Psychiatry - Research Publications
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ItemDoes cortical brain morphology act as a mediator between childhood trauma and transition to psychosis in young individuals at ultra-high risk?(ELSEVIER, 2020-10)BACKGROUND: Childhood trauma, particularly sexual abuse, has been associated with transition to psychosis in individuals at "ultra-high risk" (UHR). This study investigated whether the effects of various forms of childhood trauma on transition to psychosis are mediated by cortical thickness and surface area abnormalities. METHODS: This prospective study used data from 62 UHR individuals from a previous (PACE 400) cohort study. At follow-up, 24 individuals had transitioned to psychosis (UHR-T) and 38 individuals had not transitioned (UHR-NT). Student-t/Mann-Whitney-U tests were performed to assess morphological differences in childhood trauma (low/high) and transition. Mediation analyses were conducted using regression and bootstrapping techniques. RESULTS: UHR individuals with high sexual trauma histories presented with decreased cortical thickness in bilateral middle temporal gyri and the left superior frontal gyrus compared to those with low sexual trauma. Participants with high physical abuse had increased cortical thickness in the right middle frontal gyrus compared to those with low physical abuse. No differences were found for emotional abuse or physical/emotional neglect. Reduced cortical thickness in the right middle temporal gyrus and increased surface area in the right cingulate were found in UHR-T compared to UHR-NT individuals. Sexual abuse had an indirect effect on transition to psychosis, where decreased cortical thickness in the right middle temporal gyrus was a mediator. CONCLUSIONS: Results suggest that childhood sexual abuse negatively impacted on cortical development of the right temporal gyrus, and this heightened the risk of transition to psychosis in our sample. Further longitudinal studies are needed to precisely understand this link.
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ItemPredicting individual improvement in schizophrenia symptom severity at 1-year follow-up: Comparison of connectomic, structural, and clinical predictors(Wiley, 2020-08-15)In a machine learning setting, this study aims to compare the prognostic utility of connectomic, brain structural, and clinical/demographic predictors of individual change in symptom severity in individuals with schizophrenia. Symptom severity at baseline and 1‐year follow‐up was assessed in 30 individuals with a schizophrenia‐spectrum disorder using the Brief Psychiatric Rating Scale. Structural and functional neuroimaging was acquired in all individuals at baseline. Machine learning classifiers were trained to predict whether individuals improved or worsened with respect to positive, negative, and overall symptom severity. Classifiers were trained using various combinations of predictors, including regional cortical thickness and gray matter volume, static and dynamic resting‐state connectivity, and/or baseline clinical and demographic variables. Relative change in overall symptom severity between baseline and 1‐year follow‐up varied markedly among individuals (interquartile range: 55%). Dynamic resting‐state connectivity measured within the default‐mode network was the most accurate single predictor of change in positive (accuracy: 87%), negative (83%), and overall symptom severity (77%) at follow‐up. Incorporating predictors based on regional cortical thickness, gray matter volume, and baseline clinical variables did not markedly improve prediction accuracy and the prognostic utility of these predictors in isolation was moderate (<70%). Worsening negative symptoms at 1‐year follow‐up were predicted by hyper‐connectivity and hypo‐dynamism within the default‐mode network at baseline assessment, while hypo‐connectivity and hyper‐dynamism predicted worsening positive symptoms. Given the modest sample size investigated, we recommend giving precedence to the relative ranking of the predictors investigated in this study, rather than the prediction accuracy estimates.