MDD2000AFFY
Ontology highlight
ABSTRACT: Sub-study QI: 941 cases of Major Depressive Disorder (MDD) from the Queensland Institute of Medical Research (QIMR), Australia
Sub-study VU: 127 MDD cases from The Netherlands Study of Anxiety and Depression (NESDA) (http://www.nesda.nl) and The Netherlands Twin Registry (NTR) (http://www.tweelingenregister.org) based at the VU Amsterdam, The Netherlands.
Sub-study ED: 373 MDD cases from the University of Edinburgh, UK.
SECONDARY ACCESSION(S): PRJNA217378PRJNA217379
REPOSITORIES: dbGaP
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Project description:Interleukin-18 (IL-18) was one of the inflammatory cytokines and related to major depressive disorder (MDD) and dementia. Compared with Il18+/+ mice, IL-18 knockout (Il18−/−) mice developed impaired learning and memory, more anxiety, and less motivation. To reveal the mechanism, the microarray was performed.
2019-12-31 | GSE108485 | GEO
Project description:This study investigated gene expression changes in whole blood samples obtained from donors diagnosed with major depressive disorder (MDD) compared to healthy controls. Micro-array data were available from whole blood on patients with MDD (N=128, 64 with generalised anxiety disorder, diagnosed by the MINI questionnaire, and 64 without anxiety disorder) and healthy controls (N=64). RNA was isolated from all samples using the standard PAXgene protocol on the Qiagen Biorobot 8000. All samples gave good quality RNA, as assessed by Agilent Bioanalyser. The yield range was 0.86-15.05ug with an average of 6.25ug. Samples were then randomised into batches, with each batch containing a representative number of controls, depression with anxiety and depression without anxiety, and the same ratio of females to males (3:1). 50ng of RNA from each sample was converted to a biotin labeled cDNA probe using NuGEN SPIA amplification. The probes were then hybridized to Affymetrix U133_Plus2.0 Genechips.
2017-05-12 | GSE98793 | GEO
Project description:Major depressive disorder (MDD) is the psychiatric disorder with the highest prevalence in the world. Pharmacological antidepressant treatment (AD), such as selective serotonin reuptake inhibitors [SSRI, i.e. fluoxetine (Flx)] is the first line of treatment for MDD. Despite its efficacy, lack of AD response occurs in numerous patients characterizing Difficult-to-treat Depression. ElectroConvulsive Therapy (ECT) is a highly effective treatment inducing rapid improvement in depressive symptoms and high remission rates of ~50–63% in patients with pharmaco-resistant depression. Nevertheless, the need to develop reliable treatment response predictors to guide personalized AD strategies and supplement clinical observation is becoming a pressing clinical objective. Here, we propose to establish a proteomic peripheral biomarkers signature of ECT response in an anxio/depressive animal model of non-response to AD. Using an emotionality score based on the analysis complementary behavioral tests of anxiety/depression (Elevated Plus Maze, Novelty Suppressed Feeding, Splash Test), we showed that a 4-week corticosterone treatment (35 μg/ml, Cort model) in C57BL/6JRj male mice induced an anxiety/depressive-like behavior. A 28-days chronic fluoxetine treatment (Flx, 18 mg/kg/day) reduced corticosterone-induced increase in emotional behavior. A 50% decrease in emotionality score threshold before and after Flx, was used to separate Flx-responding mice (Flx-R, n=18), or Flx non-responder mice (Flx-NR, n=7). Then, Flx-NR mice received 7 sessions of electroconvulsive seizure (ECS, equivalent to ECT in humans) and blood was collected before and after ECS treatment. Chronic ECS normalized the elevated emotionality observed in Flx-NR mice. Then, proteins were extracted from peripheral blood mononuclear cells (PBMCs) and isolated for proteomic analysis using a high-resolution MS Orbitrap. The proteomic analysis revealed a signature of 33 peripheral proteins associated with response to ECS (7 down- and 26 upregulated). These proteins were previously associated with mental disorders and involved in regulating pathways which participate to the depressive disorder etiology. remark for sample name : ECTR=Flx-NR-ES, C=cort/Veh, CFNR= Flx-NR
2022-11-01 | PXD037392 | Pride
Project description:<p>Identification of genomic regions that confer susceptibility to or protection from major depressive disorder (MDD) via genomewide association.</p> <p><b>Consent groups and participant set</b><br/> <ul> <li>Psychiatric and Related Somatic Conditions (PRSC): 3741 (1821 cases, 1822 controls, 98 others)</li> </ul> </p>
| phs000020.v2.p1 | EGA
Project description:Genome-wide MeDIP-Sequencing of 23 monozygotic twin pairs (n=46) from Australia discordant for major depressive disorder (MDD). MeDIP-seq of 23 monozygotic twin pairs discordant for major depressive disorder. MZ twin pairs were compared to identify significantly differently methylated sites associated with MDD.
2014-01-25 | E-GEOD-54370 | biostudies-arrayexpress
Project description:<p>The objective of the Time-Dependent Proteome Study, was to evaluate changes in the proteome and phosphoproteome when there is a delay in freezing tissues following sample (tumor) excision. The biospecimens used are from patient-derived ovarian cancer tumors.<br><a href="http://www.ncbi.nlm.nih.gov/pubmed/24719451" target="_blank">Ref: Mertins P et al., (2014) Mol Cell Proteomics, Apr 9. E-Publication</a><br><a href="http://www.ncbi.nlm.nih.gov/pubmed/25670172" target="_blank">Ref: Gajadhar, A.S., et al., (2015) Cancer Res. Apr 1;75(7):1495-503. Epub 2015 Feb 10.</a></p><ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S013">https://cptac-data-portal.georgetown.edu/cptac/s/S013</a> on 11/05/18</li></ul>
2018-11-05 | MSV000083107 | MassIVE
Project description:Search for the biomarkers of major depressive disorder (MDD) has facilitated from the genes expressed in the patientâs blood cells. Because the severity of depressive symptoms and characteristics in patients with MDD are differed by the age at onset of first depressive episode, the potential transcriptomic markers in blood cells may also be different by the age at onset of MDD. In this study, we searched the transcriptomic markers of late-onset (onset ages ⥠50 years) MDD (LOD) from the expressed genes in blood cells, and identified state-dependent biomarkers in the patients. We assessed the expressed genes in blood cells by the microarray and found that the expression levels of 3,066 probes were state-dependently changed in the blood cells of patients with LOD. Elderly (age â¥50 years) outpatients and inpatients with MDD corresponding to a DSM-IV diagnosis of the melancholy type of MDD episodes were studied. The depressive state was measured using the Structured Interview Guide for the Hamilton Depression (SIGH-D) rating scale. Syndromal remission was defined as a stage in which a participant did not meet the diagnosis of a MINI major depressive episode for a period of 2 consecutive months and had a SIGH-D score of less than 8. Twelve healthy individuals were also recruited. Blood was obtained from the participants and analyzed using an Agilent SurePrint G3 Human GE 8Ã60K v2 Microarray (Design ID: 039494).
2016-01-14 | E-GEOD-76826 | biostudies-arrayexpress
Project description:Interleukin-18 (IL-18) was one of the inflammatory cytokines and related to major depressive disorder (MDD) and dementia. We previously investigated IL-18 knockout (Il18−/−) mice developed impaired learning and memory, more anxiety, and less motivation comparing to Il18+/+ mice. In the Il18−/− mice with acute stress, both the immobility time in the forced swim test and the tail suspension test were decreased, even though no difference was observed in the Il18+/+ mice. To reveal the mechanism, RNA-Seq was performed.
2022-10-21 | GSE207669 | GEO
Project description:Major depressive disorder (MDD) is one of the most common and disabling mental disorders, and current strategies remain inadequate. Although mesenchymal stromal cells (MSCs) have shown beneficial effects in experimental models of depression, underlying mechanisms remain elusive. Here, using murine depression models, we demonstrated that MSCs could alleviate depressive and anxiety-like behaviors not due to a reduction in proinflammatory cytokines, but rather activation of dorsal raphe nucleus (DRN) 5-hydroxytryptamine (5-HT) neurons. Mechanistically, peripheral delivery of MSCs activated pulmonary innervating vagal sensory neurons, which projected to the nucleus tractus solitarius, inducing the release of 5-HT in DRN. Furthermore, MSC-secreted brain-derived neurotrophic factor activated lung sensory neurons through tropomyosin receptor kinase B (TrkB), and inhalation of a TrkB agonist also achieved significant therapeutic effects in male mice. This study reveals a role of peripheral MSCs in regulating central nervous system function and demonstrates a potential "lung vagal-to-brain axis" strategy for MDD.
2023-10-30 | GSE246290 | GEO
Project description:<a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome" target="_blank">Explore This Study at the NCI Proteomic Data Commons</a><p><a href="http://www.nature.com/nature/journal/vaop/ncurrent/full/nature13438.html" target="_blank">Zhang, B., et al., Nature (2014) doi:10.1038/nature13438 Published online</a></p><p>Proteomes of colon and rectal tumors previously characterized by the Cancer Genome Atlas (TCGA) were analyzed along with integrated proteogenomic analyses. Ninety-five TCGA tumor samples were used in this study from 90 patients, with 5 samples representing different portions from the same tumor. The samples originated from two TCGA cohorts: 64 are from <a href="https://portal.gdc.cancer.gov/projects/TCGA-COAD" target="_blank">Colon Adenocarcinoma (COAD)</a> samples and 31 are from the <a href="https://portal.gdc.cancer.gov/projects/TCGA-READ" target="_blank">Rectum Adenocarcinoma (READ)</a> collection. The primary data from the liquid chromatography-tandem mass spectrometry (LC-MS/MS) global proteomic profiling of each tumor sample is associated with a data set in the table below. Three protein assemblies are provided from different protein database searches.</p><p>TCGA_VU_N95<br/>This assembly reflects the 95 TCGA samples for 90 tumors, spanning three search engines (MS-GF+, MyriMatch, and Pepitome), employing a standard RefSeq database and NIST spectral library.</p><p>TCGA_VU_N95_Custom<br/>The Custom assembly represents the same samples, the sequence database has been augmented with nonsynonymous sequence variants detected by TCGA.<br/></p><p>TCGA_VU_N95-Normal_VU_N60<br/>The third assembly contains the searches of the 95 TCGA samples employed in the first assembly alongside the 60 normal colons analyzed by Vanderbilt University as a control, employing the same three search engines, a standard RefSeq database, and a NIST spectral library.</p><p>TCGA_Colorectal_Cancer_proBAM_PSM_genome_mapping_files<br/>Peptide spectrum matches from the TCGA_VU_N95_Custom IDPicker3 protein assembly were converted to protein BAM (proBAM) format for visualization, available in the metadata folder below.</p><p>COAD tumor sample genomic data can be downloaded from <a href="https://portal.gdc.cancer.gov/legacy-archive/search/f?filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-COAD%22%5D%7D%7D%5D%7D" target="_blank">here</a>.<br/>READ tumor sample genomic data can be downloaded from <a href="https://portal.gdc.cancer.gov/legacy-archive/search/f?filters=%7B%22op%22:%22and%22,%22content%22:%5B%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.program.name%22,%22value%22:%5B%22TCGA%22%5D%7D%7D,%7B%22op%22:%22in%22,%22content%22:%7B%22field%22:%22cases.project.project_id%22,%22value%22:%5B%22TCGA-READ%22%5D%7D%7D%5D%7D" target="_blank">here</a>.<br/></p><p>Normal colon epithelium sample mass spectrometry data can be downloaded from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S019" target="_blank">here</a>.<br/>Mass spectrometry data for comparison and reference (CompRef) sample standards run with this study can be downloaded from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S017" target="_blank">here</a>.<br/>Peptide-Spectrum-Matches and Protein Reports from the CPTAC Common Data Analysis Pipeline (CDAP) can be downloaded from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S016" target="_blank">here</a>.<br/>Network analysis of this study can be viewed at the NetGestalt CRC Portal <a href="http://www.netgestalt.org/index.html" target="_blank">here</a>.<br/><br/>This work was accomplished by the Proteome Characterization Center (PCC) at Vanderbilt University led by Dr. Daniel C. Liebler.</p><ul><li>Dataset imported into MassIVE from <a href="https://cptac-data-portal.georgetown.edu/cptac/s/S022">https://cptac-data-portal.georgetown.edu/cptac/s/S022</a> on 08/26/19</li><li>Dataset source: <a href="https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome" target="_blank">https://pdc.esacinc.com/pdc/browse/filters/study_name:TCGA_Colon_Cancer_Proteome</a></li></ul>
2019-08-26 | MSV000084238 | MassIVE