From Snapshots to Stable Outcomes: Resting-State Functional Magnetic Resonance Imaging-Based Prognosis of Functioning in Patients With Psychosis Risk or Recent-Onset Depression.
Authors
Affiliations (18)
Affiliations (18)
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University Munich, Munich, Germany; International Max-Planck Research School for Translational Psychiatry, Munich, Germany.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York.
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, Bari, Italy.
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany.
- Melbourne Neuropsychiatry Centre, The University of Melbourne, Melbourne, Victoria, Australia.
- Institute of Translational Psychiatry, University of Münster, Münster, Germany; Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany.
- Department of Pathophysiology and Transplantation, University of Milan, Milan, Italy; Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Milan, Italy.
- Department of Psychiatry, University of Oxford, Oxford, United Kingdom; Institute for Mental Health and Centre for Brain Health, University of Birmingham, Birmingham, United Kingdom; Early Intervention Service, Birmingham Women's and Children's National Health Service Foundation Trust, Birmingham, United Kingdom.
- Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia; Orygen, The National Centre of Excellence for Youth Mental Health, Melbourne, Victoria, Australia.
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University Munich, Munich, Germany; Max-Planck-Institute of Psychiatry, Munich, Germany; DZPG (German Centre for Mental Health), Partner site Munich-Augsburg, Munich-Augsburg, Germany.
- Medical Faculty, University of Basel, Basel, Switzerland.
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany; University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, Bern, Switzerland; Department of Psychology, Faculty of Psychology, Airlangga University, Surabaya, Indonesia.
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine-Universität Düsseldorf, Düsseldorf, Germany.
- Department of Psychiatry, University of Turku, Turku, Finland.
- Department of Psychiatry and Psychotherapy, University of Lübeck, Lübeck, Germany; Department of Psychiatry (Psychiatric University Hospital), University of Basel, Basel, Switzerland.
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University Munich, Munich, Germany; Centre for Youth Mental Health, The University of Melbourne, Melbourne, Victoria, Australia; Orygen, The National Centre of Excellence for Youth Mental Health, Melbourne, Victoria, Australia.
- Department of Psychiatry and Psychotherapy, University of Cologne, Cologne, Germany; Department of Psychology and Educational Sciences, Ludwig-Maximilians-University, Munich, Germany.
- Department of Psychiatry and Psychotherapy, Ludwig-Maximilians-University Munich, Munich, Germany; Max-Planck-Institute of Psychiatry, Munich, Germany; DZPG (German Centre for Mental Health), Partner site Munich-Augsburg, Munich-Augsburg, Germany; Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, United Kingdom; National Institute for Health and Care Research Maudsley Biomedical Research Centre, London, United Kingdom. Electronic address: [email protected].
Abstract
Early recovery of functioning is critical for favorable outcomes in psychotic and affective disorders. Transdiagnostic brain activity patterns may capture pathways for poor outcomes before clinical manifestation, thereby supporting timely prevention and intervention. Using machine learning, we evaluated the transdiagnostic prognostic value of resting-state functional magnetic resonance imaging fractional amplitude of low-frequency fluctuations (fALFF) (slow-5 and slow-4 sub-bands) for functional outcomes in patients at clinical high risk for psychosis (n = 217) or with recent-onset depression (n = 198) from the multisite PRONIA (Prognostic Tools for Early Psychosis Management) study. Leave-site-out cross-validation assessed the geographic generalizability of models across disability and symptom domains, with outcomes defined as snapshots at 9- or 18-month follow-up or across both time points. We examined diagnosis-specific performance, generalization to recent-onset psychosis (n = 140), and negative symptoms and the added value of fALFF over clinical prognostication. Transdiagnostic models predicting stable good functioning across follow-ups showed up to 10% higher balanced accuracy (BAC) than snapshot models. Decreased slow-5 fALFFs in the default mode network, executive control network (ECN), and dorsal attentional network (DAN) and increased fALFF in the salience network, ECN, and DAN predicted impairment with BAC = 67% (sensitivity = 65%, specificity = 70%, p < .001). This model generalized to recent-onset psychosis (BAC = 62%, sensitivity = 64%, specificity = 59%, p < .001) and predicted (BAC = 65%, sensitivity = 66%, specificity = 65%, p < .001) and was mediated by negative symptoms. Slow-5-based models improved prognostic accuracy over expert ratings in disability (BAC<sub>raters</sub> = 66%, BAC<sub>raters+slow-5</sub> = 75%, W = 1680, p < .001) and symptom (BAC<sub>raters</sub> = 61%, BAC<sub>raters+slow-5</sub> = 71%, W = 1444, p < .001) domains. We highlighted the prognostic value of fALFF for functional impairment in psychosis risk and early depression. Leveraging trajectorial information, we identified candidate imaging biomarkers to improve prognostication, thereby supporting personalized prevention and recovery strategies.