Identification of Distinct Psychosis Biotypes Using Brain-Based Biomarkers

Abstract

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.

On the brain structure heterogeneity of autism: Parsing out acquisition site effects with significance‐weighted principal component analysis

“…However, these effects have a stronger impact in psychiatric conditions where the atypical radiological signs on MRI are often subtle and require large samples of patients to observe on‐average differences relative to control samples. Recent meta‐analyses point to differences being inconsistently reported in schizophrenia [Friedman and Glover, 2006; Turner et al, 2013], psychosis [Clementz et al, 2016; Wang et al, 2015], and ASD (using the multi‐centre ABIDE database) [Haar et al, 2014]. …”

Kraepelin’s Crumbling Twin Pillars: Using Biology to Reconstruct Psychiatric Nosology From the Bottom Up

“…One of the most exciting efforts in this regard is the Bipolar-Schizophrenia Network on Intermediate Phenotypes project, which attempts to redefine psychotic disorders from the bottom up (2,7). In this ambitious study, a large cohort of individuals diagnosed with schizophrenia, schizoaffective disorder, or psychotic bipolar disorder type I, in addition to first-degree relatives and healthy control subjects, have been recruited for clinical characterization and phenotyping.…”

“…In their first published work, the Bipolar-Schizophrenia Network on Intermediate Phenotypes investigators described a novel approach that was designed to be agnostic to clinical diagnoses (2,7). They began by collecting data on a wide range of potential biomarkers, including tests of cognitive control, electrophysiologic measures of sensorimotor reactivity, and both functional and structural neuroimaging.…”

“…They began by collecting data on a wide range of potential biomarkers, including tests of cognitive control, electrophysiologic measures of sensorimotor reactivity, and both functional and structural neuroimaging. From this panel, they identified six biomarkers with which they were able to parse the study population into three neurobiologically distinct groups that they named “Biotypes” (2,7). Of note, the defining features of each Biotype were distinct from those used to categorize clinical populations in the past—indeed, most could not be observed during a standard clinical interview.…”

“…Of note, the defining features of each Biotype were distinct from those used to categorize clinical populations in the past—indeed, most could not be observed during a standard clinical interview. Moreover, not only did the Biotypes show within-group homogeneity, but also they crossed traditional diagnostic boundaries: all three classic diagnoses were represented in each Biotype, therefore challenging the notion of a “continuum” (2,7). These data illustrate how we may now be in a position to reclassify a syndrome into diseases with multiple, distinct underlying causes (Figure 1).…”