Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA350561 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Transcriptome analysis of HIV-infected peripheral blood monocytes
| PRJNA215806 | ENA
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.
2022-01-19 | GSE146560 | GEO
Project description:DNA Methylome in Human Peripheral Blood Monocytes
| PRJNA171224 | ENA
Project description:Transcriptome of peripheral blood monocytes of patients with colorectal cancer
| PRJNA788191 | ENA
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
2022-07-22 | E-MTAB-12011 | biostudies-arrayexpress
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.
2014-12-02 | GSE63741 | GEO
Project description:Single cell RNA-seq analysis of peripheral blood monocytes in systemic sclerosis.
| PRJDB9416 | ENA
Project description:CD14+ monocytes sorted from the synovial fluid or peripheral blood of rheumatoid arthritis patients were analyzed by full transcriptome microarray analysis. Monocytes from healthy control samples (peripheral blood) were also profiled.
2017-01-30 | GSE71370 | GEO
Project description:Expression profiles of peripheral blood monocytes in periodontal therapy
| PRJNA98955 | ENA
Project description:human peripheral blood derived monocytes, LPS stimulation time-series
| PRJNA96153 | ENA