O3.4. PSYCHOSIS PHENOTYPES FROM B-SNIP FOR CLINICAL ADVANCES: BIOTYPE CHARACTERISTICS AND TARGETS
Authors: Clementz Brett , Trotti Rebekah , Pearlson Godfrey D , Keshavan Matcheri , Gershon Elliot , Keedy Sarah , Ivleva Elena , McDowell Jennifer E , Tamminga Carol 
Published: May 2020

Background

Psychiatry aspires to disease understanding and precision medicine. Biological research supporting such missions in psychosis may be compromised by continued reliance on clinical phenomenology in the search for pathophysiological mechanisms. A transdiagnostic deep phenotyping approach, such as that used by the Bipolar-Schizophrenia Network for Intermediate Phenotypes (B-SNIP), offers a promising strategy for discovery of biological mechanisms underlying psychosis syndromes. The B-SNIP consortium has identified biological subtypes of psychosis, Biotypes, which outperform conventional DSM diagnoses when accounting for variance of multiple external validating measures. While these biological distinctions are scientifically remarkable, their resulting clinical manifestations and potential utility in clinical practice is of paramount importance.

Methods

Approximately 1500 psychosis cases and 450 healthy persons were administered the B-SNIP biomarker battery (including MRI, EEG, ocular motor, and cognition measures). Psychosis cases were also clinically characterized using multiple measures, including MADRS, PANSS, YMRS, and Birchwood. Numerical taxonomy approaches were used for identifying biologically homogenous psychosis subgroups (gap and TWO-STEP cluster identifications, k-means clustering, and canonical discriminant analysis). ANOVA models were used to analyze external validating measures. Multivariate discriminant models were used to identify clinical features differentiating conventional psychosis syndromes and psychosis Biotypes.

Results

There was remarkable similarity between previously published biomarker profiles for DSM psychosis syndromes and a new sample of psychosis cases (average r=.92). Numerical taxonomy on biomarker data recovered three subgroups (replicating previous findings), and the biomarker profiles were highly similar to previous results (average r=.87). Schizoaffective cases were both the most diverse and the most clearly differentiated from schizophrenia and bipolar cases (on conative negative symptoms, depression, and mania) in clinical feature space. The only feature that uniquely distinguished schizophrenia was social-relational negative symptoms. Biotype-1 was characterized by accentuations on clinical features consistent with their biomarker deviations (relational negative symptoms, poor social functioning, and dysfunction of cognition). Alternatively, Biotype-2, also consistent with their biomarker deviations, had clinical features indicating neurophysiological dysregulation (most specifically physiological and behavioral dysregulation). Biotype-3 cases, the most normal across biomarkers, were noticeably absent of Biotype-1 clinical features and had more restricted clinical manifestations than any other Biotype or DSM subgroup. We illustrate three possible Biotype-specific treatment targets.

Discussion

Replication of B-SNIP psychosis Biotypes indicates the possible utility and importance of neurobiological subtyping within psychosis that can yield specific treatment targets. In an analysis of clinical features, B-SNIP found that Biotypes have unique and defining clinical features that are consistent with their neurobiological profiles. Biotypes and DSM psychosis subgroups are neither neurobiologically nor clinically redundant. Specific treatment targets for psychosis Biotypes are not derivable from conventional clinical psychosis diagnoses. B-SNIP outcomes provide a background for future work that could establish psychiatry as a laboratory discipline, at least with regard to care of psychosis patients. This path is hypothetical at the moment but aspirational for the field.