machine Learning Approach.

作者信息

McCutcheon Robert A, Keefe Richard S E, McGuire Philip M, Marquand Andre

机构信息

Department of Psychiatry, University of Oxford, Oxford, United Kingdom.

Oxford Health NHS Foundation Trust, Oxford, United Kingdom.

出版信息

JAMA Psychiatry. 2025 Jan 1;82(1):57-65. doi: 10.1001/jamapsychiatry.2024.3062.


DOI:10.1001/jamapsychiatry.2024.3062
PMID:39382875
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11465119/
Abstract

IMPORTANCE: Cognitive functioning is associated with various factors, such as age, sex, education, and childhood adversity, and is impaired in people with psychosis. In addition to specific effects of the disorder, cognitive impairments may reflect a greater exposure to general risk factors for poor cognition. OBJECTIVE: To determine the extent that impairments in cognition in psychosis reflect risk factor exposures. DESIGN, SETTING, AND PARTICIPANTS: This cross-sectional study examined the relationship between exposures and cognitive function using data from the Bipolar-Schizophrenia Network on Intermediate Phenotypes studies 1 and 2 across 6 sites. Participants included healthy controls; patients with schizophrenia, schizoaffective disorder, or bipolar I disorder with psychosis; and relatives of patients. Predictive modeling was performed using extreme gradient boosting regression to train a composite cognitive score prediction model with nested cross-validation. Shapley additive explanations values were used to examine the relationship between exposures and cognitive function. EXPOSURE: Exposures were chosen based on associations with cognition previously identified: age, sex, race and ethnicity, childhood adversity, education, parental education, parental socioeconomic status, parental age at birth, substance use, antipsychotic dose, and diagnosis. MAIN OUTCOMES AND MEASURES: Cognition was assessed using the Brief Assessment of Cognition in Schizophrenia. RESULTS: A total of 3370 participants were included: 840 healthy controls, 709 patients with schizophrenia, 541 with schizoaffective disorder, 457 with bipolar I disorder with psychosis, and 823 relatives of patients. The mean (SD) age was 37.9 (13.3) years; 1887 were female (56%) and 1483 male (44%). The model predicted cognitive scores with high accuracy: out-of-sample Pearson correlation between predicted and observed cognitive composite score was r = 0.72 (SD = 0.03). Individuals with schizophrenia (z = -1.4), schizoaffective disorder (z = -1.2), and bipolar I disorder with psychosis (z = -0.5) all had significantly worse cognitive composite scores than controls. Factors other than diagnosis and medication accounted for much of this impairment (schizophrenia z = -0.73, schizoaffective disorder z = -0.64, bipolar I disorder with psychosis z = -0.13). Diagnosis accounted for a lesser proportion of this deficit (schizophrenia z = -0.29, schizoaffective disorder z = -0.15, bipolar I disorder with psychosis z = -0.13), and antipsychotic use accounted for a similar deficit across diagnostic groups (schizophrenia z = -0.37, schizoaffective disorder z = -0.33, bipolar I disorder with psychosis z = -0.26). CONCLUSIONS AND RELEVANCE: This study found that transdiagnostic factors accounted for a meaningful share of the variance in cognitive functioning in psychosis. A significant proportion of the cognitive impairment in psychosis may reflect factors relevant to cognitive functioning in the general population. When considering interventions, a diagnosis-agnostic, symptom-targeted approach may therefore be appropriate.

摘要

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[1]
Deconstructing Cognitive Impairment in Psychosis With a Machine Learning Approach.

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本文引用的文献

[1]
The magnitude and variability of neurocognitive performance in first-episode psychosis: a systematic review and meta-analysis of longitudinal studies.

Transl Psychiatry. 2024-1-8

[2]
Cognitive impairment in schizophrenia: aetiology, pathophysiology, and treatment.

Mol Psychiatry. 2023-5

[3]
Accuracy of immediate self-assessment of neurocognitive test performance: Associations with psychiatric diagnosis and longitudinal psychotic symptoms.

J Psychiatr Res. 2022-12

[4]
Examining the variability of neurocognitive functioning in individuals at clinical high risk for psychosis: a meta-analysis.

Transl Psychiatry. 2022-5-12

[5]
Associations Between Schizophrenia Polygenic Liability, Symptom Dimensions, and Cognitive Ability in Schizophrenia.

JAMA Psychiatry. 2021-10-1

[6]
Cognitive ability and metabolic physical health in first-episode psychosis.

Schizophr Res Cogn. 2021-2-13

[7]
Cognitive functioning throughout adulthood and illness stages in individuals with psychotic disorders and their unaffected siblings.

Mol Psychiatry. 2021-8

[8]
Polygenic scores for schizophrenia and general cognitive ability: associations with six cognitive domains, premorbid intelligence, and cognitive composite score in individuals with a psychotic disorder and in healthy controls.

Transl Psychiatry. 2020-11-30

[9]
Education and Cognitive Functioning Across the Life Span.

Psychol Sci Public Interest. 2020-8

[10]
Comparison of cognitive dysfunction between schizophrenia and bipolar disorder patients: A meta-analysis of comparative studies.

J Affect Disord. 2020-9-1

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