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Serum neuronal autoantibodies, such as those to the NMDA receptor (NMDAR), are detectable in a subgroup of patients with psychotic disorders. It is not known if they are present before the onset of psychosis or whether they are associated with particular clinical features or outcomes. In a case-control study, sera from 254 subjects at clinical high risk (CHR) for psychosis and 116 healthy volunteers were tested for antibodies against multiple neuronal antigens implicated in CNS autoimmune disorders, using fixed and live cell-based assays (CBAs). Within the CHR group, the relationship between NMDAR antibodies and symptoms, cognitive function and clinical outcomes over 24 month follow-up was examined. CHR subjects were not more frequently seropositive for neuronal autoantibodies than controls (8.3% vs. 5.2%; OR = 1.50; 95% CI: 0.58-3.90). The NMDAR was the most common target antigen and NMDAR IgGs were more sensitively detected with live versus fixed CBAs (p < 0.001). Preliminary phenotypic analyses revealed that within the CHR sample, the NMDAR antibody seropositive subjects had higher levels of current depression, performed worse on the Rey Auditory Verbal Learning Task (p < 0.05), and had a markedly lower IQ (p < 0.01). NMDAR IgGs were not more frequent in subjects who later became psychotic than those who did not. NMDAR antibody serostatus and titre was associated with poorer levels of functioning at follow-up (p < 0.05) and the presence of a neuronal autoantibody was associated with larger amygdala volumes (p < 0.05). Altogether, these findings demonstrate that NMDAR autoantibodies are detectable in a subgroup of CHR subjects at equal rates to controls. In the CHR group, they are associated with affective psychopathology, impairments in verbal memory, and overall cognitive function: these findings are qualitatively and individually similar to core features of autoimmune encephalitis and/or animal models of NMDAR antibody-mediated CNS disease. Overall the current

Background The prevalence of antibodies to Toxoplasma gondii, a ubiquitous parasitic protozoan causing the infectious disease toxoplasmosis, is increased in patients with psychotic disorders compared to the general population. We have previously shown that antibody titers for T.gondii correlate with the severity of positive symptoms in young people at ultra-high risk (UHR) for psychosis, suggesting that infection with T. gondii may be relevant to the manifestation of psychosis. However, it is unclear if T. gondii antibodies represent a risk factor for psychosis onset or non-psychotic outcome in UHR individuals. The aim of the present study was to examine whether seropositivity for T.gondii is associated with transition to psychosis and other outcomes in young people at UHR for psychosis. Methods The study sample consisted of 96 individuals at UHR for psychosis who were referred to the Personal Assistance and Crisis Evaluation (PACE) clinic in Melbourne, Australia, between 2001 and 2004, consented to optional blood tests for infectious agents and were followed up for up to 10 years after baseline (median (interquartile range) duration of follow-up: 7.15 (3.14 – 7.72) years). Serum IgG antibodies to six viral and parasitic pathogens (Toxoplasma gondii, Herpes Simplex Virus Type 1 and 2, Cytomegalovirus, Epstein Barr Virus, Varicella-Zoster Virus) were measured at baseline. Outcome measures included transition to psychosis, general psychiatric symptomatology and positive psychotic symptoms (BPRS), negative symptoms (SANS), depressive symptoms (HAM-D), anxiety symptoms (HAM-A) and functioning (SOFAS and GAF). Cox proportional hazards regression and linear regression models were used to examine the associations of seropositivity and antibody titers at baseline and transition to psychosis and other outcomes at follow-up. Results A total of 17 individuals (17.7%) were seropositive for Toxoplasma gondii at baseline. The rate of transition to psychosis was higher am

Precision psychiatry is attracting increasing attention lately as a recognized priority. One of the goals of precision psychiatry is to develop tools capable of aiding a clinically informed psychiatric diagnosis objectively. Cognitive, inflammatory and immunological factors are altered in both bipolar disorder (BD) and schizophrenia (SZ), however, most of these alterations do not respect diagnostic boundaries from a phenomenological perspective and possess great variability in different individuals with the same phenotypic diagnosis and, consequently, none so far has proven to have the ability of reliably aiding in the differential diagnosis of BD and SZ. We developed a probabilistic multi-domain data integration model consisting of immune and inflammatory biomarkers in peripheral blood and cognitive biomarkers using machine learning to predict diagnosis of BD and SZ. A total of 416 participants, being 323, 372, and 279 subjects for blood, cognition and combined biomarkers analysis, respectively. Our multi-domain model performances for the BD vs. control (sensitivity 80% and specificity 71%) and for the SZ vs. control (sensitivity 84% and specificity 81%) pairs were high in general, however, our multi-domain model had only moderate performance for the differential diagnosis of BD and SZ (sensitivity 71% and specificity 73%). In conclusion, our results show that the diagnosis of BD and of SZ, and that the differential diagnosis of BD and SZ can be predicted with possible clinical utility by a computational machine learning algorithm employing blood and cognitive biomarkers, and that their integration in a multi-domain outperforms algorithms based in only one domain. Independent studies are needed to validate these findings.