Identification of distinct psychosis biotypes using brain-based biomarkers

Brett A. Clementz, John A. Sweeney, Jordan P. Hamm, Elena I. Ivleva, Lauren E. Ethridge, Godfrey D. Pearlson, Matcheri S. Keshavan, Carol A. Tamminga

Research output: Contribution to journalArticle

212 Citations (Scopus)

Abstract

Objective: Clinical phenomenology remains the primary means for classifyingpsychosesdespiteconsiderableevidence that this method incompletely captures biologically meaningful differentiations.Rather than relying onclinical 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 functionwascollected 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 varianceamongthe 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 schemesfor differentiatingpsychotic 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.

Original languageEnglish (US)
Pages (from-to)373-384
Number of pages12
JournalAmerican Journal of Psychiatry
Volume173
Issue number4
DOIs
StatePublished - Apr 1 2016

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Psychotic Disorders
Biomarkers
Brain
Schizophrenia
Acoustic Stimulation
Bipolar Disorder
Healthy Volunteers
Multivariate Analysis
Magnetic Resonance Imaging

ASJC Scopus subject areas

  • Psychiatry and Mental health

Cite this

Identification of distinct psychosis biotypes using brain-based biomarkers. / Clementz, Brett A.; Sweeney, John A.; Hamm, Jordan P.; Ivleva, Elena I.; Ethridge, Lauren E.; Pearlson, Godfrey D.; Keshavan, Matcheri S.; Tamminga, Carol A.

In: American Journal of Psychiatry, Vol. 173, No. 4, 01.04.2016, p. 373-384.

Research output: Contribution to journalArticle

Clementz, BA, Sweeney, JA, Hamm, JP, Ivleva, EI, Ethridge, LE, Pearlson, GD, Keshavan, MS & Tamminga, CA 2016, 'Identification of distinct psychosis biotypes using brain-based biomarkers', American Journal of Psychiatry, vol. 173, no. 4, pp. 373-384. https://doi.org/10.1176/appi.ajp.2015.14091200
Clementz, Brett A. ; Sweeney, John A. ; Hamm, Jordan P. ; Ivleva, Elena I. ; Ethridge, Lauren E. ; Pearlson, Godfrey D. ; Keshavan, Matcheri S. ; Tamminga, Carol A. / Identification of distinct psychosis biotypes using brain-based biomarkers. In: American Journal of Psychiatry. 2016 ; Vol. 173, No. 4. pp. 373-384.
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