Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of patients with four neurodegenerative disorders distinguishes tauopathies and identifies shared molecular pathways

ABSTRACT: We have constructed genome wide expression profiles from snap frozen post-mortem tissue from the medial temporal lobe of patients with four neurodegenerative disorders (5 AD, 5 PSP, 5 PiD and 5 FTD patients) and 5 control subjects. All patients were matched for age, gender, ApoE-epsilon and MAPT (tau) haplotype. From all groups a total of 790 probes were shown to be differently expressed when compared to control individuals. The results from these experiments were then used to investigate the correlations between clinical, pathological and molecular findings. From the 790 identified probes we extracted a gene set of 166 probes whose expression could discriminate between these disorders and normal ageing. This gene set can be further developed into an accurate microarray-based classification test. Furthermore, from this dataset we extracted a disease specific set of genes and identified two aging related transcription factors (FOXO1A and FOXO3A) as possible drug targets related to neurodegenerative disease.

ORGANISM(S): Homo sapiens

SUBMITTER: Iraad Bronner

PROVIDER: E-MEXP-2280 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Comprehensive mRNA expression profiling distinguishes tauopathies and identifies shared molecular pathways.

Bronner Iraad F IF Bochdanovits Zoltán Z Rizzu Patrizia P Kamphorst Wouter W Ravid Rivka R van Swieten John C JC Heutink Peter P

PloS one 20090828 8

<h4>Background</h4>Understanding the aetiologies of neurodegenerative diseases such as Alzheimer's disease (AD), Pick's disease (PiD), Progressive Supranuclear Palsy (PSP) and Frontotemporal dementia (FTD) is often hampered by the considerable clinical and molecular overlap between these diseases and normal ageing. The development of high throughput genomic technologies such as microarrays provide a new molecular tool to gain insight in the complexity and relationships between diseases, as they ...[more]

PMID: 19714246

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Project description:Background: To identify and functionally annotate cell type-specific gene expression in the human retinal pigment epithelium (RPE), a key tissue involved in age-related macular degeneration and retinitis pigmentosa. Methodology: RPE, photoreceptor and choroidal cells were isolated from selected freshly frozen healthy human donor eyes using laser microdissection. RNA isolation, amplification and hybridization to 44k microarrays was carried out according to Agilent specifications. Bioinformatics was carried out using Rosetta Resolver, David and Ingenuity software. Principal Findings: Our previous 22k analysis of the RPE transcriptome showed that the RPE has high levels of protein synthesis, strong energy demands, is exposed to high levels of oxidative stress and a variable degree of inflammation. We currently use a complementary new strategy aimed at the identification and functional annotation of RPE-specific expressed transcripts. This strategy takes advantage of the multilayered cellular structure of the retina and overcomes a number of limitations of previous studies. In triplicate, we compared the transcriptomes of RPE, photoreceptor and choroidal cells and we deduced RPE specific expression. We identified at least 114 entries with RPE-specific gene expression. Thirty-nine of these 114 genes also show high expression in the RPE, comparison with the literature showed that 85% of these 39 were previously identified to be expressed in the RPE. In the group of 114 RPE specific genes there was an overrepresentation of genes involved in (membrane) transport, vision and ophthalmic disease. More fundamentally, we found RPE-specific involvement in the RAR-activation, retinol metabolism and GABA receptor signaling pathways. Conclusions: In this study we provide a further specification and understanding of the RPE transcriptome by identifying and analyzing genes that are specifically expressed in the RPE. Six RPE samples, three phot samples, three choroid samples

Project description:The well-defined battery of in vitro systems applied within chemical cancer risk assessment is often characterised by a high false-positive rate, thus repeatedly failing to correctly predict the in vivo genotoxic and carcinogenic properties of test compounds. Toxicogenomics, i.e. mRNA-profiling, has been proven successful in improving the prediction of genotoxicity in vivo and the understanding of underlying mechanisms. Recently, microRNAs have been discovered as post-transcriptional regulators of mRNAs. It is thus hypothesised that using microRNA response-patterns may further improve current prediction methods. This study aimed at predicting genotoxicity and non-genotoxic carcinogenicity in vivo, by comparing microRNA- and mRNA-based profiles, using a frequently applied in vitro liver model and exposing this to a range of well-chosen prototypical carcinogens. Primary mouse hepatocytes (PMH) were treated for 24 and 48h with 21 chemical compounds [genotoxins (GTX) vs. non-genotoxins (NGTX) and non-genotoxic carcinogens (NGTX-C) versus non-carcinogens (NC)]. MicroRNA and mRNA expression changes were analysed by means of Exiqon and Affymetrix microarray-platforms, respectively. Classification was performed by using Prediction Analysis for Microarrays (PAM). Compounds were randomly assigned to training and validation sets (repeated 10 times). Before prediction analysis, pre-selection of microRNAs and mRNAs was performed by using a leave-one-out t-test. No microRNAs could be identified that accurately predicted genotoxicity or non-genotoxic carcinogenicity in vivo. However, mRNAs could be detected which appeared reliable in predicting genotoxicity in vivo after 24h (7 genes) and 48h (2 genes) of exposure (accuracy: 90% and 93%, sensitivity: 65% and 75%, specificity: 100% and 100%). Tributylinoxide and para-Cresidine were misclassified. Also, mRNAs were identified capable of classifying NGTX-C after 24h (5 genes) as well as after 48h (3 genes) of treatment (accuracy: 78% and 88%, sensitivity: 83% and 83%, specificity: 75% and 93%). Wy-14,643, phenobarbital and ampicillin trihydrate were misclassified. We conclude that genotoxicity and non-genotoxic carcinogenicity probably cannot be accurately predicted based on microRNA profiles. Overall, transcript-based prediction analyses appeared to clearly outperform microRNA-based analyses. The study investigated differential gene expression in primary mouse hepatocyte mRNA following 24 and 48 hours of exposure to di(2-ethylhexyl)phthalate(DEHP), 4-Acetylaminofluorene(4AAF), Curcumin(Cur), Phenobarbital(PhB),Reserpine(Res), 7,12-Dimethylbenzanthracene (DMBA), Resorcinol(Resorcinol), Para-cresidine(pCres), Phenacetin(Phen), Diclofenac(diclo),Wy 14643(Wy), Tributyltinoxide(TBTO), Benzo[a]pyrene(BaP), 8-Hydroxyquinoline [AKA 8-quinolinol](8HQ), 17-b-estradiol(E2), ampicillin(AmpC), cisplatin(CisPl), Aflatoxin B1(AFB1), Cyclosporin A(CsA), 2,3,7,8-Tetrachlorodibenzo-p-dioxin(TCDD), Quercetin(Que) or their responsive solvent (dimethylsulfoxide(DMSO), Ethanol(ETOH), phosphate buffered saline(PBS)). Three biological replicates per compound/solvent. In total 184 arrays.

Dataset Information

Transcription profiling of patients with four neurodegenerative disorders distinguishes tauopathies and identifies shared molecular pathways

Publications

Comprehensive mRNA expression profiling distinguishes tauopathies and identifies shared molecular pathways.

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