Objectives: Based on genetic associations, McGonagle and McDermott suggested a classification of autoimmune and autoinflammatory diseases as a continuum ranging from purely autoimmune to purely autoinflammatory diseases and comprising diseases with both components. We used deep immunophenotyping to identify immune cell populations and molecular targets characterising this continuum.
Methods: We collected blood from 443 patients with one of 15 autoimmune or autoinflammatory diseases and 71 healthy volunteers. Deep phenotyping was performed using 13 flow cytometry panels characterising over 600 innate and adaptive cell populations. Unsupervised and supervised analyses were conducted to identify disease clusters with their common and specific cell parameters.
Results: Unsupervised clustering categorised these diseases into five clusters. Principal component analysis deconvoluted this clustering into two immunological axes. The first axis was driven by the ratio of LAG3+ to ICOS+ in regulatory T lymphocytes (Tregs), and segregated diseases based on their inflammation levels. The second axis was driven by activated Tregs and type 3 innate lymphoid cells (ILC3s), and segregated diseases based on their types of affected tissues. We identified a signature of 23 cell populations that accurately characterised the five disease clusters.
Conclusions: We have refined the monodimensional continuum of autoimmune and autoinflammatory diseases as a continuum characterised by both disease inflammation levels and targeted tissues. Such classification should be helpful for defining therapies. Our results call for further investigations into the role of the LAG3+/ICOS+ balance in Tregs and the contribution of ILC3s in autoimmune and autoinflammatory diseases.
Trial registration number: NCT02466217.
Keywords: Autoimmunity; Immune System Diseases; Inflammation; T-Lymphocyte subsets.
© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ on behalf of EULAR.