M6A-seq in the human vanetromedial prefrontal cortex in major depressive disorder
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE275676 | GEO | 2024/10/31
REPOSITORIES: GEO
Similar Datasets
Project description:Major depressive disorder (MDD) exhibits numerous clinical, epidemiological, and molecular features that are consistent with partially inherited and partially acquired epigenetic misregulation. We performed microarray based DNA modification study of MDD, utilizing affected and unaffected samples from white blood cells from monozygotic twins discordant for MDD, post-mortem prefrontal cortex tissues, and sperm samples. We performed DNA methylome analysis on white blood cells from monozygotic twins discordant for depression (n=200), pre-frontal cortex (n=71), and germline samples (n=33) from affected individuals and controls (total n=304). DNA samples were enriched for unmodified fraction of the genome using DNA-modification sensitive restriction enzyme digestion followed by adaptor-mediated PCR. The enriched fractions were labelled with a fluorescent dye (Cy5) and hybridized onto the array with a common reference pool (Cy3) generated from individuals unrelated to this study.
2012-04-27 | E-GEOD-37579 | biostudies-arrayexpress
Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD. In total, 33 MDD patients and 34 healthy controls were analyzed using basal gene expression in whole blood, and gene expression from whole blood that was stimulated with LPS for 5-6 h, using microarrays. Patients were arbitrarily selected from all patients to serve as primary cohort (nMDD = 21 (MDD01-MDD21); nControls = 21 (Con01-Con21)), or replication cohort (nMDD = 12 (MDD22-MDD35); nControls = 13 (Con22-Con37)) using microarrays. This submission does not include Samples CON21_LPS or CON30_LPS.
2011-10-04 | E-GEOD-19738 | biostudies-arrayexpress
Project description:Background: Major Depressive Disorder (MDD) is a moderately heritable disorder with a high lifetime prevalence. At present, laboratory blood tests to support MDD diagnosis are not available. Methods: We used a classifier approach on blood gene expression profiles of a unique set of non-medicated subjects (MDD patients and controls) to select genes of which expression is predictive for disease status. To reveal blood gene expression changes related to MDD disease, we applied a powerful ex vivo stimulus to the blood, i.e. incubation with lipopolysaccharide (LPS; 10 ng/ml blood). Results: Based on LPS-stimulated blood gene expression using whole-genome microarrays in 42 subjects (primary cohort; 21 MDD patients (mean age 42.3 years), 21 healthy controls (mean age 41.9 years)), we identified a set of genes (CAPRIN1, CLEC4A, KRT23, MLC1, PLSCR1, PROK2, ZBTB16) that serves as a molecular signature of MDD. These findings were validated for the primary cohort using an independent quantitative PCR method (P = 0.007). The difference between depressive patients and controls was confirmed (P = 0.019) in a replication cohort of 13 patients with MDD (mean age 42.8 years) and 14 controls (mean age 45.6 years). The MDD-signature score comprised of expression levels of 7 genes could discriminate depressive patients from controls with sensitivity of 76.9% and specificity of 71.8%. Conclusions: We show for the first time that molecular analysis of stimulated blood cells can be used as an endophenotype for MDD diagnosis, which is a milestone in establishing biomarkers for neuropsychiatric disorders with moderate heritability in general. Our results may provide a new entry point for following and predicting treatment outcome, as well as prediction of severity and recurrence of MDD.
2011-10-05 | GSE19738 | GEO
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: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:Identify blood proteins relevant to paroxetine response in patients with major depressive disorder (MDD)
2022-05-20 | PXD028947 | Pride
Project description:N6-Methyladenosine (m6A) and N6,2′-O-dimethyladenosine (m6Am) are abundant mRNA modifications that regulate transcript processing and translation. The role of both, here termed m6A/m, in the human stress response are currently unknown. Here, we provide m6A/m-Seq of immortalied cell lines derived from B lymphocytes from male healthy donors or male donors diagnosed with major depressive disorder (MDD), harvested 1 h after treatment with 100 nM cortisol or mock treatment. PolyA-RNA-fragments of each sample was processed both as m6A/m-sample (RNA immunoprecipiation RIP with an m6A and m6Am antibody) and RNA-input sample.
2018-07-10 | GSE113798 | GEO
Project description:Search for the biomarkers of major depressive disorder (MDD) has facilitated from the genes expressed in the patient’s 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.
2016-01-14 | GSE76826 | GEO
Project description:Genome-wide MeDIP-Sequencing of 23 monozygotic twin pairs (n=46) from Australia discordant for major depressive disorder (MDD).
2014-01-25 | GSE54370 | GEO
Project description:Major depressive disorder (MDD) exhibits numerous clinical and molecular features that are consistent with putative epigenetic misregulation. Despite growing interest in epigenetic studies of psychiatric diseases, the methodologies guiding such studies have not been well defined. We performed DNA modification analysis in white blood cells from monozygotic twins discordant for MDD, in brain prefrontal cortex, and germline (sperm) samples from affected individuals and control subjects (total N = 304) using 8.1K CpG island microarrays and fine mapping. In addition to the traditional locus-by-locus comparisons, we explored the potential of new analytical approaches in epigenomic studies. In the microarray experiment, we detected a number of nominally significant DNA modification differences in MDD and validated selected targets using bisulfite pyrosequencing. Some MDD epigenetic changes, however, overlapped across brain, blood, and sperm more often than expected by chance. We also demonstrated that stratification for disease severity and age may increase the statistical power of epimutation detection. Finally, a series of new analytical approaches, such as DNA modification networks and machine-learning algorithms using binary and quantitative depression phenotypes, provided additional insights on the epigenetic contributions to MDD. Mapping epigenetic differences in MDD (and other psychiatric diseases) is a complex task. However, combining traditional and innovative analytical strategies may lead to identification of disease-specific etiopathogenic epimutations.
2012-04-28 | GSE37579 | GEO