Latent Brain-Symptom Dimensions Characterize Heterogeneity in Clinical High Risk for Psychosis
- 1Key Laboratory of Cognition and Personality, Ministry of Education, Faculty of Psychology, Southwest University, Chongqing, 400715, China.
Abstract
BACKGROUNDClinical high risk (CHR) for psychosis is characterized by substantial heterogeneity in symptoms, functioning, and outcomes. Although distributed resting-state functional connectivity (RSFC) abnormalities have been reported, it remains unclear whether this heterogeneity can be organized into consistent multivariate brain-symptom dimensions and clinically meaningful subgroups.
METHODSWe analyzed RSFC and 34 clinical variables from 701 CHR participants in the Accelerating Medicines Partnership(R) Schizophrenia Program (AMP(R) SCZ). Partial least squares analysis identified latent brain-symptom dimensions, which were further examined using transcriptomic annotation, independent psychosocial and cognitive measures, hierarchical clustering, and Month 2 follow-up data.
RESULTSTwo significant brain-symptom dimensions emerged. The first reflected general psychopathology and was associated with somatomotor-salience and higher-order connectivity, with enrichment for genes related to neuronal development. The second, capturing symptom differentiation, spanned negative/internalizing features with psychobehavioral overactivation and involved cerebellar-thalamic-somatomotor circuitry, with enrichment for genes related to synaptic signaling. These dimensions showed dissociable associations with broader psychosocial and cognitive measures, and their loading patterns were substantially reproducible at Month 2. Clustering based on these dimensions identified two biotypes with distinct clinical and connectivity profiles that remained broadly similar at Month 2 despite divergent short-term RSFC changes.
CONCLUSIONSThese findings support complementary dimensional and categorical representations of CHR heterogeneity that link clinical variation with distributed brain connectivity and molecular signatures, while demonstrating short-term reproducibility of the identified dimensions and divergent RSFC changes across biotypes. This multilevel framework may help characterize biologically meaningful variation in psychosis risk.
Related
- Machine learning-derived Alzheimer's disease dimensions: neuroanatomical, cognitive, clinical, functional, and genetic risk heterogeneity signatures
- Beyond criminal intent: infant-directed violence as a symptom of postpartum psychosis
- Statistical models to characterize colon tumor stiffness heterogeneity through representative atomic force microscopy maps
- Nicotine and Cannabis Co-Use are Associated with Higher Symptom Burden than Use of Either Drug Alone in Early Psychosis: Results from a Multisite Study
- Exploring sex-specific symptom trajectories in psychosis following metacognitive training (MCT): Evidence from a large-scale retrospective harmonized database
BibTeX
@misc{feng2026latent,
title = {{Latent Brain-Symptom Dimensions Characterize Heterogeneity in Clinical High Risk for Psychosis}},
author = {J. Feng and S. Genon and S. B. Eickhoff and F. Li and L. Jiang and Y. Wang and D. Dong},
howpublished = {medRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.08.26364664},
url = {https://www.medrxiv.org/content/10.64898/2026.10.08.26364664v1},
note = {CC BY-NC-ND},
}
RIS
TY - UNPB
TI - Latent Brain-Symptom Dimensions Characterize Heterogeneity in Clinical High Risk for Psychosis
AU - J. Feng
AU - S. Genon
AU - S. B. Eickhoff
AU - F. Li
AU - L. Jiang
AU - Y. Wang
AU - D. Dong
PY - 2026
DA - 2026/10/08
PB - medRxiv
DO - 10.64898/2026.10.08.26364664
UR - https://www.medrxiv.org/content/10.64898/2026.10.08.26364664v1
AB - BACKGROUNDClinical high risk (CHR) for psychosis is characterized by substantial heterogeneity in symptoms, functioning, and outcomes. Although distributed resting-state functional connectivity (RSFC) abnormalities have been reported, it remains unclear whether this heterogeneity can be organized into consistent multivariate brain-symptom dimensions and clinically meaningful subgroups. METHODSWe analyzed RSFC and 34 clinical variables from 701 CHR participants in the Accelerating Medicines Partnership(R) Schizophrenia Program (AMP(R) SCZ). Partial least squares analysis identified latent brain-symptom dimensions, which were further examined using transcriptomic annotation, independent psychosocial and cognitive measures, hierarchical clustering, and Month 2 follow-up data. RESULTSTwo significant brain-symptom dimensions emerged. The first reflected general psychopathology and was associated with somatomotor-salience and higher-order connectivity, with enrichment for genes related to neuronal development. The second, capturing symptom differentiation, spanned negative/internalizing features with psychobehavioral overactivation and involved cerebellar-thalamic-somatomotor circuitry, with enrichment for genes related to synaptic signaling. These dimensions showed dissociable associations with broader psychosocial and cognitive measures, and their loading patterns were substantially reproducible at Month 2. Clustering based on these dimensions identified two biotypes with distinct clinical and connectivity profiles that remained broadly similar at Month 2 despite divergent short-term RSFC changes. CONCLUSIONSThese findings support complementary dimensional and categorical representations of CHR heterogeneity that link clinical variation with distributed brain connectivity and molecular signatures, while demonstrating short-term reproducibility of the identified dimensions and divergent RSFC changes across biotypes. This multilevel framework may help characterize biologically meaningful variation in psychosis risk.
ER -