Demuxafy: improvement in droplet assignment by integrating multiple single-cell demultiplexing and doublet detection methods

Recent innovations in single-cell RNA-sequencing (scRNA-seq) provide the technology to investigate biological questions at cellular resolution. Pooling cells from multiple individuals has become a common strategy, and droplets can subsequently be assigned to a specific individual by leveraging their inherent genetic differences. An implicit challenge with scRNA-seq is the occurrence of doublets-droplets containing two or more cells. We develop Demuxafy, a framework to enhance donor assignment and doublet removal through the consensus intersection of multiple demultiplexing and doublet detecting methods. Demuxafy significantly improves droplet assignment by separating singlets from doublets and classifying the correct individual.

CD4+ CAR-T cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR-T cell therapy

Multiple myeloma is characterized by frequent clinical relapses following conventional therapy. Recently, chimeric antigen receptor T (CAR-T) cells targeting B-cell maturation antigen (BCMA) has been established as a treatment option for patients with relapsed or refractory disease. However, while >70% of patients initially respond to this treatment, clinical relapse and disease progression occur in most cases. Recent studies showed persistent expression of BCMA at the time of relapse, indicating that immune intrinsic mechanisms may contribute to this resistance. While there were no pre-existing T cell features associated with clinical outcomes, we found that patients with a durable response to CAR-T cell treatment had greater persistence of their CAR-T cells compared to patients with transient clinical responses. They also possessed a significantly higher proportion of CD8+ T effector memory cells. In contrast, patients with short-lived responses to treatment have increased frequencies of cytotoxic CD4+ CAR-T cells. These cells expand in vivo early after infusion but express exhaustion markers (HAVCR2 and TIGIT) and remain polyclonal. Finally, we demonstrate that non-classical monocytes are enriched in the myeloma niche and may induce CAR-T cell dysfunction through mechanisms that include TGFβ. These findings shed new light on the role of cytotoxic CD4+ T cells in disease progression after CAR-T cell therapy.

Cell subtype-specific effects of genetic variation in the Alzheimer's disease brain

The relationship between genetic variation and gene expression in brain cell types and subtypes remains understudied. Here, we generated single-nucleus RNA sequencing data from the neocortex of 424 individuals of advanced age; we assessed the effect of genetic variants on RNA expression in cis (cis-expression quantitative trait loci) for seven cell types and 64 cell subtypes using 1.5 million transcriptomes. This effort identified 10,004 eGenes at the cell type level and 8,099 eGenes at the cell subtype level. Many eGenes are only detected within cell subtypes. A new variant influences APOE expression only in microglia and is associated with greater cerebral amyloid angiopathy but not Alzheimer's disease pathology, after adjusting for APOEε4, providing mechanistic insights into both pathologies. Furthermore, only a TMEM106B variant affects the proportion of cell subtypes. Integration of these results with genome-wide association studies highlighted the targeted cell type and probable causal gene within Alzheimer's disease, schizophrenia, educational attainment and Parkinson's disease loci.

SingleQ: a comprehensive database of single-cell expression quantitative trait loci (sc-eQTLs) cross human tissues

Mapping of expression quantitative trait loci (eQTLs) and other molecular QTLs can help characterize the modes of action of disease-associated genetic variants. However, current eQTL databases present data from bulk RNA-seq approaches, which cannot shed light on the cell type- and environment-specific regulation of disease-associated genetic variants. Here, we introduce our Single-cell eQTL Interactive Database which collects single-cell eQTL (sc-eQTL) datasets and provides online visualization of sc-eQTLs across different cell types in a user-friendly manner. Although sc-eQTL mapping is still in its early stage, our database curates the most comprehensive summary statistics of sc-eQTLs published to date. sc-eQTL studies have revolutionized our understanding of gene regulation in specific cellular contexts, and we anticipate that our database will further accelerate the research of functional genomics. Database URL: http://www.sqraolab.com/scqtl.

Functional genomics in inborn errors of immunity

Inborn errors of immunity (IEI) comprise a diverse spectrum of 485 disorders as recognized by the International Union of Immunological Societies Committee on Inborn Error of Immunity in 2022. While IEI are monogenic by definition, they illuminate various pathways involved in the pathogenesis of polygenic immune dysregulation as in autoimmune or autoinflammatory syndromes, or in more common infectious diseases that may not have a significant genetic basis. Rapid improvement in genomic technologies has been the main driver of the accelerated rate of discovery of IEI and has led to the development of innovative treatment strategies. In this review, we will explore various facets of IEI, delving into the distinctions between PIDD and PIRD. We will examine how Mendelian inheritance patterns contribute to these disorders and discuss advancements in functional genomics that aid in characterizing new IEI. Additionally, we will explore how emerging genomic tools help to characterize new IEI as well as how they are paving the way for innovative treatment approaches for managing and potentially curing these complex immune conditions.

Population Diversity at the Single-Cell Level

Population-scale single-cell genomics is a transformative approach for unraveling the intricate links between genetic and cellular variation. This approach is facilitated by cutting-edge experimental methodologies, including the development of high-throughput single-cell multiomics and advances in multiplexed environmental and genetic perturbations. Examining the effects of natural or synthetic genetic variants across cellular contexts provides insights into the mutual influence of genetics and the environment in shaping cellular heterogeneity. The development of computational methodologies further enables detailed quantitative analysis of molecular variation, offering an opportunity to examine the respective roles of stochastic, intercellular, and interindividual variation. Future opportunities lie in leveraging long-read sequencing, refining disease-relevant cellular models, and embracing predictive and generative machine learning models. These advancements hold the potential for a deeper understanding of the genetic architecture of human molecular traits, which in turn has important implications for understanding the genetic causes of human disease. Expected final online publication date for the Annual Review of Genomics and Human Genetics, Volume 25 is August 2024. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

SURGE: uncovering context-specific genetic-regulation of gene expression from single-cell RNA sequencing using latent-factor models

Genetic regulation of gene expression is a complex process, with genetic effects known to vary across cellular contexts such as cell types and environmental conditions. We developed SURGE, a method for unsupervised discovery of context-specific expression quantitative trait loci (eQTLs) from single-cell transcriptomic data. This allows discovery of the contexts or cell types modulating genetic regulation without prior knowledge. Applied to peripheral blood single-cell eQTL data, SURGE contexts capture continuous representations of distinct cell types and groupings of biologically related cell types. We demonstrate the disease-relevance of SURGE context-specific eQTLs using colocalization analysis and stratified LD-score regression.

Base-editing mutagenesis maps alleles to tune human T cell functions

CRISPR-enabled screening is a powerful tool for the discovery of genes that control T cell function and has nominated candidate targets for immunotherapies1-6. However, new approaches are required to probe specific nucleotide sequences within key genes. Systematic mutagenesis in primary human T cells could reveal alleles that tune specific phenotypes. DNA base editors are powerful tools for introducing targeted mutations with high efficiency7,8. Here we develop a large-scale base-editing mutagenesis platform with the goal of pinpointing nucleotides that encode amino acid residues that tune primary human T cell activation responses. We generated a library of around 117,000 single guide RNA molecules targeting base editors to protein-coding sites across 385 genes implicated in T cell function and systematically identified protein domains and specific amino acid residues that regulate T cell activation and cytokine production. We found a broad spectrum of alleles with variants encoding critical residues in proteins including PIK3CD, VAV1, LCP2, PLCG1 and DGKZ, including both gain-of-function and loss-of-function mutations. We validated the functional effects of many alleles and further demonstrated that base-editing hits could positively and negatively tune T cell cytotoxic function. Finally, higher-resolution screening using a base editor with relaxed protospacer-adjacent motif requirements9 (NG versus NGG) revealed specific structural domains and protein-protein interaction sites that can be targeted to tune T cell functions. Base-editing screens in primary immune cells thus provide biochemical insights with the potential to accelerate immunotherapy design.

Vaccine breakthrough hypoxemic COVID-19 pneumonia in patients with auto-Abs neutralizing type I IFNs

Life-threatening "breakthrough" cases of critical COVID-19 are attributed to poor or waning antibody (Ab) response to SARS-CoV-2 vaccines in individuals already at risk. Preexisting auto-Abs neutralizing type I IFNs underlie at least 15% of critical COVID-19 pneumonia cases in unvaccinated individuals; their contribution to hypoxemic breakthrough cases in vaccinated people is unknown. We studied a cohort of 48 individuals (aged 20 to 86 years) who received two doses of a messenger RNA (mRNA) vaccine and developed a breakthrough infection with hypoxemic COVID-19 pneumonia 2 weeks to 4 months later. Ab levels to the vaccine, neutralization of the virus, and auto-Abs to type I IFNs were measured in the plasma. Forty-two individuals had no known deficiency of B cell immunity and a normal Ab response to the vaccine. Among them, 10 (24%) had auto-Abs neutralizing type I IFNs (aged 43 to 86 years). Eight of these 10 patients had auto-Abs neutralizing both IFN-α2 and IFN-ω, whereas two neutralized IFN-ω only. No patient neutralized IFN-β. Seven neutralized type I IFNs at 10 ng/ml and three at 100 pg/ml only. Seven patients neutralized SARS-CoV-2 D614G and Delta efficiently, whereas one patient neutralized Delta slightly less efficiently. Two of the three patients neutralizing only type I IFNs at 100 pg/ml neutralized both D614G and Delta less efficiently. Despite two mRNA vaccine inoculations and the presence of circulating Abs capable of neutralizing SARS-CoV-2, auto-Abs neutralizing type I IFNs may underlie a notable proportion of hypoxemic COVID-19 pneumonia cases, highlighting the importance of this particularly vulnerable population.

ADPKD-Causing Missense Variants in Polycystin-1 Disrupt Cell Surface Localization or Polycystin Channel Function

Autosomal dominant polycystic kidney disease (ADPKD) is the leading monogenic cause of kidney failure and affects millions of people worldwide. Despite the prevalence of this monogenic disorder, our limited mechanistic understanding of ADPKD has hindered therapeutic development. Here, we successfully developed bioassays that functionally classify missense variants in polycystin-1 (PC1). Strikingly, ADPKD pathogenic missense variants cluster into two major categories: 1) those that disrupt polycystin cell surface localization or 2) those that attenuate polycystin ion channel activity. We found that polycystin channels with defective surface localization could be rescued with a small molecule. We propose that small-molecule-based strategies to improve polycystin cell surface localization and channel function will be effective therapies for ADPKD patients.

Coordinated immune dysregulation in Juvenile Dermatomyositis revealed by single-cell genomics

Juvenile Dermatomyositis (JDM) is one of several childhood-onset autoimmune disorders characterized by a type I interferon response and autoantibodies. Treatment options are limited due to incomplete understanding of how the disease emerges from dysregulated cell states across the immune system. We therefore investigated the blood of JDM patients at different stages of disease activity using single-cell transcriptomics paired with surface protein expression. By immunophenotyping peripheral blood mononuclear cells, we observed skewing of the B cell compartment towards an immature naive state as a hallmark of JDM. Furthermore, we find that these changes in B cells are paralleled by signatures of Th2-mediated inflammation. Additionally, our work identified SIGLEC-1 expression in monocytes as a composite measure of heterogeneous type I interferon activity in disease. We applied network analysis to reveal that hyperactivation of the type I interferon response in all immune populations is coordinated with dysfunctional protein processing and regulation of cell death programming. This analysis separated the ubiquitously expressed type I interferon response into a central hub and revealed previously masked cell states. Together, these findings reveal the coordinated immune dysregulation underpinning JDM and provide novel insight into strategies for restoring balance in immune function.

A myeloid program associated with COVID-19 severity is decreased by therapeutic blockade of IL-6 signaling

Altered myeloid inflammation and lymphopenia are hallmarks of severe infections. We identified the upregulated EN-RAGE gene program in airway and blood myeloid cells from patients with acute lung injury from SARS-CoV-2 or other causes across 7 cohorts. This program was associated with greater clinical severity and predicted future mechanical ventilation and death. EN-RAGEhi myeloid cells express features consistent with suppressor cell functionality, including low HLA-DR and high PD-L1. Sustained EN-RAGE program expression in airway and blood myeloid cells correlated with clinical severity and increasing expression of T cell dysfunction markers. IL-6 upregulated many EN-RAGE program genes in monocytes in vitro. IL-6 signaling blockade by tocilizumab in a placebo-controlled clinical trial led to rapid normalization of EN-RAGE and T cell gene expression. This identifies IL-6 as a key driver of myeloid dysregulation associated with worse clinical outcomes in COVID-19 patients and provides insights into shared pathophysiological mechanisms in non-COVID-19 ARDS.

Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome remains a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that chromosome loss was generalizable across the genome and resulted in partial and entire loss of the targeted chromosome, including in preclinical chimeric antigen receptor T cells. T cells with chromosome loss persisted for weeks in culture, implying the potential to interfere with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells (NCT03399448), reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with protection from chromosome loss observed in this protocol, suggesting both a mechanism and strategy for T cell engineering that mitigates this genotoxicity in the clinic.

Systematic functional interrogation of SARS-CoV-2 host factors using Perturb-seq

Genomic and proteomic screens have identified numerous host factors of SARS-CoV-2, but efficient delineation of their molecular roles during infection remains a challenge. Here we use Perturb-seq, combining genetic perturbations with a single-cell readout, to investigate how inactivation of host factors changes the course of SARS-CoV-2 infection and the host response in human lung epithelial cells. Our high-dimensional data resolve complex phenotypes such as shifts in the stages of infection and modulations of the interferon response. However, only a small percentage of host factors showed such phenotypes upon perturbation. We further identified the NF-κB inhibitor IκBα (NFKBIA), as well as the translation factors EIF4E2 and EIF4H as strong host dependency factors acting early in infection. Overall, our study provides massively parallel functional characterization of host factors of SARS-CoV-2 and quantitatively defines their roles both in virus-infected and bystander cells.

Functional characterization of Alzheimer's disease genetic variants in microglia

Candidate cis-regulatory elements (cCREs) in microglia demonstrate the most substantial enrichment for Alzheimer's disease (AD) heritability compared to other brain cell types. However, whether and how these genome-wide association studies (GWAS) variants contribute to AD remain elusive. Here we prioritize 308 previously unreported AD risk variants at 181 cCREs by integrating genetic information with microglia-specific 3D epigenome annotation. We further establish the link between functional variants and target genes by single-cell CRISPRi screening in microglia. In addition, we show that AD variants exhibit allelic imbalance on target gene expression. In particular, rs7922621 is the effective variant in controlling TSPAN14 expression among other nominated variants in the same cCRE and exerts multiple physiological effects including reduced cell surface ADAM10 and altered soluble TREM2 (sTREM2) shedding. Our work represents a systematic approach to prioritize and characterize AD-associated variants and provides a roadmap for advancing genetic association to experimentally validated cell-type-specific phenotypes and mechanisms.

Modular pooled discovery of synthetic knockin sequences to program durable cell therapies

Chronic stimulation can cause T cell dysfunction and limit the efficacy of cellular immunotherapies. Improved methods are required to compare large numbers of synthetic knockin (KI) sequences to reprogram cell functions. Here, we developed modular pooled KI screening (ModPoKI), an adaptable platform for modular construction of DNA KI libraries using barcoded multicistronic adaptors. We built two ModPoKI libraries of 100 transcription factors (TFs) and 129 natural and synthetic surface receptors (SRs). Over 30 ModPoKI screens across human TCR- and CAR-T cells in diverse conditions identified a transcription factor AP4 (TFAP4) construct that enhanced fitness of chronically stimulated CAR-T cells and anti-cancer function in vitro and in vivo. ModPoKI's modularity allowed us to generate an ∼10,000-member library of TF combinations. Non-viral KI of a combined BATF-TFAP4 polycistronic construct enhanced fitness. Overexpressed BATF and TFAP4 co-occupy and regulate key gene targets to reprogram T cell function. ModPoKI facilitates the discovery of complex gene constructs to program cellular functions.

Genome-wide prediction of disease variant effects with a deep protein language model

Predicting the effects of coding variants is a major challenge. While recent deep-learning models have improved variant effect prediction accuracy, they cannot analyze all coding variants due to dependency on close homologs or software limitations. Here we developed a workflow using ESM1b, a 650-million-parameter protein language model, to predict all ~450 million possible missense variant effects in the human genome, and made all predictions available on a web portal. ESM1b outperformed existing methods in classifying ~150,000 ClinVar/HGMD missense variants as pathogenic or benign and predicting measurements across 28 deep mutational scan datasets. We further annotated ~2 million variants as damaging only in specific protein isoforms, demonstrating the importance of considering all isoforms when predicting variant effects. Our approach also generalizes to more complex coding variants such as in-frame indels and stop-gains. Together, these results establish protein language models as an effective, accurate and general approach to predicting variant effects.

Narcolepsy risk loci outline role of T cell autoimmunity and infectious triggers in narcolepsy

Narcolepsy type 1 (NT1) is caused by a loss of hypocretin/orexin transmission. Risk factors include pandemic 2009 H1N1 influenza A infection and immunization with Pandemrix®. Here, we dissect disease mechanisms and interactions with environmental triggers in a multi-ethnic sample of 6,073 cases and 84,856 controls. We fine-mapped GWAS signals within HLA (DQ0602, DQB1*03:01 and DPB1*04:02) and discovered seven novel associations (CD207, NAB1, IKZF4-ERBB3, CTSC, DENND1B, SIRPG, PRF1). Significant signals at TRA and DQB1*06:02 loci were found in 245 vaccination-related cases, who also shared polygenic risk. T cell receptor associations in NT1 modulated TRAJ*24, TRAJ*28 and TRBV*4-2 chain-usage. Partitioned heritability and immune cell enrichment analyses found genetic signals to be driven by dendritic and helper T cells. Lastly comorbidity analysis using data from FinnGen, suggests shared effects between NT1 and other autoimmune diseases. NT1 genetic variants shape autoimmunity and response to environmental triggers, including influenza A infection and immunization with Pandemrix®.

Reply to Barton et al: signatures of natural selection during the Black Death

Barton et al.1 raise several statistical concerns regarding our original analyses2 that highlight the challenge of inferring natural selection using ancient genomic data. We show here that these concerns have limited impact on our original conclusions. Specifically, we recover the same signature of enrichment for high FST values at the immune loci relative to putatively neutral sites after switching the allele frequency estimation method to a maximum likelihood approach, filtering to only consider known human variants, and down-sampling our data to the same mean coverage across sites. Furthermore, using permutations, we show that the rs2549794 variant near ERAP2 continues to emerge as the strongest candidate for selection (p = 1.2×10-5), falling below the Bonferroni-corrected significance threshold recommended by Barton et al. Importantly, the evidence for selection on ERAP2 is further supported by functional data demonstrating the impact of the ERAP2 genotype on the immune response to Y. pestis and by epidemiological data from an independent group showing that the putatively selected allele during the Black Death protects against severe respiratory infection in contemporary populations.

Mitigation of chromosome loss in clinical CRISPR-Cas9-engineered T cells

CRISPR-Cas9 genome editing has enabled advanced T cell therapies, but occasional loss of the targeted chromosome remains a safety concern. To investigate whether Cas9-induced chromosome loss is a universal phenomenon and evaluate its clinical significance, we conducted a systematic analysis in primary human T cells. Arrayed and pooled CRISPR screens revealed that chromosome loss was generalizable across the genome and resulted in partial and entire loss of the chromosome, including in pre-clinical chimeric antigen receptor T cells. T cells with chromosome loss persisted for weeks in culture, implying the potential to interfere with clinical use. A modified cell manufacturing process, employed in our first-in-human clinical trial of Cas9-engineered T cells, 1 dramatically reduced chromosome loss while largely preserving genome editing efficacy. Expression of p53 correlated with protection from chromosome loss observed in this protocol, suggesting both a mechanism and strategy for T cell engineering that mitigates this genotoxicity in the clinic.

Pooled screening of CAR T cells identifies diverse immune signaling domains for next-generation immunotherapies

Chimeric antigen receptors (CARs) repurpose natural signaling components to retarget T cells to refractory cancers but have shown limited efficacy in persistent, recurrent malignancies. Here, we introduce "CAR Pooling," a multiplexed approach to rapidly identify CAR designs with clinical potential. Forty CARs with signaling domains derived from a range of immune cell lineages were evaluated in pooled assays for their ability to stimulate critical T cell effector functions during repetitive stimulation that mimics long-term tumor antigen exposure. Several domains were identified from the tumor necrosis factor (TNF) receptor family that have been primarily associated with B cells. CD40 enhanced proliferation, whereas B cell-activating factor receptor (BAFF-R) and transmembrane activator and CAML interactor (TACI) promoted cytotoxicity. These functions were enhanced relative to clinical benchmarks after prolonged antigen stimulation, and CAR T cell signaling through these domains fell into distinct states of memory, cytotoxicity, and metabolism. BAFF-R CAR T cells were enriched for a highly cytotoxic transcriptional signature previously associated with positive clinical outcomes. We also observed that replacing the 4-1BB intracellular signaling domain with the BAFF-R signaling domain in a clinically validated B cell maturation antigen (BCMA)-specific CAR resulted in enhanced activity in a xenotransplant model of multiple myeloma. Together, these results show that CAR Pooling is a general approach for rapid exploration of CAR architecture and activity to improve the efficacy of CAR T cell therapies.

[Clinical pathologic analysis and review of literature on 11 cases of calcifying epithelial odontogenic tumor]

Objective: To improve the understanding of histological variants of calcifying epithelial odontogenic tumor (CEOT). Methods: In this retrospective study, 11 cases of CEOT diagnosed from January 2008 to March 2022 were enrolled in the Department of Oral Pathology of Nanjing Stomatological Hospital, Medical School of Nanjing University. Among them, 10 were male and 1 was female. The patients were 19 to 58 years old [(43.0±11.9) years] and the course of disease was 2 weeks to 5 years. The clinicopathological characteristics were analyzed and the follow-up of patients ranged from 1 to 8 years, including 8 cases with follow-up data and 3 cases lost to follow-up. Furthermore, the related domestic and international literature was reviewed. Results: Eleven cases of CEOT included 6 cases of classic CEOT, 2 cases of clear cell CEOT, 2 cases of Langerhans cell-rich variant of CEOT and 1 case of non-calcified CEOT. In 6 cases of classic CEOT, the ratio of occurrence in mandible to maxilla was 2∶1, the ratio in central parts to peripheral parts was 5∶1, 2 cases were associated with unerupted teeth and 3 cases showed local aggressiveness. Histopathologically, classic CEOT showed eosinophilic epithelial cells, amyloid and calcification with Ki-67 value<5%. Among 4 cases with follow-up information, 1 case recurred after 1 year and 3 cases did not recur for 3 to 8 years. In 2 cases of clear cell CEOT, they both occurred in the periphery of mandible, pathologically showing a mix of lamellar balloon-like clear cells and typical CEOT, positive for CK5/6 and p63 in the area where the epithelial cells and clear cells were located, scattered positive for periodic acid-Schiff (PAS) in clear cells, which indicated the presence of glycogen. The maximum Ki-67 value was 5% in this type. One case lost to follow-up and the other case did not recur for 1 year follow-up after surgery. In 2 cases of Langerhans cell-rich variant of CEOT, they were cystic solid lesions and both occurred in the anterior maxilla. Langerhans cells were scattered in the epithelium and non-calcified amyloid glomeruli were present. Two cases were followed up for 1 year and 2 years without recurrence after surgery. One case of non-calcified CEOT that occurs within the jan showed invasion of surrounding soft tissues and the highest of Ki-67 value at 8% in all 11 cases without recurrence at 1 year follow-up. Conclusions: The histological pattern of classic CEOT is unique, and it is necessary to prompt the understanding of several histological variants derived from it.

Evolution of immune genes is associated with the Black Death

Infectious diseases are among the strongest selective pressures driving human evolution1,2. This includes the single greatest mortality event in recorded history, the first outbreak of the second pandemic of plague, commonly called the Black Death, which was caused by the bacterium Yersinia pestis3. This pandemic devastated Afro-Eurasia, killing up to 30-50% of the population4. To identify loci that may have been under selection during the Black Death, we characterized genetic variation around immune-related genes from 206 ancient DNA extracts, stemming from two different European populations before, during and after the Black Death. Immune loci are strongly enriched for highly differentiated sites relative to a set of non-immune loci, suggesting positive selection. We identify 245 variants that are highly differentiated within the London dataset, four of which were replicated in an independent cohort from Denmark, and represent the strongest candidates for positive selection. The selected allele for one of these variants, rs2549794, is associated with the production of a full-length (versus truncated) ERAP2 transcript, variation in cytokine response to Y. pestis and increased ability to control intracellular Y. pestis in macrophages. Finally, we show that protective variants overlap with alleles that are today associated with increased susceptibility to autoimmune diseases, providing empirical evidence for the role played by past pandemics in shaping present-day susceptibility to disease.

Multi-context genetic modeling of transcriptional regulation resolves novel disease loci

A majority of the variants identified in genome-wide association studies fall in non-coding regions of the genome, indicating their mechanism of impact is mediated via gene expression. Leveraging this hypothesis, transcriptome-wide association studies (TWAS) have assisted in both the interpretation and discovery of additional genes associated with complex traits. However, existing methods for conducting TWAS do not take full advantage of the intra-individual correlation inherently present in multi-context expression studies and do not properly adjust for multiple testing across contexts. We introduce CONTENT-a computationally efficient method with proper cross-context false discovery correction that leverages correlation structure across contexts to improve power and generate context-specific and context-shared components of expression. We apply CONTENT to bulk multi-tissue and single-cell RNA-seq data sets and show that CONTENT leads to a 42% (bulk) and 110% (single cell) increase in the number of genetically predicted genes relative to previous approaches. We find the context-specific component of expression comprises 30% of heritability in tissue-level bulk data and 75% in single-cell data, consistent with cell-type heterogeneity in bulk tissue. In the context of TWAS, CONTENT increases the number of locus-phenotype associations discovered by over 51% relative to previous methods across 22 complex traits.

Circulating monocytes associated with anti-PD-1 resistance in human biliary cancer induce T cell paralysis

Suppressive myeloid cells can contribute to immunotherapy resistance, but their role in response to checkpoint inhibition (CPI) in anti-PD-1 refractory cancers, such as biliary tract cancer (BTC), remains elusive. We use multiplexed single-cell transcriptomic and epitope sequencing to profile greater than 200,000 peripheral blood mononuclear cells from advanced BTC patients (n = 9) and matched healthy donors (n = 8). Following anti-PD-1 treatment, CD14⁺ monocytes expressing high levels of immunosuppressive cytokines and chemotactic molecules (CD14_CTX) increase in the circulation of patients with BTC tumors that are CPI resistant. CD14_CTX can directly suppress CD4⁺ T cells and induce SOCS3 expression in CD4⁺ T cells, rendering them functionally unresponsive. The CD14_CTX gene signature associates with worse survival in patients with BTC as well as in other anti-PD-1 refractory cancers. These results demonstrate that monocytes arising after anti-PD-1 treatment can induce T cell paralysis as a distinct mode of tumor-mediated immunosuppression leading to CPI resistance.

[Research advances on the treatment of hydrofluoric acid burns]

Hydrofluoric acid is a highly dangerous and toxic inorganic acid, which is widely used in industrial fields and daily life. The risk of hydrofluoric acid burns is related to hydrofluoric acid mass fraction, duration of exposure to hydrofluoric acid, burn area, burn depth, and burn site, etc. Hydrofluoric acid has strong toxicity and tissue penetration ability. A small area of hydrofluoric acid burns can cause death in a short time. Therefore, improving the understanding of the mechanism of hydrofluoric acid burns and learning how to treat hydrofluoric acid burns in different sites can further improve the cure rate of hydrofluoric acid burns.

Multi-Modal Single-Cell Sequencing Identifies Cellular Immunophenotypes Associated With Juvenile Dermatomyositis Disease Activity

Juvenile dermatomyositis (JDM) is a rare autoimmune condition with insufficient biomarkers and treatments, in part, due to incomplete knowledge of the cell types mediating disease. We investigated immunophenotypes and cell-specific genes associated with disease activity using multiplexed RNA and protein single-cell sequencing applied to PBMCs from 4 treatment-naïve JDM (TN-JDM) subjects at baseline, 2, 4, and 6 months post-treatment and 4 subjects with inactive disease on treatment. Analysis of 55,564 cells revealed separate clustering of TN-JDM cells within monocyte, NK, CD8+ effector T and naïve B populations. The proportion of CD16+ monocytes was reduced in TN-JDM, and naïve B cells and CD4+ Tregs were expanded. Cell-type differential gene expression analysis and hierarchical clustering identified a pan-cell-type IFN gene signature over-expressed in TN-JDM in all cell types and correlated with disease activity most strongly in cytotoxic cell types. TN-JDM CD16+ monocytes expressed the highest IFN gene score and were highly skewed toward an inflammatory and antigen-presenting phenotype at both the transcriptomic and proteomic levels. A transitional B cell population with a distinct transcriptomic signature was expanded in TN-JDM and characterized by higher CD24 and CD5 proteins and less CD39, an immunoregulatory protein. This data provides new insights into JDM immune dysregulation at cellular resolution and serves as a novel resource for myositis investigators.

Single-cell RNA-seq reveals cell type-specific molecular and genetic associations to lupus

Systemic lupus erythematosus (SLE) is a heterogeneous autoimmune disease. Knowledge of circulating immune cell types and states associated with SLE remains incomplete. We profiled more than 1.2 million peripheral blood mononuclear cells (162 cases, 99 controls) with multiplexed single-cell RNA sequencing (mux-seq). Cases exhibited elevated expression of type 1 interferon-stimulated genes (ISGs) in monocytes, reduction of naïve CD4+ T cells that correlated with monocyte ISG expression, and expansion of repertoire-restricted cytotoxic GZMH+ CD8+ T cells. Cell type-specific expression features predicted case-control status and stratified patients into two molecular subtypes. We integrated dense genotyping data to map cell type-specific cis-expression quantitative trait loci and to link SLE-associated variants to cell type-specific expression. These results demonstrate mux-seq as a systematic approach to characterize cellular composition, identify transcriptional signatures, and annotate genetic variants associated with SLE.

Single-cell eQTL mapping identifies cell type-specific genetic control of autoimmune disease

The human immune system displays substantial variation between individuals, leading to differences in susceptibility to autoimmune disease. We present single-cell RNA sequencing (scRNA-seq) data from 1,267,758 peripheral blood mononuclear cells from 982 healthy human subjects. For 14 cell types, we identified 26,597 independent cis-expression quantitative trait loci (eQTLs) and 990 trans-eQTLs, with most showing cell type-specific effects on gene expression. We subsequently show how eQTLs have dynamic allelic effects in B cells that are transitioning from naïve to memory states and demonstrate how commonly segregating alleles lead to interindividual variation in immune function. Finally, using a Mendelian randomization approach, we identify the causal route by which 305 risk loci contribute to autoimmune disease at the cellular level. This work brings together genetic epidemiology with scRNA-seq to uncover drivers of interindividual variation in the immune system.

Obesity alters pathology and treatment response in inflammatory disease

Decades of work have elucidated cytokine signalling and transcriptional pathways that control T cell differentiation and have led the way to targeted biologic therapies that are effective in a range of autoimmune, allergic and inflammatory diseases. Recent evidence indicates that obesity and metabolic disease can also influence the immune system1-7, although the mechanisms and effects on immunotherapy outcomes remain largely unknown. Here, using two models of atopic dermatitis, we show that lean and obese mice mount markedly different immune responses. Obesity converted the classical type 2 T helper (TH2)-predominant disease associated with atopic dermatitis to a more severe disease with prominent TH17 inflammation. We also observed divergent responses to biologic therapies targeting TH2 cytokines, which robustly protected lean mice but exacerbated disease in obese mice. Single-cell RNA sequencing coupled with genome-wide binding analyses revealed decreased activity of nuclear receptor peroxisome proliferator-activated receptor-γ (PPARγ) in TH2 cells from obese mice relative to lean mice. Conditional ablation of PPARγ in T cells revealed that PPARγ is required to focus the in vivo TH response towards a TH2-predominant state and prevent aberrant non-TH2 inflammation. Treatment of obese mice with a small-molecule PPARγ agonist limited development of TH17 pathology and unlocked therapeutic responsiveness to targeted anti-TH2 biologic therapies. These studies reveal the effects of obesity on immunological disease and suggest a precision medicine approach to target the immune dysregulation caused by obesity.

Combined Single Cell Transcriptome and Surface Epitope Profiling Identifies Potential Biomarkers of Psoriatic Arthritis and Facilitates Diagnosis via Machine Learning

Early diagnosis of psoriatic arthritis (PSA) is important for successful therapeutic intervention but currently remains challenging due, in part, to the scarcity of non-invasive biomarkers. In this study, we performed single cell profiling of transcriptome and cell surface protein expression to compare the peripheral blood immunocyte populations of individuals with PSA, individuals with cutaneous psoriasis (PSO) alone, and healthy individuals. We identified genes and proteins differentially expressed between PSA, PSO, and healthy subjects across 30 immune cell types and observed that some cell types, as well as specific phenotypic subsets of cells, differed in abundance between these cohorts. Cell type-specific gene and protein expression differences between PSA, PSO, and healthy groups, along with 200 previously published genetic risk factors for PSA, were further used to perform machine learning classification, with the best models achieving AUROC ≥ 0.87 when either classifying subjects among the three groups or specifically distinguishing PSA from PSO. Our findings thus expand the repertoire of gene, protein, and cellular biomarkers relevant to PSA and demonstrate the utility of machine learning-based diagnostics for this disease.

The development and evolution of inhibitory neurons in primate cerebrum

Neuroanatomists have long speculated that expanded primate brains contain an increased morphological diversity of inhibitory neurons (INs)¹, and recent studies have identified primate-specific neuronal populations at the molecular level². However, we know little about the developmental mechanisms that specify evolutionarily novel cell types in the brain. Here, we reconstruct gene expression trajectories specifying INs generated throughout the neurogenic period in macaques and mice by analysing the transcriptomes of 250,181 cells. We find that the initial classes of INs generated prenatally are largely conserved among mammals. Nonetheless, we identify two contrasting developmental mechanisms for specifying evolutionarily novel cell types during prenatal development. First, we show that recently identified primate-specific TAC3 striatal INs are specified by a unique transcriptional programme in progenitors followed by induction of a distinct suite of neuropeptides and neurotransmitter receptors in new-born neurons. Second, we find that multiple classes of transcriptionally conserved olfactory bulb (OB)-bound precursors are redirected to expanded primate white matter and striatum. These classes include a novel peristriatal class of striatum laureatum neurons that resemble dopaminergic periglomerular cells of the OB. We propose an evolutionary model in which conserved initial classes of neurons supplying the smaller primate OB are reused in the enlarged striatum and cortex. Together, our results provide a unified developmental taxonomy of initial classes of mammalian INs and reveal multiple developmental mechanisms for neural cell type evolution.

Evolutionary modelling shows that an initial set of inhibitory neurons serving olfactory bulbs may have been repurposed to diversify the taxonomy of interneurons found in the expanded striata and cortices in primates.

CRISPR activation and interference screens decode stimulation responses in primary human T cells

Regulation of cytokine production in stimulated T cells can be disrupted in autoimmunity, immunodeficiencies, and cancer. Systematic discovery of stimulation-dependent cytokine regulators requires both loss-of-function and gain-of-function studies, which have been challenging in primary human cells. We now report genome-wide CRISPR activation (CRISPRa) and interference (CRISPRi) screens in primary human T cells to identify gene networks controlling interleukin-2 (IL-2) and interferon-γ (IFN-γ) production. Arrayed CRISPRa confirmed key hits and enabled multiplexed secretome characterization, revealing reshaped cytokine responses. Coupling CRISPRa screening with single-cell RNA sequencing enabled deep molecular characterization of screen hits, revealing how perturbations tuned T cell activation and promoted cell states characterized by distinct cytokine expression profiles. These screens reveal genes that reprogram critical immune cell functions, which could inform the design of immunotherapies.

CloudPred: Predicting Patient Phenotypes From Single-cell RNA-seq

Single-cell RNA sequencing (scRNA-seq) has the potential to provide powerful, high-resolution signatures to inform disease prognosis and precision medicine. This paper takes an important first step towards this goal by developing an interpretable machine learning algorithm, CloudPred, to predict individuals' disease phenotypes from their scRNA-seq data. Predicting phenotype from scRNA-seq is challenging for standard machine learning methods-the number of cells measured can vary by orders of magnitude across individuals and the cell populations are also highly heterogeneous. Typical analysis creates pseudo-bulk samples which are biased toward prior annotations and also lose the single cell resolution. CloudPred addresses these challenges via a novel end-to-end differentiable learning algorithm which is coupled with a biologically informed mixture of cell types model. CloudPred automatically infers the cell subpopulation that are salient for the phenotype without prior annotations. We developed a systematic simulation platform to evaluate the performance of CloudPred and several alternative methods we propose, and find that CloudPred outperforms the alternative methods across several settings. We further validated CloudPred on a real scRNA-seq dataset of 142 lupus patients and controls. CloudPred achieves AUROC of 0.98 while identifying a specific subpopulation of CD4 T cells whose presence is highly indicative of lupus. CloudPred is a powerful new framework to predict clinical phenotypes from scRNA-seq data and to identify relevant cells.

Monoclonal antibody-mediated neutralization of SARS-CoV-2 in an IRF9-deficient child

We describe an unvaccinated child at risk for life-threatening COVID-19 due to an inherited deficiency of IRF9, which governs ISGF-3-dependent responses to type I and III interferons (IFN). She was admitted, with a high nasal SARS-CoV-2 load on day 1 of upper respiratory tract infection. She was viremic on day 2 and received casirivimab and imdevimab. Her clinical manifestations and viremia disappeared on days 3 and 4, respectively. Circulating SARS-CoV-2 virus induced the expression of IFN-stimulated genes in leukocytes on day 1, whereas the secretion of blood type I IFNs, which peaked on day 4, did not. Antibody-mediated SARS-CoV-2 neutralization is, therefore, sufficient to overcome a deficiency of antiviral IFNs.

676 Altered circulating myeloid states associated with anti-PD-1 resistance induce T cell paralysis in human biliary cancer

Background

Advanced biliary cancers (ABC) have a poor prognosis and low rates of response to immune checkpoint inhibition (CPI), with overall response rates ranging from 3–13%.1–3 Although suppressive myeloid cells have been proposed as a mechanism of resistance to immunotherapy in general, their relationship to response to CPI is unknown.

Methods

We used multiplexed simultaneous single cell RNA sequencing and cell surface proteomics (CITE-seq) to profile circulating immune cells in ABC patients receiving anti-PD-1 at longitudinal timepoints pre-immunotherapy and on treatment, as well as from healthy donors. We also performed single cell RNA sequencing on resected biliary tumors.

Results

We identified a novel population of circulating cancer-enriched myeloid cells (CEM) characterized by chemokines and extracellular matrix digestion-related gene expression, which were present pre-treatment. Anti-PD-1 treatment drove the CEMs into two diverging states that were associated with response or resistance to treatment. CEM induced in non-responders constituted over 40% of the circulating myeloid cells and expressed immunosuppressive programs, including the upregulation of suppressive cytokines and chemokines. The frequency of these myeloid cells were correlated with the abundance of SOCS3-expressing CD4+ T cells. These SOCS3+CD4+ T cells also colocalized with tumor-infiltrating myeloid cells that share CEM gene expression signatures in the biliary cancer microenvironment. Moreover, CEM can directly induce SOCS3-expressing T cells, which despite their naïve phenotype are functionally unresponsive. Finally, expression signatures of CEM and of SOCS3+CD4+ T cells are associated with worse survival in a larger cohort of ABC patients.

Conclusions

These results demonstrate the capacity of CEM to induce T cell paralysis as an alternate mode of tumor-mediated immunosuppression. A deeper understanding of immune cell biology in ABC provides insights for developing novel therapeutics that can overcome immunotherapy resistance in biliary cancer as well as other tumor types.

Trial Registration

NCT02703714

References

Ueno M, et al. Nivolumab alone or in combination with cisplatin plus gemcitabine in Japanese patients with unresectable or recurrent biliary tract cancer: a non-randomised, multicentre, open-label, phase 1 study. Lancet Gastroenterol Hepatol 2019;4:611–621.

Piha-Paul SA, et al. Efficacy and safety of pembrolizumab for the treatment of advanced biliary cancer: results from the KEYNOTE-158 and KEYNOTE-028 studies. Int J Cancer 2020.

Kim RD, et al. A Phase 2 Multi-institutional study of nivolumab for patients with advanced refractory biliary tract cancer. JAMA Oncol 2020;6:888–894.

Ethics Approval

Informed consent was obtained from all patients for participation in the listed trial and for use of blood and tumor samples in research studies.

[The role of first-aid network construction in the early treatment of patients with critically severe hydrofluoric acid burns]

Objective: To explore the role of first-aid network construction in the early treatment of patients with critically severe hydrofluoric acid burns. Methods: Twenty-seven fluorine chemical enterprises distributed in Zhejiang province, Jiangxi Province, Fujian Province, and Inner Mongolia Autonomous Region and 22 hospitals with burn/plastic department or professional burn treatment group in Zhejiang province, including Zhejiang Quhua Hospital, and 5 hospitals outside Zhejiang province were involved in the first-aid network construction as member units. As the main unit, Zhejiang Quhua Hospital was responsible for the daily maintenance and technical guidance of the first-aid network. Zhejiang Quhua Hospital was assigned as the designated emergency hospital for 20 fluorine chemical enterprises, a near emergency hospital to the other 7 fluorine chemical enterprises was assigned as the designated hospital for them. Medical records of 56 patients (all males) with critically severe hydrofluoric acid burns who admitted to 5 first-aid network hospitals from January 2006 to June 2021, meeting the inclusion criteria, were involved in the retrospective cohort study. Based on whether the enterprise belonging to the first-aid network construction or not, the patients were divided into first-aid network group (27 cases, aged (41±9) years) and non first-aid network group (29 cases, aged (42±10) years). After the patients in the first-aid network group were injured, the enterprises and hospitals linked up immediately. The hospital where the patient was treated mobilize the treatment force, equipment, materials, and drugs in advance by the first-aid network, thereby realizing seamless joint between pre-hospital first-aid and in-hospital treatment. The hospital started the first-aid process and temporarily mobilized the rescue forces, equipment, materials, and drug after patients in non first-aid network group arrived at the department of emergency of the hospital. The time from injury to medical service, the first detection time of serum calcium, the time staying in department of emergency, the duration of hypocalcemia and hypomagnesemia, and the treatment outcome of patients in the two groups were recorded. Data were statistically analyzed with chi-square test, Fisher's exact probability test, independent-sample t test, and Wilcoxon rank-sum test. Results: The time from injury to medical service, the first detection time of serum calcium, and the time staying in department of emergency of patients in first-aid network group were 40.0 (30.0, 55.0), 23.0 (17.5, 37.5), and 42.0 (37.0, 53.0) min, which were significantly shorter than 180.0 (120.0, 240.0), 31.0 (22.5, 47.5), 61.0 (52.0, 65.5) min in non first-aid network group (Z=-6.17, -1.98, -4.15, P<0.05 or P<0.01). The duration of hypocalcemia and hypo- magnesemia of patients in first-aid network group were 1.2 (1.1, 1.6) and 1.9 (1.7, 2.1) h, which were significantly shorter than 4.6 (3.1, 6.2) and 3.2 (2.5, 4.6) h in non first-aid network group (Z=-5.80, -4.81, P<0.01). Three patients (11.1%) in first-aid network group died, among whom 2 patients died at 40 min after injury and 1 patient died 9.0 h after injury. Four patients (13.8%) died in non first-aid network group at 3.0, 3.0, 4.5, and 7.0 h after injury, respectively. The mortality rates of patients in the two groups were similar (P>0.05). Conclusions: Critically severe hydrofluoric acid burn is an extremely urgent situation encountered in clinical practice. The construction of a first-aid network creates condition for on-site treatment of patients and improves the first-aid efficiency, thereby gaining time to save lives.

Type I interferon autoantibodies are associated with systemic immune alterations in patients with COVID-19

A subset of patients diagnosed with coronavirus disease 2019 (COVID-19) present with autoantibodies specific to type I interferons (IFNs). However, the systemic impacts of type I IFN–specific autoantibodies are not fully understood. Here, van der Wijst et al. longitudinally evaluated the relationship between type I IFN–specific autoantibody abundance and changes to the immune system of individuals with COVID-19. Using single-cell transcriptomics, the authors found that the presence of type I IFN autoantibodies correlated with reduced type I IFN–stimulated gene (ISG) expression in patients with critical COVID-19. Reduced ISG expression, in turn, correlated with increased expression of the inhibitory receptor, leukocyte-associated immunoglobulin-like receptor 1 (LAIR1), on monocytes. Together, these findings suggest that early evidence of type I IFN autoantibodies and increased LAIR1 expression may help distinguish severe cases of COVID-19.

Neutralizing autoantibodies against type I interferons (IFNs) have been found in some patients with critical coronavirus disease 2019 (COVID-19), the disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, the prevalence of these antibodies, their longitudinal dynamics across the disease severity scale, and their functional effects on circulating leukocytes remain unknown. Here, in 284 patients with COVID-19, we found type I IFN–specific autoantibodies in peripheral blood samples from 19% of patients with critical disease and 6% of patients with severe disease. We found no type I IFN autoantibodies in individuals with moderate disease. Longitudinal profiling of over 600,000 peripheral blood mononuclear cells using multiplexed single-cell epitope and transcriptome sequencing from 54 patients with COVID-19 and 26 non–COVID-19 controls revealed a lack of type I IFN–stimulated gene (ISG-I) responses in myeloid cells from patients with critical disease. This was especially evident in dendritic cell populations isolated from patients with critical disease producing type I IFN–specific autoantibodies. Moreover, we found elevated expression of the inhibitory receptor leukocyte-associated immunoglobulin-like receptor 1 (LAIR1) on the surface of monocytes isolated from patients with critical disease early in the disease course. LAIR1 expression is inversely correlated with ISG-I expression response in patients with COVID-19 but is not expressed in healthy controls. The deficient ISG-I response observed in patients with critical COVID-19 with and without type I IFN–specific autoantibodies supports a unifying model for disease pathogenesis involving ISG-I suppression through convergent mechanisms.

CCR2 deficiency alters activation of microglia subsets in traumatic brain injury

In traumatic brain injury (TBI), a diversity of brain resident and peripherally derived myeloid cells have the potential to worsen damage and/or to assist in healing. We define the heterogeneity of microglia and macrophage phenotypes during TBI in wild-type (WT) mice and Ccr2^−/− mice, which lack macrophage influx following TBI and are resistant to brain damage. We use unbiased single-cell RNA sequencing methods to uncover 25 microglia, monocyte/macrophage, and dendritic cell subsets in acute TBI and normal brains. We find alterations in transcriptional profiles of microglia subsets in Ccr2^−/− TBI mice compared to WT TBI mice indicating that infiltrating monocytes/macrophages influence microglia activation to promote a type I IFN response. Preclinical pharmacological blockade of hCCR2 after injury reduces expression of IFN-responsive gene, Irf7, and improves outcomes. These data extend our understanding of myeloid cell diversity and crosstalk in brain trauma and identify therapeutic targets in myeloid subsets.

By single-cell RNA sequencing of traumatically injured and normal brains from wild-type and Ccr2^−/− mice, Somebang et al. define microglia, macrophage, and dendritic cell phenotypes in TBI. Targeting mouse and/or human CCR2 reduces specific TBI brain CNS myeloid compartments, dampens type I interferon responses, and improves cognition after TBI.

SCITO-seq: single-cell combinatorial indexed cytometry sequencing

The development of DNA-barcoded antibodies to tag cell surface molecules has enabled the use of droplet-based single-cell sequencing (dsc-seq) to profile protein abundances from thousands of cells simultaneously. As compared to flow and mass cytometry, the high per cell cost of current dsc-seq-based workflows precludes their use in clinical applications and large-scale pooled screens. Here, we introduce SCITO-seq, a workflow that uses splint oligonucleotides (oligos) to enable combinatorially indexed dsc-seq of DNA-barcoded antibodies from over 10⁵ cells per reaction using commercial microfluidics. By encoding sample barcodes into splint oligos, we demonstrate that multiplexed SCITO-seq produces reproducible estimates of cellular composition and surface protein expression comparable to those from mass cytometry. We further demonstrate two modified splint oligo designs that extend SCITO-seq to achieve compatibility with commercial DNA-barcoded antibodies and simultaneous expression profiling of the transcriptome and surface proteins from the same cell. These results demonstrate SCITO-seq as a flexible and ultra-high-throughput platform for sequencing-based single-cell protein and multimodal profiling.

Single-cell transcriptome analysis defines heterogeneity of the murine pancreatic ductal tree

To study disease development, an inventory of an organ's cell types and understanding of physiologic function is paramount. Here, we performed single-cell RNA-sequencing to examine heterogeneity of murine pancreatic duct cells, pancreatobiliary cells, and intrapancreatic bile duct cells. We describe an epithelial-mesenchymal transitory axis in our three pancreatic duct subpopulations and identify osteopontin as a regulator of this fate decision as well as human duct cell dedifferentiation. Our results further identify functional heterogeneity within pancreatic duct subpopulations by elucidating a role for geminin in accumulation of DNA damage in the setting of chronic pancreatitis. Our findings implicate diverse functional roles for subpopulations of pancreatic duct cells in maintenance of duct cell identity and disease progression and establish a comprehensive road map of murine pancreatic duct cell, pancreatobiliary cell, and intrapancreatic bile duct cell homeostasis.

Transcriptomic analysis of immune cells in a multi-ethnic cohort of systemic lupus erythematosus patients identifies ethnicity- and disease-specific expression signatures

Systemic lupus erythematosus (SLE) is an autoimmune disease in which outcomes vary among different racial groups. We leverage cell-sorted RNA-seq data (CD14+ monocytes, B cells, CD4+ T cells, and NK cells) from 120 SLE patients (63 Asian and 57 White individuals) and apply a four-tier approach including unsupervised clustering, differential expression analyses, gene co-expression analyses, and machine learning to identify SLE subgroups within this multiethnic cohort. K-means clustering on each cell-type resulted in three clusters for CD4 and CD14, and two for B and NK cells. To understand the identified clusters, correlation analysis revealed significant positive associations between the clusters and clinical parameters including disease activity as well as ethnicity. We then explored differentially expressed genes between Asian and White groups for each cell-type. The shared differentially expressed genes across cells were involved in SLE or other autoimmune-related pathways. Co-expression analysis identified similarly regulated genes across samples and grouped these genes into modules. Finally, random forest classification of disease activity in the White and Asian cohorts showed the best classification in CD4+ T cells in White individuals. The results from these analyses will help stratify patients based on their gene expression signatures to enable SLE precision medicine.

XYZeq: Spatially resolved single-cell RNA sequencing reveals expression heterogeneity in the tumor microenvironment

Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue.

Longitudinal single-cell epitope and RNA-sequencing reveals the immunological impact of type 1 interferon autoantibodies in critical COVID-19: Anti-IFN antibodies in critical COVID-19 correlate with poor ISG response and upregulation of LAIR1 surface protein in PBMCs

Type I interferon (IFN-I) neutralizing autoantibodies have been found in some critical COVID-19 patients; however, their prevalence and longitudinal dynamics across the disease severity scale, and functional effects on circulating leukocytes remain unknown. Here, in 284 COVID-19 patients, we found IFN-I autoantibodies in 19% of critical, 6% of severe and none of the moderate cases. Longitudinal profiling of over 600,000 peripheral blood mononuclear cells using multiplexed single-cell epitope and transcriptome sequencing from 54 COVID-19 patients, 15 non-COVID-19 patients and 11 non-hospitalized healthy controls, revealed a lack of IFN-I stimulated gene (ISG-I) response in myeloid cells from critical cases, including those producing anti-IFN-I autoantibodies. Moreover, surface protein analysis showed an inverse correlation of the inhibitory receptor LAIR-1 with ISG-I expression response early in the disease course. This aberrant ISG-I response in critical patients with and without IFN-I autoantibodies, supports a unifying model for disease pathogenesis involving ISG-I suppression via convergent mechanisms.

Single-Cell Mapping of Progressive Fetal-to-Adult Transition in Human Naive T Cells

Whereas the human fetal immune system is poised to generate immune tolerance and suppress inflammation in utero, an adult-like immune system emerges to orchestrate anti-pathogen immune responses in post-natal life. It has been posited that cells of the adult immune system arise as a discrete ontological "layer" of hematopoietic stem-progenitor cells (HSPCs) and their progeny; evidence supporting this model in humans has, however, been inconclusive. Here, we combine bulk and single-cell transcriptional profiling of lymphoid cells, myeloid cells, and HSPCs from fetal, perinatal, and adult developmental stages to demonstrate that the fetal-to-adult transition occurs progressively along a continuum of maturity-with a substantial degree of inter-individual variation at the time of birth-rather than via a transition between discrete waves. These findings have important implications for the design of strategies for prophylaxis against infection in the newborn and for the use of umbilical cord blood (UCB) in the setting of transplantation.

Optimized design of single-cell RNA sequencing experiments for cell-type-specific eQTL analysis

Single-cell RNA-sequencing (scRNA-Seq) is a compelling approach to directly and simultaneously measure cellular composition and state, which can otherwise only be estimated by applying deconvolution methods to bulk RNA-Seq estimates. However, it has not yet become a widely used tool in population-scale analyses, due to its prohibitively high cost. Here we show that given the same budget, the statistical power of cell-type-specific expression quantitative trait loci (eQTL) mapping can be increased through low-coverage per-cell sequencing of more samples rather than high-coverage sequencing of fewer samples. We use simulations starting from one of the largest available real single-cell RNA-Seq data from 120 individuals to also show that multiple experimental designs with different numbers of samples, cells per sample and reads per cell could have similar statistical power, and choosing an appropriate design can yield large cost savings especially when multiplexed workflows are considered. Finally, we provide a practical approach on selecting cost-effective designs for maximizing cell-type-specific eQTL power which is available in the form of a web tool.

Author Correction: Multiplexed droplet single-cell RNA-sequencing using natural genetic variation

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Evaluation of SARS-CoV-2 serology assays reveals a range of test performance

Appropriate use and interpretation of serological tests for assessments of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exposure, infection and potential immunity require accurate data on assay performance. We conducted a head-to-head evaluation of ten point-of-care-style lateral flow assays (LFAs) and two laboratory-based enzyme-linked immunosorbent assays to detect anti-SARS-CoV-2 IgM and IgG antibodies in 5-d time intervals from symptom onset and studied the specificity of each assay in pre-coronavirus disease 2019 specimens. The percent of seropositive individuals increased with time, peaking in the latest time interval tested (>20 d after symptom onset). Test specificity ranged from 84.3% to 100.0% and was predominantly affected by variability in IgM results. LFA specificity could be increased by considering weak bands as negative, but this decreased detection of antibodies (sensitivity) in a subset of SARS-CoV-2 real-time PCR-positive cases. Our results underline the importance of seropositivity threshold determination and reader training for reliable LFA deployment. Although there was no standout serological assay, four tests achieved more than 80% positivity at later time points tested and more than 95% specificity.