The immunogenetic mechanisms of response to biologic drugs in rheumatoid arthritis
Lead Research Organisation:
University of Manchester
Department Name: School of Biological Sciences
Abstract
The project will consist in identifying genetic, demographic and clinical factors, as well as immune cell types associated with response to biologic treatment in rheumatoid arthritis. Background: Rheumatoid arthritis (RA) is an autoimmune disease of unknown aetiology. Disease course and response to treatment are partially genetically determined [1]. Our lack of understanding of RA pathophysiology results in a trial and error in the prescription of biologic drugs with 30% of patients failing to respond. A few pathogenic immune cell types involved in the aetiology of RA have been recently identified [2,3,4,5], but their role in treatment response is unknown.
Aim: To evaluate the joint contribution of genetic susceptibility/severity polymorphisms and immune cell subsets (f.e. CD4+ T lymphocyte subsets) on RA susceptibility, clinical subphenotypes and response to biologic treatments.
Methods: We will use the world's largest prospective cohort of RA patients undergoing treatment with biologics, the BRAGGSS cohort, and the National Repository of Healthy Volunteers (NRHV). The following data on 300 BRAGGSS patients and 150 NRHV individuals will be available at the start of this project:
a) demographic and clinical patients' characteristics, inc. response to treatment;
b) immunophenotypes (peripheral blood) as determined by 2 mass and 3 flow cytometry panels (level and functions of lymphocyte and myeloid cell subsets, inc. those recently published [2,3,4,5]);
c) genome-wide genetic profiles.
Immunophenotypes will be analysed using unbiased clustering algorithms to define cellular clusters agnostically (FlowSOM, tSNE). Linear mixed models will be used for association testing with disease outcome (f.e. MASC [5]) or covarying neighborhood analysis (CNA). The association between genetic risk scores and cellular clusters will define cellular Quantitative Trait Loci (cQTL); mediation analysis and interaction testing will assess their effect on disease (susceptibility, severity or response to treatment).
Aim: To evaluate the joint contribution of genetic susceptibility/severity polymorphisms and immune cell subsets (f.e. CD4+ T lymphocyte subsets) on RA susceptibility, clinical subphenotypes and response to biologic treatments.
Methods: We will use the world's largest prospective cohort of RA patients undergoing treatment with biologics, the BRAGGSS cohort, and the National Repository of Healthy Volunteers (NRHV). The following data on 300 BRAGGSS patients and 150 NRHV individuals will be available at the start of this project:
a) demographic and clinical patients' characteristics, inc. response to treatment;
b) immunophenotypes (peripheral blood) as determined by 2 mass and 3 flow cytometry panels (level and functions of lymphocyte and myeloid cell subsets, inc. those recently published [2,3,4,5]);
c) genome-wide genetic profiles.
Immunophenotypes will be analysed using unbiased clustering algorithms to define cellular clusters agnostically (FlowSOM, tSNE). Linear mixed models will be used for association testing with disease outcome (f.e. MASC [5]) or covarying neighborhood analysis (CNA). The association between genetic risk scores and cellular clusters will define cellular Quantitative Trait Loci (cQTL); mediation analysis and interaction testing will assess their effect on disease (susceptibility, severity or response to treatment).
Organisations
People |
ORCID iD |
Sebastien Viatte (Primary Supervisor) | |
Lysette Marshall (Student) |
Studentship Projects
Project Reference | Relationship | Related To | Start | End | Student Name |
---|---|---|---|---|---|
MR/W007428/1 | 01/10/2022 | 30/09/2028 | |||
2770779 | Studentship | MR/W007428/1 | 01/10/2022 | 30/09/2026 | Lysette Marshall |