Blood transcriptomics of drug-na\uefve sporadic Parkinson's disease patients

BACKGROUND: Parkinson's disease (PD) is a chronic progressive neurodegenerative disorder that is clinically defined in terms of motor symptoms. These are preceded by prodromal non-motor manifestations that prove the systemic nature of the disease. Identifying genes and pathways altered in living patients provide new information on the diagnosis and pathogenesis of sporadic PD. METHODS: Changes in gene expression in the blood of 40 sporadic PD patients and 20 healthy controls ("Discovery set") were analyzed by taking advantage of the Affymetrix platform. Patients were at the onset of motor symptoms and before initiating any pharmacological treatment. Data analysis was performed by applying Ranking-Principal Component Analysis, PUMA and Significance Analysis of Microarrays. Functional annotations were assigned using GO, DAVID, GSEA to unveil significant enriched biological processes in the differentially expressed genes. The expressions of selected genes were validated using RT-qPCR and samples from an independent cohort of 12 patients and controls ("Validation set"). RESULTS: Gene expression profiling of blood samples discriminates PD patients from healthy controls and identifies differentially expressed genes in blood. The majority of these are also present in dopaminergic neurons of the Substantia Nigra, the key site of neurodegeneration. Together with neuronal apoptosis, lymphocyte activation and mitochondrial dysfunction, already found in previous analysis of PD blood and post-mortem brains, we unveiled transcriptome changes enriched in biological terms related to epigenetic modifications including chromatin remodeling and methylation. Candidate transcripts as CBX5, TCF3, MAN1C1 and DOCK10 were validated by RT-qPCR. CONCLUSIONS: Our data support the use of blood transcriptomics to study neurodegenerative diseases. It identifies changes in crucial components of chromatin remodeling and methylation machineries as early events in sporadic PD suggesting epigenetics as target for therapeutic intervention

L'adoption lyonnaise des orphelins légitimes (1536-1793) : thèse pour le doctorat.... Tome 2 / présentée... par Paul Gonnet... ; Université de Paris, Faculté de droit

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Additional file 8: of Blood transcriptomics of drug-naïve sporadic Parkinson’s disease patients

List of differentially expressed genes between PD patients and controls based on Rank Product analysis (RP). Rank Product analysis was performed on normalized and filtered microarray data as described in the main text. The RP test was run using 100 permutations and an FDR of 0.005 % and looking for up- and down-regulated genes separately. Low RP-Values indicate high significance of the results. Genes are shown with the most significant first. (PDF 3122 kb

Additional file 9: of Blood transcriptomics of drug-naïve sporadic Parkinson’s disease patients

List of common differentially expressed genes between PD patients and controls based on SAM and PUMA analyses and the 395 selected variables of the Ranking-PCA. Genes are ranked according to the P- values based on PUMA analysis. Order of the 395 variables, Affymetrix Probe Set IDs, gene symbols and names are indicated. Names shown in bold indicate transcripts validated by RT-qPCR (Fig. 2a). (PDF 3122 kb

Additional file 2: of Blood transcriptomics of drug-naïve sporadic Parkinson’s disease patients

Score plots of the first 6 PCs calculated on the dataset constituted by the 395 variables selected by Ranking-PCA. Control samples are represented as filled circles while pathological samples as void circles. Of the original 60 samples, one (a control sample) did not pass the microarray hybridization quality controls and was excluded from further analyses. All results of bioinformatics analyses shown in this paper refer to this set of 59 samples. (PDF 3122 kb

Additional file 14: of Blood transcriptomics of drug-naïve sporadic Parkinson’s disease patients

List of similar- and anti-similar-to-PD compounds from drug network analysis. Community identifiers, drugs and community enrichment p-values resulting from the drug network analysis of genome-wide ranked lists of genes sorted according to their differential expression in PD. Drugs are sorted according to their similarity to PD (a) and according to their “anti-similarity” (b) as explained in the main manuscript. (PDF 3121 kb

Additional file 11: of Blood transcriptomics of drug-naïve sporadic Parkinson’s disease patients

Statistically significant gene sets from GSEA analyses. GSEA was run on the normalized, unfiltered microarray dataset as suggested in the tools implementation ( http://www.broadinstitute.org/gsea/ version 2.06), and using the c5 - GO gene sets collection of the Molecular Signatures Database (MSigDB) ( http://www.broadinstitute.org/gsea/msigdb/ ). The test was performed separately on each of the c5 sub-collections (biological process, molecular function and cellular component), running 1000 permutations and excluding gene sets with fewer than 5 genes or more than 150 (the latter, to retain granularity). Names (Gene Symbol) shown in bold indicate transcripts measured by RT-qPCR (Additional file 12). (PDF 3122 kb

Additional file 5: of Blood transcriptomics of drug-naïve sporadic Parkinson’s disease patients

Main processes (GOTERM_BP_FAT as classified by DAVID Gene Ontology) altered in whole peripheral blood cells in the 395 selected variables comparing PD patients and controls. GO annotations with at least 3 genes and P < 0.05 (Fisher exact probability) are presented. Count: number of genes involved in the term; %: percentage of involved genes/total genes; P-Value: modified fisher exact P-value, EASE Score; Benjamini: adjusted P-value using Benjamini-Hochberg procedure. (PDF 3122 kb

Additional file 13: of Blood transcriptomics of drug-naïve sporadic Parkinson’s disease patients

Selection of reliable reference genes for peripheral blood gene expression analyses. TaqMan® array human endogenous control cards (Applied Biosystems, Foster City, CA, USA) are 384-well microfluidic cards containing 16 human TaqMan Gene Expression Assays. They were used to evaluate the endogenous controls specific for peripheral blood that exhibit minimal differential expression. Peripheral blood samples from 8 PD and 8 HC gender- and age-matched subjects were processed following the manufacturer’s instructions (Applied Biosystems, Foster City, CA, USA). The expression stability was determined and compared by two commonly used algorithms (geNorm and NormFinder). By comparing the output of these two methods and by accepting gene expression levels of qPCR at Ct values ≤ 29, we obtained a list of the most stable reference genes in human peripheral blood. See the following Figures reporting output files of the analyses. As the best reference genes, PGK1, UBC and GAPDH were selected according to the following practical considerations: PGK1 is the best reference gene according to geNorm and NormFinder analyses; UBC presents similar stability strength to PGK1 and a different threshold Ct value; GAPDH is one of the most widely used reference genes in peripheral blood expression studies. The gene expression analyses of the first experimental data sets (data not shown) reveled that GAPDH had a higher variability compared to PGK1 and UBC; therefore, we decided to evaluate the relative gene expression by normalizing the data to the geometric mean of PGK1 and UBC. (PDF 3122 kb