High-parametric evaluation of human invariant natural killer T cells to delineate heterogeneity in allo- and autoimmunity Article Swipe
Tom Erkers
,
Bryan J. Xie
,
Laura J. Kenyon
,
Brian R. Smith
,
Mary Rieck
,
Kent P. Jensen
,
Xuhuai Ji
,
Marina Basina
,
Samuel Strober
,
Robert S. Negrin
,
Holden T. Maecker
,
Everett Meyer
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1182/blood.2019001903
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1182/blood.2019001903
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.
Related Topics
Concepts
CD1D
Biology
Immunology
Natural killer T cell
Population
Phenotype
Autoimmunity
Immune system
Cell biology
T cell
Medicine
Genetics
Gene
Environmental health
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1182/blood.2019001903
- https://ashpublications.org/blood/article-pdf/135/11/814/1718674/bloodbld2019001903.pdf
- OA Status
- bronze
- Cited By
- 15
- References
- 37
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2999882761
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2999882761Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1182/blood.2019001903Digital Object Identifier
- Title
-
High-parametric evaluation of human invariant natural killer T cells to delineate heterogeneity in allo- and autoimmunityWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2020Year of publication
- Publication date
-
2020-01-14Full publication date if available
- Authors
-
Tom Erkers, Bryan J. Xie, Laura J. Kenyon, Brian R. Smith, Mary Rieck, Kent P. Jensen, Xuhuai Ji, Marina Basina, Samuel Strober, Robert S. Negrin, Holden T. Maecker, Everett MeyerList of authors in order
- Landing page
-
https://doi.org/10.1182/blood.2019001903Publisher landing page
- PDF URL
-
https://ashpublications.org/blood/article-pdf/135/11/814/1718674/bloodbld2019001903.pdfDirect link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://ashpublications.org/blood/article-pdf/135/11/814/1718674/bloodbld2019001903.pdfDirect OA link when available
- Concepts
-
CD1D, Biology, Immunology, Natural killer T cell, Population, Phenotype, Autoimmunity, Immune system, Cell biology, T cell, Medicine, Genetics, Gene, Environmental healthTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
15Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1, 2024: 4, 2023: 6, 2022: 3, 2021: 1Per-year citation counts (last 5 years)
- References (count)
-
37Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.revealed | 84 |
| abstract_inverted_index.contrast, | 49 |
| abstract_inverted_index.correlate | 135 |
| abstract_inverted_index.cytotoxic | 127 |
| abstract_inverted_index.described | 88 |
| abstract_inverted_index.diabetes, | 152 |
| abstract_inverted_index.framework | 76 |
| abstract_inverted_index.increased | 113 |
| abstract_inverted_index.interest: | 102 |
| abstract_inverted_index.invariant | 2 |
| abstract_inverted_index.outcomes. | 47 |
| abstract_inverted_index.presented | 17 |
| abstract_inverted_index.targeting | 175 |
| abstract_inverted_index.activation | 116 |
| abstract_inverted_index.allogeneic | 141 |
| abstract_inverted_index.associated | 161 |
| abstract_inverted_index.biomarkers | 172 |
| abstract_inverted_index.functions, | 36 |
| abstract_inverted_index.functions. | 94 |
| abstract_inverted_index.identifies | 156 |
| abstract_inverted_index.lymphocyte | 12 |
| abstract_inverted_index.phenotypes | 91, 100, 160 |
| abstract_inverted_index.population | 13, 105, 124 |
| abstract_inverted_index.previously | 87 |
| abstract_inverted_index.recognizes | 15 |
| abstract_inverted_index.CD4–CD94+ | 131 |
| abstract_inverted_index.composition | 39 |
| abstract_inverted_index.data-driven | 71 |
| abstract_inverted_index.development | 170 |
| abstract_inverted_index.expression, | 120 |
| abstract_inverted_index.expression. | 132 |
| abstract_inverted_index.glycolipids | 16 |
| abstract_inverted_index.innate-like | 11 |
| abstract_inverted_index.particular, | 96 |
| abstract_inverted_index.populations | 134 |
| abstract_inverted_index.therapeutics | 174 |
| abstract_inverted_index.characterized | 117, 129 |
| abstract_inverted_index.hematopoietic | 142 |
| abstract_inverted_index.heterogeneity | 56 |
| abstract_inverted_index.heterogeneous | 29 |
| abstract_inverted_index.respectively. | 153 |
| abstract_inverted_index.heterogeneity. | 81 |
| abstract_inverted_index.HLA-II+CD161– | 119 |
| abstract_inverted_index.transplantation | 145 |
| abstract_inverted_index.graft-versus-host | 138 |
| abstract_inverted_index.high-dimensional, | 70 |
| cited_by_percentile_year.max | 98 |
| cited_by_percentile_year.min | 89 |
| corresponding_author_ids | https://openalex.org/A5085120006, https://openalex.org/A5005502949 |
| countries_distinct_count | 2 |
| institutions_distinct_count | 12 |
| corresponding_institution_ids | https://openalex.org/I2800139495, https://openalex.org/I28166907, https://openalex.org/I97018004 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
| sustainable_development_goals[0].score | 0.550000011920929 |
| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.71192115 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |