Project description:Analysis of gene-expression changes in depressed subjects with bipolar disorder compared to healthy controls. Results provide information on pathways that may be involved in the pathogenesis of bipolar depression. Total RNA isolated from PAXgene blood RNA tubes from 20 depressed subjects with bipolar disorder and 15 healthy controls.
Project description:Analysis of gene-expression changes in depressed subjects with bipolar disorder compared to healthy controls. Results provide information on pathways that may be involved in the pathogenesis of bipolar depression.
Project description:RNA was extracted from peripheral blood mononuclear cells (PBMC) of 24 adult healthy controls, 8 adult patients with bipolar disorder, and 21 adult patients with major depressive disorder to analyze gene expression patterns that identify biomarkers of disease and that may be correlated with fMRI data.
Project description:This SuperSeries is composed of the following subset Series:; GSE5388: Adult postmortem brain tissue (dorsolateral prefrontal cortex) in subjects with bipolar disorder; GSE5389: Adult postmortem brain tissue (ortibtofrontal cortex) in subjects with bipolar disorder; Bipolar affective disorder is a severe psychiatric disorder with a strong genetic component but unknown pathophysiology. We used microarray technology (Affymetrix HG-U133A GeneChips) to determine the expression of approximately 22 000 mRNA transcripts in post-mortem brain tissue (dorsolateral prefrontal cortex and orbitofrontal cortex) from patients with bipolar disorder and matched healthy controls. Experiment Overall Design: Refer to individual Series
Project description:There are currently no biological tests that differentiate patients with bipolar disorder (BPD) from healthy controls. While there is evidence that peripheral gene expression differences between patients and controls can be utilized as biomarkers for psychiatric illness, it is unclear whether current use or residual effects of antipsychotic and mood stabilizer medication drives much of the differential transcription. We therefore tested whether expression changes in first-episode, never-medicated bipolar patients, can contribute to a biological classifier that is less influenced by medication and could potentially form a practicable biomarker assay for BPD. We employed microarray technology to measure global leukocyte gene expression in first-episode (n=3) and currently medicated BPD patients (n=26), and matched healthy controls (n=25). Following an initial feature selection of the microarray data, we developed a cross-validated 10-gene model that was able to correctly predict the diagnostic group of the training sample (26 medicated patients and 12 controls), with 89% sensitivity and 75% specificity (p<0.001). The 10-gene predictor was further explored via testing on an independent test cohort consisting of three pairs of monozygotic twins discordant for BPD, plus the original enrichment sample cohort (the three never-medicated BPD patients and 13 matched control subjects), and a sample of experimental replicates (n=34). 83% of the independent test sample was correctly predicted, with a sensitivity of 67% and specificity of 100% (although this result did not reach statistical significance). Additionally, 88% of sample diagnostic classes were classified correctly for both the enrichment (p=0.015) and the replicate samples (p<0.001). Peripheral blood leukocytes (PBLs) from whole blood were collected from 26 patients with bipolar disorder who had previously received medication, three patients with bipolar disorder who were experiencing their first hospitalization and had not previously received medication, and 25 matched control subjects, for RNA extraction and hybridization on Affymetrix microarrays. Immediately after blood collection, blood samples were split into two (when a sufficient volume had been collected); an "1" and replicate "2" sample (thus two separate RNA extractions, cDNA and cRNA syntheses and array hybridizations were performed).
Project description:Bipolar affective disorder is a severe psychiatric disorder with a strong genetic component but unknown pathophysiology. We used microarray technology (Affymetrix HG-U133A GeneChips) to determine the expression of approximately 22 000 mRNA transcripts in post-mortem brain tissue (dorsolateral prefrontal cortex) from patients with bipolar disorder and matched healthy controls. A cohort of 70 subjects was investigated and the final analysis included 30 bipolar and 31 control subjects. Differences between disease and control groups were identified using a rigorous statistical analysis with correction for confounding variables and multiple testing. Keywords: disease state analysis
Project description:Bipolar affective disorder is a severe psychiatric disorder with a strong genetic component but unknown pathophysiology. We used microarray technology (Affymetrix HG-U133A GeneChips) to determine the expression of approximately 22 000 mRNA transcripts in post-mortem brain tissue (dorsolateral prefrontal cortex) from patients with bipolar disorder and matched healthy controls. A cohort of 70 subjects was investigated and the final analysis included 30 bipolar and 31 control subjects. Differences between disease and control groups were identified using a rigorous statistical analysis with correction for confounding variables and multiple testing.
Project description:Bipolar affective disorder is a severe psychiatric disorder with a strong genetic component but unknown pathophysiology. We used microarray technology (Affymetrix HG-U133A GeneChips) to determine the expression of approximately 22 000 mRNA transcripts in post-mortem brain tissue (orbitofrontal cortex) from patients with bipolar disorder and matched healthy controls. Orbitofrontal cortex tissue from a cohort of 30 subjects was investigated and the final analysis included 10 bipolar and 11 control subjects. Differences between disease and control groups were identified using a rigorous statistical analysis with correction for confounding variables and multiple testing.