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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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Citations
Cites
Diagnostic and Statistical Manual of Mental Disorders
American Psychiatric Association (2013) · doi:10.1176/appi.books.9780890425596 · Cited by 116,369
Data clustering: 50 years beyond K-means
Jain, A. K. (2009) · Pattern Recognition Letters · doi:10.1016/j.patrec.2009.09.011 · Cited by 10,021
Insel, T., Cuthbert, B., Garvey, M., Heinssen, R., Pine, D. S., Quinn, K., Sanislow, C., & Wang, P. (2010) · American Journal of Psychiatry · doi:10.1176/appi.ajp.2010.09091379 · Cited by 7,067
Estimating the Number of Clusters in a Data Set Via the Gap Statistic
Tibshirani, R., Walther, G., & Hastie, T. (2001) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/1467-9868.00293 · Cited by 6,205
The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups
METABRIC Group, Curtis, C., Shah, S. P., Chin, S.-F., Turashvili, G., Rueda, O. M., Dunning, M. J., Speed, D., Lynch, A. G., Samarajiwa, S., et al. (2012) · Nature · doi:10.1038/nature10983 · Cited by 6,097
Leucht, S., Cipriani, A., Spineli, L., Mavridis, D., Örey, D., Richter, F., Samara, M., Barbui, C., Engel, R. R., Geddes, J. R., et al. (2013) · The Lancet · doi:10.1016/s0140-6736(13)60733-3 · Cited by 2,561
Preterm labor: One syndrome, many causes
Romero, R., Dey, S. K., & Fisher, S. J. (2014) · Science · doi:10.1126/science.1251816 · Cited by 1,984
The Family History Method Using Diagnostic Criteria
Andreasen, N. C. (1977) · Archives of General Psychiatry · doi:10.1001/archpsyc.1977.01770220111013 · Cited by 1,903
Keefe, R. (2004) · Schizophrenia Research · doi:10.1016/j.schres.2003.09.011 · Cited by 1,573
K -means clustering via principal component analysis
Ding, C. H. Q., & He, X. (2004) · doi:10.1145/1015330.1015408 · Cited by 1,412
Research works printed but not linked: 7
- Bethune G, 2010, J Thorac Dis, 2, 48
- National Research Council (US), 2011, Committee on a Framework for Developing a New Taxonomy of Disease: Toward Precision Medicine: Building a Knowledge Network for Biomedical Research and a New Taxonomy of Disease
- Hyman SE, Cerebrum
- Zanarini MC, 1996, Diagnostic Interview for DSM-IV Personality Disorders (DIPD-IV)
- Iacono WG, 1993, Prog Exp Pers Psychopathol Res, 16, 11
- Friston KJ, 1995, Clin Neurosci, 3, 89
- Rosenberg RN, 2014, Rosenberg’s Molecular and Genetic Basis of Neurological and Psychiatric Diseases
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(2016) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.140304
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(2018) · FOCUS The Journal of Lifelong Learning in Psychiatry · doi:10.1176/appi.focus.160202
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Reviewer #1 (Public Review): The scheduling of adolescence with Netrin-1 and UNC5C
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Reviewer #2 (Public Review): The scheduling of adolescence with Netrin-1 and UNC5C
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Watson, C. J., Zvrskovec, J., Merola, G. P., Gilchrist, L., Haussler, S. M., Schattner, M., Lo, C. W. H., Breen, G. D., Murray, R. M., Lewis, C. M., et al. (2024) · medRxiv · doi:10.1101/2024.10.23.24315121
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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
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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