Molecular Reclassification to Find Clinically Useful Biomarkers for Systemic Autoimmune Diseases: Case-control
Overview
- Phase
- Not Applicable
- Intervention
- Not specified
- Conditions
- Healthy Subjects
- Sponsor
- Fundación Pública Andaluza Progreso y Salud
- Enrollment
- 649
- Locations
- 17
- Primary Endpoint
- Cytokine profile determination
- Status
- Completed
- Last Updated
- 7 years ago
Overview
Brief Summary
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.
Detailed Description
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.
Investigators
Eligibility Criteria
Inclusion Criteria
- •Aged 18 years or older at the time of consent
- •Signed the informed consent form
Exclusion Criteria
- •Individuals on chronic medication.
- •Individuals suffering from any inflammatory, autoimmune, allergic or infectious condition and if possible without a history of autoimmune disease, particularly thyroid disease or other diseases that may modify cellular profiles in blood.
- •Pregnant women.
Outcomes
Primary Outcomes
Cytokine profile determination
Time Frame: 2 years
88 different cytokines will be assessed with Luminex
Gene expression in total blood
Time Frame: 2 years
Gene expression will be done using commercial gene expression microarrays in total blood from all samples using the RNA Paxgene tube.
Genotyping
Time Frame: 2 years
Genotyping will be done using a whole genome array.
Exosome isolation from plasma and urine
Time Frame: 2 years
set up of the methodology for isolating exosomes in these bodily fluids for gene expression analysis
routine autoantibodies in serum
Time Frame: 2 years
set of serum autoantibodies will be determined in a European validated laboratory. Also, they will perform detection of antibodies against small lipid moieties i.e.antiphosphorylcholine), lupus anticoagulant and complement proteins in plasma.
Gene expression methylation in total blood
Time Frame: 2 years
Methylation analysis will be done using the methylome 450k array using the DNA obtained from total blood. MicroRNA gene expression arrays using total blood.
Flow cytometry analysis to determine cell proportions in the total blood mixture in all individuals.
Time Frame: 24 hours
9 optimized panels of antibodies will be used to determine cell subpopulations in peripheral blood (including very minor cell populations).
Metabolite determination
Time Frame: 2 years
Metabolite determination in plasma and urine using Nuclear Magnetic Resonance