Extreme deviations from the normative model reveal cortical heterogeneity and associations with negative symptom severity in first-episode psychosis from the OPTiMiSE and GAP studies
Year: 2023
Type: article
Abstract: There is currently no quantifiable method to predict long-term clinical outcomes in patients presenting with a first episode of psychosis. A major barrier to developing useful markers for this is biological heterogeneity, where many different pathological mechanisms may underly the same set of symptoms in different individuals. Normative modelling has been used to quantify this heterogeneity in established psychotic disorders by identifying regions of the cortex which are thinner than expected based on a normative healthy population range. These brain atypicalities are measured at the individual level and therefore potentially useful in a clinical setting. However, it is still unclear whether alterations in individual brain structure can be detected at the time of the first psychotic episode, and whether they are associated with subsequent clinical outcomes. We applied normative modelling of cortical thickness to a sample of first-episode psychosis patients, with the aim of quantifying heterogeneity and to use any pattern of cortical atypicality to predict symptoms and response to antipsychotic medication at timepoints from baseline up to 95 weeks (median follow-ups = 4). T1-weighted brain magnetic resonance images from the GAP and OPTiMiSE samples were processed with Freesurfer V6.0.0 yielding 148 cortical thickness features. An existing normative model of cortical thickness (n = 37,126) was adapted to integrate data from each clinical site and account for effects of gender and site. Our test sample consisted of control participants (n = 149, mean age = 26, SD = 6.7) and patient data (n = 295, mean age = 26, SD = 6.7), this sample was used for estimating deviations from the normative model and subsequent statistical analysis. For each individual, the 148 cortical thickness features were mapped to centiles of the normative distribution and converted to z-scores reflecting the distance from the population mean. Individual cortical thickness metrics of +/- 2.6 standard deviations from the mean were considered extreme deviations from the norm. We found that no more than 6.4% of psychosis patients had extreme deviations in a single brain region (regional overlap) demonstrating a high degree of heterogeneity. Mann-Whitney U tests were run on z-scores for each region and significantly lower z-scores were observed in FEP patients in the frontal, temporal, parietal and occipital lobes. Finally, linear mixed-effects modelling showed that negative deviations in cortical thickness in parietal and temporal regions at baseline are related to more severe negative symptoms over the medium-term. This study shows that even at the early stage of symptom onset normative modelling provides a framework to identify individualised cortical markers which can be used for early personalised intervention and stratification.
Source: Translational Psychiatry
Authors: Amanda Worker, Pierre Berthert, Andrew J. Lawrence, Seyed Mostafa Kia, Celso Arango, Richard Dinga, Silvana Galderisi, Birte Glenthøj, René S. Kahn, Anoushka Leslie, Robin M. Murray, Carmine M. Pariante, Christos Pantelis, Mark Weiser, Inge Winter-van Rossum, Philip McGuire, Paola Dazzan, Andre F. Marquand
Institutions: King's College London, Oslo University Hospital, University of Oslo, Radboud University Nijmegen, Tilburg University, Radboud University Medical Center, Donders Institute for Brain, Cognition and Behaviour, Universidad Complutense de Madrid, Hospital General Universitario Gregorio Marañón, Centro de Investigación Biomédica en Red de Salud Mental, University of Campania "Luigi Vanvitelli", University of Copenhagen, Mental Health Services, Glostrup Hospital, Copenhagen University Hospital, Icahn School of Medicine at Mount Sinai, National Health Service, South London and Maudsley NHS Foundation Trust, National Institute for Health and Care Research, The University of Melbourne, Melbourne Health, Tel Aviv University, Sheba Medical Center, Utrecht University, University Medical Center Utrecht
Language: English
Subfield: Psychiatry and Mental health
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $4,790
Funders: Fundación Alicia Koplowitz, Wellcome Trust, National Institute for Health and Care Research, Department of Health and Social Care, King's College London, European Commission, Ministerio de Ciencia e Innovación, Centro de Investigación Biomédica en Red de Salud Mental, National Institutes of Health, Horizon 2020 Framework Programme, HORIZON EUROPE Framework Programme, NIHR Maudsley Biomedical Research Centre, National Health and Medical Research Council, Instituto de Salud Carlos III, European Regional Development Fund, National Institute of Mental Health, NextGenerationEU
Awards: G1033681661, BRAINCHART: Normative brain charting for predicting and stratifying psychosis, BRAINCHART: Normative brain charting for predicting and stratifying psychosis, G2017605187, G2628364946, G3764841371, Developing Novel Preclinical Models for Neurodevelopmental Disorders - From Bedside to Bench, Estudio integral de variación genética y molecular de una cohorte española de trastornos del espectro autista y diseño de algoritmos de diagnóstico genético y de biotipos terapéuticos. Cohorte ESTEA., NIHR Senior Investigator Award, G4937468798, NIHR Senior Investigator Award, Psychiatric Ratings using Intermediate Stratified Markers 2, G5983053349, OPtimization of Treatment and Management of Schizophrenia in Europe (OPTiMiSE), Autism Innovative Medicine Studies – 2 – Trials, G6972650492, G7114038015, G7336256237, G8351277590, Neurobiological ‘risk’ and ‘resilience’ biomarkers of severe mental illness, ProNET: Psychosis-Risk Outcomes Network, G8824911526, G8858395165, Laboratory for Early Psychosis Research (LEAP)
OpenAlex ID: W4389275018