https://ogma.newcastle.edu.au/vital/access/ /manager/Index ${session.getAttribute("locale")} 5 Transcriptomic abnormalities in peripheral blood in bipolar disorder, and discrimination of the major psychoses https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:41878 Tue 16 Aug 2022 10:04:26 AEST ]]> Age effects on cerebral grey matter and their associations with psychopathology, cognition and treatment response in previously untreated schizophrenia patients https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20972 Sat 24 Mar 2018 07:54:21 AEDT ]]> Gene expression profiling in treatment-naive schizophrenia patients identifies abnormalities in biological pathways involving AKT1 that are corrected by antipsychotic medication https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:20137 Sat 24 Mar 2018 07:51:34 AEDT ]]> Transcriptome-wide mega-analyses reveal joint dysregulation of immunologic genes and transcription regulators in brain and blood in schizophrenia https://ogma.newcastle.edu.au/vital/access/ /manager/Repository/uon:25812 postmortem brain tissue, and later in studies of peripheral blood. The collective body of schizophrenia microarray literature contains apparent inconsistencies between studies, with failures to replicate top hits, in part due to small sample sizes, cohort-specific effects, differences in array types, and other confounders. In an attempt to summarize existing studies of schizophrenia cases and non-related comparison subjects, we performed two mega-analyses of a combined set of microarray data from postmortem prefrontal cortices (n = 315) and from ex-vivo blood tissues (n = 578). We adjusted regression models per gene to remove non-significant covariates, providing best-estimates of transcripts dysregulated in schizophrenia. We also examined dysregulation of functionally related gene sets and gene co-expression modules, and assessed enrichment of cell types and genetic risk factors. The identities of the most significantly dysregulated genes were largely distinct for each tissue, but the findings indicated common emergent biological functions (e.g. immunity) and regulatory factors (e.g., predicted targets of transcription factors and miRNA species across tissues). Our network-based analyses converged upon similar patterns of heightened innate immune gene expression in both brain and blood in schizophrenia. We also constructed generalizable machine-learning classifiers using the blood-based microarray data. Our study provides an informative atlas for future pathophysiologic and biomarker studies of schizophrenia.]]> Sat 24 Mar 2018 07:34:35 AEDT ]]>