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:Introduction: Diagnosis of severe influenza pneumonia remains challenging because of the lack of correlation between presence of influenza virus and patient’s clinical status. We conducted gene expression profiling in the whole blood of critically ill patients to identify a gene signature that would allow clinicians to distinguish influenza infection from other causes of severe respiratory failure (e.g. bacterial pneumonia, non-infective systemic inflammatory response syndrome). Methods: Whole blood samples were collected from critically ill individuals and assayed on Illumina HT-12 gene expression beadarrays. Differentially expressed genes were determined by linear mixed model analysis and over-represented biological pathways determined using GeneGo MetaCore. Results: The gene expression profile of H1N1 influenza A pneumonia was distinctly different from bacterial pneumonia and systemic inflammatory response syndrome. The influenza gene expression profile is characterized by up-regulation of genes from cell cycle regulation, apoptosis and DNA-damage response pathways. In contrast, no distinctive gene-expression signature was found in patients with bacterial pneumonia or systemic inflammatory response syndrome. The gene expression profile of influenza infection persisted through five days of follow-up. Furthermore, in patients with primary H1N1 influenza A infection who subsequently developed bacterial co-infection, the influenza gene-expression signature remained unaltered, despite the presence of a super-imposed bacterial infection. Conclusions: The whole blood expression profiling data indicates that the host response to influenza pneumonia is distinctly different from that caused by bacterial pathogens. This information may speed up identification of the cause of infection in patients presenting with severe respiratory failure, allowing appropriate patient care to be undertaken more rapidly. Daily PAXgene samples for up to 5 days for; influenza A pneumonia patients (n=8), bacterial pneumonia patients (n=16), mixed bacterial and influenza A pneumonia patients (n=3), systemic inflammatory response patients (SIRS, n=13). Days 1 and 5 PAXgene samples for healthy control individuals

Project description:Pseudoexfoliation syndrome (PEX) is a systemic disorder that manifests as a fluffy, proteinaceous fibrillar material throughout the body. In the eye, such deposits result in glaucoma (PEXG), due to impeding aqueous humor outflow. When a patient presents acute glaucoma, it is necessary to remove some of the aqueous fluid within the eye to relief pain and pressure. This label free proteomics dataset was collected from human donors during cataract surgery. The aqueous humor was collected during essential ophthalmic procedures that allowed paracentesis after obtaining informed consents from human subjects without collecting identifiers, but all disease and medication history were collected. The sample collection included non-glaucomatous controls (CTL-GC), those with pseudoexfoliation syndrome (PEX-GC), and synthesized GC-Globulin pure protein (GC-Pure). Approximately 50-120 ul volume of AH was collected by paracentesis and stored in -80C immediately upon acquisition until analysis. Protein extraction was carried out by homogenization of the tissue in extraction buffer (TEAB, NaCl and SDS). Protein amounts were estimated and normalized to 10 ug across experimental samples. Samples were reduced using TCEP, alkylated with iodoacetamide and digested overnight with trypsin. Untargeted liquid chromatography-mass spectrometry was performed on an Easy nLC 1000 liquid chromatograph coupled to a QExactive mass spectrometer (LC-MS/MS). Data analysis was performed using Proteome Discoverer 3.0 and Graph Pad Prism 10. Each sample was run three separate times. Raw mass spectrometry data files were analyzed using Proteome Discoverer 3.0. The human proteome was downloaded from UniProt and used as the target database for protein identification. Max missed cleavage site was set to 2 and minimum peptide length to 6. Precursor Mass Tolerance was set to 10ppm and Fragment Mass Tolerance to 0.02 Da. Post-translational modifications for experimental proteins included oxidation, acetylation, and carbamidomethylation. The normalization was set to total peptide amount and confidence to low.

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Homo sapiens

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