Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Tandem mass tag (TMT) quantification data from knee chondrocytes for 12 osteoarthritis patients, comparing disease tissue against control tissue in each individual

ABSTRACT: This data set is made up of 4 experiments (batches) analysing chondrocytes from healthy and diseased knees in 12 patients with osteoarthritis. There are 6 samples (from 3 patients) for each batch, where diseased and control samples were extracted from each patient and compared within patient. The batches were necessary due to the maximum sample capacity (6) of the mass spectrometer. The raw data files were deposited at EBI PRIDE database under accession number PXD002014 ( http://www.ebi.ac.uk/pride/archive/projects/PXD002014 ). This ArrayExpress record contains sample meta-data and processed data in the form of ratios and the log2 fold changes. The ratios were calculated for each patient as diseased vs control (the reference). Please note that one patient (number 52) was excluded from the fold change analysis as no proteins showed any significant change which suggests the samples were not correct or something went wrong with them. There is also the median and standard deviation across the patients.

ORGANISM(S): Homo sapiens

SUBMITTER: James Wright

PROVIDER: E-PROT-4 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

ACCESS DATA

Similar Datasets

Project description:Recent studies have suggested that deregulated AKT1 signaling is associated with schizophrenia. We hypothesized that if this is indeed the case, we should observe both decreased AKT1 expression as well as deregulation of AKT1 regulated pathways in Peripheral Blood Mononuclear Cells (PBMCs) of schizophrenia patients. We therefore examined PBMC expression levels of AKT1 in schizophrenia patients versus controls, and examined whether functional biological processes in which AKT1 plays an important role are deregulated in schizophrenia patients. We performed a case-control study, investigating whole-genome PBMC gene expression in male, recent onset (<5 years) schizophrenia patients (N=43) as compared to controls (N=29). Genes, differentially expressed between patients and controls were identified using ANOVA with Benjamini-Hochberg correction (false discovery rate (FDR)= 0.05). Functional aspects of the deregulated set of genes were investigated with the Ingenuity Pathway Analysis (IPA) Software Tool. From each participant 30 ml of blood was drawn into heparinized tubes. All blood samples were obtained between 10.00 and 11.00 am to minimize diurnal variation. PBMC’s were isolated by Ficoll gradient separation, started within 20 minutes after the drawing of blood and performed with minimum time variation. Cells were subsequently disrupted (Qiashredder kit; Qiagen), and RNA was isolated (RNeasy minikit; Qiagen) with an additional DNAse digestion step (RNase-free DNase set; Qiagen), all according to the manufacturer’s protocol, diluted in nuclease free water, and frozen at –80 C before use. Before freezing, RNA purity and quantity was assessed with the NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies). After thawing the isolated RNA was biotinylated into cRNA using the One-Cycle Target Labeling and Control Reagents Kit (Affymetric Co) according to the manufacturer’s protocol. Before hybridisation RNA quality and integrity was assessed using the Agilent 2100 BioAnalyzer (Agilent). Biotinylated cRNA was hybridized to the Affymetrix Human Genome U133 plus 2.0 GeneChip© microarray containing 54,675 probe sets (Affymetrix Co). Each sample was individually biotinylated and hybridized to an individual microarray. Biotinylation was performed in batches with randomisation of patients and controls according to their ratios across the batches. The arrays were scanned and analyzed using Affymetrix Microarray Suite 4.2 software. Scanning was performed in three batches with randomization of patients and controls according to their ratios across the batches.

Project description:Comparative genomic hybridization microarrays (array CGH or molecular karyotyping) for the detection of congenital chromosomal aberrations is the application of microarray technology that is coming fastest into routine clinical application. When using a two-channel microarray of genomic DNA probes for array CGH, the basic setup consists in hybridizing a patient sample against a normal reference sample and detecting copy number variations through the deviation of fluorescent signal intensity between patient and normal reference. Two major disadvantages of this setup are (1) the use of half of the resources to measure a (little informative) reference sample and (2) the possibility that deviating signals are caused by benign copy number variation in the ânormalâ reference instead of a patient aberration. We therefore propose a new experimental loop design that compares three patients in three hybridizations (Patient 1 vs. Patient 3, Patient 3 vs. Patient 2, and Patient 2 vs. Patient 1). We develop and compare two statistical methods (linear models of log ratios and mixed models of absolute measurements). In an analysis of data from 27 patients seen at our genetics center, this new setup together with the linear model analysis significantly overcomes the limitations of the classical setup. Furthermore, we observed that the linear models of the log-ratios had a higher signal-to-noise ratio than the mixed models of the absolute intensities. These improvements are important to guarantee a maximal efficiency of array CGH in a clinical setting and will therefore contribute to its quick adoption as a routine diagnostic tool. The method is implemented as a web application and is available at www.esat.kuleuven.be/loop. Keywords: comparative genomic hybridization The data set consists out of nine loop designs or 27 patients with mental retardation (MR) and multiple congenital anomalies (MCA). The patients were seen at our genetics center (Center for Human Genetics, U.Z.Leuven).

Dataset Information

Tandem mass tag (TMT) quantification data from knee chondrocytes for 12 osteoarthritis patients, comparing disease tissue against control tissue in each individual

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure