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Rheumatoid arthritis (RA) is a disabling disease leading to joint and bones destruction. This autoimmune disease is multifactorial, and some genetic and environmental risk factors are already described. However, a part of heritability is still unknown. Previous genomics studies dedicated to deciphering this missing heritability did not pay attention to age of onset. The purpose of this protocol is to determine genomic markers which are specific of RA with an age of onset above 65 years old. Indeed, clinical presentation, treatment tolerance and efficiency, and frequent comorbidities of this phenotype are particular. This signature of genomic biomarkers will be integrated in known molecular pathways to highlight specificities, helpful for biological targets identification.
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The purpose of this protocol is to identify a genomic signature specific of late onset RA and to contribute to the characterization of dedicated therapeutic targets. Collection of patients will be held at the rheumatology service of CHSF (Corbeil-Essonnes, France) and salivary samples will be collected for further genomic analyses conducted by GenHotel lab (Univ Evry - Univ Paris-Saclay, Evry, France).
First, analysis of whole genome/DNA sequences will allow to identify specific variants of late onset RA. Such identified biomarkers would help differential diagnosis and contribute to earlier initiation of care for RA relatives at risk of developing RA. Second, analysis of RNA sequences, including coding protein genes and non-coding RNA, will give information about gene expression and regulation, and molecular pathways. Comparison of patient groups will allow discrimination of biomarkers and molecular signature specific to the disease and to its onset phenotypes. Integration of such genomic data in the RA disease map (consisted of a network of biological pathways), and further modeling approaches, will highlight late onset RA particularities on which research of therapeutic target could be focused on.
To complete genomic analysis, methylome and proteome data will be produced in a second phase. Such data will help in identification of regulation process leading to a protein profile specific of late onset RA.
An ancillary study is planned from familial samples identified after analysis of data collected from RA patients. Risk genetic markers identification is facilitated in a familial context of analyses. Furthermore, non RA individuals in familial sample provide a control sample allowing better discrimination between family-dependent and phenotype-dependent genomic markers
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0 participants in 4 patient groups
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Caroline TOURTE; Pascal HILLIQUIN, MD
Data sourced from clinicaltrials.gov
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