Unique NK-like T cell population identified in UBA1mt cells in vexas associated with IL-8 mediated activity and cytotoxic response pathways

Abstract Introduction: VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is an aggressive auto-inflammatory disorder defined by somatic UBA1 mutations. UBA1 mutations arise in hematopoietic stem cells and bias differentiation toward myeloid lineages. Clonal involvement of monocytes and neutrophils in VEXAS is frequent. Recently, natural killer (NK) cells have been recognized within the UBA1 mutant clone; mutated NK cells have an exhausted phenotype and impaired cytotoxicity (Ganesan BioRxiv 2025; Breillat et al, Blood 2025). A unique NK-like T cell type (CD3+CD16+[CD56-] T cells) has a role in the immunopathogenesis of severe COVID-19, resulting in heightened cytotoxicity and tissue damage (Georg et all, Cell 2022). As NK cells do not typically express CD3, and as the activation of inflammatory pathways is not restricted to myeloid cells in VEXAS, (Mizumaki et al, Nat Comm 2025) we sought to assess the CD3+ cell populations for co-expression of CD16 using single-cell (sc) multiomic data from VEXAS patients. Methods: After IRB approval, we performed sc-proteogenomic sequencing using a custom-made gene panel (Tapestri, MissionBio) in 2 VEXAS patients. Libraries were sequenced on an Illumina NovaSeq instrument. In one case, we performed in parallel CITE-Seq in parallel and used canonical correlation analysis (CCA) to integrate these immunophenotypic and transcriptomic data with matching cell populations identified from proteogenomic sequencing. We used pathway analysis (IPA) and gene ontology enrichment (gProfiler), as well as differential gene expression (RNA-seq) to identify significant gene signatures. T-tests with Welch's correction were performed for statistical significance on surface markers from proteogenomic data which were transformed by center log ratio. Our observations were then validated in sc-proteogenomic data from two additional VEXAS patients profiled at the NIH. Results: We used a sc-multiomic strategy to study CD3+ T cell subsets in VEXAS patients. In the first UBA1 mutant (mt) sample, using clusters defined by UMAP overlay of CITE-Seq/proteogenomic data, we defined positive expression of CD3 expression in the non-UBA1mt T cell cluster. We then examined the proteogenomic data (n=700 cells) to identify CD3+ cells (n=89 UBA1mt, n=42 UBA1wt). We then divided the CD3+ fraction into CD56+ vs CD56- to obtain CD3+CD56+ (n=25 UBA1mt, n=12 UBA1wt) and CD3+CD56- (n=64 UBA1mt, n=0 UBA1wt) cells. The CD3+CD56- cells were not only entirely UBA1mt, but also co-expressed CD16, significantly elevated from CD3+CD56+ UBA1wt cells (p<0.0001; and no significance from granulocyte populations): 10% of UBA1mt cells were CD3+CD16+CD56-. This cell subset was detected in an additional 3 VEXAS samples, and, in each case, there was no significant difference between UBA1mt/UBA1wt CD3 expression (both were T cell subsets) and no significant difference in CD56 expression. There was a significant increase in CD16+ expression in UBA1mt over UBA1wt (p<0.0001) cells, but not between UBA1mt cells and other granulocytes. Finally, we assessed the CITEseq data from the first UBA1mt case and focussed on gene expression and pathway differences between CD3+ and CD3+CD16+(CD56-) cell populations. Using IPA, we found top differentially expressed pathways included neutrophil degranulation, inflammation, cell killing, and IL-8 activity. Differentially expressed genes included FCGR3B, TLR2, IL1R2, FCGR2A, CCR1, CXCL8, and CXCR1, some of these overlapping with what was reported in similar cells (CD3+CD16+) detected in COVID-19 (Georg et all, Cell 2022). Conclusion: We identify a unique NK-T cell like [CD3+CD16+(CD56] subset of cells within UBA1mt cells in patients with VEXAS. This cell type has been reported in patients with severe COVID-19 as having increased cytotoxic functions and associated with fatal outcomes. Rare or aberrant cell clusters defined by standard clustering analysis may mis-identify some cell types, especially if they aberrantly express CD3+CD16+, as either marker could be used to pre-gate cells into larger clusters of lymphoid or myeloid cells. Prospective and functional profiling of this cell type in VEXAS patients is ongoing.

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Publication Details

Journal
Blood
Published
2025-11-03
DOI
https://doi.org/10.1182/blood-2025-1428
Primary Topic
Otitis Media and Relapsing Polychondritis
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article
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article

Unique NK-like T cell population identified in UBA1mt cells in vexas associated with IL-8 mediated activity and cytotoxic response pathways

Blood
Otitis Media and Relapsing Polychondritis
article

Unique NK-like T cell population identified in UBA1mt cells in vexas associated with IL-8 mediated activity and cytotoxic response pathways

article en

Abstract

Abstract Introduction: VEXAS (vacuoles, E1 enzyme, X-linked, autoinflammatory, somatic) is an aggressive auto-inflammatory disorder defined by somatic UBA1 mutations. UBA1 mutations arise in hematopoietic stem cells and bias differentiation toward myeloid lineages. Clonal involvement of monocytes and neutrophils in VEXAS is frequent. Recently, natural killer (NK) cells have been recognized within the UBA1 mutant clone; mutated NK cells have an exhausted phenotype and impaired cytotoxicity (Ganesan BioRxiv 2025; Breillat et al, Blood 2025). A unique NK-like T cell type (CD3+CD16+[CD56-] T cells) has a role in the immunopathogenesis of severe COVID-19, resulting in heightened cytotoxicity and tissue damage (Georg et all, Cell 2022). As NK cells do not typically express CD3, and as the activation of inflammatory pathways is not restricted to myeloid cells in VEXAS, (Mizumaki et al, Nat Comm 2025) we sought to assess the CD3+ cell populations for co-expression of CD16 using single-cell (sc) multiomic data from VEXAS patients. Methods: After IRB approval, we performed sc-proteogenomic sequencing using a custom-made gene panel (Tapestri, MissionBio) in 2 VEXAS patients. Libraries were sequenced on an Illumina NovaSeq instrument. In one case, we performed in parallel CITE-Seq in parallel and used canonical correlation analysis (CCA) to integrate these immunophenotypic and transcriptomic data with matching cell populations identified from proteogenomic sequencing. We used pathway analysis (IPA) and gene ontology enrichment (gProfiler), as well as differential gene expression (RNA-seq) to identify significant gene signatures. T-tests with Welch's correction were performed for statistical significance on surface markers from proteogenomic data which were transformed by center log ratio. Our observations were then validated in sc-proteogenomic data from two additional VEXAS patients profiled at the NIH. Results: We used a sc-multiomic strategy to study CD3+ T cell subsets in VEXAS patients. In the first UBA1 mutant (mt) sample, using clusters defined by UMAP overlay of CITE-Seq/proteogenomic data, we defined positive expression of CD3 expression in the non-UBA1mt T cell cluster. We then examined the proteogenomic data (n=700 cells) to identify CD3+ cells (n=89 UBA1mt, n=42 UBA1wt). We then divided the CD3+ fraction into CD56+ vs CD56- to obtain CD3+CD56+ (n=25 UBA1mt, n=12 UBA1wt) and CD3+CD56- (n=64 UBA1mt, n=0 UBA1wt) cells. The CD3+CD56- cells were not only entirely UBA1mt, but also co-expressed CD16, significantly elevated from CD3+CD56+ UBA1wt cells (p<0.0001; and no significance from granulocyte populations): 10% of UBA1mt cells were CD3+CD16+CD56-. This cell subset was detected in an additional 3 VEXAS samples, and, in each case, there was no significant difference between UBA1mt/UBA1wt CD3 expression (both were T cell subsets) and no significant difference in CD56 expression. There was a significant increase in CD16+ expression in UBA1mt over UBA1wt (p<0.0001) cells, but not between UBA1mt cells and other granulocytes. Finally, we assessed the CITEseq data from the first UBA1mt case and focussed on gene expression and pathway differences between CD3+ and CD3+CD16+(CD56-) cell populations. Using IPA, we found top differentially expressed pathways included neutrophil degranulation, inflammation, cell killing, and IL-8 activity. Differentially expressed genes included FCGR3B, TLR2, IL1R2, FCGR2A, CCR1, CXCL8, and CXCR1, some of these overlapping with what was reported in similar cells (CD3+CD16+) detected in COVID-19 (Georg et all, Cell 2022). Conclusion: We identify a unique NK-T cell like [CD3+CD16+(CD56] subset of cells within UBA1mt cells in patients with VEXAS. This cell type has been reported in patients with severe COVID-19 as having increased cytotoxic functions and associated with fatal outcomes. Rare or aberrant cell clusters defined by standard clustering analysis may mis-identify some cell types, especially if they aberrantly express CD3+CD16+, as either marker could be used to pre-gate cells into larger clusters of lymphoid or myeloid cells. Prospective and functional profiling of this cell type in VEXAS patients is ongoing.

BloodVol. 146(Supplement 1)
Brooklyn Navy Yard (US), Hematology\Oncology Clinic (US), National Heart, Lung, and Blood Institute (US)
Openalex Percentile: Top 32%
Otitis Media and Relapsing Polychondritis
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