43Biomarkers are now used in many areas of medicine but are still lacking for psychiatric conditions 44 such as schizophrenia (SCZ). We have used a multiplex molecular profiling approach to measure
52demonstrate for the first time that a biological signature for SCZ can be identified in blood serum. This 53 study lays the groundwork for development of a diagnostic test that can be used as an aid for 54 distinguishing SCZ subjects from healthy controls and from those affected by related psychiatric 55 illnesses with overlapping symptoms.
Autism spectrum conditions have been hypothesized to be an exaggeration of normal male low-empathizing and high-systemizing behaviors. We tested this hypothesis at the molecular level by performing comprehensive multi-analyte profiling of blood serum from adult subjects with Asperger's syndrome (AS) compared with controls. This led to identification of distinct sex-specific biomarker fingerprints for male and female subjects. Males with AS showed altered levels of 24 biomarkers including increased levels of cytokines and other inflammatory molecules. Multivariate statistical classification of males using this panel of 24 biomarkers revealed a marked separation between AS and controls with a sensitivity of 0.86 and specificity of 0.88. Testing this same panel in females did not result in a separation between the AS and control groups. In contrast, AS females showed altered levels of 17 biomarkers including growth factors and hormones such as androgens, growth hormone and insulin-related molecules. Classification of females using this biomarker panel resulted in a separation between AS and controls with sensitivities and specificities of 0.96 and 0.83, respectively, and testing this same panel in the male group did not result in a separation between the AS and control groups. The finding of elevated testosterone in AS females confirmed predictions from the 'extreme male brain' and androgen theories of autism spectrum conditions. We conclude that to understand the etiology and development of autism spectrum conditions, stratification by sex is essential.
We describe the validation of a serum-based test developed by Rules-Based Medicine which can be used to help confirm the diagnosis of schizophrenia. In preliminary studies using multiplex immunoassay profiling technology, we identified a disease signature comprised of 51 analytes which could distinguish schizophrenia (n = 250) from control (n = 230) subjects. In the next stage, these analytes were developed as a refined 51-plex immunoassay panel for validation using a large independent cohort of schizophrenia (n = 577) and control (n = 229) subjects. The resulting test yielded an overall sensitivity of 83% and specificity of 83% with a receiver operating characteristic area under the curve (ROC-AUC) of 89%. These 51 immunoassays and the associated decision rule delivered a sensitive and specific prediction for the presence of schizophrenia in patients compared to matched healthy controls.
Major depressive disorder (MDD) is a leading cause of disability worldwide and results tragically in the loss of almost one million lives in Western societies every year. This is due to poor understanding of the disease pathophysiology and lack of empirical medical tests for accurate diagnosis or for guiding antidepressant treatment strategies. Here, we have used shotgun proteomics in the analysis of post-mortem dorsolateral prefrontal cortex brain tissue from 24 MDD patients and 12 matched controls. Brain proteomes were pre-fractionated by gel electrophoresis and further analyzed by shotgun data-independent label-free liquid chromatography-mass spectrometry. This led to identification of distinct proteome fingerprints between MDD and control subjects. Some of these differences were validated by Western blot or selected reaction monitoring mass spectrometry. This included proteins associated with energy metabolism and synaptic function and we also found changes in the histidine triad nucleotide-binding protein 1 (HINT1), which has been implicated recently in regulation of mood and behavior. We also found differential proteome profiles in MDD with (n=11) and without (n=12) psychosis. Interestingly, the psychosis fingerprint showed a marked overlap to changes seen in the brain proteome of schizophrenia patients. These findings suggest that it may be possible to contribute to the disease understanding by distinguishing different subtypes of MDD based on distinct brain proteomic profiles.
Recent research efforts have progressively shifted towards preventative psychiatry and prognostic identification of individuals before disease onset. We describe the development of a serum biomarker test for the identification of individuals at risk of developing schizophrenia based on multiplex immunoassay profiling analysis of 957 serum samples. First, we conducted a meta-analysis of five independent cohorts of 127 first-onset drug-naive schizophrenia patients and 204 controls. Using least absolute shrinkage and selection operator regression, we identified an optimal panel of 26 biomarkers that best discriminated patients and controls. Next, we successfully validated this biomarker panel using two independent validation cohorts of 93 patients and 88 controls, which yielded an area under the curve (AUC) of 0.97 (0.95–1.00) for schizophrenia detection. Finally, we tested its predictive performance for identifying patients before onset of psychosis using two cohorts of 445 pre-onset or at-risk individuals. The predictive performance achieved by the panel was excellent for identifying USA military personnel (AUC: 0.90 (0.86–0.95)) and help-seeking prodromal individuals (AUC: 0.82 (0.71–0.93)) who developed schizophrenia up to 2 years after baseline sampling. The performance increased further using the latter cohort following the incorporation of CAARMS (Comprehensive Assessment of At-Risk Mental State) positive subscale symptom scores into the model (AUC: 0.90 (0.82–0.98)). The current findings may represent the first successful step towards a test that could address the clinical need for early intervention in psychiatry. Further developments of a combined molecular/symptom-based test will aid clinicians in the identification of vulnerable patients early in the disease process, allowing more effective therapeutic intervention before overt disease onset.
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