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- High-parametric evaluation of human invariant natural killer T cells to delineate heterogeneity in allo- and autoimmunity.
High-parametric evaluation of human invariant natural killer T cells to delineate heterogeneity in allo- and autoimmunity.
Citation | “High-Parametric Evaluation Of Human Invariant Natural Killer T Cells To Delineate Heterogeneity In Allo- And Autoimmunity.”. Blood, pp. 814-825. . |
Center | Stanford University |
Author | Tom Erkers, Bryan J Xie, Laura J Kenyon, Brian Smith, Mary Rieck, Kent P Jensen, Xuhuai Ji, Marina Basina, Samuel Strober, Robert S Negrin, Holden T Maecker, Everett H Meyer |
Abstract |
Human invariant natural killer T (iNKT) cells are a rare innate-like lymphocyte population that recognizes glycolipids presented on CD1d. Studies in mice have shown that these cells are heterogeneous and are capable of enacting diverse functions, and the composition of iNKT cell subsets can alter disease outcomes. In contrast, far less is known about how heterogeneity in human iNKT cells relates to disease. To address this, we used a high-dimensional, data-driven approach to devise a framework for parsing human iNKT heterogeneity. Our data revealed novel and previously described iNKT cell phenotypes with distinct functions. In particular, we found 2 phenotypes of interest: (1) a population with T helper 1 function that was increased with iNKT activation characterized by HLA-II+CD161- expression, and (2) a population with enhanced cytotoxic function characterized by CD4-CD94+ expression. These populations correlate with acute graft-versus-host disease after allogeneic hematopoietic stem cell transplantation and with new onset type 1 diabetes, respectively. Our study identifies human iNKT cell phenotypes associated with human disease that could aid in the development of biomarkers or therapeutics targeting iNKT cells. |
Year of Publication |
2020
|
Journal |
Blood
|
Volume |
135
|
Issue |
11
|
Number of Pages |
814-825
|
Date Published |
03/2020
|
ISSN Number |
1528-0020
|
DOI |
10.1182/blood.2019001903
|
Alternate Journal |
Blood
|
PMID |
31935280
|
PMCID |
PMC7068034
|
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