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Saadoun, D.

Publications and source records attributed to Saadoun, D..

2 recordsLinked to original sources

Genome-wide DNA methylation study reveals specific signatures in the affected arterial tissue of giant cell arteritis patients

ObjectivesGiant cell arteritis (GCA) is a large-vessel vasculitis, potentially causing complications such as blindness and strokes. This study aims to gain insights into the pathogenesis of GCA by identifying specific DNA methylation signatures in the arterial tissue of patients with this vasculitis. MethodsDNA methylation profiling was analyzed in 79 temporal artery biopsy samples (69 patients with GCA and 10 controls) by performing an epigenome-wide association study (EWAS). Differential analysis was performed to identify differentially methylated positions (DMPs) and regions (DMRs). Lastly, we compared our findings with previous transcriptomics and epigenomics studies on GCA-affected arteries. ResultsEWAS identified 3,644 DMPs (FDR < 0.05, |{Delta}{beta}| > 0.3), indicating a profound alteration within GCA-affected arterial tissue. These DMPs were annotated to 1,517 potentially dysregulated genes. 282 additional genes were identified by annotation of significant DMRs. Pathway enrichment analysis revealed a significant alteration of inflammatory mechanisms, such as interleukins 2 and 7, as well as pathways related to vascular remodeling. Omics study comparison revealed 37 genes consistently affected across datasets, many of them linked to immune signaling and T cell regulation. Notably, markers of exhausted T cells, including SLAMF6 and HAVCR2, were present among them. ConclusionsOur study identified GCA-specific DNA methylation signatures in arterial tissue, revealing disrupted inflammatory and vascular pathways, and suggesting the involvement of exhausted T cells in this condition. These findings offer new insights into GCA pathogenesis and provide new potential targets for the treatment of this debilitating disease. Key messagesO_ST_ABSWhat is already known on this topicC_ST_ABS{square} Affected arteries by giant cell arteritis (GCA) exhibit unique epigenetic signatures, reflecting significant disruptions in gene regulation. However, small sample sizes have constrained the clinical translation and broader interpretation of these findings, leaving key gaps in understanding GCA pathogenesis and identifying therapeutic targets. What this study adds{square} This study provides the largest-to-date epigenome-wide DNA methylation profiling in GCA-affected arteries, uncovering thousands of epigenetic changes and revealing profound disruptions in inflammatory and vascular pathways, including IL-2, IL-7, and CXCR4 signaling. {square}We compiled 37 genes consistently affected across different omics datasets in GCA-affected arteries, providing a robust list of candidates for further research into GCA pathogenesis and treatment. {square}Our findings provide evidence of T cell exhaustion in GCA-affected arteries, supported by consistent changes in key markers such as SLAMF6 and HAVCR2 (TIM-3), suggesting a novel mechanism of immune dysregulation in GCA. How this study might affect research, practice or policy{square} This study nominates exhausted T cells, the NLRP3 inflammasome, and CXCR4 signaling as novel contributors in GCA pathogenesis, suggesting new therapeutic targets for further research in the treatment of this disease.

immunology↗

Clinical data specification and coding for cross-analyses with omics data in autoimmune disease trials

ObjectivesAutoimmune and inflammatory diseases (AIDs) form a continuum of autoimmune and inflammatory diseases, yet AIDs nosology is based on syndromic classification. The TRANSIMMUNOM trial (NCT02466217) was designed to re-evaluate AIDs nosology through clinic-biological and multi-omics investigations of patients with one of 19 selected AIDs. To allow cross-analyses of clinic-biological data together with omics data, we needed to integrate clinical data in a harmonized database.\n\nMaterials and MethodsWe assembled a clinical expert consortium (CEC) to select relevant clinic-biological features to be collected for all patients and a cohort management team comprising biologists, clinicians and computer scientists to design an electronic case report form (eCRF). The eCRF design and implementation has been done on OpenClinica, an open-source CFR-part 11 compliant electronic data capture system.\n\nResultsThe CEC selected 865 clinical and biological parameters. The CMT selected coded the items using CDISC standards into 5835 coded values organized in 28 structured eCRFs. Examples of such coding are check boxes for clinical investigation, numerical values with units, disease scores as a result of an automated calculations, and coding of possible treatment formulas, doses and dosage regimens per disease.\n\nDiscussion21 CRFs were designed using OpenClinica v3.14 capturing the 5835 coded values per patients. Technical adjustment have been implemented to allow data entry and extraction of this amount of data, rarely achieved in classical eCRFs designs.\n\nConclusionsA multidisciplinary endeavour offers complete and harmonized CRFs for AID clinical investigations that are used in TRANSIMMUNOM and will benefit translational research team.

clinical trials↗