Identifying critical pathways regulating autoimmunity in immuno-oncology and arthritis patients. Short title: IPADS (Immune PAthways for Drug Side-effects)
About the Project
Inflammatory arthritis (IA) can result from non-autoimmune diseases (like crystal arthritis) and from autoimmune diseases like rheumatoid arthritis (RA) and spondyloarthropathies (inc. psoriatic arthritis). The presentation of autoantigens by APCs to T cells is likely to be involved in the aetiology of autoimmune diseases [1]. For examples, a strong genetic association between HLA-DRB1 alleles and RA susceptibility suggests a role for the presentation of an arthritogenic peptide by APC to CD4+ T cells in the aetiology of RA [1-4]. However, the exact antigens, APC subsets (stromal cells versus immune cells) and compartment (secondary or tertiary lymphoid structures) of antigen presentation remains poorly explored across autoimmune diseases.
The aim of this study is to characterize HLA-DR+cell subsets (therefore potentially antigen-presenting) with a large mass cytometry (CyTOF) panel (> 40 markers) across 3 compartments (blood, synovial fluid and disaggregated synovial biopsies) across 5 different arthritic diseases (> 60 patients). Insight into the function of APC subsets will be gained at the single cell level by analysing the expression of co-stimulatory molecules (like f.e. CD80) and polarising cytokines (for example, IL6 and IL23, to induce the inflammatory Th17 CD4+ T cell subset).
The data has already been generated and this project is a data analysis / bioinformatics project – it will not include any wet lab experiments.
Objective 1, quality control and batch correction:
Quality control procedures will be applied to remove bad markers, samples and batches (using custom R scripts [4]); batch detection and correction will be performed with R packages (like CytoNorm).
Objective 2, identification of stromal and immune cell subsets:
Automated clustering algorithms (FlowSOM) will be used to agnostically define cell populations (subsets of monocytes, macrophages, dendritic cells, fibroblasts and epithelial cells) based on lineage markers (f.e. CD45 for immune cells; podoplanin for stromal cells like fibroblasts; etc…).
Objective 3, association testing:
The association of cell clusters with compartment and disease will be performed with linear mixed models (f.e. MASC [3]) or CNA [5].
Objective 4, functional insight:
Differential expression of co-stimulatory molecules, activation markers and inflammatory cytokines across various HLA-DR+ cell clusters will be tested
Outcome:
a) An atlas of APCs across compartments and various types of IA; b) the identification of compartment- and disease-specific APC subsets; c) functional insight to inform further experiments and suggest new therapeutic targets for precision medicine in rheumatology
https://www.musculoskeletal.manchester.ac.uk/
http://www.cfgg.manchester.ac.uk
Entry Requirements
Candidates are expected to hold (or be about to obtain) a minimum upper second class honours degree (or equivalent) in a related area/subject. Candidates with previous laboratory experience, particularly in cell culture and molecular biology, are particularly encouraged to apply.
How To Apply
For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (https://www.bmh.manchester.ac.uk/study/research/apply/). Informal enquiries may be made directly to the primary supervisor. On the online application form select PhD Genetics
For international students, we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences.
Equality, Diversity and Inclusion
Equality, diversity and inclusion is fundamental to the success of The University of Manchester, and is at the heart of all of our activities. The full Equality, diversity and inclusion statement can be found on the website https://www.bmh.manchester.ac.uk/study/research/apply/equality-diversity-inclusion/
Funding Notes
References
Mar;9(3):141-53.
[2] Viatte S, Plant D, Han B, Fu B, Yarwood A, Thomson W, Symmons DP, Worthington J, Young A, Hyrich KL, Morgan AW,
Wilson AG, Isaacs JD, Raychaudhuri S, Barton A. Association of HLA-DRB1 haplotypes with rheumatoid arthritis severity,
mortality, and treatment response. JAMA. 2015 Apr 28;313(16):1645-56.
[3] Fonseka CY, Rao DA, Teslovich NC, Korsunsky I, Hannes SK, Slowikowski K, Gurish MF, Donlin LT, Lederer JA, Weinblatt
ME, Massarotti EM, Coblyn JS, Helfgott SM, Todd DJ, Bykerk VP, Karlson EW, Ermann J, Lee YC, Brenner MB, Raychaudhuri
S. Mixed-effects association of single cells identifies an expanded effector CD4+ T cell subset in rheumatoid arthritis. Sci
Transl Med. 2018 Oct 17;10(463)
[4] Mulhearn B, Marshall L, Sutcliffe M, Hannes SK, Fonseka C, Hussell T, Raychaudhuri S, Barton A, Viatte S. Automated
clustering reveals CD4+ T cell subset imbalances in rheumatoid arthritis. Front Immunol. 2023
[5] Reshef YA, Rumker L, Kang JB, Nathan A, Korsunsky I, Asgari S, Murray MB, Moody DB, Raychaudhuri S. Co-varying
neighborhood analysis identifies cell populations associated with phenotypes of interest from single-cell transcriptomics.
Nat Biotechnol. 2022 Mar;40(3):355-363.
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