Emma L. Kuan
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Emma L. Kuan has a total of 143 co-authors. Here are the top co-authors by number of shared publications:
- Julian Reading
Allen Institute for Immunology
5 shared publications - Lucas T. Graybuck
Allen Institute for Immunology
5 shared publications - Marla C. Glass
Allen Institute for Immunology
5 shared publications - Peter J. Skene
Allen Institute for Immunology, Seattle, USA
5 shared publications - Troy Robert Torgerson
Allen Institute for Immunology
5 shared publications - Xiao-Jun Li
Allen Institute for Immunology
5 shared publications
Latest Publications
- Open Access
Type I Interferon-Driven Monocyte Dysregulation and MAS-associated CD8 + T cells During Macrophage Activation Syndrome
Macrophage activation syndrome (MAS) is driven by a hyperinflammatory response characterized by aberrant activation of lymphocytes and phagocytes. While monocytes and macrophages are thought to be important in MAS pathogenesis, their role remains poorly understood. We used bulk and single-cell RNA sequencing (RNA-Seq) on sorted monocytes from children with MAS and healthy controls to identify transcriptional changes during MAS. We defined a MAS signature in classical monocytes that correlated with ferritin and was elevated in monocytes from systemic lupus erythematosus and COVID-19 patients. We also identified a subset of classical monocytes with high levels of interferon-stimulated genes (ISGs) that expanded during MAS. Surprisingly, the transcriptional signature of these cells was driven by type I IFNs, rather than IFNγ. Consistent with this finding, we detected increased levels of circulating IFNβ during MAS, suggesting that IFNβ plays an unrecognized role in driving MAS monocyte responses. We also identified a MAS-associated CD8 + T cell population with a distinctive transcriptional signature. We used cell-cell communication algorithms to predict increased immunoregulatory interactions between monocytes and T cells during MAS. Together, these results provide new evidence for a role for type I IFN during MAS and identify a unique CD8 + T cell population that may contribute to MAS pathophysiology.
Open AccessType I Interferon-Driven Monocyte Dysregulation and MAS-associated CD8 + T cells During Macrophage Activation Syndrome
Macrophage activation syndrome (MAS) is driven by a hyperinflammatory response characterized by aberrant activation of lymphocytes and phagocytes. While monocytes and macrophages are thought to be important in MAS pathogenesis, their role remains poorly understood. We used bulk and single-cell RNA sequencing (RNA-Seq) on sorted monocytes from children with MAS and healthy controls to identify transcriptional changes during MAS. We defined a MAS signature in classical monocytes that correlated with ferritin and was elevated in monocytes from systemic lupus erythematosus and COVID-19 patients. We also identified a subset of classical monocytes with high levels of interferon-stimulated genes (ISGs) that expanded during MAS. Surprisingly, the transcriptional signature of these cells was driven by type I IFNs, rather than IFNγ. Consistent with this finding, we detected increased levels of circulating IFNβ during MAS, suggesting that IFNβ plays an unrecognized role in driving MAS monocyte responses. We also identified a MAS-associated CD8 + T cell population with a distinctive transcriptional signature. We used cell-cell communication algorithms to predict increased immunoregulatory interactions between monocytes and T cells during MAS. Together, these results provide new evidence for a role for type I IFN during MAS and identify a unique CD8 + T cell population that may contribute to MAS pathophysiology.
- Open Access
Myeloma and therapy reshape the bone marrow niche to durably constrain immune reconstitution and vaccine responsiveness
Summary: Infections are the most common cause of non-relapse mortality in multiple myeloma (MM), but the basis of persistent immune dysfunction is obscured by patient heterogeneity and complex treatment regimens, including autologous stem cell transplant (ASCT). We performed longitudinal multi-omic profiling of matched bone marrow and peripheral blood from MM patients across diagnosis, induction, ASCT, and recovery. We found the tumor imposes a compartment-specific immune program where the marrow exhibits metabolic and inflammatory changes that bias hematopoiesis and alter cytotoxic effector programs not mirrored in blood. Adaptive immune reconstitution is impaired up to two years post-ASCT. Half of patients fail to mount IgG responses to high-dose non-adjuvanted influenza vaccine, a defect overcome by the lipid nanoparticle (LNP) adjuvanted COVID mRNA vaccine, which elicited responses in all patients, supporting adjuvanted influenza vaccine strategies in MM. Together these findings define how myeloma and its treatment durably reshape immunity from the marrow outward. Highlights: Multiple Myeloma marrow and blood show opposing metabolic and inflammatory states Induction therapy selects durable myeloma plasma-cell transcriptional states B cell and follicular helper T deficits blunt antigen responses after transplant COVID-19 vaccination builds immune memory with variable responses to flu vaccination eTOC: Multiple myeloma and its treatment leave a lasting imprint on the bone marrow niche. By profiling bone marrow and blood longitudinally at diagnosis, through induction, autologous transplant, and recovery, we show that marrow-local metabolic and inflammatory constraints persist and help explain why influenza vaccination often fails while mRNA vaccination succeeds.
Open AccessMyeloma and therapy reshape the bone marrow niche to durably constrain immune reconstitution and vaccine responsiveness
Summary: Infections are the most common cause of non-relapse mortality in multiple myeloma (MM), but the basis of persistent immune dysfunction is obscured by patient heterogeneity and complex treatment regimens, including autologous stem cell transplant (ASCT). We performed longitudinal multi-omic profiling of matched bone marrow and peripheral blood from MM patients across diagnosis, induction, ASCT, and recovery. We found the tumor imposes a compartment-specific immune program where the marrow exhibits metabolic and inflammatory changes that bias hematopoiesis and alter cytotoxic effector programs not mirrored in blood. Adaptive immune reconstitution is impaired up to two years post-ASCT. Half of patients fail to mount IgG responses to high-dose non-adjuvanted influenza vaccine, a defect overcome by the lipid nanoparticle (LNP) adjuvanted COVID mRNA vaccine, which elicited responses in all patients, supporting adjuvanted influenza vaccine strategies in MM. Together these findings define how myeloma and its treatment durably reshape immunity from the marrow outward. Highlights: Multiple Myeloma marrow and blood show opposing metabolic and inflammatory states Induction therapy selects durable myeloma plasma-cell transcriptional states B cell and follicular helper T deficits blunt antigen responses after transplant COVID-19 vaccination builds immune memory with variable responses to flu vaccination eTOC: Multiple myeloma and its treatment leave a lasting imprint on the bone marrow niche. By profiling bone marrow and blood longitudinally at diagnosis, through induction, autologous transplant, and recovery, we show that marrow-local metabolic and inflammatory constraints persist and help explain why influenza vaccination often fails while mRNA vaccination succeeds.
- Open Access
- 23 December 2025
- Published by Springer Nature in Research Square
Dissecting type I and II interferon impacts on human immune cells in disease by a cell type-specific interferon response atlas
Interferons (IFNs) orchestrate diverse immune responses, but distinguishing individual IFN contributions in human transcriptomic data is challenging due to overlapping interferon-stimulated gene (ISG) signatures and limited cell-type-specific datasets. To address this, we generated a single-cell transcriptomic atlas of IFN responses by stimulating primary human T, B, NK, and CD14 monocytes with IFN-I, IFN-II, and IFN-III. This revealed core and cell-type-specific ISG programs across 13 subsets, highlighting distinct functions of IFNs. We developed an algorithm to separate IFN-I and IFN-II activity in transcriptomic data. Applied to multiple myeloma samples, it showed elevated IFN-I and IFN-II responses, with induction therapy reducing only IFN-I. Extending to multiple disease datasets provided a cross-disease overview of IFN-I and IFN-II activities and revealed increased IFN-II activities in T cells during lupus flares. This resource and the accompanying analytical framework enable dissection of IFN-driven transcriptional programs in a cell-type specific manner in human disease.
- 23 December 2025
- Published by Springer Nature in Research Square
Open AccessDissecting type I and II interferon impacts on human immune cells in disease by a cell type-specific interferon response atlas
Interferons (IFNs) orchestrate diverse immune responses, but distinguishing individual IFN contributions in human transcriptomic data is challenging due to overlapping interferon-stimulated gene (ISG) signatures and limited cell-type-specific datasets. To address this, we generated a single-cell transcriptomic atlas of IFN responses by stimulating primary human T, B, NK, and CD14 monocytes with IFN-I, IFN-II, and IFN-III. This revealed core and cell-type-specific ISG programs across 13 subsets, highlighting distinct functions of IFNs. We developed an algorithm to separate IFN-I and IFN-II activity in transcriptomic data. Applied to multiple myeloma samples, it showed elevated IFN-I and IFN-II responses, with induction therapy reducing only IFN-I. Extending to multiple disease datasets provided a cross-disease overview of IFN-I and IFN-II activities and revealed increased IFN-II activities in T cells during lupus flares. This resource and the accompanying analytical framework enable dissection of IFN-driven transcriptional programs in a cell-type specific manner in human disease.
- Open Access
Dissecting type I and II interferon impacts on human immune cells in disease by a cell type-specific interferon response atlas
Interferons (IFNs) orchestrate diverse immune responses, but distinguishing individual IFN contributions in human transcriptomic data is challenging due to overlapping interferon-stimulated gene (ISG) signatures and limited cell-type-specific datasets. To address this, we generated a single-cell transcriptomic atlas of IFN responses by stimulating primary human T, B, NK, and CD14 monocytes with IFN-I, IFN-II, and IFN-III. This revealed core and cell-type-specific ISG programs across 13 subsets, highlighting distinct functions of IFNs. We developed an algorithm to separate IFN-I and IFN-II activity in transcriptomic data. Applied to multiple myeloma samples, it showed elevated IFN-I and IFN-II responses, with induction therapy reducing only IFN-I. Extending to multiple disease datasets provided a cross-disease overview of IFN-I and IFN-II activities and revealed increased IFN-II activities in T cells during lupus flares. This resource and the accompanying analytical framework enable dissection of IFN-driven transcriptional programs in a cell-type specific manner in human disease.
Open AccessDissecting type I and II interferon impacts on human immune cells in disease by a cell type-specific interferon response atlas
Interferons (IFNs) orchestrate diverse immune responses, but distinguishing individual IFN contributions in human transcriptomic data is challenging due to overlapping interferon-stimulated gene (ISG) signatures and limited cell-type-specific datasets. To address this, we generated a single-cell transcriptomic atlas of IFN responses by stimulating primary human T, B, NK, and CD14 monocytes with IFN-I, IFN-II, and IFN-III. This revealed core and cell-type-specific ISG programs across 13 subsets, highlighting distinct functions of IFNs. We developed an algorithm to separate IFN-I and IFN-II activity in transcriptomic data. Applied to multiple myeloma samples, it showed elevated IFN-I and IFN-II responses, with induction therapy reducing only IFN-I. Extending to multiple disease datasets provided a cross-disease overview of IFN-I and IFN-II activities and revealed increased IFN-II activities in T cells during lupus flares. This resource and the accompanying analytical framework enable dissection of IFN-driven transcriptional programs in a cell-type specific manner in human disease.
- Open Access
Systemic inflammation and lymphocyte activation precede rheumatoid arthritis
Some autoimmune diseases, including rheumatoid arthritis (RA), are preceded by a critical subclinical phase of disease activity. Proactive clinical management is hampered by a lack of biological understanding of this subclinical ‘at-risk’ state and the changes underlying disease development. In a cross-sectional and longitudinal multi-omics study of peripheral immunity in the autoantibody-positive at-risk for RA period, we identified systemic inflammation, proinflammatory-skewed B cells, expanded Tfh17-like cells, epigenetic bias in naive T cells, TNF+IL1B+ monocytes resembling a synovial macrophage population, and CD4 T cell transcriptional features resembling those suppressed by abatacept (CTLA4-Ig) in RA patients. Our findings characterize pathogenesis prior to clinical diagnosis and suggest the at-risk state exhibits substantial immune alterations that could potentially be targeted for early intervention to delay or prevent autoimmunity. We provide a suite of tools at https://apps.allenimmunology.org/aifi/insights/ra-progression/ to facilitate exploration and enhance accessibility of this extensive dataset. One Sentence Summary: ACPA+ at-risk individuals show RA-like inflammation and multi-compartment immune dysregulation during transition to clinically active RA
Open AccessSystemic inflammation and lymphocyte activation precede rheumatoid arthritis
Some autoimmune diseases, including rheumatoid arthritis (RA), are preceded by a critical subclinical phase of disease activity. Proactive clinical management is hampered by a lack of biological understanding of this subclinical ‘at-risk’ state and the changes underlying disease development. In a cross-sectional and longitudinal multi-omics study of peripheral immunity in the autoantibody-positive at-risk for RA period, we identified systemic inflammation, proinflammatory-skewed B cells, expanded Tfh17-like cells, epigenetic bias in naive T cells, TNF+IL1B+ monocytes resembling a synovial macrophage population, and CD4 T cell transcriptional features resembling those suppressed by abatacept (CTLA4-Ig) in RA patients. Our findings characterize pathogenesis prior to clinical diagnosis and suggest the at-risk state exhibits substantial immune alterations that could potentially be targeted for early intervention to delay or prevent autoimmunity. We provide a suite of tools at https://apps.allenimmunology.org/aifi/insights/ra-progression/ to facilitate exploration and enhance accessibility of this extensive dataset. One Sentence Summary: ACPA+ at-risk individuals show RA-like inflammation and multi-compartment immune dysregulation during transition to clinically active RA
- Open Access
Longitudinal Multi-omic Immune Profiling Reveals Age-Related Immune Cell Dynamics in Healthy Adults
Summary: The generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases. Here, we use multi-omic profiling (scRNA-seq, proteomics, flow cytometry) to examined human peripheral immunity in over 300 healthy adults, with 96 young and older adults followed over two years with yearly vaccination. The resulting resource includes scRNA-seq datasets of >16 million PBMCs, interrogating 71 immune cell subsets from our new Immune Health Atlas. This study allows unique insights into the composition and transcriptional state of immune cells at homeostasis, with vaccine perturbation, and across age. We find that T cells specifically accumulate age-related transcriptional changes more than other immune cells, independent from inflammation and chronic perturbation. Moreover, impaired memory B cell responses to vaccination are linked to a Th2-like state shift in older adults’ memory CD4 T cells, revealing possible mechanisms of immune dysregulation during healthy human aging. This extensive resource is provided with a suite of exploration tools at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/ to enhance data accessibility and further the understanding of immune health across age.
Open AccessLongitudinal Multi-omic Immune Profiling Reveals Age-Related Immune Cell Dynamics in Healthy Adults
Summary: The generation and maintenance of protective immunity is a dynamic interplay between host and environment that is impacted by age. Understanding fundamental changes in the healthy immune system that occur over a lifespan is critical in developing interventions for age-related susceptibility to infections and diseases. Here, we use multi-omic profiling (scRNA-seq, proteomics, flow cytometry) to examined human peripheral immunity in over 300 healthy adults, with 96 young and older adults followed over two years with yearly vaccination. The resulting resource includes scRNA-seq datasets of >16 million PBMCs, interrogating 71 immune cell subsets from our new Immune Health Atlas. This study allows unique insights into the composition and transcriptional state of immune cells at homeostasis, with vaccine perturbation, and across age. We find that T cells specifically accumulate age-related transcriptional changes more than other immune cells, independent from inflammation and chronic perturbation. Moreover, impaired memory B cell responses to vaccination are linked to a Th2-like state shift in older adults’ memory CD4 T cells, revealing possible mechanisms of immune dysregulation during healthy human aging. This extensive resource is provided with a suite of exploration tools at https://apps.allenimmunology.org/aifi/insights/dynamics-imm-health-age/ to enhance data accessibility and further the understanding of immune health across age.
- 18 June 2018
- Published by Springer Nature in Nature Immunology
- Vol. 19 (9) , 1037
Publisher Correction: A tumor–myeloid cell axis, mediated via the cytokines IL-1α and TSLP, promotes the progression of breast cancer
In the version of this article initially published, the far right label along the horizontal axis of the right plot of Fig. 1e (4T1-Tslp–/– 4-6), the middle and right labels along the horizontal axis of the far right plot of Fig. 3d (4T1-Tslpr–/– 4-6 and 4T1-Tslpr–/– 2-3, respectively), and the far right label along the horizontal axis of Fig. 6h (4T1-Tslpr–/– 2-3) were incorrect. The correct labels are as follows: Fig. 1e, 4T1-Tslpr–/– 4-6; Fig. 3d, 4T1-Tslp–/– 2-3 and 4T1-Tslpr–/– 4-6, respectively; and Fig. 6h, 4T1-Tslpr–/– 4-6. Also, Fig. 4e was incorrectly a duplicate of an adjacent panel. The errors have been corrected in the HTML and PDF version of the article.
- 18 June 2018
- Published by Springer Nature in Nature Immunology
- Vol. 19 (9) , 1037
Publisher Correction: A tumor–myeloid cell axis, mediated via the cytokines IL-1α and TSLP, promotes the progression of breast cancer
In the version of this article initially published, the far right label along the horizontal axis of the right plot of Fig. 1e (4T1-Tslp–/– 4-6), the middle and right labels along the horizontal axis of the far right plot of Fig. 3d (4T1-Tslpr–/– 4-6 and 4T1-Tslpr–/– 2-3, respectively), and the far right label along the horizontal axis of Fig. 6h (4T1-Tslpr–/– 2-3) were incorrect. The correct labels are as follows: Fig. 1e, 4T1-Tslpr–/– 4-6; Fig. 3d, 4T1-Tslp–/– 2-3 and 4T1-Tslpr–/– 4-6, respectively; and Fig. 6h, 4T1-Tslpr–/– 4-6. Also, Fig. 4e was incorrectly a duplicate of an adjacent panel. The errors have been corrected in the HTML and PDF version of the article.
- Open Access
- 19 March 2018
- Published by Springer Nature in Nature Immunology
- Vol. 19 (4) , 366-374
A tumor–myeloid cell axis, mediated via the cytokines IL-1α and TSLP, promotes the progression of breast cancer
Tumors actively manipulate the immune response through the production of factors that attract immune cells and subsequently alter their ability to recognize and effectively remove the tumor. While this mechanism for evading the immune system is an important aspect of tumor survival, the factors that serve as primary growth factors for the tumor are less understood. Here we demonstrate a previously unknown mechanism by which breast-cancer cells manipulate tumor-infiltrating myeloid cells to maintain their survival. Tumor-derived interleukin 1α (IL-1α), acting on infiltrating myeloid cells, induced the expression of a critical tumor survival factor, the cytokine TSLP. TSLP promoted the survival of the tumor cells through induction of the expression of the anti-apoptotic molecule Bcl-2. TSLP signaling was also required for metastasis to the lungs. These studies define a novel IL-1α–TSLP-mediated crosstalk between tumor-infiltrating myeloid cells and tumor cells in the control of metastatic breast cancer.
- 19 March 2018
- Published by Springer Nature in Nature Immunology
- Vol. 19 (4) , 366-374
Open AccessA tumor–myeloid cell axis, mediated via the cytokines IL-1α and TSLP, promotes the progression of breast cancer
Tumors actively manipulate the immune response through the production of factors that attract immune cells and subsequently alter their ability to recognize and effectively remove the tumor. While this mechanism for evading the immune system is an important aspect of tumor survival, the factors that serve as primary growth factors for the tumor are less understood. Here we demonstrate a previously unknown mechanism by which breast-cancer cells manipulate tumor-infiltrating myeloid cells to maintain their survival. Tumor-derived interleukin 1α (IL-1α), acting on infiltrating myeloid cells, induced the expression of a critical tumor survival factor, the cytokine TSLP. TSLP promoted the survival of the tumor cells through induction of the expression of the anti-apoptotic molecule Bcl-2. TSLP signaling was also required for metastasis to the lungs. These studies define a novel IL-1α–TSLP-mediated crosstalk between tumor-infiltrating myeloid cells and tumor cells in the control of metastatic breast cancer.