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Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers
Open accessAbstract
OBJECTIVE: Clinical phenomenology remains the primary means for classifying psychoses despite considerable evidence that this method incompletely captures biologically meaningful differentiations. Rather than relying on clinical diagnoses as the gold standard, this project drew on neurobiological heterogeneity among psychosis cases to delineate subgroups independent of their phenomenological manifestations. METHOD: A large biomarker panel (neuropsychological, stop signal, saccadic control, and auditory stimulation paradigms) characterizing diverse aspects of brain function was collected on individuals with schizophrenia, schizoaffective disorder, and bipolar disorder with psychosis (N=711), their first-degree relatives (N=883), and demographically comparable healthy subjects (N=278). Biomarker variance across paradigms was exploited to create nine integrated variables that were used to capture neurobiological variance among the psychosis cases. Data on external validating measures (social functioning, structural magnetic resonance imaging, family biomarkers, and clinical information) were collected. RESULTS: Multivariate taxometric analyses identified three neurobiologically distinct psychosis biotypes that did not respect clinical diagnosis boundaries. The same analysis procedure using clinical DSM diagnoses as the criteria was best described by a single severity continuum (schizophrenia worse than schizoaffective disorder worse than bipolar psychosis); this was not the case for biotypes. The external validating measures supported the distinctiveness of these subgroups compared with clinical diagnosis, highlighting a possible advantage of neurobiological versus clinical categorization schemes for differentiating psychotic disorders. CONCLUSIONS: These data illustrate how multiple pathways may lead to clinically similar psychosis manifestations, and they provide explanations for the marked heterogeneity observed across laboratories on the same biomarker variables when DSM diagnoses are used as the gold standard.
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“Indeed, clusters of individuals with neural network alterations have been identified in depression [7–8], psychotic disorders [9] and attention-deficit/hyperactivity disorder (ADHD [10]).”
From Toward a neurocircuit-based taxonomy to guide treatment of obsessive-compulsive disorder (2021) · cites this paper as [9]
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Resting-state connectivity biomarkers define neurophysiological subtypes of depression
Drysdale, A. T., Grosenick, L., Downar, J., Dunlop, K., Mansouri, F., Meng, Y., Fetcho, R. N., Zebley, B., Oathes, D. J., Etkin, A., et al. (2017) · Nature Medicine · doi:10.1038/nm.4246 · Cited by 2,170
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Metadata
- Authors
- Clementz, B. A., Sweeney, J. A., Hamm, J. P., Ivleva, E. I., Ethridge, L. E., Pearlson, G. D., Keshavan, M. S., & Tamminga, C. A.
- Affiliations
- Hartford Hospital (US)
- ORCID
- Venue
- American Journal of Psychiatry
- Published
- 2016-04-01
- Volume
- 173
- Issue
- 4
- Pages
- 373-384
- ISSN
- 0002-953X (ISSN-L)
- 1535-7228
- PMC
- PMC5314432
- OpenAlex
- W2190536949
- Cited by
- 768
- References
- 50
- Citations by year
- 2026: 64 · 2025: 59 · 2024: 58 · 2023: 61 · 2022: 70 · 2021: 78 · 2020: 72 · 2019: 122 · 2018: 68 · 2017: 75 · 2016: 40
- FWCI
- 49.56
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- American Journal of Psychiatry (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institute of Mental Health (R01MH077852, MH‐077945, MH 077852, R01MH077851, MH-078113, MH077851, R01MH096913, MH‐077862, R01MH078113, R01MH077862, R01MH077945)
- Topics
- Health Sciences › Medicine › Psychiatry and Mental health › Schizophrenia research and treatment
- Social Sciences › Arts and Humanities › Philosophy › Mental Health and Psychiatry
- Health Sciences › Medicine › Psychiatry and Mental health › Bipolar Disorder and Treatment
- Keywords
- schizophrenia, schizoaffective disorder, taxometric analysis, neuropsychological assessment, stop-signal task, auditory stimulation, first-degree relatives, social functioning, structural MRI
- MeSH terms
- Acoustic Stimulation, Adult, Bipolar Disorder, Brain, Electroencephalography, Evoked Potentials, Auditory, Family, Female, Humans, Magnetic Resonance Imaging, Male, Middle Aged, Neuropsychological Tests, Phenotype, Psychotic Disorders, Saccades, Schizophrenia, Schizophrenic Psychology, Case-Control Studies, Young Adult
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