AB0050 EXTENDED POLYDIMENSIONAL IMMUNOME CHARACTERISATION (EPIC) PLATFORM AS A TOOL FOR TRANSLATIONAL RESEARCH. (2nd June 2020)

• Record Type: Journal Article
• Authors: Yeo, J. G.; Wasser, M.; Kumar, P.; Pan, L.; Poh, S. L.; Ally, F.; Arkachaisri, T.; Lim, A. J. M.; Leong, J. Y.; Yeo, K. T.; Lai, L.; Lee, E. S. C.; Chua, C.; Paleja, B.; Tang, S. P.; Ng, S. K.; Tan, A. Y. J.; Lee, S. Y.; Ginhoux, F.; Ng, T. P.; Larbi, A.; Albani, S.
• Is Part Of: Annals of the rheumatic diseases. Volume 79(2020)Supplement 1
• Page Start: 1327
• Page End: 1327
• Publication Date: 2020-06-02
• Subjects: Rheumatism -- Periodicals; 616.723005
• DOI: 10.1136/annrheumdis-2020-eular.4068
• Languages: English
• ISSNs: 0003-4967

Abstract

Abstract : Background: We created a high dimensionality healthy human Immunome atlas by interrogating the peripheral blood mononuclear cells (PBMC) of >200 healthy subjects (cord blood to adult) with 63 unique mechanistic and phenotypic markers per cell by mass cytometry (CyTOF). This database is built with an open source, web-based bioinformatics toolkit, enabling its mining and uploading of datasets for comparison with the EPIC healthy database. Objectives: Here, we demonstrate the platform's ability to identify the immunological differences of mechanistically important cell subsets in the uploaded data in comparison with EPIC. Methods: CyTOF data from 37 healthy elderly (>60 years old) was uploaded onto the EPIC Discovery tool where down-sampling, normalising and FlowSOM (Flow analysis with Self-Organising Maps) clustering were done with the EPIC database for comparison. Online visualisation outputs include cluster frequency boxplots, correspondence analysis (CA) plot and markers expression heat-map. The CA 2-dimensional plot depicts the global differences in immune cells composition between subjects with proximity between points (subjects) denoting similarity. Kruskal-Wallis test was done to identify age groups differences. Results: Increasing distances on the CA plot with age were observed with the elderly being farthest from the new-borns. Notably, we observed significant changes in naive CD4 + IL8 + T cells (p<1×10 -20 ), memory CD4 + IL17A + T cells (p<1×10 -20 ) and type 2 innate lymphoid cells (ILC2) (Lin - CD7 + CD25 + CD127 + CD161 +, p<1×10 -17 ) with increasing age. The naive CD4 + IL8 + T cells (median: 0.68%, interquartile range: 0.415 to 1.055% of CD45+ PBMC) and ILC2 (0.09%, 0.065 to 0.12%) were lowest and memory IL17A + T cells (0.58%, 0.41 to 0.905%) highest in the elderly. Significantly, the memory IL17A + T cells and ILC2 have been implicated in the pathogenesis of auto-immune conditions 1, 2 . Conclusion: With EPIC, we have created an online tool enabling data uploading for comparison to a healthy database, allowing the holistic characterisation of immunological changes in different clinical scenarios. Using it, we were able to identify mechanistically important differences in immune cells composition in a distinct clinical cohort (elderly) compared to the younger ages. Translationally, the EPIC platform can be utilised similarly to catalyse the discovery process in auto-immune diseases interrogated with the EPIC antibody panels. References: [1]Fasching P, Stradner M, Graninger W, Dejaco C, Fessler J. Therapeutic Potential of Targeting the Th17/Treg Axis in Autoimmune Disorders. Molecules. 2017 Jan 14;22(1). pii: E134. [2]Klose CS, Artis D. Innate lymphoid cells as regulators of immunity, inflammation and tissue homeostasis. Nat Immunol. 2016 Jun 21; 17(7): 765-74. Disclosure of Interests: None declared