Immunophenotyping of COVID-19 and influenza highlights the role of type I interferons in development of severe COVID-19

Pathogenesis and virulence of coronavirus disease: Comparative pathology of animal models for COVID-19

Animal models that can replicate clinical and pathologic features of severe human coronavirus infections have been instrumental in the development of novel vaccines and therapeutics. The goal of this review is to summarize our current understanding of the pathogenesis of coronavirus disease 2019 (COVID-19) and the pathologic features that can be observed in several currently available animal models. Knowledge gained from studying these animal models of SARS-CoV-2 infection can help inform appropriate model selection for disease modelling as well as for vaccine and therapeutic developments.

The role of plasmacytoid dendritic cells (pDCs) in immunity during viral infections and beyond

Type I and III interferons (IFNs) are essential for antiviral immunity and act through two different but complimentary pathways. First, IFNs activate intracellular antimicrobial programs by triggering the upregulation of a broad repertoire of viral restriction factors. Second, IFNs activate innate and adaptive immunity. Dysregulation of IFN production can lead to severe immune system dysfunction. It is thus crucial to identify and characterize the cellular sources of IFNs, their effects, and their regulation to promote their beneficial effects and limit their detrimental effects, which can depend on the nature of the infected or diseased tissues, as we will discuss. Plasmacytoid dendritic cells (pDCs) can produce large amounts of all IFN subtypes during viral infection. pDCs are resistant to infection by many different viruses, thus inhibiting the immune evasion mechanisms of viruses that target IFN production or their downstream responses. Therefore, pDCs are considered essential for the control of viral infections and the establishment of protective immunity. A thorough bibliographical survey showed that, in most viral infections, despite being major IFN producers, pDCs are actually dispensable for host resistance, which is achieved by multiple IFN sources depending on the tissue. Moreover, primary innate and adaptive antiviral immune responses are only transiently affected in the absence of pDCs. More surprisingly, pDCs and their IFNs can be detrimental in some viral infections or autoimmune diseases. This makes the conservation of pDCs during vertebrate evolution an enigma and thus raises outstanding questions about their role not only in viral infections but also in other diseases and under physiological conditions.

Early inflammatory profiles predict maximal disease severity in COVID-19: An unsupervised cluster analysis

Background

The inflammatory changes that underlie the heterogeneous presentations of COVID-19 remain incompletely understood. In this study we aimed to identify inflammatory profiles that precede the development of severe COVID-19, that could serve as targets for optimised delivery of immunomodulatory therapies and provide insights for the development of new therapies.

Methods

We included individuals sampled <10 days from COVID-19 symptom onset, recruited from both inpatient and outpatient settings. We measured 61 biomarkers in plasma, including markers of innate immune and T cell activation, coagulation, tissue repair and lung injury. We used principal component analysis and hierarchical clustering to derive biomarker clusters, and ordinal logistic regression to explore associations between cluster membership and maximal disease severity, adjusting for known risk factors for severe COVID-19.

Results

In 312 individuals, median (IQR) 7 (4-9) days from symptom onset, we found four clusters. Cluster 1 was characterised by low overall inflammation, cluster 2 was characterised by higher levels of growth factors and markers of endothelial activation (EGF, VEGF, PDGF, TGFα, PAI-1 and p-selectin). Cluster 3 and 4 both had higher overall inflammation. Cluster 4 had the highest levels of most markers including markers of innate immune activation (IL6, procalcitonin, CRP, TNFα), and coagulation (D-dimer, TPO), in contrast cluster 3 had the highest levels of alveolar epithelial injury markers (RAGE, ST2), but relative downregulation of growth factors and endothelial activation markers, suggesting a dysfunctional inflammatory pattern. In unadjusted and adjusted analysis, compared to cluster 1, cluster 3 had the highest odds of progressing to more severe disease (unadjusted OR (95%CI) 9.02 (4.53-17.96), adjusted OR (95%CI) 6.02 (2.70-13.39)).

Conclusion

Early inflammatory profiles predicted subsequent maximal disease severity independent of risk factors for severe COVID-19. A cluster with downregulation of growth factors and endothelial activation markers, and early evidence of alveolar epithelial injury, had the highest risk of severe COVID-19.

Cellular spermine targets JAK signaling to restrain cytokine-mediated autoimmunity

Prolonged activation of the type I interferon (IFN-I) pathway leads to autoimmune diseases such as systemic lupus erythematosus (SLE). Metabolic regulation of cytokine signaling is critical for cellular homeostasis. Through metabolomics analyses of IFN-β-activated macrophages and an IFN-stimulated-response-element reporter screening, we identified spermine as a metabolite brake for Janus kinase (JAK) signaling. Spermine directly bound to the FERM and SH2 domains of JAK1 to impair JAK1-cytokine receptor interaction, thus broadly suppressing JAK1 phosphorylation triggered by cytokines IFN-I, IFN-II, interleukin (IL)-2, and IL-6. Peripheral blood mononuclear cells (PBMCs) from individuals with SLE showing decreased spermine concentrations exhibited enhanced IFN-I and lupus gene signatures. Spermine treatment attenuated autoimmune pathogenesis in SLE and psoriasis mice and reduced IFN-I signaling in monocytes from individuals with SLE. We synthesized a spermine derivative (spermine derivative 1 [SD1]) and showed that it had a potent immunosuppressive function. Our findings reveal spermine as a metabolic checkpoint for cellular homeostasis and a potential immunosuppressive molecule for controlling autoimmune disease.

Hub genes identification and validation of ferroptosis in SARS-CoV-2 induced ARDS: perspective from transcriptome analysis

Introduction

Acute Respiratory Distress Syndrome (ARDS) poses a significant health challenge due to its high incidence and mortality rates. The emergence of SARS-CoV-2 has added complexity, with evidence suggesting a correlation between COVID-19 induced ARDS and post-COVID symptoms. Understanding the underlying mechanisms of ARDS in COVID-19 patients is crucial for effective clinical treatment.

Method

To investigate the potential role of ferroptosis in SARS-CoV-2 induced ARDS, we conducted a comprehensive analysis using bioinformatics methods. Datasets from the Gene Expression Omnibus (GEO) were utilized, focusing on COVID-19 patients with varying ARDS severity. We employed weighted gene co-expression network analysis (WGCNA), differential gene expression analysis, and single-cell sequencing to identify key genes associated with ferroptosis in ARDS. Hub genes were validated using additional GEO datasets and cell experiment.

Result

The analysis discerned 916 differentially expressed genes in moderate/severe ARDS patients compared to non-critical individuals. Weighted Gene Co-expression Network Analysis (WGCNA) unveiled two modules that exhibited a positive correlation with ARDS, subsequently leading to the identification of 15 hub genes associated with ferroptosis. Among the noteworthy hub genes were MTF1, SAT1, and TXN. Protein-protein interaction analysis, and pathway analysis further elucidated their roles. Immune infiltrating analysis highlighted associations between hub genes and immune cells. Validation in additional datasets confirmed the upregulation of MTF1, SAT1, and TXN in SARS-CoV-2-induced ARDS. This was also demonstrated by qRT-PCR results in the BEAS-2B cells vitro model, suggesting their potential as diagnostic indicators.

Discussion

This study identifies MTF1, SAT1, and TXN as hub genes associated with ferroptosis in SARS-CoV-2-induced ARDS. These findings provide novel insights into the molecular mechanisms underlying ARDS in COVID-19 patients and offer potential targets for immune therapy and targeted treatment. Further experimental validation is warranted to solidify these findings and explore therapeutic interventions for ARDS in the context of COVID-19.

Longitudinal transcriptomic analysis reveals persistent enrichment of iron homeostasis and erythrocyte function pathways in severe COVID-19 ARDS

Introduction

The acute respiratory distress syndrome (ARDS) is a common complication of severe COVID-19 and contributes to patient morbidity and mortality. ARDS is a heterogeneous syndrome caused by various insults, and results in acute hypoxemic respiratory failure. Patients with ARDS from COVID-19 may represent a subgroup of ARDS patients with distinct molecular profiles that drive disease outcomes. Here, we hypothesized that longitudinal transcriptomic analysis may identify distinct dynamic pathobiological pathways during COVID-19 ARDS.

Methods

We identified a patient cohort from an existing ICU biorepository and established three groups for comparison: 1) patients with COVID-19 ARDS that survived hospitalization (COVID survivors, n = 4), 2) patients with COVID-19 ARDS that did not survive hospitalization (COVID non-survivors, n = 5), and 3) patients with ARDS from other causes as a control group (ARDS controls, n = 4). RNA was isolated from peripheral blood mononuclear cells (PBMCs) at 4 time points (Days 1, 3, 7, and 10 following ICU admission) and analyzed by bulk RNA sequencing.

Results

We first compared transcriptomes between groups at individual timepoints and observed significant heterogeneity in differentially expressed genes (DEGs). Next, we utilized the likelihood ratio test to identify genes that exhibit different patterns of change over time between the 3 groups and identified 341 DEGs across time, including hemoglobin subunit alpha 2 (HBA1, HBA2), hemoglobin subunit beta (HBB), von Willebrand factor C and EGF domains (VWCE), and carbonic anhydrase 1 (CA1), which all demonstrated persistent upregulation in the COVID non-survivors compared to COVID survivors. Of the 341 DEGs, 314 demonstrated a similar pattern of persistent increased gene expression in COVID non-survivors compared to survivors, associated with canonical pathways of iron homeostasis signaling, erythrocyte interaction with oxygen and carbon dioxide, erythropoietin signaling, heme biosynthesis, metabolism of porphyrins, and iron uptake and transport.

Discussion

These findings describe significant differences in gene regulation during patient ICU course between survivors and non-survivors of COVID-19 ARDS. We identified multiple pathways that suggest heme and red blood cell metabolism contribute to disease outcomes. This approach is generalizable to larger cohorts and supports an approach of longitudinal sampling in ARDS molecular profiling studies, which may identify novel targetable pathways of injury and resolution.

Biochemical implication of acetylcholine, histamine, IL-18, and interferon-alpha as diagnostic biomarkers in hepatitis C virus, coronavirus disease 2019, and dual hepatitis C virus-coronavirus disease 2019 patients

Globally, hepatitis C virus (HCV) and coronavirus disease 2019 (COVID-19) are the most common causes of death due to the lack of early predictive and diagnostic tools. Therefore, research for a new biomarker is crucial. Inflammatory biomarkers are critical central players in the pathogenesis of viral infections. IL-18, produced by macrophages in early viral infections, triggers inflammatory biomarkers and interferon production, crucial for viral host defense. Finding out IL-18 function can help understand COVID-19 pathophysiology and predict disease prognosis. Histamine and its receptors regulate allergic lung responses, with H1 receptor inhibition potentially reducing inflammation in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. angiotensin-converting enzyme 2 (ACE-2) receptors on cholangiocytes suggest liver involvement in SARS-CoV-2 infection. The current study presents the potential impact of circulating acetylcholine, histamine, IL-18, and interferon-Alpha as diagnostic tools in HCV, COVID-19, and dual HCV-COVID-19 pathogenesis. The current study was a prospective cross-section conducted on 188 participants classified into the following four groups: Group 1 COVID-19 (n = 47), Group 2 HCV (n = 47), and Group 3 HCV-COVID-19 patients (n = 47), besides the healthy control Group 4 (n = 47). The levels of acetylcholine, histamine, IL-18, and interferon-alpha were assayed using the ELISA method. Liver and kidney functions within all groups showed a marked alteration compared to the healthy control group. Our statistical analysis found that individuals with dual infection with HCV-COVID-19 had high ferritin levels compared to other biomarkers while those with COVID-19 infection had high levels of D-Dimer. The histamine, acetylcholine, and IL-18 biomarkers in both COVID-19 and dual HCV-COVID-19 groups have shown discriminatory power, making them potential diagnostic tests for infection. These three biomarkers showed satisfactory performance in identifying HCV infection. The IFN-Alpha test performed well in the HCV-COVID-19 group and was fair in the COVID-19 group, but it had little discriminative value in the HCV group. Moreover, our findings highlighted the pivotal role of acetylcholine, histamine, IL-18, and interferon-Alpha in HCV, COVID-19, and dual HCV-COVID-19 infection. Circulating levels of acetylcholine, histamine, IL-18, and interferon-Alpha can be potential early indicators for HCV, COVID-19, and dual HCV-COVID-19 infection. We acknowledge that further large multicenter experimental studies are needed to further investigate the role biomarkers play in influencing the likelihood of infection to confirm and extend our observations and to better understand and ultimately prevent or treat these diseases.

Immunological characterization and comparison of children with COVID-19 from their adult counterparts at single-cell resolution

Introduction

The immunological characteristics that could protect children with coronavirus disease 2019 (COVID-19) from severe or fatal illnesses have not been fully understood yet.

Methods

Here, we performed single-cell RNA sequencing (scRNA-seq) analysis on peripheral blood samples of 15 children (8 with COVID-19) and compared them to 18 adults (13 with COVID-19).

Results

The child-adult integrated single cell data indicated that children with the disease presented a restrained response to type I interferon in most of the major immune cell types, along with suppression of upstream interferon regulatory factor and toll-like receptor expression in monocytes, which was confirmed by in vitro interferon stimulation assays. Unlike adult patients, children with COVID-19 showed lower frequencies of activated proinflammatory CD14+ monocytes, possibly explaining the rareness of cytokine storm in them. Notably, natural killer (NK) cells in pediatric patients displayed potent cytotoxicity with a rich expression of cytotoxic molecules and upregulated cytotoxic pathways, whereas the cellular senescence, along with the Notch signaling pathway, was significantly downregulated in NK cells, all suggesting more robust cytotoxicity in NK cells of children than adult patients that was further confirmed by CD107a degranulation assays. Lastly, a modest adaptive immune response was evident with more naïve T cells but less activated and proliferated T cells while less naïve B cells but more activated B cells in children over adult patients.

Conclusion

Conclusively, this preliminary study revealed distinct cell frequency and activation status of major immune cell types, particularly more robust NK cell cytotoxicity in PBMC that might help protect children from severe COVID-19.

Molecular mimicry in multisystem inflammatory syndrome in children

Multisystem inflammatory syndrome in children (MIS-C) is a severe, post-infectious sequela of SARS-CoV-2 infection1,2, yet the pathophysiological mechanism connecting the infection to the broad inflammatory syndrome remains unknown. Here we leveraged a large set of samples from patients with MIS-C to identify a distinct set of host proteins targeted by patient autoantibodies including a particular autoreactive epitope within SNX8, a protein involved in regulating an antiviral pathway associated with MIS-C pathogenesis. In parallel, we also probed antibody responses from patients with MIS-C to the complete SARS-CoV-2 proteome and found enriched reactivity against a distinct domain of the SARS-CoV-2 nucleocapsid protein. The immunogenic regions of the viral nucleocapsid and host SNX8 proteins bear remarkable sequence similarity. Consequently, we found that many children with anti-SNX8 autoantibodies also have cross-reactive T cells engaging both the SNX8 and the SARS-CoV-2 nucleocapsid protein epitopes. Together, these findings suggest that patients with MIS-C develop a characteristic immune response to the SARS-CoV-2 nucleocapsid protein that is associated with cross-reactivity to the self-protein SNX8, demonstrating a mechanistic link between the infection and the inflammatory syndrome, with implications for better understanding a range of post-infectious autoinflammatory diseases.

scCross: a deep generative model for unifying single-cell multi-omics with seamless integration, cross-modal generation, and in silico exploration

Single-cell multi-omics data reveal complex cellular states, providing significant insights into cellular dynamics and disease. Yet, integration of multi-omics data presents challenges. Some modalities have not reached the robustness or clarity of established transcriptomics. Coupled with data scarcity for less established modalities and integration intricacies, these challenges limit our ability to maximize single-cell omics benefits. We introduce scCross, a tool leveraging variational autoencoders, generative adversarial networks, and the mutual nearest neighbors (MNN) technique for modality alignment. By enabling single-cell cross-modal data generation, multi-omics data simulation, and in silico cellular perturbations, scCross enhances the utility of single-cell multi-omics studies.

An ex vivo human precision-cut lung slice platform provides insight into SARS-CoV-2 pathogenesis and antiviral drug efficacy

Coronavirus disease 2019 (COVID-19) has claimed millions of lives since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and lung disease appears the primary cause of death in COVID-19 patients. However, the underlying mechanisms of COVID-19 pathogenesis remain elusive, and there is no existing model where human disease can be faithfully recapitulated and conditions for the infection process can be experimentally controlled. Herein we report the establishment of an ex vivo human precision-cut lung slice (hPCLS) platform for studying SARS-CoV-2 pathogenicity and innate immune responses, and for evaluating the efficacy of antiviral drugs against SARS-CoV-2. We show that while SARS-CoV-2 continued to replicate during the course of infection of hPCLS, infectious virus production peaked within 2 days, and rapidly declined thereafter. Although most proinflammatory cytokines examined were induced by SARS-CoV-2 infection, the degree of induction and types of cytokines varied significantly among hPCLS from individual donors. Two cytokines in particular, IP-10 and IL-8, were highly and consistently induced, suggesting a role in the pathogenesis of COVID-19. Histopathological examination revealed focal cytopathic effects late in the infection. Transcriptomic and proteomic analyses identified molecular signatures and cellular pathways that are largely consistent with the progression of COVID-19 in patients. Furthermore, we show that homoharringtonine, a natural plant alkaloid derived from Cephalotoxus fortunei, not only inhibited virus replication but also production of pro-inflammatory cytokines, and thus ameliorated the histopathological changes caused by SARS-CoV-2 infection, demonstrating the usefulness of the hPCLS platform for evaluating antiviral drugs.

IMPORTANCE

Here, established an ex vivo human precision-cut lung slice platform for assessing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, viral replication kinetics, innate immune response, disease progression, and antiviral drugs. Using this platform, we identified early induction of specific cytokines, especially IP-10 and IL-8, as potential predictors for severe coronavirus disease 2019 (COVID-19), and uncovered a hitherto unrecognized phenomenon that while infectious virus disappears at late times of infection, viral RNA persists and lung histopathology commences. This finding may have important clinical implications for both acute and post-acute sequelae of COVID-19. This platform recapitulates some of the characteristics of lung disease observed in severe COVID-19 patients and is therefore a useful platform for understanding mechanisms of SARS-CoV-2 pathogenesis and for evaluating the efficacy of antiviral drugs.

scSemiProfiler: Advancing large-scale single-cell studies through semi-profiling with deep generative models and active learning

Single-cell sequencing is a crucial tool for dissecting the cellular intricacies of complex diseases. Its prohibitive cost, however, hampers its application in expansive biomedical studies. Traditional cellular deconvolution approaches can infer cell type proportions from more affordable bulk sequencing data, yet they fall short in providing the detailed resolution required for single-cell-level analyses. To overcome this challenge, we introduce "scSemiProfiler", an innovative computational framework that marries deep generative models with active learning strategies. This method adeptly infers single-cell profiles across large cohorts by fusing bulk sequencing data with targeted single-cell sequencing from a few rigorously chosen representatives. Extensive validation across heterogeneous datasets verifies the precision of our semi-profiling approach, aligning closely with true single-cell profiling data and empowering refined cellular analyses. Originally developed for extensive disease cohorts, "scSemiProfiler" is adaptable for broad applications. It provides a scalable, cost-effective solution for single-cell profiling, facilitating in-depth cellular investigation in various biological domains.

Single-cell transcriptomics by clinical course of Mycobacterium avium complex pulmonary disease

Mycobacterium avium complex pulmonary disease (MAC-PD) has a heterogeneous clinical course. However, immune profiles associated with MAC-PD clinical course are limited. We performed single-cell RNA sequencing of peripheral blood mononuclear cells from 21 MAC-PD patients divided into three clinical courses: group A, spontaneous culture conversion; group B, stable disease without antibiotic treatment; and group C, progressive disease with antibiotic treatment. A lower proportion of NK cells and higher proportion of monocytes were noted in group C compared to combined groups A and B. The proportion of classical monocytes was higher in group C compared to groups A and B, while the proportion of non-classical monocytes decreased. EGR1, HSPA1A, HSPA1B, and CD83 were up-regulated in spontaneous culture conversion group A compared to progressive disease group C. Up-regulation of MYOM2 and LILRA4 and down-regulation of MT-ATP8, CD83, and CCL3L1 was found in progressive disease group C. PCBP1, FOS, RGCC, S100B, G0S2, AREG, and LYN were highly expressed in favorable treatment response compared to unfavorable response. Our findings may offer a comprehensive understanding of the host immune profiles that influence a particular MAC-PD clinical course and could suggest an immunological mechanism associated with the disease progression of MAC-PD.

Microheterogeneity in the Kinetics and Sex-Specific Response to Type I IFN

The response to type I IFNs involves the rapid induction of prototypical IFN signature genes (ISGs). It is not known whether the tightly controlled ISG expression observed at the cell population level correctly represents the coherent responses of individual cells or whether it masks some heterogeneity in gene modules and/or responding cells. We performed a time-resolved single-cell analysis of the first 3 h after in vivo IFN stimulation in macrophages and CD4+ T and B lymphocytes from mice. All ISGs were generally induced in concert, with no clear cluster of faster- or slower-responding ISGs. Response kinetics differed between cell types: mostly homogeneous for macrophages, but with far more kinetic diversity among B and T lymphocytes, which included a distinct subset of nonresponsive cells. Velocity analysis confirmed the differences between macrophages in which the response progressed throughout the full 3 h, versus B and T lymphocytes in which it was rapidly curtailed by negative feedback and revealed differences in transcription rates between the lineages. In all cell types, female cells responded faster than their male counterparts. The ISG response thus seems to proceed as a homogeneous gene block, but with kinetics that vary between immune cell types and with sex differences that might underlie differential outcomes of viral infections.

Vaccination reduces central nervous system IL-1β and memory deficits after COVID-19 in mice

Up to 25% of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) exhibit postacute cognitive sequelae. Although millions of cases of coronavirus disease 2019 (COVID-19)-mediated memory dysfunction are accumulating worldwide, the underlying mechanisms and how vaccination lowers risk are unknown. Interleukin-1 (IL-1), a key component of innate immune defense against SARS-CoV-2 infection, is elevated in the hippocampi of individuals with COVID-19. Here we show that intranasal infection of C57BL/6J mice with SARS-CoV-2 Beta variant leads to central nervous system infiltration of Ly6Chi monocytes and microglial activation. Accordingly, SARS-CoV-2, but not H1N1 influenza virus, increases levels of brain IL-1β and induces persistent IL-1R1-mediated loss of hippocampal neurogenesis, which promotes postacute cognitive deficits. Vaccination with a low dose of adenoviral-vectored spike protein prevents hippocampal production of IL-1β during breakthrough SARS-CoV-2 infection, loss of neurogenesis and subsequent memory deficits. Our study identifies IL-1β as one potential mechanism driving SARS-CoV-2-induced cognitive impairment in a new mouse model that is prevented by vaccination.

SARS-CoV-2: pathogenesis, therapeutics, variants, and vaccines

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), emerged in December 2019 with staggering economic fallout and human suffering. The unique structure of SARS-CoV-2 and its underlying pathogenic mechanism were responsible for the global pandemic. In addition to the direct damage caused by the virus, SARS-CoV-2 triggers an abnormal immune response leading to a cytokine storm, culminating in acute respiratory distress syndrome and other fatal diseases that pose a significant challenge to clinicians. Therefore, potential treatments should focus not only on eliminating the virus but also on alleviating or controlling acute immune/inflammatory responses. Current management strategies for COVID-19 include preventative measures and supportive care, while the role of the host immune/inflammatory response in disease progression has largely been overlooked. Understanding the interaction between SARS-CoV-2 and its receptors, as well as the underlying pathogenesis, has proven to be helpful for disease prevention, early recognition of disease progression, vaccine development, and interventions aimed at reducing immunopathology have been shown to reduce adverse clinical outcomes and improve prognosis. Moreover, several key mutations in the SARS-CoV-2 genome sequence result in an enhanced binding affinity to the host cell receptor, or produce immune escape, leading to either increased virus transmissibility or virulence of variants that carry these mutations. This review characterizes the structural features of SARS-CoV-2, its variants, and their interaction with the immune system, emphasizing the role of dysfunctional immune responses and cytokine storm in disease progression. Additionally, potential therapeutic options are reviewed, providing critical insights into disease management, exploring effective approaches to deal with the public health crises caused by SARS-CoV-2.

Aging is associated with an insufficient early inflammatory response of lung endothelial cells in SARS-CoV-2 infection

Advanced age is associated with an increased susceptibility to Coronavirus Disease (COVID)-19 and more severe outcomes, although the underlying mechanisms are understudied. The lung endothelium is located next to infected epithelial cells and bystander inflammation may contribute to thromboinflammation and COVID-19-associated coagulopathy. Here, we investigated age-associated SARS-CoV-2 pathogenesis and endothelial inflammatory responses using humanized K18-hACE2 mice. Survival was reduced to 20% in aged mice (85-112 weeks) versus 50% in young mice (12-15 weeks) at 10 days post infection (dpi). Bulk RNA-sequencing of endothelial cells from mock and infected mice at 2dpi of both age groups (aged: 72-85 weeks; young: 15 weeks) showed substantially lower significant differentially regulated genes in infected aged mice than in young mice (712 versus 2294 genes). Viral recognition and anti-viral pathways such as RIG-I-like receptor signaling, NOD-like receptor signaling and interferon signaling were regulated in response to SARS-CoV-2. Young mice showed several fold higher interferon responses (Ifitm3, Ifit1, Isg15, Stat1) and interferon-induced chemokines (Cxcl10 and Cxcl11) than aged mice. Endothelial cells from infected young mice displayed elevated expression of chemokines (Cxcl9, Ccl2) and leukocyte adhesion markers (Icam1) underscoring that inflammation of lung endothelium during infection could facilitate leukocyte adhesion and thromboinflammation. TREM1 and acute phase response signaling were particularly prominent in endothelial cells from infected young mice. Immunohistochemistry was unable to detect viral protein in pulmonary endothelium. In conclusion, our data demonstrate that the early host response of the endothelium to SARS-CoV-2 infection declines with aging, which could be a potential contributor to disease severity.

BCG priming followed by a novel interleukin combination activates Natural Killer cells to selectively proliferate and become anti-tumour long-lived effectors

The short-lived nature and heterogeneity of Natural Killer (NK) cells limit the development of NK cell-based therapies, despite their proven safety and efficacy against cancer. Here, we describe the biological basis, detailed phenotype and function of long-lived anti-tumour human NK cells (CD56highCD16+), obtained without cell sorting or feeder cells, after priming of peripheral blood cells with Bacillus Calmette-Guérin (BCG). Further, we demonstrate that survival doses of a cytokine combination, excluding IL18, administered just weekly to BCG-primed NK cells avoids innate lymphocyte exhaustion and leads to specific long-term proliferation of innate cells that exert potent cytotoxic function against a broad range of solid tumours, mainly through NKG2D. Strikingly, a NKG2C+CD57-FcεRIγ+ NK cell population expands after BCG and cytokine stimulation, independently of HCMV serology. This strategy was exploited to rescue anti-tumour NK cells even from the suppressor environment of cancer patients' bone marrow, demonstrating that BCG confers durable anti-tumour features to NK cells.

An enhanced IL17 and muted type I interferon nasal epithelial cell state characterizes severe COVID-19 with fungal coinfection

Recent case reports and epidemiological data suggest that fungal infections represent an underappreciated complication among people with severe COVID-19. However, the frequency of fungal colonization in patients with COVID-19 and associations with specific immune responses in the airways remain incompletely defined. We previously generated a single-cell RNA-sequencing data set characterizing the upper respiratory microenvironment during COVID-19 and mapped the relationship between disease severity and the local behavior of nasal epithelial cells and infiltrating immune cells. Our previous study, in agreement with findings from related human cohorts, demonstrated that a profound deficiency in host immunity, particularly in type I and type III interferon signaling in the upper respiratory tract, is associated with rapid progression to severe disease and worse clinical outcomes. We have now performed further analysis of this cohort and identified a subset of participants with severe COVID-19 and concurrent detection of Candida species-derived transcripts within samples collected from the nasopharynx and trachea. Here, we present the clinical characteristics of these individuals. Using matched single-cell transcriptomic profiles of these individuals' respiratory mucosa, we identify epithelial immune signatures suggestive of IL17 stimulation and anti-fungal immunity. Further, we observe a significant expression of anti-fungal inflammatory cascades in the nasal and tracheal epithelium of all participants who went on to develop severe COVID-19, even among participants without detectable genetic material from fungal pathogens. Together, our data suggest that IL17 stimulation-in part driven by Candida colonization-and blunted interferon signaling represent a common feature of severe COVID-19 infection.

IMPORTANCE

In this paper, we present an analysis suggesting that symptomatic and asymptomatic fungal coinfections can impact patient disease progression during COVID-19 hospitalization. By looking into the presence of other pathogens and their effect on the host immune response during COVID-19 hospitalizations, we aim to offer insight into an underestimated scenario, furthering our current knowledge of determinants of severity that could be considered for future diagnostic and intervention strategies.

ISMI-VAE: A deep learning model for classifying disease cells using gene expression and SNV data

Various studies have linked several diseases, including cancer and COVID-19, to single nucleotide variations (SNV). Although single-cell RNA sequencing (scRNA-seq) technology can provide SNV and gene expression data, few studies have integrated and analyzed these multimodal data. To address this issue, we introduce Interpretable Single-cell Multimodal Data Integration Based on Variational Autoencoder (ISMI-VAE). ISMI-VAE leverages latent variable models that utilize the characteristics of SNV and gene expression data to overcome high noise levels and uses deep learning techniques to integrate multimodal information, map them to a low-dimensional space, and classify disease cells. Moreover, ISMI-VAE introduces an attention mechanism to reflect feature importance and analyze genetic features that could potentially cause disease. Experimental results on three cancer data sets and one COVID-19 data set demonstrate that ISMI-VAE surpasses the baseline method in terms of both effectiveness and interpretability and can effectively identify disease-causing gene features.

Deciphering Abnormal Platelet Subpopulations in COVID-19, Sepsis and Systemic Lupus Erythematosus through Machine Learning and Single-Cell Transcriptomics

This study focuses on understanding the transcriptional heterogeneity of activated platelets and its impact on diseases such as sepsis, COVID-19, and systemic lupus erythematosus (SLE). Recognizing the limited knowledge in this area, our research aims to dissect the complex transcriptional profiles of activated platelets to aid in developing targeted therapies for abnormal and pathogenic platelet subtypes. We analyzed single-cell transcriptional profiles from 47,977 platelets derived from 413 samples of patients with these diseases, utilizing Deep Neural Network (DNN) and eXtreme Gradient Boosting (XGB) to distinguish transcriptomic signatures predictive of fatal or survival outcomes. Our approach included source data annotations and platelet markers, along with SingleR and Seurat for comprehensive profiling. Additionally, we employed Uniform Manifold Approximation and Projection (UMAP) for effective dimensionality reduction and visualization, aiding in the identification of various platelet subtypes and their relation to disease severity and patient outcomes. Our results highlighted distinct platelet subpopulations that correlate with disease severity, revealing that changes in platelet transcription patterns can intensify endotheliopathy, increasing the risk of coagulation in fatal cases. Moreover, these changes may impact lymphocyte function, indicating a more extensive role for platelets in inflammatory and immune responses. This study identifies crucial biomarkers of platelet heterogeneity in serious health conditions, paving the way for innovative therapeutic approaches targeting platelet activation, which could improve patient outcomes in diseases characterized by altered platelet function.

Ruxolitinib plus standard of care in severe hospitalized adults with severe fever with thrombocytopenia syndrome (SFTS): an exploratory, single-arm trial

BACKGROUND

Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne infectious disease, and its morbidity and mortality are increasing. At present, there is no specific therapy available. An exacerbated IFN-I response and cytokine storm are related to the mortality of patients with SFTS. Ruxolitinib is a Janus kinase (JAK) 1/2 inhibitor that can block proinflammatory cytokines and inhibit the type I IFN pathway. We aimed to explore the use of ruxolitinib plus standard of care for severe SFTS.

METHODS

We conducted a prospective, single-arm study of severe SFTS. We recruited participants aged 18 years or older who were admitted to the hospital with laboratory-confirmed severe SFTS and whose clinical score exceeded 8 points within 6 days of symptom onset. Participants received oral ruxolitinib (10 mg twice a day) for up to 10 days. The primary endpoint was 28-day overall survival. The secondary endpoints included the proportion of participants who needed intensive care unit (ICU) admission, total cost, changes in neurologic symptoms and clinical laboratory parameters, and adverse events (AEs) within 28 days. A historical control group (HC group, n = 26) who met the upper criteria for inclusion and hospitalized from April 1, 2021, to September 16, 2022, was selected and 1:1 matched for baseline characteristics by propensity score matching.

RESULTS

Between Sep 16, 2022, and Sep 16, 2023, 26 participants were recruited into the ruxolitinib treatment group (RUX group). The 28-day overall mortality was 7.7% in the RUX group and 46.2% in the HC group (P = 0.0017). There was a significantly lower proportion of ICU admissions (15.4% vs 65.4%, p < 0.001) and total hospitalization cost in the RUX group. Substantial improvements in neurologic symptoms, platelet counts, hyperferritinemia, and an absolute decrease in the serum SFTS viral load were observed in all surviving participants. Treatment-related adverse events were developed in 6 patients (23.2%) and worsened in 8 patients (30.8%), and no treatment-related serious adverse events were reported.

CONCLUSIONS

Our findings indicate that ruxolitinib has the potential to increase the likelihood of survival as well as reduce the proportion of ICU hospitalization and being tolerated in severe SFTS. Further trials are needed.

TRAIL REGISTRATION

ChiCTR2200063759, September 16, 2022.

Sustained IFN signaling is associated with delayed development of SARS-CoV-2-specific immunity

Plasma RNAemia, delayed antibody responses and inflammation predict COVID-19 outcomes, but the mechanisms underlying these immunovirological patterns are poorly understood. We profile 782 longitudinal plasma samples from 318 hospitalized patients with COVID-19. Integrated analysis using k-means reveals four patient clusters in a discovery cohort: mechanically ventilated critically-ill cases are subdivided into good prognosis and high-fatality clusters (reproduced in a validation cohort), while non-critical survivors segregate into high and low early antibody responders. Only the high-fatality cluster is enriched for transcriptomic signatures associated with COVID-19 severity, and each cluster has distinct RBD-specific antibody elicitation kinetics. Both critical and non-critical clusters with delayed antibody responses exhibit sustained IFN signatures, which negatively correlate with contemporaneous RBD-specific IgG levels and absolute SARS-CoV-2-specific B and CD4+ T cell frequencies. These data suggest that the "Interferon paradox" previously described in murine LCMV models is operative in COVID-19, with excessive IFN signaling delaying development of adaptive virus-specific immunity.

Vitamin D regulates COVID-19 associated severity by suppressing the NLRP3 inflammasome pathway

BACKGROUND

The role of vitamin D3 (VitD3) in modulating innate and adaptive immunity has been reported in different disease contexts. Since the start of the coronavirus disease-2019 (COVID-19) pandemic, the role of VitD3 has been highlighted in many correlational and observational studies. However, the exact mechanisms of action are not well identified. One of the mechanisms via which VitD3 modulates innate immunity is by regulating the NLRP3-inflammasome pathway, being a main underlying cause of SARS-CoV-2-induced hyperinflammation.

AIMS AND MAIN METHODS

Blood specimens of severe COVID-19 patients with or without VitD3 treatment were collected during their stay in the intensive care unit and patients were followed up for 29 days. qPCR, western blot, and ELISA were done to investigate the mechanism of action of VitD3 on the NLRP3 inflammasome activation.

KEY FINDINGS

We here report the ability of VitD3 to downregulate the NLRP3-inflammsome pathway in severe COVID-19 patients. Lower inflammasome pathway activation was observed with significantly lower gene and protein expression of NLRP3, cleaved caspase-1, ASC and IL-1β among severe COVID-19 patients treated with VitD3. The reduction of the inflammasome pathway was associated with a reduction in disease severity markers and enhancement of type I IFN pathway.

SIGNIFICANCE

Our data reveals an important anti-inflammatory effect of VitD3 during SARS-CoV-2 infection. Further investigations are warranted to better characterize the ability of VitD3 to control disease pathogenesis and prevent progression to severe states. This will allow for a more efficient use of a low cost and accessible treatment like VitD3.

Immunophenotypes of Newborns From SARS-CoV-2-infected Mothers

BACKGROUND

Little is known about the neonatal immunologic response to a maternal SARS-CoV-2 infection present during childbirth. Here we analyze a cohort of 75 neonates from SARS-CoV-2-infected mothers.

METHODS

The SARS-CoV-2 infection status was laboratory assessed by real-time reverse transcription polymerase chain reaction on nasopharyngeal swabs (NPS) in both mothers during childbirth and neonates within 24 hours of life. Immunophenotypes of peripheral blood mononucleated cells and SARS-CoV-2 antispike IgA, IgM and IgG of the newborns were recorded. Ten (13.3%) of 75 neonates had positive NPS for SARS-CoV-2; 17 of 75 (23%) were SARS-CoV-2-IgG seropositive, of which one with positive NPS. All the newborns resulted seronegative for SARS-CoV-2 IgA and IgM and were asymptomatic. Our cohort of newborns was divided into groups according to IgG seropositivity (IgG+/-) and NPS results (NPS+/-).

RESULTS

The count and proportion of lymphocyte subsets (evaluated measuring CD3, CD4, CD8 and CD19 markers) and of natural killer cells (evaluated by measuring the CD3-/CD16+/CD56+ subset) were all in the normal range, with no statistical differences among groups. We found a significant expansion of the T cell (CD3+) subset in the IgG+ group interpreted as the result of immune effects triggered by trained immunity in these newborns, but a decrease in CD4+ T cells for NPS+ neonates. It is therefore difficult to conclude that the decrease in CD4 can certainly be caused by an infection.

CONCLUSIONS

A maternal SARS-CoV-2 infection resulted in an expansive effect of CD3+ T cells in IgG+ newborns; nonetheless, it seems not to affect structural and functional development of the newborn immune system.

The regulation of cGAS-STING signaling by RNA virus-derived components

The Cyclic GMP-AMP synthase-stimulator of interferon genes (cGAS-STING) serves as a key innate immune signaling axis involved in the regulation of various human diseases. It has been found that cGAS-STING pathway can recognize a variety of cytosolic double-stranded DNA (dsDNA), contributing to cause a robust type I interferon response thereby affecting the occurrence and progression of viral infection. Accumulating evidence indicates RNA virus-derived components play an important role in regulating cGAS-STING signaling, either as protective or pathogenic factors in the pathogenesis of diseases. Thus, a comprehensive understanding of the function of RNA virus-derived components in regulating cGAS-STING signaling will provide insights into developing novel therapies. Here, we review the existing literature on cGAS-STING pathway regulated by RNA virus-derived components to propose insights into pharmacologic strategies targeting the cGAS-STING pathway.

Feruloylated Oligosaccharides Prevented Influenza-Induced Lung Inflammation via the RIG-I/MAVS/TRAF3 Pathway

Uncontrolled inflammation contributes significantly to the mortality in acute respiratory infections. Our previous research has demonstrated that maize bran feruloylated oligosaccharides (FOs) possess notable anti-inflammatory properties linked to the NF-kB pathway regulation. In this study, we clarified that the oral administration of FOs moderately inhibited H1N1 virus infection and reduced lung inflammation in influenza-infected mice by decreasing a wide spectrum of cytokines (IFN-α, IFN-β, IL-6, IL-10, and IL-23) in the lungs. The mechanism involves FOs suppressing the transduction of the RIG-I/MAVS/TRAF3 signaling pathway, subsequently lowering the expression of NF-κB. In silico analysis suggests that FOs have a greater binding affinity for the RIG-I/MAVS signaling complex. This indicates that FOs have potential as promising targets for immune modulation. Moreover, in MAVS knockout mice, we confirmed that the anti-inflammatory function of FOs against influenza depends on MAVS. Comprehensive analysis using 16S rRNA gene sequencing and metabolite profiling techniques showed that FOs have the potential to restore immunity by modulating the gut microbiota. In conclusion, our study demonstrates that FOs are effective anti-inflammatory phytochemicals in inhibiting lung inflammation caused by influenza. This suggests that FOs could serve as a potential nutritional strategy for preventing the H1N1 virus infection and associated lung inflammation.

Structural properties of immune complexes formed by viral antigens and specific antibodies shape the inflammatory response of macrophages

Data on the course of viral infections revealed severe inflammation as a consequence of antiviral immune response. Despite extensive research, there are insufficient data on the role of innate immune cells in promoting inflammation mediated by immune complexes (IC) of viral antigens and their specific antibodies. Recently, we demonstrated that antigens of human polyomaviruses (PyVs) induce an inflammatory response in macrophages. Here, we investigated macrophage activation by IC. We used primary murine macrophages as a cell model, virus-like particles (VLPs) of PyV capsid protein as antigens, and a collection of murine monoclonal antibodies (mAbs) of IgG1, IgG2a, IgG2b subclasses. The inflammatory response was investigated by analysing inflammatory chemokines and activation of NLRP3 inflammasome. We observed a diverse pattern of chemokine secretion in macrophages treated with different IC compared to VLPs alone. To link IC properties with cell activation status, we characterised the IC by advanced optical and acoustic techniques. Ellipsometry provided precise real-time kinetics of mAb-antigen interactions, while quartz crystal microbalance measurements showed changes in conformation and viscoelastic properties during IC formation. These results revealed differences in mAb-antigen interaction and mAb binding parameters of the investigated IC. We found that IC-mediated cell activation depends more on IC characteristics, including mAb affinity, than on mAb affinity for the activating Fc receptor. IC formed by the highest affinity mAb showed a significant enhancement of inflammasome activation. This may explain the hyperinflammation related to viral infection and vaccination. Our findings demonstrate that IC promote the viral antigen-induced inflammatory response depending on antibody properties.

Identification of Age-Related Characteristic Genes Involved in Severe COVID-19 Infection Among Elderly Patients Using Machine Learning and Immune Cell Infiltration Analysis

Elderly patients infected with severe acute respiratory syndrome coronavirus 2 are at higher risk of severe clinical manifestation, extended hospitalization, and increased mortality. Those patients are more likely to experience persistent symptoms and exacerbate the condition of basic diseases with long COVID-19 syndrome. However, the molecular mechanisms underlying severe COVID-19 in the elderly patients remain unclear. Our study aims to investigate the function of the interaction between disease-characteristic genes and immune cell infiltration in patients with severe COVID-19 infection. COVID-19 datasets (GSE164805 and GSE180594) and aging dataset (GSE69832) were obtained from the Gene Expression Omnibus database. The combined different expression genes (DEGs) were subjected to Gene Ontology (GO) functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Diseases Ontology functional enrichment analysis, Gene Set Enrichment Analysis, machine learning, and immune cell infiltration analysis. GO and KEGG enrichment analyses revealed that the eight DEGs (IL23A, PTGER4, PLCB1, IL1B, CXCR1, C1QB, MX2, ALOX12) were mainly involved in inflammatory mediator regulation of TRP channels, coronavirus disease-COVID-19, and cytokine activity signaling pathways. Three-degree algorithm (LASSO, SVM-RFE, KNN) and correlation analysis showed that the five DEGs up-regulated the immune cells of macrophages M0/M1, memory B cells, gamma delta T cell, dendritic cell resting, and master cell resisting. Our study identified five hallmark genes that can serve as disease-characteristic genes and target immune cells infiltrated in severe COVID-19 patients among the elderly population, which may contribute to the study of pathogenesis and the evaluation of diagnosis and prognosis in aging patients infected with severe COVID-19.

Suppression of Type I Interferon Signaling in Myeloid Cells by Autoantibodies in Severe COVID-19 Patients

PURPOSE

Auto-antibodies (auto-abs) to type I interferons (IFNs) have been identified in patients with life-threatening coronavirus disease 2019 (COVID-19), suggesting that the presence of auto-abs may be a risk factor for disease severity. We therefore investigated the mechanism underlying COVID-19 exacerbation induced by auto-abs to type I IFNs.

METHODS

We evaluated plasma from 123 patients with COVID-19 to measure auto-abs to type I IFNs. We performed single-cell RNA sequencing (scRNA-seq) of peripheral blood mononuclear cells from the patients with auto-abs and conducted epitope mapping of the auto-abs.

RESULTS

Three of 19 severe and 4 of 42 critical COVID-19 patients had neutralizing auto-abs to type I IFNs. Patients with auto-abs to type I IFNs showed no characteristic clinical features. scRNA-seq from 38 patients with COVID-19 revealed that IFN signaling in conventional dendritic cells and canonical monocytes was attenuated, and SARS-CoV-2-specific BCR repertoires were decreased in patients with auto-abs. Furthermore, auto-abs to IFN-α2 from COVID-19 patients with auto-abs recognized characteristic epitopes of IFN-α2, which binds to the receptor.

CONCLUSION

Auto-abs to type I IFN found in COVID-19 patients inhibited IFN signaling in dendritic cells and monocytes by blocking the binding of type I IFN to its receptor. The failure to properly induce production of an antibody to SARS-CoV-2 may be a causative factor of COVID-19 severity.

Comparative single-cell RNA sequencing analysis of immune response to inactivated vaccine and natural SARS-CoV-2 infection

Uncovering the immune response to an inactivated SARS-CoV-2 vaccine (In-Vac) and natural infection is crucial for comprehending COVID-19 immunology. Here we conducted an integrated analysis of single-cell RNA sequencing (scRNA-seq) data from serial peripheral blood mononuclear cell (PBMC) samples derived from 12 individuals receiving In-Vac compared with those from COVID-19 patients. Our study reveals that In-Vac induces subtle immunological changes in PBMC, including cell proportions and transcriptomes, compared with profound changes for natural infection. In-Vac modestly upregulates IFN-α but downregulates NF-κB pathways, while natural infection triggers hyperactive IFN-α and NF-κB pathways. Both In-Vac and natural infection alter T/B cell receptor repertoires, but COVID-19 has more significant change in preferential VJ gene, indicating a vigorous immune response. Our study reveals distinct patterns of cellular communications, including a selective activation of IL-15RA/IL-15 receptor pathway after In-Vac boost, suggesting its potential role in enhancing In-Vac-induced immunity. Collectively, our study illuminates multifaceted immune responses to In-Vac and natural infection, providing insights for optimizing SARS-CoV-2 vaccine efficacy.

Shared Immune Associations Between COVID-19 and Inflammatory Bowel Disease: A Cross-Sectional Observational Study in Shanghai, China

Purpose

The rapid global spread of the SARS-CoV-2 Omicron variant introduces a novel complication: the emergence of IBD (inflammatory bowel disease)-like ulcers in certain patients. This research delves into this new challenge by juxtaposing the clinical manifestations and genetic expression patterns of individuals affected by the Omicron variant of COVID-19 with those diagnosed with IBD. It aims to decode the link between these conditions, potentially shedding light on previously unexplored facets of COVID-19 pathophysiology. This investigation emphasizes gene expression analysis as a key tool to identify wider disease correlations and innovative therapeutic avenues.

Patients and Methods

From March to December 2022, patients with SARS-CoV-2 Omicron infection and inflammatory bowel disease and healthy controls were recruited in Shanghai East Hospital, Shanghai, China. The epidemiological and clinical characteristics of the patients were compared. Four RNA sequencing datasets (GSE205244, GSE201530, GSE174159, and GSE186507) were extracted from the Gene Expression Omnibus database to detect mutually differentially expressed genes and common pathways in patients with SARS-CoV-2 infection and inflammatory bowel disease.

Results

Compared to patients with active inflammatory bowel disease, patients with SARS-CoV-2 infection were more likely to have elevated interferon-α levels and an increased lymphocyte count and less likely to have high interleukin-6, tumor necrosis factor-α, and C-reactive protein levels and an elevated neutrophil count. A total of 51 common differentially expressed genes were identified in the four RNA-sequencing datasets. Enrichment analysis suggested that these genes were related to inflammation and the immune response, especially the innate immune response and nucleotide oligomerization domain-like receptor signaling pathway.

Conclusion

The inflammation and immune-response pathways in COVID-19 and inflammatory bowel disease have several similarities and some differences. The study identifies the NLR signaling pathway's key role in both COVID-19 and IBD, suggesting its potential as a target for therapeutic intervention and vaccine development.

Integrating single-cell RNA sequencing data to genome-wide association analysis data identifies significant cell types in influenza A virus infection and COVID-19

With the global pandemic of COVID-19, the research on influenza virus has entered a new stage, but it is difficult to elucidate the pathogenesis of influenza disease. Genome-wide association studies (GWASs) have greatly shed light on the role of host genetic background in influenza pathogenesis and prognosis, whereas single-cell RNA sequencing (scRNA-seq) has enabled unprecedented resolution of cellular diversity and in vivo following influenza disease. Here, we performed a comprehensive analysis of influenza GWAS and scRNA-seq data to reveal cell types associated with influenza disease and provide clues to understanding pathogenesis. We downloaded two GWAS summary data, two scRNA-seq data on influenza disease. After defining cell types for each scRNA-seq data, we used RolyPoly and LDSC-cts to integrate GWAS and scRNA-seq. Furthermore, we analyzed scRNA-seq data from the peripheral blood mononuclear cells (PBMCs) of a healthy population to validate and compare our results. After processing the scRNA-seq data, we obtained approximately 70 000 cells and identified up to 13 cell types. For the European population analysis, we determined an association between neutrophils and influenza disease. For the East Asian population analysis, we identified an association between monocytes and influenza disease. In addition, we also identified monocytes as a significantly related cell type in a dataset of healthy human PBMCs. In this comprehensive analysis, we identified neutrophils and monocytes as influenza disease-associated cell types. More attention and validation should be given in future studies.

Excess of body weight is associated with accelerated T-cell senescence in hospitalized COVID-19 patients

BACKGROUND

Several risk factors have been involved in the poor clinical progression of coronavirus disease-19 (COVID-19), including ageing, and obesity. SARS-CoV-2 may compromise lung function through cell damage and paracrine inflammation; and obesity has been associated with premature immunosenescence, microbial translocation, and dysfunctional innate immune responses leading to poor immune response against a range of viruses and bacterial infections. Here, we have comprehensively characterized the immunosenescence, microbial translocation, and immune dysregulation established in hospitalized COVID-19 patients with different degrees of body weight.

RESULTS

Hospitalised COVID-19 patients with overweight and obesity had similarly higher plasma LPS and sCD14 levels than controls (all p < 0.01). Patients with obesity had higher leptin levels than controls. Obesity and overweight patients had similarly higher expansions of classical monocytes and immature natural killer (NK) cells (CD56+CD16-) than controls. In contrast, reduced proportions of intermediate monocytes, mature NK cells (CD56+CD16+), and NKT were found in both groups of patients than controls. As expected, COVID-19 patients had a robust expansion of plasmablasts, contrasting to lower proportions of major T-cell subsets (CD4 + and CD8+) than controls. Concerning T-cell activation, overweight and obese patients had lower proportions of CD4+CD38+ cells than controls. Contrasting changes were reported in CD25+CD127low/neg regulatory T cells, with increased and decreased proportions found in CD4+ and CD8+ T cells, respectively. There were similar proportions of T cells expressing checkpoint inhibitors across all groups. We also investigated distinct stages of T-cell differentiation (early, intermediate, and late-differentiated - TEMRA). The intermediate-differentiated CD4 + T cells and TEMRA cells (CD4+ and CD8+) were expanded in patients compared to controls. Senescent T cells can also express NK receptors (NKG2A/D), and patients had a robust expansion of CD8+CD57+NKG2A+ cells than controls. Unbiased immune profiling further confirmed the expansions of senescent T cells in COVID-19.

CONCLUSIONS

These findings suggest that dysregulated immune cells, microbial translocation, and T-cell senescence may partially explain the increased vulnerability to COVID-19 in subjects with excess of body weight.

Coronavirus Disease-2019 in the Immunocompromised Host

Immunocompromised hosts, which encompass a diverse population of persons with malignancies, human immunodeficiency virus disease, solid organ, and hematologic transplants, autoimmune diseases, and primary immunodeficiencies, bear a significant burden of the morbidity and mortality due to coronavirus disease-2019 (COVID-19). Immunocompromised patients who develop COVID-19 have a more severe illness, higher hospitalization rates, and higher mortality rates than immunocompetent patients. There are no well-defined treatment strategies that are specific to immunocompromised patients and vaccines, monoclonal antibodies, and convalescent plasma are variably effective. This review focuses on the specific impact of COVID-19 in immunocompromised patients and the gaps in knowledge that require further study.

Long-Term Autoimmune Inflammatory Rheumatic Outcomes of COVID-19 : A Binational Cohort Study

BACKGROUND

Some data suggest a higher incidence of diagnosis of autoimmune inflammatory rheumatic diseases (AIRDs) among patients with a history of COVID-19 compared with uninfected patients. However, these studies had methodological shortcomings.

OBJECTIVE

To investigate the effect of COVID-19 on long-term risk for incident AIRD over various follow-up periods.

DESIGN

Binational, longitudinal, propensity-matched cohort study.

SETTING

Nationwide claims-based databases in South Korea (K-COV-N cohort) and Japan (JMDC cohort).

PARTICIPANTS

10 027 506 Korean and 12 218 680 Japanese patients aged 20 years or older, including those with COVID-19 between 1 January 2020 and 31 December 2021, matched to patients with influenza infection and to uninfected control patients.

MEASUREMENTS

The primary outcome was onset of AIRD (per appropriate codes from the International Classification of Diseases, 10th Revision) 1, 6, and 12 months after COVID-19 or influenza infection or the respective matched index date of uninfected control patients.

RESULTS

Between 2020 and 2021, among the 10 027 506 Korean participants (mean age, 48.4 years [SD, 13.4]; 50.1% men), 394 274 (3.9%) and 98 596 (0.98%) had a history of COVID-19 or influenza, respectively. After propensity score matching, beyond the first 30 days after infection, patients with COVID-19 were at increased risk for incident AIRD compared with uninfected patients (adjusted hazard ratio, 1.25 [95% CI, 1.18 to 1.31]) and influenza-infected control patients (adjusted hazard ratio, 1.30 [CI, 1.02 to 1.59]). The risk for incident AIRD was higher with more severe acute COVID-19. Similar patterns were observed in the Japanese cohort.

LIMITATIONS

Referral bias due to the pandemic; residual confounding.

CONCLUSION

SARS-CoV-2 infection was associated with increased risk for incident AIRD compared with matched patients without SARS-CoV-2 infection or with influenza infection. The risk for incident AIRD was higher with greater severity of acute COVID-19.

PRIMARY FUNDING SOURCE

National Research Foundation of Korea.

Cell-specific housekeeping role of lncRNAs in COVID-19-infected and recovered patients

A plethora of studies have demonstrated the roles of lncRNAs in modulating disease severity and outcomes during infection. However, the spatio-temporal expression of these lncRNAs is poorly understood. In this study, we used single-cell RNA-seq to understand the spatio-temporal expression dynamics of lncRNAs across healthy, SARS-CoV-2-infected, and recovered individuals and their functional role in modulating the disease and recovery. We identified 203 differentially expressed lncRNAs, including cell type-specific ones like MALAT1, NEAT1, ZFAS1, SNHG7, SNHG8, and SNHG25 modulating immune function in classical monocyte, NK T, proliferating NK, plasmablast, naive, and activated B/T cells. Interestingly, we found invariant lncRNAs (no significant change in expression across conditions) regulating essential housekeeping functions (for example, HOTAIR, NRAV, SNHG27, SNHG28, and UCA1) in infected and recovered individuals. Despite similar repeat element abundance, variant lncRNAs displayed higher Alu content, suggesting increased interactions with proximal and distal genes, crucial for immune response modulation. The comparable repeat abundance but distinct expression levels of variant and invariant lncRNAs highlight the significance of investigating the regulatory mechanisms of invariant lncRNAs. Overall, this study offers new insights into the spatio-temporal expression patterns and functional roles of lncRNAs in SARS-CoV-2-infected and recovered individuals while highlighting the importance of invariant lncRNAs in the disease context.

Understanding COVID-19-associated endothelial dysfunction: role of PIEZO1 as a potential therapeutic target

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Due to its high infectivity, the pandemic has rapidly spread and become a global health crisis. Emerging evidence indicates that endothelial dysfunction may play a central role in the multiorgan injuries associated with COVID-19. Therefore, there is an urgent need to discover and validate novel therapeutic strategies targeting endothelial cells. PIEZO1, a mechanosensitive (MS) ion channel highly expressed in the blood vessels of various tissues, has garnered increasing attention for its potential involvement in the regulation of inflammation, thrombosis, and endothelial integrity. This review aims to provide a novel perspective on the potential role of PIEZO1 as a promising target for mitigating COVID-19-associated endothelial dysfunction.

Single-cell transcriptome landscape of circulating CD4+ T cell populations in autoimmune diseases

CD4+ T cells are key mediators of various autoimmune diseases; however, their role in disease progression remains unclear due to cellular heterogeneity. Here, we evaluated CD4+ T cell subpopulations using decomposition-based transcriptome characterization and canonical clustering strategies. This approach identified 12 independent gene programs governing whole CD4+ T cell heterogeneity, which can explain the ambiguity of canonical clustering. In addition, we performed a meta-analysis using public single-cell datasets of over 1.8 million peripheral CD4+ T cells from 953 individuals by projecting cells onto the reference and cataloging cell frequency and qualitative alterations of the populations in 20 diseases. The analyses revealed that the 12 transcriptional programs were useful in characterizing each autoimmune disease and predicting its clinical status. Moreover, genetic variants associated with autoimmune diseases showed disease-specific enrichment within the 12 gene programs. The results collectively provide a landscape of single-cell transcriptomes of CD4+ T cell subpopulations involved in autoimmune disease.

Acellular Human Amniotic Fluid-Derived Extracellular Vesicles as Novel Anti-Inflammatory Therapeutics against SARS-CoV-2 Infection

The ongoing COVID-19 pandemic caused by SARS-CoV-2 is associated with acute respiratory distress syndrome (ARDS) and fatal pneumonia. Excessive inflammation caused by SARS-CoV-2 is the key driver of ARDS and lethal disease. Several FDA-approved drugs that suppress virus replication are in clinical use. However, despite strong evidence for the role of virus-induced inflammation in severe COVID-19, no effective anti-inflammatory drug is available to control fatal inflammation as well as efficiently clear the virus. Therefore, there is an urgent need to identify biologically derived immunomodulators that suppress inflammation and promote antiviral immunity. In this study, we evaluated acellular human amniotic fluid (acAF) containing extracellular vesicles (hAF-EVs) as a potential non-toxic and safe biologic for immunomodulation during COVID-19. Our in vitro results showed that acAF significantly reduced inflammatory cytokine production in TLR2/4/7 and SARS-CoV-2 structural protein-stimulated mouse macrophages. Importantly, an intraperitoneal administration of acAF reduced morbidity and mortality in SARS-CoV-2-infected mice. A detailed examination of SARS-CoV-2-infected lungs revealed that the increased protection in acAF-treated mice was associated with reduced viral titers and levels of inflammatory myeloid cell infiltration. Collectively, our results identify a novel biologic that has potential to suppress excessive inflammation and enhance survival following SARS-CoV-2 infection, highlighting the translational potential of acAF against COVID-19.

Dictionary learning for integrative, multimodal and scalable single-cell analysis

Mapping single-cell sequencing profiles to comprehensive reference datasets provides a powerful alternative to unsupervised analysis. However, most reference datasets are constructed from single-cell RNA-sequencing data and cannot be used to annotate datasets that do not measure gene expression. Here we introduce 'bridge integration', a method to integrate single-cell datasets across modalities using a multiomic dataset as a molecular bridge. Each cell in the multiomic dataset constitutes an element in a 'dictionary', which is used to reconstruct unimodal datasets and transform them into a shared space. Our procedure accurately integrates transcriptomic data with independent single-cell measurements of chromatin accessibility, histone modifications, DNA methylation and protein levels. Moreover, we demonstrate how dictionary learning can be combined with sketching techniques to improve computational scalability and harmonize 8.6 million human immune cell profiles from sequencing and mass cytometry experiments. Our approach, implemented in version 5 of our Seurat toolkit ( http://www.satijalab.org/seurat ), broadens the utility of single-cell reference datasets and facilitates comparisons across diverse molecular modalities.

scDisInFact: disentangled learning for integration and prediction of multi-batch multi-condition single-cell RNA-sequencing data

Single-cell RNA-sequencing (scRNA-seq) has been widely used for disease studies, where sample batches are collected from donors under different conditions including demographic groups, disease stages, and drug treatments. It is worth noting that the differences among sample batches in such a study are a mixture of technical confounders caused by batch effect and biological variations caused by condition effect. However, current batch effect removal methods often eliminate both technical batch effect and meaningful condition effect, while perturbation prediction methods solely focus on condition effect, resulting in inaccurate gene expression predictions due to unaccounted batch effect. Here we introduce scDisInFact, a deep learning framework that models both batch effect and condition effect in scRNA-seq data. scDisInFact learns latent factors that disentangle condition effect from batch effect, enabling it to simultaneously perform three tasks: batch effect removal, condition-associated key gene detection, and perturbation prediction. We evaluate scDisInFact on both simulated and real datasets, and compare its performance with baseline methods for each task. Our results demonstrate that scDisInFact outperforms existing methods that focus on individual tasks, providing a more comprehensive and accurate approach for integrating and predicting multi-batch multi-condition single-cell RNA-sequencing data.

Early immune factors associated with the development of post-acute sequelae of SARS-CoV-2 infection in hospitalized and non-hospitalized individuals

Background

Infection by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can lead to post-acute sequelae of SARS-CoV-2 (PASC) that can persist for weeks to years following initial viral infection. Clinical manifestations of PASC are heterogeneous and often involve multiple organs. While many hypotheses have been made on the mechanisms of PASC and its associated symptoms, the acute biological drivers of PASC are still unknown.

Methods

We enrolled 494 patients with COVID-19 at their initial presentation to a hospital or clinic and followed them longitudinally to determine their development of PASC. From 341 patients, we conducted multi-omic profiling on peripheral blood samples collected shortly after study enrollment to investigate early immune signatures associated with the development of PASC.

Results

During the first week of COVID-19, we observed a large number of differences in the immune profile of individuals who were hospitalized for COVID-19 compared to those individuals with COVID-19 who were not hospitalized. Differences between individuals who did or did not later develop PASC were, in comparison, more limited, but included significant differences in autoantibodies and in epigenetic and transcriptional signatures in double-negative 1 B cells, in particular.

Conclusions

We found that early immune indicators of incident PASC were nuanced, with significant molecular signals manifesting predominantly in double-negative B cells, compared with the robust differences associated with hospitalization during acute COVID-19. The emerging acute differences in B cell phenotypes, especially in double-negative 1 B cells, in PASC patients highlight a potentially important role of these cells in the development of PASC.

Epigenetic and transcriptional responses in circulating leukocytes are associated with future decompensation during SARS-CoV-2 infection

To elucidate host response elements that define impending decompensation during SARS-CoV-2 infection, we enrolled subjects hospitalized with COVID-19 who were matched for disease severity and comorbidities at the time of admission. We performed combined single-cell RNA sequencing (scRNA-seq) and single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) on peripheral blood mononuclear cells (PBMCs) at admission and compared subjects who improved from their moderate disease with those who later clinically decompensated and required invasive mechanical ventilation or died. Chromatin accessibility and transcriptomic immune profiles were markedly altered between the two groups, with strong signals in CD4+ T cells, inflammatory T cells, dendritic cells, and NK cells. Multiomic signature scores at admission were tightly associated with future clinical deterioration (auROC 1.0). Epigenetic and transcriptional changes in PBMCs reveal early, broad immune dysregulation before typical clinical signs of decompensation are apparent and thus may act as biomarkers to predict future severity in COVID-19.

Longitudinal single cell atlas identifies complex temporal relationship between type I interferon response and COVID-19 severity

Due to the paucity of longitudinal molecular studies of COVID-19, particularly those covering the early stages of infection (Days 1-8 symptom onset), our understanding of host response over the disease course is limited. We perform longitudinal single cell RNA-seq on 286 blood samples from 108 age- and sex-matched COVID-19 patients, including 73 with early samples. We examine discrete cell subtypes and continuous cell states longitudinally, and we identify upregulation of type I IFN-stimulated genes (ISGs) as the predominant early signature of subsequent worsening of symptoms, which we validate in an independent cohort and corroborate by plasma markers. However, ISG expression is dynamic in progressors, spiking early and then rapidly receding to the level of severity-matched non-progressors. In contrast, cross-sectional analysis shows that ISG expression is deficient and IFN suppressors such as SOCS3 are upregulated in severe and critical COVID-19. We validate the latter in four independent cohorts, and SOCS3 inhibition reduces SARS-CoV-2 replication in vitro. In summary, we identify complexity in type I IFN response to COVID-19, as well as a potential avenue for host-directed therapy.

High-dimensional comparison of monocytes and T cells in post-COVID and idiopathic pulmonary fibrosis

Introduction

Up to 30% of hospitalized COVID-19 patients experience persistent sequelae, including pulmonary fibrosis (PF).

Methods

We examined COVID-19 survivors with impaired lung function and imaging worrisome for developing PF and found within six months, symptoms, restriction and PF improved in some (Early-Resolving COVID-PF), but persisted in others (Late-Resolving COVID-PF). To evaluate immune mechanisms associated with recovery versus persistent PF, we performed single-cell RNA-sequencing and multiplex immunostaining on peripheral blood mononuclear cells from patients with Early- and Late-Resolving COVID-PF and compared them to age-matched controls without respiratory disease.

Results and discussion

Our analysis showed circulating monocytes were significantly reduced in Late-Resolving COVID-PF patients compared to Early-Resolving COVID-PF and non-diseased controls. Monocyte abundance correlated with pulmonary function forced vital capacity and diffusion capacity. Differential expression analysis revealed MHC-II class molecules were upregulated on the CD8 T cells of Late-Resolving COVID-PF patients but downregulated in monocytes. To determine whether these immune signatures resembled other interstitial lung diseases, we analyzed samples from Idiopathic Pulmonary Fibrosis (IPF) patients. IPF patients had a similar marked decrease in monocyte HLA-DR protein expression compared to Late-Resolving COVID-PF patients. Our findings indicate decreased circulating monocytes are associated with decreased lung function and uniquely distinguish Late-Resolving COVID-PF from Early-Resolving COVID-PF, IPF, and non-diseased controls.

Interferon response and profiling of interferon response genes in peripheral blood of vaccine-naive COVID-19 patients

Introduction

There is insufficient understanding on systemic interferon (IFN) responses during COVID-19 infection. Early reports indicated that interferon responses were suppressed by the coronavirus (SARS-CoV-2) and clinical trials of administration of various kinds of interferons had been disappointing. Expression of interferon-stimulated genes (ISGs) in peripheral blood (better known as interferon score) has been a well-established bioassay marker of systemic IFN responses in autoimmune diseases. Therefore, with archival samples of a cohort of COVID-19 patients collected before the availability of vaccination, we aimed to better understand this innate immune response by studying the IFN score and related ISGs expression in bulk and single cell RNAs sequencing expression datasets.

Methods

In this study, we recruited 105 patients with COVID-19 and 30 healthy controls in Hong Kong. Clinical risk factors, disease course, and blood sampling times were recovered. Based on a set of five commonly used ISGs (IFIT1, IFIT2, IFI27, SIGLEC1, IFI44L), the IFN score was determined in blood leukocytes collected within 10 days after onset. The analysis was confined to those blood samples collected within 10 days after disease onset. Additional public datasets of bulk gene and single cell RNA sequencing of blood samples were used for the validation of IFN score results.

Results

Compared to the healthy controls, we showed that ISGs expression and IFN score were significantly increased during the first 10 days after COVID infection in majority of patients (71%). Among those low IFN responders, they were more commonly asymptomatic patients (71% vs 25%). 22 patients did not mount an overall significant IFN response and were classified as low IFN responders (IFN score < 1). However, early IFN score or ISGs level was not a prognostic biomarker and could not predict subsequent disease severity. Both IFI27 and SIGLEC1 were monocyte-predominant expressing ISGs and IFI27 were activated even among those low IFN responders as defined by IFN score. In conclusion, a substantial IFN response was documented in this cohort of COVID-19 patients who experience a natural infection before the vaccination era. Like innate immunity towards other virus, the ISGs activation was observed largely during the early course of infection (before day 10). Single-cell RNA sequencing data suggested monocytes were the cell-type that primarily accounted for the activation of two highly responsive ISGs (IFI44L and IFI27).

Discussion

As sampling time and age were two major confounders of ISG expression, they may account for contradicting observations among previous studies. On the other hand, the IFN score was not associated with the severity of the disease.

Single-cell RNA sequencing reveals characteristics of myeloid cells in post-acute sequelae of SARS-CoV-2 patients with persistent respiratory symptoms

Background

Although our understanding of the immunopathology and subsequent risk and severity of COVID-19 disease is evolving, a detailed account of immune responses that contribute to the long-term consequences of pulmonary complications in COVID-19 infection remains unclear. Few studies have detailed the immune and cytokine profiles associated with post-acute sequelae of SARS-CoV-2 infection (PASC) with persistent pulmonary symptoms. The dysregulation of the immune system that drives pulmonary sequelae in COVID-19 survivors and PASC sufferers remains largely unknown.

Results

To characterize the immunological features of pulmonary PASC (PPASC), we performed droplet-based single-cell RNA sequencing (scRNA-seq) to study the transcriptomic profiles of peripheral blood mononuclear cells (PBMCs) from a participant naïve to SARS-CoV-2 (Control) (n=1) and infected with SARS-CoV-2 with chronic pulmonary symptoms (PPASC) (n=2). After integrating scRNA-seq data with a naïve participant from a published dataset, 11 distinct cell populations were identified based on the expression of canonical markers. The proportion of myeloid-lineage cells ([MLCs]; CD14+/CD16+monocytes, and dendritic cells) was increased in PPASC (n=2) compared to controls (n=2). MLCs from PPASC displayed up-regulation of genes associated with pulmonary symptoms/fibrosis, while glycolysis metabolism-related genes were downregulated. Similarly, pathway analysis showed that fibrosis-related (VEGF, WNT, and SMAD) and cell death pathways were up-regulated, but immune pathways were down-regulated in PPASC. Further comparison of PPASC with scRNA-seq data with Severe COVID-19 (n=4) data demonstrated enrichment of fibrotic transcriptional signatures. In PPASC, we observed interactive VEGF ligand-receptor pairs among MLCs, and network modules in CD14+ (cluster 4) and CD16+ (Cluster 5) monocytes displayed a significant enrichment for biological pathways linked to adverse COVID-19 outcomes, fibrosis, and angiogenesis. Further analysis revealed a distinct metabolic alteration in MLCs with a down-regulation of glycolysis/gluconeogenesis in PPASC compared to SARS-CoV-2 naïve samples.

Conclusion

Analysis of a small scRNA-seq dataset demonstrated alterations in the immune response and cellular landscape in PPASC. The presence of elevated MLC levels and their corresponding gene signatures associated with fibrosis, immune response suppression, and altered metabolic states suggests a potential role in PPASC development.

Reduced monocyte proportions and responsiveness in convalescent COVID-19 patients

Introduction

The clinical manifestations of acute severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) infection and coronavirus disease 2019 (COVID-19) suggest a dysregulation of the host immune response that leads to inflammation, thrombosis, and organ dysfunction. It is less clear whether these dysregulated processes persist during the convalescent phase of disease or during long COVID. We sought to examine the effects of SARS-CoV-2 infection on the proportions of classical, intermediate, and nonclassical monocytes, their activation status, and their functional properties in convalescent COVID-19 patients.

Methods

Peripheral blood mononuclear cells (PBMCs) from convalescent COVID-19 patients and uninfected controls were analyzed by multiparameter flow cytometry to determine relative percentages of total monocytes and monocyte subsets. The expression of activation markers and proinflammatory cytokines in response to LPS treatment were measured by flow cytometry and ELISA, respectively.

Results

We found that the percentage of total monocytes was decreased in convalescent COVID-19 patients compared to uninfected controls. This was due to decreased intermediate and non-classical monocytes. Classical monocytes from convalescent COVID-19 patients demonstrated a decrease in activation markers, such as CD56, in response to stimulation with bacterial lipopolysaccharide (LPS). In addition, classical monocytes from convalescent COVID-19 patients showed decreased expression of CD142 (tissue factor), which can initiate the extrinsic coagulation cascade, in response to LPS stimulation. Finally, we found that monocytes from convalescent COVID-19 patients produced less TNF-α and IL-6 in response to LPS stimulation, than those from uninfected controls.

Conclusion

SARS-CoV-2 infection exhibits a clear effect on the relative proportions of monocyte subsets, the activation status of classical monocytes, and proinflammatory cytokine production that persists during the convalescent phase of disease.

Pathway analysis through mutual information

MOTIVATION

In pathway analysis, we aim to establish a connection between the activity of a particular biological pathway and a difference in phenotype. There are many available methods to perform pathway analysis, many of them rely on an upstream differential expression analysis, and many model the relations between the abundances of the analytes in a pathway as linear relationships.

RESULTS

Here, we propose a new method for pathway analysis, MIPath, that relies on information theoretical principles and, therefore, does not model the association between pathway activity and phenotype, resulting in relatively few assumptions. For this, we construct a graph of the data points for each pathway using a nearest-neighbor approach and score the association between the structure of this graph and the phenotype of these same samples using Mutual Information while adjusting for the effects of random chance in each score. The initial nearest neighbor approach evades individual gene-level comparisons, hence making the method scalable and less vulnerable to missing values. These properties make our method particularly useful for single-cell data. We benchmarked our method on several single-cell datasets, comparing it to established and new methods, and found that it produces robust, reproducible, and meaningful scores.

AVAILABILITY AND IMPLEMENTATION

Source code is available at https://github.com/statisticalbiotechnology/mipath, or through Python Package Index as "mipathway."