Biosignatures of cognitive basic symptoms mark a distinct neurodevelopmental pathway to schizophrenia.
Authors
Affiliations (37)
Affiliations (37)
- Department of Psychiatry and Psychotherapy, University Hospital, Ludwig-Maximilians-University Munich, 80336 Munich, Germany.
- Department of Psychosis Studies, Institute of Psychiatry, Psychology and Neuroscience, King's College London, London SE5 8AB, UK.
- Max-Planck Institute of Psychiatry, 80804 Munich, Germany.
- International Max-Planck Research School for Translational Psychiatry, 80804 Munich, Germany.
- Munich-Augsburg site of the German Centre for Mental Health, 80336 Munich, Germany.
- Department of Psychiatry, Harvard Medical School, Boston, MA 02115, USA.
- Department of Psychiatry, Icahn School of Medicine at Mount Sinai, New York, New York, NY 10029-5674, USA.
- Department of Psychiatry and Psychotherapy, Faculty of Medicine and University Hospital, University of Cologne, 50931 Cologne, Germany.
- School of Psychology, The University of Sussex, Falmer, BN1 9QH, UK.
- Department of Child and Adolescent Psychiatry, University of Münster, 48149 Münster, Germany.
- Department of Translational Biomedicine and Neuroscience, University of Bari Aldo Moro, 70124 Bari, Italy.
- Institute of Mental Health, University of Birmingham, Birmingham B15 2SA, UK.
- Orygen, the National Centre of Excellence for Youth Mental Health, Melbourne, Parkville VIC 3052, Australia.
- Department of Psychiatry (Psychiatric University Hospital, UPK), University of Basel, 4002 Basel, Switzerland.
- Department of Psychiatry, University of Melbourne, Parkville VIC 3010, Australia.
- Florey Institute of Neuroscience and Mental Health, Parkville VIC 3052, Australia.
- Monash Institute of Pharmaceutical Sciences (MIPS), Monash University, Parkville VIC 3052, Australia.
- Department of Psychiatry, University of Turku, 20700 Turku, Finland.
- Institute for Translational Psychiatry, University of Münster, 48149 Münster, Germany.
- Department of Psychiatry, Medical School and University Medical Center OWL, Protestant Hospital of the Bethel Foundation, Bielefeld University, 33617 Bielefeld, Germany.
- German Center for Mental Health (DZPG), Â Site Jena Magdeburg Halle, 07743 Jena, Germany.
- Center for Intervention and Research on Adaptive and Maladaptive Brain Circuits Underlying Mental Health (C-I-R-C), Site Jena Magdeburg Halle, 07743 Jena, Germany.
- Department of Psychiatry and Psychotherapy, University of Lübeck, 23562 Lübeck, Germany.
- Department of Psychiatry, University of Basel, 4002 Basel, Switzerland.
- Institute of Human Genetics, Rheinische Friedrich-Wilhelms-Universität Bonn, 53127 Bonn, Germany.
- Institute of Genomic Statistics and Bioinformatics, University of Bonn, 53113 Bonn, Germany.
- Centre for Human Genetics, University of Marburg, 35033 Marburg, Germany.
- Department of Neurosciences and Mental Health, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, 20122 Milano, Italy.
- Department of Pathophysiology and Transplantation, University of Milan, 20122 Milan, Italy.
- Centre for Mental Health and Brain Sciences, Swinburne University of Technology, Hawthorn VIC 3122, Australia.
- Department of Psychiatry, University of Oxford, Warneford Hospital, Oxford OX3 7JX, UK.
- Department of Psychiatry and Psychotherapy, LVR Clinic Cologne and Faculty of Medicine, University of Cologne, 51109 Cologne, Germany.
- St. Hedwig Hospital, Charité, 10115 Berlin, Germany.
- Department of Psychiatry and Psychotherapy, Medical Faculty, Heinrich-Heine University, 40629 Düsseldorf, Germany.
- Department of Psychiatry, Psychotherapy and Psychosomatics, University Hospital of Psychiatry Zurich, 8032 Zurich, Switzerland.
- University Hospital of Child and Adolescent Psychiatry and Psychotherapy, University of Bern, 3000 Bern 60, Switzerland.
- Department of Psychology, Faculty of Psychology, Airlangga University, Campus B UNAIR, Surabaya, East Java 60286, Indonesia.
Abstract
Efforts to predict schizophrenia risk using biological data have been hampered by the heterogeneity of current "clinical-high-risk" (CHR-P) criteria, which pool phenomenologically and biologically distinct syndromes under a single label. In particular, the field has focused almost exclusively on ultra-high-risk (UHR) symptoms, while cognitive basic symptoms (COGDIS)-despite their close alignment with schizophrenia's core features such as formal thought disorder-have remained underutilised. To date, no study has directly compared brain signatures of different CHR-P definitions with respect to their similarity to schizophrenia and their diagnostic, biopsychosocial, and prognostic profiles. We applied machine learning to structural MRI data from 1,425 patients (CHR-P subgroups, recent-onset psychosis, depression) and 907 healthy controls to derive and compare diagnostic brain signatures for Cognitive Disturbances (COGDIS), Ultra-High-Risk (UHR), their overlap (MIXED), and schizophrenia. The MIXED and UHR signatures lacked diagnostic separability and similarity with schizophrenia. Contrarily, the COGDIS signature distinguished patients from controls (BAC=69%, P < .001) and aligned with the schizophrenia signature (r = 0.60), involving shared fronto-parieto-perisylvian volume reductions. UHR was characterised by volume enlargements, whereas MIXED exhibited a mixed pattern of reductions and enlargements relative to healthy controls. COGDIS and schizophrenia signature expressions were predictable with 12%-21% variance explained based on polygenic, cognitive, and exposomal factors both in a transdiagnostic patient cohort and in healthy controls. Their expressions increased from health to schizophrenia. MIXED signature expression was also predictable from biopsychosocial data, but with higher explained variance in patient samples (21%) than in healthy controls (3%). UHR signature expression showed no significant biopsychosocial predictability in either group. Cell-enriched polygenic risk profiles differed across signatures, with COGDIS and schizophrenia showing enrichment patterns implicated in neurodevelopmental processes, while MIXED being associated with immune- and blood-brain-barrier-related enrichments. Longitudinally, COGDIS and schizophrenia brain scores stratified patients with functional disability, while UHR scores predicted better outcomes. Together, these findings indicate that psychosis-risk syndromes differ markedly in the diagnostic specificity, biopsychosocial informativeness and prognostic value of their underlying brain signatures. UHR symptoms are linked to a weak and diagnostically unspecific brain pattern, while the MIXED phenotype is characterised by a dimensional, transdiagnostic signature enriched across early psychotic and affective disease states. In contrast, COGDIS aligns with a neurodevelopmentally grounded vulnerability pattern that converges with schizophrenia's cognitive-disorganisation dimension. These distinctions support a biologically informed reconceptualization of psychosis risk, with cognitive basic symptoms capturing a core liability dimension of schizophrenia, while other risk states reflecting more transient processes underlying psychotic symptom expression.