Enhancing Precision in Detecting Severe Immune-Related Adverse Events: Comparative Analysis of Large Language Models and International Classification of Disease Codes in Patient Records.

PURPOSE: Current approaches to accurately identify immune-related adverse events (irAEs) in large retrospective studies are limited. Large language models (LLMs) offer a potential solution to this challenge, given their high performance in natural language comprehension tasks. Therefore, we investigated the use of an LLM to identify irAEs among hospitalized patients, comparing its performance with manual adjudication and International Classification of Disease (ICD) codes. METHODS: Hospital admissions of patients receiving immune checkpoint inhibitor (ICI) therapy at a single institution from February 5, 2011, to September 5, 2023, were individually reviewed and adjudicated for the presence of irAEs. ICD codes and an LLM with retrieval-augmented generation were applied to detect frequent irAEs (ICI-induced colitis, hepatitis, and pneumonitis) and the most fatal irAE (ICI-myocarditis) from electronic health records. The performance between ICD codes and LLM was compared via sensitivity and specificity with an α = .05, relative to the gold standard of manual adjudication. External validation was performed using a data set of hospital admissions from June 1, 2018, to May 31, 2019, from a second institution. RESULTS: Of the 7,555 admissions for patients on ICI therapy in the initial cohort, 2.0% were adjudicated to be due to ICI-colitis, 1.1% ICI-hepatitis, 0.7% ICI-pneumonitis, and 0.8% ICI-myocarditis. The LLM demonstrated higher sensitivity than ICD codes (94.7% v 68.7%), achieving significance for ICI-hepatitis (P < .001), myocarditis (P < .001), and pneumonitis (P = .003) while yielding similar specificities (93.7% v 92.4%). The LLM spent an average of 9.53 seconds/chart in comparison with an estimated 15 minutes for adjudication. In the validation cohort (N = 1,270), the mean LLM sensitivity and specificity were 98.1% and 95.7%, respectively. CONCLUSION: LLMs are a useful tool for the detection of irAEs, outperforming ICD codes in sensitivity and adjudication in efficiency.

A γδ T cell-IL-3 axis controls allergic responses through sensory neurons.

In naive individuals, sensory neurons directly detect and respond to allergens, leading to both the sensation of itch and the activation of local innate immune cells, which initiate the allergic immune response1,2. In the setting of chronic allergic inflammation, immune factors prime sensory neurons, causing pathologic itch3-7. Although these bidirectional neuroimmune circuits drive responses to allergens, whether immune cells regulate the set-point for neuronal activation by allergens in the naive state is unknown. Here we describe a γδ T cell-IL-3 signalling axis that controls the allergen responsiveness of cutaneous sensory neurons. We define a poorly characterized epidermal γδ T cell subset8, termed GD3 cells, that produces its hallmark cytokine IL-3 to promote allergic itch and the initiation of the allergic immune response. Mechanistically, IL-3 acts on Il3ra-expressing sensory neurons in a JAK2-dependent manner to lower their threshold for allergen activation without independently eliciting itch. This γδ T cell-IL-3 signalling axis further acts by means of STAT5 to promote neuropeptide production and the initiation of allergic immunity. These results reveal an endogenous immune rheostat that sits upstream of and governs sensory neuronal responses to allergens on first exposure. This pathway may explain individual differences in allergic susceptibility and opens new therapeutic avenues for treating allergic diseases.

IL-2 family cytokines IL-9 and IL-21 differentially regulate innate and adaptive type 2 immunity in asthma.

BACKGROUND: Asthma is often accompanied by type 2 immunity rich in IL-4, IL-5, and IL-13 cytokines produced by TH2 lymphocytes or type 2 innate lymphoid cells (ILC2s). IL-2 family cytokines play a key role in the differentiation, homeostasis, and effector function of innate and adaptive lymphocytes. OBJECTIVE: IL-9 and IL-21 boost activation and proliferation of TH2 and ILC2s, but the relative importance and potential synergism between these γ common chain cytokines are currently unknown. METHODS: Using newly generated antibodies, we inhibited IL-9 and IL-21 alone or in combination in various murine models of asthma. In a translational approach using segmental allergen challenge, we recently described elevated IL-9 levels in human subjects with allergic asthma compared with nonasthmatic controls. Here, we also measured IL-21 in both groups. RESULTS: IL-9 played a central role in controlling innate IL-33-induced lung inflammation by promoting proliferation and activation of ILC2s in an IL-21-independent manner. Conversely, chronic house dust mite-induced airway inflammation, mainly driven by adaptive immunity, was solely dependent on IL-21, which controlled TH2 activation, eosinophilia, total serum IgE, and formation of tertiary lymphoid structures. In a model of innate on adaptive immunity driven by papain allergen, a clear synergy was found between both pathways, as combined anti-IL-9 or anti-IL-21 blockade was superior in reducing key asthma features. In human bronchoalveolar lavage samples we measured elevated IL-21 protein within the allergic asthmatic group compared with the allergic control group. We also found increased IL21R transcripts and predicted IL-21 ligand activity in various disease-associated cell subsets. CONCLUSIONS: IL-9 and IL-21 play important and nonredundant roles in allergic asthma by boosting ILC2s and TH2 cells, revealing a dual IL-9 and IL-21 targeting strategy as a new and testable approach.

scTab: Scaling cross-tissue single-cell annotation models.

Identifying cellular identities is a key use case in single-cell transcriptomics. While machine learning has been leveraged to automate cell annotation predictions for some time, there has been little progress in scaling neural networks to large data sets and in constructing models that generalize well across diverse tissues. Here, we propose scTab, an automated cell type prediction model specific to tabular data, and train it using a novel data augmentation scheme across a large corpus of single-cell RNA-seq observations (22.2 million cells). In this context, we show that cross-tissue annotation requires nonlinear models and that the performance of scTab scales both in terms of training dataset size and model size. Additionally, we show that the proposed data augmentation schema improves model generalization. In summary, we introduce a de novo cell type prediction model for single-cell RNA-seq data that can be trained across a large-scale collection of curated datasets and demonstrate the benefits of using deep learning methods in this paradigm.

Identification of Immune Checkpoint Inhibitor-Induced Diabetes.

Importance: Immune checkpoint inhibitors (ICIs) have revolutionized cancer care; however, accompanying immune-related adverse events (irAEs) confer substantial morbidity and occasional mortality. Life-threatening irAEs may require permanent cessation of ICI, even in patients with positive tumor response. Therefore, it is imperative to comprehensively define the spectrum of irAEs to aid individualized decision-making around the initiation of ICI therapy. Objective: To define incidence, risk factors, and clinical spectrum of an irreversible and life-threatening irAE: ICI-induced diabetes. Design, Setting, and Participants: This cohort study, conducted at an academic integrated health care system examined 14 328 adult patients treated with ICIs, including 64 patients who developed ICI-induced diabetes, from July 2010 to January 2022. The data were analyzed from 2022 to 2023. Cases of ICI-induced diabetes were manually confirmed; detailed clinical phenotyping was performed at diagnosis and 1-year follow-up. For 862 patients, genotyping data were available, and polygenic risk for type 1 diabetes was determined. Main Outcomes and Measures: For ICI-induced diabetes cases and controls, demographic characteristics, comorbidities, tumor category, and ICI category were compared. Among ICI-induced diabetes cases, markers of glycemic physiology were examined at diagnosis and 1-year follow-up. For patients with available genotyping, a published type 1 diabetes polygenic score (T1D GRS2) was calculated. Results: Of 14 328 participants, 6571 (45.9%) were women, and the median (range) age was 66 (8-106) years. The prevalence of ICI-induced diabetes among ICI-treated patients was 0.45% (64 of 14 328), with an incidence of 124.8 per 100 000 person-years. Preexisting type 2 diabetes (odds ratio [OR], 5.91; 95% CI, 3.34-10.45) and treatment with combination ICI (OR, 2.57; 95% CI, 1.44-4.59) were significant clinical risk factors of ICI-induced diabetes. T1D GRS2 was associated with ICI-induced diabetes risk, with an OR of 4.4 (95% CI, 1.8-10.5) for patients in the top decile of T1D GRS2, demonstrating a genetic association between spontaneous autoimmunity and irAEs. Patients with ICI-induced diabetes were in 3 distinct phenotypic categories based on autoantibodies and residual pancreatic function, with varying severity of initial presentation. Conclusions and Relevance: The results of this analysis of 14 328 ICI-treated patients followed up from ICI initiation determined the incidence, risk factors and clinical spectrum of ICI-induced diabetes. Widespread implementation of this approach across organ-specific irAEs may enhance diagnosis and management of these conditions, and this becomes especially pertinent as ICI treatment rapidly expands to treat a wide spectrum of cancers and is used at earlier stages of treatment.

Airway basal stem cells are necessary for the maintenance of functional intraepithelial airway macrophages.

Adult stem cells play a crucial role in tissue homeostasis and repair through multiple mechanisms. In addition to being able to replace aged or damaged cells, stem cells provide signals that contribute to the maintenance and function of neighboring cells. In the lung, airway basal stem cells also produce cytokines and chemokines in response to inhaled irritants, allergens, and pathogens, which affect specific immune cell populations and shape the nature of the immune response. However, direct cell-to-cell signaling through contact between airway basal stem cells and immune cells has not been demonstrated. Recently, a unique population of intraepithelial airway macrophages (IAMs) has been identified in the murine trachea. Here, we demonstrate that IAMs require Notch signaling from airway basal stem cells for maintenance of their differentiated state and function. Furthermore, we demonstrate that Notch signaling between airway basal stem cells and IAMs is required for antigen-induced allergic inflammation only in the trachea where the basal stem cells are located whereas allergic responses in distal lung tissues are preserved consistent with a local circuit linking stem cells to proximate immune cells. Finally, we demonstrate that IAM-like cells are present in human conducting airways and that these cells display Notch activation, mirroring their murine counterparts. Since diverse lung stem cells have recently been identified and localized to specific anatomic niches along the proximodistal axis of the respiratory tree, we hypothesize that the direct functional coupling of local stem cell-mediated regeneration and immune responses permits a compartmentalized inflammatory response.

Single-cell transcriptomic analyses reveal distinct immune cell contributions to epithelial barrier dysfunction in checkpoint inhibitor colitis.

Immune checkpoint inhibitor (ICI) therapy has revolutionized oncology, but treatments are limited by immune-related adverse events, including checkpoint inhibitor colitis (irColitis). Little is understood about the pathogenic mechanisms driving irColitis, which does not readily occur in model organisms, such as mice. To define molecular drivers of irColitis, we used single-cell multi-omics to profile approximately 300,000 cells from the colon mucosa and blood of 13 patients with cancer who developed irColitis (nine on anti-PD-1 or anti-CTLA-4 monotherapy and four on dual ICI therapy; most patients had skin or lung cancer), eight controls on ICI therapy and eight healthy controls. Patients with irColitis showed expanded mucosal Tregs, ITGAEHi CD8 tissue-resident memory T cells expressing CXCL13 and Th17 gene programs and recirculating ITGB2Hi CD8 T cells. Cytotoxic GNLYHi CD4 T cells, recirculating ITGB2Hi CD8 T cells and endothelial cells expressing hypoxia gene programs were further expanded in colitis associated with anti-PD-1/CTLA-4 therapy compared to anti-PD-1 therapy. Luminal epithelial cells in patients with irColitis expressed PCSK9, PD-L1 and interferon-induced signatures associated with apoptosis, increased cell turnover and malabsorption. Together, these data suggest roles for circulating T cells and epithelial-immune crosstalk critical to PD-1/CTLA-4-dependent tolerance and barrier function and identify potential therapeutic targets for irColitis.

SARS-CoV-2 infection elucidates unique features of pregnancy-specific immunity.

Pregnancy is a risk factor for increased severity of SARS-CoV-2 and other respiratory infections. The mechanisms underlying this risk have not been well-established, partly due to a limited understanding of how pregnancy shapes immune responses. To gain insight into the role of pregnancy in modulating immune responses at steady state and upon perturbation, we collected peripheral blood mononuclear cells (PBMC), plasma, and stool from 226 women, including 152 pregnant individuals (n = 96 with SARS-CoV-2 infection and n = 56 healthy controls) and 74 non-pregnant women (n = 55 with SARS-CoV-2 and n = 19 healthy controls). We found that SARS-CoV-2 infection was associated with altered T cell responses in pregnant compared to non-pregnant women. Differences included a lower percentage of memory T cells, a distinct clonal expansion of CD4-expressing CD8 + T cells, and the enhanced expression of T cell exhaustion markers, such as programmed cell death-1 (PD-1) and T cell immunoglobulin and mucin domain-3 (Tim-3), in pregnant women. We identified additional evidence of immune dysfunction in severely and critically ill pregnant women, including a lack of expected elevation in regulatory T cell (Treg) levels, diminished interferon responses, and profound suppression of monocyte function. Consistent with earlier data, we found maternal obesity was also associated with altered immune responses to SARS-CoV-2 infection, including enhanced production of inflammatory cytokines by T cells. Certain gut bacterial species were altered in pregnancy and upon SARS-CoV-2 infection in pregnant individuals compared to non-pregnant women. Shifts in cytokine and chemokine levels were also identified in the sera of pregnant individuals, most notably a robust increase of interleukin-27 (IL-27), a cytokine known to drive T cell exhaustion, in the pregnant uninfected control group compared to all non-pregnant groups. IL-27 levels were also significantly higher in uninfected pregnant controls compared to pregnant SARS-CoV-2-infected individuals. Using two different preclinical mouse models of inflammation-induced fetal demise and respiratory influenza viral infection, we found that enhanced IL-27 protects developing fetuses from maternal inflammation but renders adult female mice vulnerable to viral infection. These combined findings from human and murine studies reveal nuanced pregnancy-associated immune responses, suggesting mechanisms underlying the increased susceptibility of pregnant individuals to viral respiratory infections.

Gene-based association study of rare variants in children of diverse ancestries implicates TNFRSF21 in the development of allergic asthma.

BACKGROUND: Most genetic studies of asthma and allergy have focused on common variation in individuals primarily of European ancestry. Studying the role of rare variation in quantitative phenotypes and in asthma phenotypes in populations of diverse ancestries can provide additional, important insights into the development of these traits. OBJECTIVE: We sought to examine the contribution of rare variants to different asthma- or allergy-associated quantitative traits in children with diverse ancestries and explore their role in asthma phenotypes. METHODS: We examined whole-genome sequencing data from children participants in longitudinal studies of asthma (n = 1035; parent-identified as 67% Black and 25% Hispanic) to identify rare variants (minor allele frequency < 0.01). We assigned variants to genes and tested for associations using an omnibus variant-set test between each of 24,902 genes and 8 asthma-associated quantitative traits. On combining our results with external data on predicted gene expression in humans and mouse knockout studies, we identified 3 candidate genes. A burden of rare variants in each gene and in a combined 3-gene score was tested for its associations with clinical phenotypes of asthma. Finally, published single-cell gene expression data in lower airway mucosal cells after allergen challenge were used to assess transcriptional responses to allergen. RESULTS: Rare variants in USF1 were significantly associated with blood neutrophil count (P = 2.18 × 10-7); rare variants in TNFRSF21 with total IgE (P = 6.47 × 10-6) and PIK3R6 with eosinophil count (P = 4.10 × 10-5) reached suggestive significance. These 3 findings were supported by independent data from human and mouse studies. A burden of rare variants in TNFRSF21 and in a 3-gene score was associated with allergy-related phenotypes in cohorts of children with mild and severe asthma. Furthermore, TNFRSF21 was significantly upregulated in bronchial basal epithelial cells from adults with allergic asthma but not in adults with allergies (but not asthma) after allergen challenge. CONCLUSIONS: We report novel associations between rare variants in genes and allergic and inflammatory phenotypes in children with diverse ancestries, highlighting TNFRSF21 as contributing to the development of allergic asthma.

Single-cell RNA sequencing of murine ankle joints over time reveals distinct transcriptional changes following Borrelia burgdorferi infection.

Lyme disease is caused by the bacterial pathogen Borrelia burgdorferi, which can be readily modeled in laboratory mice. In order to understand the cellular and transcriptional changes that occur during B. burgdorferi infection, we conducted single-cell RNA sequencing (scRNA-seq) of ankle joints of infected C57BL/6 mice over time. We found that macrophages/monocytes, T cells, synoviocytes and fibroblasts all showed significant differences in gene expression of both inflammatory and non-inflammatory genes that peaked early and returned to baseline before the typical resolution of arthritis. Predictions of cellular interactions showed that macrophages appear to communicate extensively between different clusters of macrophages as well as with fibroblasts and synoviocytes. Our data give unique insights into the interactions between B. burgdorferi and the murine immune system over time and allow for a better understanding of mechanisms by which the dysregulation of the immune response may lead to prolonged symptoms in some patients.

Immune Responses in Checkpoint Myocarditis Across Heart, Blood, and Tumor.

Immune checkpoint inhibitors (ICIs) are widely used anti-cancer therapies that can cause morbid and potentially fatal immune-related adverse events (irAEs). ICI-related myocarditis (irMyocarditis) is uncommon but has the highest mortality of any irAE. The pathogenesis of irMyocarditis and its relationship to anti-tumor immunity remain poorly understood. We sought to define immune responses in heart, tumor, and blood during irMyocarditis and identify biomarkers of clinical severity by leveraging single-cell (sc)RNA-seq coupled with T cell receptor (TCR) sequencing, microscopy, and proteomics analysis of 28 irMyocarditis patients and 23 controls. Our analysis of 284,360 cells from heart and blood specimens identified cytotoxic T cells, inflammatory macrophages, conventional dendritic cells (cDCs), and fibroblasts enriched in irMyocarditis heart tissue. Additionally, potentially targetable, pro-inflammatory transcriptional programs were upregulated across multiple cell types. TCR clones enriched in heart and paired tumor tissue were largely non-overlapping, suggesting distinct T cell responses within these tissues. We also identify the presence of cardiac-expanded TCRs in a circulating, cycling CD8 T cell population as a novel peripheral biomarker of fatality. Collectively, these findings highlight critical biology driving irMyocarditis and putative biomarkers for therapeutic intervention.

Scaling cross-tissue single-cell annotation models.

Identifying cellular identities (both novel and well-studied) is one of the key use cases in single-cell transcriptomics. While supervised machine learning has been leveraged to automate cell annotation predictions for some time, there has been relatively little progress both in scaling neural networks to large data sets and in constructing models that generalize well across diverse tissues and biological contexts up to whole organisms. Here, we propose scTab, an automated, feature-attention-based cell type prediction model specific to tabular data, and train it using a novel data augmentation scheme across a large corpus of single-cell RNA-seq observations (22.2 million human cells in total). In addition, scTab leverages deep ensembles for uncertainty quantification. Moreover, we account for ontological relationships between labels in the model evaluation to accommodate for differences in annotation granularity across datasets. On this large-scale corpus, we show that cross-tissue annotation requires nonlinear models and that the performance of scTab scales in terms of training dataset size as well as model size - demonstrating the advantage of scTab over current state-of-the-art linear models in this context. Additionally, we show that the proposed data augmentation schema improves model generalization. In summary, we introduce a de novo cell type prediction model for single-cell RNA-seq data that can be trained across a large-scale collection of curated datasets from a diverse selection of human tissues and demonstrate the benefits of using deep learning methods in this paradigm. Our codebase, training data, and model checkpoints are publicly available at https://github.com/theislab/scTab to further enable rigorous benchmarks of foundation models for single-cell RNA-seq data.

Resident memory T cell development is associated with AP-1 transcription factor upregulation across anatomical niches.

Tissue-resident memory T (T RM ) cells play a central role in immune responses to pathogens across all barrier tissues after infection. However, the underlying mechanisms that drive T RM differentiation and priming for their recall effector function remains unclear. In this study, we leveraged both newly generated and publicly available single-cell RNA-sequencing (scRNAseq) data generated across 10 developmental time points to define features of CD8 T RM across both skin and small-intestine intraepithelial lymphocytes (siIEL). We employed linear modeling to capture temporally-associated gene programs that increase their expression levels in T cell subsets transitioning from an effector to a memory T cell state. In addition to capturing tissue-specific gene programs, we defined a consensus T RM signature of 60 genes across skin and siIEL that can effectively distinguish T RM from circulating T cell populations, providing a more specific T RM signature than what was previously generated by comparing bulk T RM to naïve or non-tissue resident memory populations. This updated T RM signature included the AP-1 transcription factor family members Fos, Fosb and Fosl2 . Moreover, ATACseq analysis detected an enrichment of AP-1-specific motifs at open chromatin sites in mature T RM . CyCIF tissue imaging detected nuclear co-localization of AP-1 members Fosb and Junb in resting CD8 T RM >100 days post-infection. Taken together, these results reveal a critical role of AP-1 transcription factor members in T RM biology and suggests a novel mechanism for rapid reactivation of resting T RM in tissue upon antigen encounter.

A human model of asthma exacerbation reveals transcriptional programs and cell circuits specific to allergic asthma.

Asthma is a chronic disease most commonly associated with allergy and type 2 inflammation. However, the mechanisms that link airway inflammation to the structural changes that define asthma are incompletely understood. Using a human model of allergen-induced asthma exacerbation, we compared the lower airway mucosa in allergic asthmatics and allergic non-asthmatic controls using single-cell RNA sequencing. In response to allergen, the asthmatic airway epithelium was highly dynamic and up-regulated genes involved in matrix degradation, mucus metaplasia, and glycolysis while failing to induce injury-repair and antioxidant pathways observed in controls. IL9-expressing pathogenic TH2 cells were specific to asthmatic airways and were only observed after allergen challenge. Additionally, conventional type 2 dendritic cells (DC2 that express CD1C) and CCR2-expressing monocyte-derived cells (MCs) were uniquely enriched in asthmatics after allergen, with up-regulation of genes that sustain type 2 inflammation and promote pathologic airway remodeling. In contrast, allergic controls were enriched for macrophage-like MCs that up-regulated tissue repair programs after allergen challenge, suggesting that these populations may protect against asthmatic airway remodeling. Cellular interaction analyses revealed a TH2-mononuclear phagocyte-basal cell interactome unique to asthmatics. These pathogenic cellular circuits were characterized by type 2 programming of immune and structural cells and additional pathways that may sustain and amplify type 2 signals, including TNF family signaling, altered cellular metabolism, failure to engage antioxidant responses, and loss of growth factor signaling. Our findings therefore suggest that pathogenic effector circuits and the absence of proresolution programs drive structural airway disease in response to type 2 inflammation.

Protocol for bulk RNA sequencing of enriched human neutrophils from whole blood and estimation of sample purity.

Although neutrophils are the most abundant leukocyte in healthy individuals and impact outcomes of diseases ranging from sepsis to cancer, they remain understudied due to technical constraints of isolation, preservation, and sequencing. We present a modified Smart-Seq2 protocol for bulk RNA sequencing of neutrophils enriched from whole blood. We describe steps for neutrophil isolation, cDNA generation, library preparation, and sample purity estimation via a bioinformatic approach. Our approach permits the collection of large cohorts and enables detection of neutrophil transcriptomic subtypes. For complete details on the use and execution of this protocol, please refer to LaSalle et al. (2022)1 and Boribong et al. (2022).2.

Soluble and cell-based markers of immune checkpoint inhibitor-associated nephritis.

BACKGROUND: Non-invasive biomarkers of immune checkpoint inhibitor-associated acute tubulointerstitial nephritis (ICI-nephritis) are urgently needed. Because ICIs block immune checkpoint pathways that include cytotoxic T lymphocyte antigen 4 (CTLA4), we hypothesized that biomarkers of immune dysregulationpreviously defined in patients with congenital CTLA4 deficiency, including elevated soluble interleukin-2 receptor alpha (sIL-2R) and flow cytometric cell-based markers of B and T cell dysregulation in peripheral blood may aid the diagnosis of ICI-nephritis. METHODS: A retrospective cohort of patients diagnosed with ICI-nephritis was compared with three prospectively enrolled control cohorts: ICI-treated controls without immune-related adverse events, patients not on ICIs with hemodynamic acute kidney injury (hemodynamic AKI), and patients not on ICIs with biopsy proven acute interstitial nephritis from other causes (non-ICI-nephritis). sIL-2R level and flow cytometric parameters were compared between groups using Wilcoxon rank sum test or Kruskal-Wallis test. Receiver operating characteristic curves were generated to define the accuracy of sIL-2R and flow cytometric biomarkers in diagnosing ICI-nephritis. The downstream impact of T cell activation in the affected kidney was investigated using archived biopsy samples to evaluate the gene expression of IL2RA, IL-2 signaling, and T cell receptor signaling in patients with ICI-nephritis compared with other causes of drug-induced nephritis, acute tubular injury, and histologically normal controls. RESULTS: sIL-2R level in peripheral blood was significantly higher in patients with ICI-nephritis (N=24) (median 2.5-fold upper limit of normal (ULN), IQR 1.9-3.3), compared with ICI-treated controls (N=10) (median 0.8-fold ULN, IQR 0.5-0.9, p<0.001) and hemodynamic AKI controls (N=6) (median 0.9-fold-ULN, IQR 0.7-1.1, p=0.008). A sIL-2R cut-off point of 1.75-fold ULN was highly diagnostic of ICI-nephritis (area under the curve >96%) when compared with either ICI-treated or hemodynamic AKI controls. By peripheral blood flow cytometry analysis, lower absolute CD8+T cells, CD45RA+CD8+ T cells, memory CD27+B cells, and expansion of plasmablasts were prominent features of ICI-nephritis compared with ICI-treated controls. Gene expressions for IL2RA, IL-2 signaling, and T cell receptor signaling in the kidney tissue with ICI-nephritis were significantly higher compared with controls. CONCLUSION: Elevated sIL-2R level and flow cytometric markers of both B and T cell dysregulation may aid the diagnosis of ICI-nephritis.

Germline variants associated with toxicity to immune checkpoint blockade.

Immune checkpoint inhibitors (ICIs) have yielded remarkable responses but often lead to immune-related adverse events (irAEs). Although germline causes for irAEs have been hypothesized, no individual variant associated with developing irAEs has been identified. We carried out a genome-wide association study of 1,751 patients on ICIs across 12 cancer types. We investigated two irAE phenotypes: (1) high-grade (3-5) and (2) all-grade events. We identified 3 genome-wide significant associations (P < 5 × 10-8) in the discovery cohort associated with all-grade irAEs: rs16906115 near IL7 (combined P = 3.6 × 10-11; hazard ratio (HR) = 2.1); rs75824728 near IL22RA1 (combined P = 3.5 × 10-8; HR = 1.8); and rs113861051 on 4p15 (combined P = 1.2 × 10-8, HR = 2.0); rs16906115 was replicated in 3 independent studies. The association near IL7 colocalized with the gain of a new cryptic exon for IL7, a critical regulator of lymphocyte homeostasis. Patients carrying the IL7 germline variant exhibited significantly increased lymphocyte stability after ICI initiation, which was itself predictive of downstream irAEs and improved survival.

Longitudinal characterization of circulating neutrophils uncovers phenotypes associated with severity in hospitalized COVID-19 patients.

Mechanisms of neutrophil involvement in severe coronavirus disease 2019 (COVID-19) remain incompletely understood. Here, we collect longitudinal blood samples from 306 hospitalized COVID-19+ patients and 86 controls and perform bulk RNA sequencing of enriched neutrophils, plasma proteomics, and high-throughput antibody profiling to investigate relationships between neutrophil states and disease severity. We identify dynamic switches between six distinct neutrophil subtypes. At days 3 and 7 post-hospitalization, patients with severe disease display a granulocytic myeloid-derived suppressor cell-like gene expression signature, while patients with resolving disease show a neutrophil progenitor-like signature. Humoral responses are identified as potential drivers of neutrophil effector functions, with elevated severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)-specific immunoglobulin G1 (IgG1)-to-IgA1 ratios in plasma of severe patients who survived. In vitro experiments confirm that while patient-derived IgG antibodies induce phagocytosis in healthy donor neutrophils, IgA antibodies predominantly induce neutrophil cell death. Overall, our study demonstrates a dysregulated myelopoietic response in severe COVID-19 and a potential role for IgA-dominant responses contributing to mortality.

Plasmacytoid dendritic cells: Welcome back to the DC fold.

The presumed common origin of plasmacytoid and conventional dendritic cells has been the contentious subject of recent debate. In this issue of Immunity, Feng et al. employed an inducible cell barcoding system to track clonal relationships and uncovered a surprising close developmental relationship between cDC1s and pDCs.