Project description:To explore which miRNAs were altered in COPD, we performed a microRNA microarray analysis of peripheral blood mononuclear cells from stable COPD patients (n=6) and healthy controls (n=6). Sex, age, BMI and history of cigarette smoke were matched between different groups. Blood samples were obtained from stable COPD patients(n=6) and healthy adults (n=6) from clinical trial (NCT02037828). The study was in compliance with the Declaration of Helsinki and was approved by Peking University Institutional Review Board Office.
Project description:Differential profiles from whole genome human expression arrays on monocytes obtained from peripheral blood in COPD was studied and compared with controls. Monocytes were isolated from Controls (Group 1) which included Control Smokers (Group 1A) and Control Never Smokers (Group 1B) and COPD (Group 2) which included COPD Smokers (Group 2A) and COPD ExSmokers (Group 2B). Differential transcriptomic expression associated with (i) Smoking, (ii) COPD, and (iii) cessation of smoking were identified.
Project description:Rationale: COPD is characterized by an abnormal regulatory T cell (Treg) response and increases in Th1 and Th17 cell responses. It is unclear if dysregulation of miRNAs within Treg alters the adaptive immunophenotype in COPD. Objectives: To compare the miRNA profile of COPD Treg cells with that of healthy controls and to explore the function of differentially expressed miRNAs. Methods: Treg cells (CD4+CD25+CD49-CD127-) and T effector (CD4+CD25-) cells were obtained from the peripheral blood of 4 nonsmokers, 4 healthy current smokers, and 4 COPD current smokers for analysis of miRNA expression, matching them for age and sex. We assessed expression initially by microarray analysis on the Illumina miRNA platform then conducted real time RT-PCR validation of the microarray results. 24 samples were analyzed. 8 from each patient group of healthy Normal, Healthy Smoker, and COPD Smoker.
Project description:Investigation of whole genome gene expression level changes of the dynamic gene profiling of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD) on day1, 3 and 10, compared to the normal people and stable COPD patients. A five chip study using total RNA recovered from Peripheral Blood Mononuclear Cell of Peripheral Blood.Evaluating the dynamic gene profiling of peripheral blood mononuclear cells (PBMCs) from patients with AECOPD) on day1, 3 and 10 after the hospital admission, to compared with healthy controls or patients with stable COPD. Slides were scanned at 5 μm/pixel resolution using an Axon GenePix 4000B scanner (Molecular Devices Corporation) piloted by GenePix Pro 6.0 software (Axon). Scanned images (TIFF format) were then imported into NimbleScan software (version 2.5) for grid alignment and expression data analysis. Expression data were normalized through quantile normalization and the Robust Multichip Average (RMA) algorithm included in the NimbleScan software. The Probe level (*_norm_RMA.pair) files and Gene level (*_RMA.calls) files were generated after normalization.
Project description:Rationale: COPD is characterized by an abnormal regulatory T cell (Treg) response and increases in Th1 and Th17 cell responses. It is unclear if dysregulation of miRNAs within Treg alters the adaptive immunophenotype in COPD. Objectives: To compare the miRNA profile of COPD Treg cells with that of healthy controls and to explore the function of differentially expressed miRNAs. Methods: Treg cells (CD4+CD25+CD49-CD127-) and T effector (CD4+CD25-) cells were obtained from the peripheral blood of 4 nonsmokers, 4 healthy current smokers, and 4 COPD current smokers for analysis of miRNA expression, matching them for age and sex. We assessed expression initially by microarray analysis on the Illumina miRNA platform then conducted real time RT-PCR validation of the microarray results.
Project description:Transcriptional profiling of Homo sapiens inflammatory skin diseases (whole skin biospies): Psoriasis (Pso), vs Atopic Dermatitis (AD) vs Lichen planus (Li), vs Contact Eczema (KE), vs Healthy control (KO) In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation. In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation.
Project description:As part of our study in understanding the role of SP140 in inflammatory pathways in macrophages, we inhibited SP140 mRNA using siRNA. Peripheral blood mononuclear cells (PBMCs) were obtained from whole blood of healthy donors (from Sanquin Institute Amsterdam or from GSK Stevenage Blood Donation Unit) by Ficoll density gradient (Invitrogen). CD14+ monocytes were positively selected from PBMCs using CD14 Microbeads according to the manufacturer’s instructions (Miltenyi Biotec). CD14+ cells were differentiated with 20 ng/mL of macrophage colony-stimulating factor (M-CSF) (R&D systems) for 3 days followed by 3 days of polarization into classically activated (inflammatory) M1 macrophages (100 ng/mL IFN-γ; R&D systems). M1 macrophages were transfected with siGENOME human smartpool SP140 siRNA or non-targeting scrambled siRNA for 48h with DharmaFECT™ transfection reagents according to manufacturer’s protocol (Dharmacon). The cells were left unstimulated or stimulated with 100 ng/mL LPS (E. coli 0111:B4; Sigma) for 4h (for qPCR) or 24h (for Elisa). The cells were lysed (ISOLATE II RNA Lysis Buffer RLY-Bioline) for RNA extraction.150 ng total RNA was labelled using the cRNA labelling kit for Illumina BeadArrays (Ambion) and hybridized with Ref8v3 BeadArrays (Illumina). Arrays were scanned on a BeadArray 500GX scanner and data were normalized using quantile normalization with background subtraction (GenomeStudio software; Illumina). This submission only contains processed data