Abstract
Autoimmune processes are suspected to play a role in the pathophysiology of psychotic disorders. Better understanding of the associations between auto-immunoglobulin G (IgG) repertoires and clinical features of mental illness could yield novel models of the pathophysiology of psychosis, and markers for biological patient stratification. We undertook cross-sectional detection and quantification of auto-IgGs in peripheral blood plasma of 461 people (39% females) with established psychotic disorder diagnoses. Broad screening of 24 individuals was carried out on group level in eight clinically defined groups using planar protein microarrays containing 42,100 human antigens representing 18,914 proteins. Autoantibodies indicated by broad screening and in the previous literature were measured using a 380-plex bead-based array for autoantibody profiling of all 461 individuals. Associations between autoantibody profiles and dichotomized clinical characteristics were assessed using a stepwise selection procedure. Broad screening and follow-up targeted analyses revealed highly individual autoantibody profiles. Females, and people with family histories of obesity or of psychiatric disorders other than schizophrenia had the highest overall autoantibody counts. People who had experienced subjective thought disorder and/or were treated with clozapine (trend) had the lowest overall counts. Furthermore, six autoantibodies were associated with specific psychopathology symptoms: anti-AP3B2 (persecutory delusions), anti-TDO2 (hallucinations), anti-CRYGN (initial insomnia); anti-APMAP (poor appetite), anti-OLFM1 (above-median cognitive function), and anti-WHAMMP3 (anhedonia and dysphoria). Future studies should clarify whether there are causal biological relationships, and whether autoantibodies could be used as clinical markers to inform diagnostic patient stratification and choice of treatment.
Highlights
Mental illnesses with psychosis as a clinical feature such as schizophrenia (SCZ), schizoaffective disorder (SCZAD), bipolar disorder (BD), and psychotic major depressive disorder affect about 3% of the population [1] and are associated with longterm disability and catastrophic outcomes such as suicide
Autoimmunity, characterized by the production of antibodies against the body’s own antigens, is a feature of immune system dysfunction and could play a role in mental disorder pathophysiology. Autoantibodies against neuroreceptors such as the N-methyl-D-aspartate receptor (NMDAR) are found in about 1–5% of various neuropsychiatric patient groups and healthy individuals, and in some cases are causally associated with psychopathology [8]
Meta-analytic epidemiological evidence demonstrates that non-neurological autoimmune disorders are more common in people with mental disorders than in the general population [9] and common auto-immunoglobulin G (IgG) proteins are increased in people with SCZ [10]
Summary
Mental illnesses with psychosis as a clinical feature such as schizophrenia (SCZ), schizoaffective disorder (SCZAD), bipolar disorder (BD), and psychotic major depressive disorder affect about 3% of the population [1] and are associated with longterm disability and catastrophic outcomes such as suicide. Autoimmunity, characterized by the production of antibodies against the body’s own antigens, is a feature of immune system dysfunction and could play a role in mental disorder pathophysiology. Demonstrating the feasibility and potential clinical utility of this approach, a previous untargeted autoimmune profiling study comparing young people with first-episode psychosis and healthy controls identified a novel autoantibody target in the N-terminal portion of the p antigen (PAGE) protein group (PAGE2B/PAGE2/PAGE5), which was found in cases only and associated with the later development of SCZ as opposed to other first-episode psychosis outcomes [13]. As autoantibody data is known to be highly individual [12], we tested these hypotheses using a stepwise selection procedure We based this procedure on clinically relevant assumptions, in order to maximize our chances of identifying associations with potential for translation to clinical practice
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