Mass cytometry reveals systemic and local immune signatures that distinguish inflammatory bowel diseases
Inflammatory bowel disease (IBD) includes Crohn’s disease and ulcerative colitis. Each disease is characterized by a diverse set of potential manifestations, which determine patients’ disease phenotype. Current understanding of phenotype determinants is limited, despite increasing prevalence and hea...
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Published in: | Nature communications Vol. 10; no. 1; pp. 2686 - 14 |
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Main Authors: | , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
London
Nature Publishing Group UK
19-06-2019
Nature Publishing Group Nature Portfolio |
Subjects: | |
Online Access: | Get full text |
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Summary: | Inflammatory bowel disease (IBD) includes Crohn’s disease and ulcerative colitis. Each disease is characterized by a diverse set of potential manifestations, which determine patients’ disease phenotype. Current understanding of phenotype determinants is limited, despite increasing prevalence and healthcare costs. Diagnosis and monitoring of disease requires invasive procedures, such as endoscopy and tissue biopsy. Here we report signatures of heterogeneity between disease diagnoses and phenotypes. Using mass cytometry, we analyze leukocyte subsets, characterize their function(s), and examine gut-homing molecule expression in blood and intestinal tissue from healthy and/or IBD subjects. Some signatures persist in IBD despite remission, and many signatures are highly represented by leukocytes that express gut trafficking molecules. Moreover, distinct systemic and local immune signatures suggest patterns of cell localization in disease. Our findings highlight the importance of gut tropic leukocytes in circulation and reveal that blood-based immune signatures differentiate clinically relevant subsets of IBD.
Distinguishing clinical subtypes of IBD is critical for optimal treatments, outcome prediction, and better understanding of disease pathogenesis. Here the authors phenotype blood and intestinal immune cells by mass cytometry and identify signatures associated with distinct disease states. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 2041-1723 2041-1723 |
DOI: | 10.1038/s41467-019-10387-7 |