Gene expression signatures of target tissues in endocrine and non-endocrine autoimmune diseases. Presente par Prof. Miriam Cnop

Background: Rheumatoid Arthritis (RA) is an autoimmune, chronic, and systematic disease. It affects joints and bones. The exact etiology of RA is still unclear. Varied genetic and environmental factors have been associated with the increased risk for RA. Overactivation of Toll-Like Receptors (TLRs) could initiate the development of autoimmune diseases including RA. Objective: The aim of the study was to evaluate TLR2 gene expression in rheumatoid arthritis patients and investigate its correlation with the disease activity. Materials and Methods: This study included 60 patients and 20 healthy individuals. The patients were diagnosed with RA according to the 2010 American College of Rheumatology/ European League Against Rheumatism criteria (ACR/EULAR). All included subjects did not have any joint disorders and /or autoimmune diseases. RA disease activity was determined by the disease activity score of 28 joints. Whole blood was collected from all participants. Total RNA extraction was done. TLR2 mRNA expression was assessed by reverse transcription-PCR (RT-PCR). Results: TLR2 mRNA expression was found to be significantly higher in RA patients compared to healthy controls. Also, a strong positive correlation was found between TLR2 expression level and the disease activity score. A non significant positive correlation was found between TLR2 expression and serum Rheumatoid Factor (RF) level. Conclusion: TLR2 pathway may have an important role in RA pathogenesis and could be a new biomarker for diagnosis and monitoring disease activity.

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The Integrated RNA Landscape of Renal Preconditioning against Ischemia-Reperfusion Injury

Journal of the American Society of Nephrology ◽

10.1681/asn.2019050534 ◽

2020 ◽

Vol 31 (4) ◽

pp. 716-730 ◽

Cited By ~ 1

Author(s):

Marc Johnsen ◽

Torsten Kubacki ◽

Assa Yeroslaviz ◽

Martin Richard Späth ◽

Jannis Mörsdorf ◽

...

Keyword(s):

Gene Expression ◽

Reperfusion Injury ◽

Caloric Restriction ◽

Molecular Mechanisms ◽

Target Genes ◽

Ischemia Reperfusion Injury ◽

Ischemia Reperfusion ◽

Hypoxic Preconditioning ◽

Preventive Strategies ◽

Gene Expression Signatures

BackgroundAlthough AKI lacks effective therapeutic approaches, preventive strategies using preconditioning protocols, including caloric restriction and hypoxic preconditioning, have been shown to prevent injury in animal models. A better understanding of the molecular mechanisms that underlie the enhanced resistance to AKI conferred by such approaches is needed to facilitate clinical use. We hypothesized that these preconditioning strategies use similar pathways to augment cellular stress resistance.MethodsTo identify genes and pathways shared by caloric restriction and hypoxic preconditioning, we used RNA-sequencing transcriptome profiling to compare the transcriptional response with both modes of preconditioning in mice before and after renal ischemia-reperfusion injury.ResultsThe gene expression signatures induced by both preconditioning strategies involve distinct common genes and pathways that overlap significantly with the transcriptional changes observed after ischemia-reperfusion injury. These changes primarily affect oxidation-reduction processes and have a major effect on mitochondrial processes. We found that 16 of the genes differentially regulated by both modes of preconditioning were strongly correlated with clinical outcome; most of these genes had not previously been directly linked to AKI.ConclusionsThis comparative analysis of the gene expression signatures in preconditioning strategies shows overlapping patterns in caloric restriction and hypoxic preconditioning, pointing toward common molecular mechanisms. Our analysis identified a limited set of target genes not previously known to be associated with AKI; further study of their potential to provide the basis for novel preventive strategies is warranted. To allow for optimal interactive usability of the data by the kidney research community, we provide an online interface for user-defined interrogation of the gene expression datasets (http://shiny.cecad.uni-koeln.de:3838/IRaP/).

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