4.5 Article

Testing Psychosis Phenotypes From Bipolar-Schizophrenia Network for Intermediate Phenotypes for Clinical Application: Biotype Characteristics and Targets

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ELSEVIER
DOI: 10.1016/j.bpsc.2020.03.011

Keywords

Biomarkers; Computational neuroscience; Neurobiological; Precision medicine; Psychopathology; Transdiagnostic

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Funding

  1. National Institute of Mental Health (NIMH) through its the Bipolar-Schizophrenia Network for Intermediate Phenotypes [MH077851, MH078113, MH077945, MH096942, MH096957]
  2. NIMH [1K23 MH102656, T32MHo76690, P50MH096890]
  3. National Institute on Alcohol Abuse and Alcoholism
  4. National Institute on Drug Abuse
  5. National Highway Traffic Safety Administration
  6. National Institute of Diabetes and Digestive and Kidney Diseases
  7. Bear Foundation
  8. Natalia Foundation
  9. National Institutes of Health [HL143440]

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BACKGROUND: Psychiatry aspires to the molecular understanding of its disorders and, with that knowledge, to precision medicine. Research supporting such goals in the dimension of psychosis has been compromised, in part, by using phenomenology alone to estimate disease entities. To this end, we are proponents of a deep phenotyping approach in psychosis, using computational strategies to discover the most informative phenotypic fingerprint as a promising strategy to uncover mechanisms in psychosis. METHODS: Doing this, the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP) has used biomarkers to identify distinct subtypes of psychosis with replicable biomarker characteristics. While we have presented these entities as relevant, their potential utility in clinical practice has not yet been demonstrated. RESULTS: Here we carried out an analysis of clinical features that characterize biotypes. We found that biotypes have unique and defining clinical characteristics that could be used as initial screens in the clinical and research settings. Differences in these clinical features appear to be consistent with biotype biomarker profiles, indicating a link between biological features and clinical presentation. Clinical features associated with biotypes differ from those associated with DSM diagnoses, indicating that biotypes and DSM syndromes are not redundant and are likely to yield different treatment predictions. We highlight 3 predictions based on biotype that are derived from individual biomarker features and cannot be obtained from DSM psychosis syndromes. CONCLUSIONS: In the future, biotypes may prove to be useful for targeting distinct molecular, circuit, cognitive, and psychosocial therapies for improved functional outcomes.

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