Project description:Long noncoding RNAs (lncRNAs) are pervasively transcribed and have a direct role in the regulation of genes involved in neural plasticity and cognitive function. Moreover, alterations in the expression of several lncRNAs have been observed in some psychiatric disorders. However, changes in the expression of regulatory lncRNAs in MDD have not yet been reported. Using microarrays, we profiled the expression of 51513 lncRNAs and 35123 mRNAs in peripheral blood sampled from MDD patients as well as demographically-matched controls.
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
Project description:we studied the expression profile of lncRNA in peripheral blood of patients with active RA LncRNA and mRNA expression in peripheral blood from two activity RA patients and two healthy donors were analyzed with microarray profiling. peripheral blood of five active RA patients and five healthy control members were collected. Quantitative real-time PCR was further used to screen and verify the expression of lncRNA to verify the expression of the selected lncRNA; perform bioinformatics analysis to study the potential function of the differentially expressed genes, construct a receiver operating characteristic (ROC) curve to evaluate the clinical diagnostic value of the identified lncRNA, and use correlation analysis to explore the relationship between aberrantly expressed lncRNA that may have diagnostic value and clinical indicators.
Project description:This study aimed at identifying molecular biomarkers specific to inflammation-related subtype of MDD in order to improve diagnosis and treatment. For this, we performed whole-genome expression profiling from peripheral blood in a naturalistic model of inflammation-associated MDD represented by comorbid depression in obese patients.