In:
Annals of the Rheumatic Diseases, BMJ, Vol. 79, No. Suppl 1 ( 2020-06), p. 1327.1-1327
Abstract:
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
Type of Medium:
Online Resource
ISSN:
0003-4967
,
1468-2060
DOI:
10.1136/annrheumdis-2020-eular.4068
Language:
English
Publisher:
BMJ
Publication Date:
2020
detail.hit.zdb_id:
1481557-6
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