White Matter Microstructure and the General Psychopathology Factor in Children

Journal of the American Academy of Child & Adolescent Psychiatry(2020)

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摘要
Objective: Co-occurrence of behavioral and emotional problems in childhood is widespread, and previous studies have suggested that this reflects vulnerability to experience a range of psychiatric problems, often termed a general psychopathology factor. However, the neurobiological substrate of this general factor is not well understood. We tested the hypothesis that lower overall white matter microstructure is associated with higher levels of the general psychopathology factor in children and less with specific factors. Method: Global white matter microstructure at age 10 years was related to general and specific psychopathology factors. These factors were estimated using a latent bifactor model with multiple informants and instruments between ages 6 and 10 years in 3,030 children from the population-based birth cohort Generation R. The association of global white matter microstructure and the psychopathology factors was examined with a structural equation model adjusted for sex, age at scan, age at psychopathology assessment, parental education/income, and genetic ancestry. Results: A 1-SD increase of the global white matter factor was associated with a beta = -0.07SD (standard error [SE] = 0.02, p < .01) decrease in general psychopathology. In contrast, a 1-SD increase of white matter microstructure predicted an increase of beta = +0.07 SD (SE = 0.03, p < .01) specific externalizing factor levels. No association was found with the specific internalizing and specific attention factor. Conclusion: The results suggest that general psychopathology in childhood is related to white matter structure across the brain and not only to specific tracts. Taking into account general psychopathology may also help reveal neurobiological mechanisms behind specific symptoms that are otherwise obscured by comorbidity.
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关键词
magnetic resonance imaging,externalizing disorder,internalizing disorder,attention,structural equation modeling
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