Project description:To directly compare the SLE monocyte transcriptional program with that of blood mDC precursors, we purified lineage HLA-DRhighCD11chigh mDCs and CD14+ monocytes from the blood of five healthy donors. Their gene expression profiles were then compared to those of blood SLE monocytes. An unsupervised clustering analysis of transcripts present in >20% of the samples classified healthy monocytes, SLE monocytes and healthy mDCs into three well defined groups. A supervised analysis was then performed to find genes: 1) differentially expressed in healthy mDCs compared to monocytes; 2) shared by healthy blood mDCs and SLE blood monocytes. To directly compare the SLE monocyte transcriptional program with that of blood mDC precursors, we purified lineage HLA-DRhighCD11chigh mDCs and CD14+ monocytes from the blood of five healthy donors. Their gene expression profiles were then compared to those of blood SLE monocytes. An unsupervised clustering analysis of transcripts present in >20% of the samples classified healthy monocytes, SLE monocytes and healthy mDCs into three well defined groups. A supervised analysis was then performed to find genes: 1) differentially expressed in healthy mDCs compared to monocytes; 2) shared by healthy blood mDCs and SLE blood monocytes.
Project description:To directly compare the SLE monocyte transcriptional program with that of blood mDC precursors, we purified lineage HLA-DRhighCD11chigh mDCs and CD14+ monocytes from the blood of five healthy donors. Their gene expression profiles were then compared to those of blood SLE monocytes. An unsupervised clustering analysis of transcripts present in >20% of the samples classified healthy monocytes, SLE monocytes and healthy mDCs into three well defined groups. A supervised analysis was then performed to find genes: 1) differentially expressed in healthy mDCs compared to monocytes; 2) shared by healthy blood mDCs and SLE blood monocytes.
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:In our study, MegaClust - an unsupervised, data-driven algorithm - barely described mDCs and pDC subsets were identified. To confirm these findings we performed RNA sequencing Facs sorted of mDCs (CD123-CD11c+CD4+HLA-DR+), pDCs (CD123+CD11c-CD4+HLA-DR+) and monocytes (CD14+) from healthy donors and compared these with publicly available data.
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.