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    White matter integrity as a predictor of response to treatment in first episode psychosis
    Marques, TR ; Taylor, H ; Chaddock, C ; Dell'Acqua, F ; Handley, R ; Reinders, AATS ; Mondelli, V ; Bonaccorso, S ; DiForti, M ; Simmons, A ; David, AS ; Murray, RM ; Pariante, CM ; Kapur, S ; Dazzan, P (OXFORD UNIV PRESS, 2014-01)
    The integrity of brain white matter connections is central to a patient's ability to respond to pharmacological interventions. This study tested this hypothesis using a specific measure of white matter integrity, and examining its relationship to treatment response using a prospective design in patients within their first episode of psychosis. Diffusion tensor imaging data were acquired in 63 patients with first episode psychosis and 52 healthy control subjects (baseline). Response was assessed after 12 weeks and patients were classified as responders or non-responders according to treatment outcome. At this second time-point, they also underwent a second diffusion tensor imaging scan. Tract-based spatial statistics were used to assess fractional anisotropy as a marker of white matter integrity. At baseline, non-responders showed lower fractional anisotropy than both responders and healthy control subjects (P < 0.05; family-wise error-corrected), mainly in the uncinate, cingulum and corpus callosum, whereas responders were indistinguishable from healthy control subjects. After 12 weeks, there was an increase in fractional anisotropy in both responders and non-responders, positively correlated with antipsychotic exposure. This represents one of the largest, controlled investigations of white matter integrity and response to antipsychotic treatment early in psychosis. These data, together with earlier findings on cortical grey matter, suggest that grey and white matter integrity at the start of treatment is an important moderator of response to antipsychotics. These findings can inform patient stratification to anticipate care needs, and raise the possibility that antipsychotics may restore white matter integrity as part of the therapeutic response.
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    Individualized prediction of illness course at the first psychotic episode: a support vector machine MRI study
    Mourao-Miranda, J ; Reinders, AATS ; Rocha-Rego, V ; Lappin, J ; Rondina, J ; Morgan, C ; Morgan, KD ; Fearon, P ; Jones, PB ; Doody, GA ; Murray, RM ; Kapur, S ; Dazzan, P (CAMBRIDGE UNIV PRESS, 2012-05)
    BACKGROUND: To date, magnetic resonance imaging (MRI) has made little impact on the diagnosis and monitoring of psychoses in individual patients. In this study, we used a support vector machine (SVM) whole-brain classification approach to predict future illness course at the individual level from MRI data obtained at the first psychotic episode. METHOD: One hundred patients at their first psychotic episode and 91 healthy controls had an MRI scan. Patients were re-evaluated 6.2 years (s.d.=2.3) later, and were classified as having a continuous, episodic or intermediate illness course. Twenty-eight subjects with a continuous course were compared with 28 patients with an episodic course and with 28 healthy controls. We trained each SVM classifier independently for the following contrasts: continuous versus episodic, continuous versus healthy controls, and episodic versus healthy controls. RESULTS: At baseline, patients with a continuous course were already distinguishable, with significance above chance level, from both patients with an episodic course (p=0.004, sensitivity=71, specificity=68) and healthy individuals (p=0.01, sensitivity=71, specificity=61). Patients with an episodic course could not be distinguished from healthy individuals. When patients with an intermediate outcome were classified according to the discriminating pattern episodic versus continuous, 74% of those who did not develop other episodes were classified as episodic, and 65% of those who did develop further episodes were classified as continuous (p=0.035). CONCLUSIONS: We provide preliminary evidence of MRI application in the individualized prediction of future illness course, using a simple and automated SVM pipeline. When replicated and validated in larger groups, this could enable targeted clinical decisions based on imaging data.
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    The effect of perinatal brain injury on dopaminergic function and hippocampal volume in adult life
    Froudist-Walsh, S ; Bloomfield, MAP ; Veronese, M ; Kroll, J ; Karolis, VR ; Jauhar, S ; Bonoldi, I ; McGuire, PK ; Kapur, S ; Murray, RM ; Nosarti, C ; Howes, O (ELIFE SCIENCES PUBLICATIONS LTD, 2017-11-28)
    Perinatal brain injuries, including hippocampal lesions, cause lasting changes in dopamine function in rodents, but it is not known if this occurs in humans. We compared adults who were born very preterm with perinatal brain injury to those born very preterm without perinatal brain injury, and age-matched controls born at full term using [18F]-DOPA PET and structural MRI. Dopamine synthesis capacity was reduced in the perinatal brain injury group relative to those without brain injury (Cohen's d = 1.36, p=0.02) and the control group (Cohen's d = 1.07, p=0.01). Hippocampal volume was reduced in the perinatal brain injury group relative to controls (Cohen's d = 1.17, p=0.01) and was positively correlated with striatal dopamine synthesis capacity (r = 0.344, p=0.03). This is the first evidence in humans linking neonatal hippocampal injury to adult dopamine dysfunction, and provides a potential mechanism linking early life risk factors to adult mental illness.