Search

The etiology of psychotic disorders is still unknown, but in a subgroup of patients symptoms might be caused by an autoimmune reaction. In this study, we tested patterns of autoimmune reactivity against potentially novel hippocampal antigens. Serum of a cohort of 621 individuals with psychotic disorders and 257 controls were first tested for reactivity on neuropil of rat brain sections. Brain reactive sera (67 diseased, 27 healthy) were further tested for antibody binding to glutamic acid decarboxylase (GAD) isotype 65 and 67 by cell-based assay (CBA). A sub-cohort of 199 individuals with psychotic disorders and 152 controls was tested for the prevalence of anti-nuclear antibodies (ANA) on HEp2-substrate as well as for reactivity to double-stranded DNA, ribosomal P (RPP), and cardiolipin (CL). Incubation of rat brain with serum resulted in unidentified hippocampal binding patterns in both diseased and control groups. Upon screening with GAD CBA, one of these patterns was identified as GAD65 in one individual with schizophrenia and also in one healthy individual. Two diseased and two healthy individuals had low antibody levels targeting GAD67 by CBA. Antibody reactivity on HEp-2-substrate was increased in patients with schizoaffective disorder, but only in 3 patients did antibody testing hint at a possible diagnosis of systemic lupus erythematosus. Although reactivity of serum to intracellular antigens might be increased in patients with psychotic disorder, no specific targets could be identified. GAD antibodies are very rare and do not seem increased in serum of patients with psychotic disorders. ispartof: Schizophrenia Research vol:228 pages:462-471 ispartof: location:Netherlands status: Published online

BACKGROUND: Bipolar disorder (BD) is a costly, devastating and life shortening mental disorder that is often misdiagnosed, especially on initial presentation. Misdiagnosis frequently results in ineffective treatment. We investigated the utility of a biomarker panel as a diagnostic test for BD. METHODS AND FINDINGS: We performed a meta-analysis of eight case-control studies to define a diagnostic biomarker panel for BD. After validating the panel on established BD patients, we applied it to undiagnosed BD patients. We analysed 249 BD, 122 pre-diagnostic BD, 75 pre-diagnostic schizophrenia and 90 first onset major depression disorder (MDD) patients and 371 controls. The biomarker panel was identified using ten-fold cross-validation with lasso regression applied to the 87 analytes available across the meta-analysis studies. We identified 20 protein analytes with excellent predictive performance [area under the curve (AUC)?0.90]. Importantly, the panel had a good predictive performance (AUC 0.84) to differentiate 12 misdiagnosed BD patients from 90 first onset MDD patients, and a fair to good predictive performance (AUC 0.79) to differentiate between 110 pre-diagnostic BD patients and 184 controls. We also demonstrated the disease specificity of the panel. CONCLUSIONS: An early and accurate diagnosis has the potential to delay or even prevent the onset of BD. This study demonstrates the potential utility of a biomarker panel as a diagnostic test for BD. We would like to thank all participants of this study as well as all participating centres for the collaboration and for access to the serum samples. We gratefully acknowledge support by the Stanley Medical Research Institute (no. 07R-1888). The infrastructure for the NESDA study (www.nesda.nl) has been funded through the Geestkracht program of the Netherlands Organisation for Health Research and Development (Zon-Mw, grant number 10-000-1002) and participating universities (VU University Medical Center, Leiden University Medical Center, University Medical Center Groningen). DNC, DWN and NSW efforts were funded by the Stanley Medical Research Institute and the US Department of the Army.

There is a major unmet clinical need for molecular blood-based biomarkers in studies of major psychiatric disorders. Thus far, identification of such biomarkers has been sparse, most likely due to the fact that this is reliant on long-standing diagnostic concepts used in psychiatry, which are notoriously heterogeneous. Also, identification of biomarkers for a syndrome that has already been categorized based on clinical phenomenology is not useful in the clinic. This chapter describes the need for innovative approaches for identification of biomarkers which can been used to classify at-risk patients such as youngsters with prodromal symptoms for psychosis and existing patients who are likely to progress to more severe states. The authors argued for the use of broader categories of related patients and to deconstruct the traditional diagnoses in favor of molecular biomarker profiles.