Healthy Subjects Clinical Trial
Official title:
Molecular Reclassification to Find Clinically Useful Biomarkers for Systemic Autoimmune Diseases: Case-control
Connective tissue diseases (CTD) or systemic autoimmune diseases (SADs) as they are known today are a group of chronic inflammatory conditions with autoimmune aetiology with few treatment options and difficult diagnosis.Brest team contribute to perform a new classification of the following systemic autoimmune diseases in a European Union's Seventh Framework Programme. The aim of this research is to constitute a Healthy Volunteers cohort to compare with systemic autoimmune diseases cohort into molecular clusters instead of clinical entities through the determination of molecular profiles using several "Omics" techniques.
The main objective of the PRECISESADS project is to reclassify the individuals affected by
SADs into molecular clusters instead of clinical entities through the determination of
molecular profiles using several "-omics" techniques.
The specific objectives of this cross sectional study and sub-study are:
1. To identify a systemic taxonomy for patients with SADs by producing the following data
in individuals with SADs and controls: genetic, epigenomic, transcriptomic, flow
cytometric (from peripheral blood mononuclear and polymorphonuclear cells (PBMCs)),
metabolomics and proteomic in plasma and urine, exosome analysis, classical serology
(antibodies and autoantibodies), and clinical data.
2. To better characterize individual SADs at the omics level.
3. To perform clustering analyses to determine the groups of individuals who,
differentially from other groups, share specific molecular features (precision
medicine).
4. To identify gene expression, methylation profiles through deconvolution methods
comparing a mixture of cells with subpopulations determined by flow cytometry with
separated cells, cytokine profiles and plasma metabolomics using Mass Spectrometry, in a
substudy of 288 individuals.
The clustering process will be data-driven with the aim to find the most homogenous and
differentiated clusters of diseases that clearly separate individuals on the basis of,
serological, genetic, epigenomic, cellular (cell proportions), metabolomic, proteomic
(cytokines, autoantibodies) and transcriptome characteristics and differentiate them from
controls and other patient clusters.
A total of 2000 patients and 666 controls will be included in the study.
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