Integrating population and single-cell variations in vaccine responses identifies a naturally adjuvanted human immune setpoint

Multimodal single-cell profiling methods can capture immune cell variations unfolding over time at the molecular, cellular, and population levels. Transforming these data into biological insights remains challenging. Here, we introduce a framework to integrate variations at the human population and single-cell levels in vaccination responses. Comparing responses following AS03-adjuvanted versus unadjuvanted influenza vaccines with CITE-seq revealed AS03-specific early (day 1) response phenotypes, including a B cell signature of elevated germinal center competition. A correlated network of cell-type-specific transcriptional states defined the baseline immune status associated with high antibody responders to the unadjuvanted vaccine. Certain innate subsets in the network appeared "naturally adjuvanted," with transcriptional states resembling those induced uniquely by AS03-adjuvanted vaccination. Consistently, CD14+ monocytes from high responders at baseline had elevated phospho-signaling responses to lipopolysaccharide stimulation. Our findings link baseline immune setpoints to early vaccine responses, with positive implications for adjuvant development and immune response engineering.

Characterization of the antispike IgG immune response to COVID-19 vaccines in people with a wide variety of immunodeficiencies

Research on coronavirus disease 2019 vaccination in immune-deficient/disordered people (IDP) has focused on cancer and organ transplantation populations. In a prospective cohort of 195 IDP and 35 healthy volunteers (HV), antispike immunoglobulin G (IgG) was detected in 88% of IDP after dose 2, increasing to 93% by 6 months after dose 3. Despite high seroconversion, median IgG levels for IDP never surpassed one-third that of HV. IgG binding to Omicron BA.1 was lowest among variants. Angiotensin-converting enzyme 2 pseudo-neutralization only modestly correlated with antispike IgG concentration. IgG levels were not significantly altered by receipt of different messenger RNA-based vaccines, immunomodulating treatments, and prior severe acute respiratory syndrome coronavirus 2 infections. While our data show that three doses of coronavirus disease 2019 vaccinations induce antispike IgG in most IDP, additional doses are needed to increase protection. Because of the notably reduced IgG response to Omicron BA.1, the efficacy of additional vaccinations, including bivalent vaccines, should be studied in this population.

Systems immunology of regulatory T cells: can one circuit explain it all?

Regulatory T (Treg) cells play vital roles in immune homeostasis and response, including discrimination between self- and non-self-antigens, containment of immunopathology, and inflammation resolution. These diverse functions are orchestrated by cellular circuits involving Tregs and other cell types across space and time. Despite dramatic progress in our understanding of Treg biology, a quantitative framework capturing how Treg-containing circuits give rise to these diverse functions is lacking. Here, we propose that different facets of Treg function can be interpreted as distinct operating regimes of the same underlying circuit. We discuss how a systems immunology approach, involving quantitative experiments, computational modeling, and machine learning, can advance our understanding of Treg function, and help identify general operating and design principles underlying immune regulation.

Tracking B cell responses to the SARS-CoV-2 mRNA-1273 vaccine

Protective immunity following vaccination is sustained by long-lived antibody-secreting cells and resting memory B cells (MBCs). Responses to two-dose SARS-CoV-2 mRNA-1273 vaccination are evaluated longitudinally by multimodal single-cell analysis in three infection-naïve individuals. Integrated surface protein, transcriptomics, and B cell receptor (BCR) repertoire analysis of sorted plasmablasts and spike+ (S-2P+) and S-2P- B cells reveal clonal expansion and accumulating mutations among S-2P+ cells. These cells are enriched in a cluster of immunoglobulin G-expressing MBCs and evolve along a bifurcated trajectory rooted in CXCR3+ MBCs. One branch leads to CD11c+ atypical MBCs while the other develops from CD71+ activated precursors to resting MBCs, the dominant population at month 6. Among 12 evolving S-2P+ clones, several are populated with plasmablasts at early timepoints as well as CD71+ activated and resting MBCs at later timepoints, and display intra- and/or inter-cohort BCR convergence. These relationships suggest a coordinated and predictable evolution of SARS-CoV-2 vaccine-generated MBCs.

Non-coding sequence variation reveals fragility within interleukin 2 feedback circuitry and shapes autoimmune disease risk

Genetic variants associated with human autoimmune diseases commonly map to non-coding control regions, particularly enhancers that function selectively in immune cells and fine-tune gene expression within a relatively narrow range of values. How such modest, cell-type-selective changes can meaningfully shape organismal disease risk remains unclear. To explore this issue, we experimentally manipulated species-conserved enhancers within the disease-associated IL2RA locus and studied accompanying changes in the progression of autoimmunity. Perturbing distinct enhancers with restricted activity in conventional T cells (Tconvs) or regulatory T cells (Tregs)-two functionally antagonistic T cell subsets-caused only modest, cell-type-selective decreases in IL2ra expression parameters. However, these same perturbations had striking and opposing effects in vivo , completely preventing or severely accelerating disease in a murine model of type 1 diabetes. Quantitative tissue imaging and computational modelling revealed that each enhancer manipulation impinged on distinct IL-2-dependent feedback circuits. These imbalances altered the intracellular signaling and intercellular communication dynamics of activated Tregs and Tconvs, producing opposing spatial domains that amplified or constrained ongoing autoimmune responses. These findings demonstrate how subtle changes in gene regulation stemming from non-coding variation can propagate across biological scales due to non-linearities in intra- and intercellular feedback circuitry, dramatically shaping disease risk at the organismal level.

Inflammatory and interferon gene expression signatures in patients with mitochondrial disease

BACKGROUND

People with mitochondrial disease (MtD) are susceptible to metabolic decompensation and neurological symptom progression in response to an infection. Increasing evidence suggests that mitochondrial dysfunction may cause chronic inflammation, which may promote hyper-responsiveness to pathogens and neurodegeneration. We sought to examine transcriptional changes between MtD patients and healthy controls to identify common gene signatures of immune dysregulation in MtD.

METHODS

We collected whole blood from a cohort of MtD patients and healthy controls and performed RNAseq to examine transcriptomic differences. We performed GSEA analyses to compare our findings against existing studies to identify commonly dysregulated pathways.

RESULTS

Gene sets involved in inflammatory signaling, including type I interferons, interleukin-1β and antiviral responses, are enriched in MtD patients compared to controls. Monocyte and dendritic cell gene clusters are also enriched in MtD patients, while T cell and B cell gene sets are negatively enriched. The enrichment of antiviral response corresponds with an independent set of MELAS patients, and two mouse models of mtDNA dysfunction.

CONCLUSIONS

Through the convergence of our results, we demonstrate translational evidence of systemic peripheral inflammation arising from MtD, predominantly through antiviral response gene sets. This provides key evidence linking mitochondrial dysfunction to inflammation, which may contribute to the pathogenesis of primary MtD and other chronic inflammatory disorders associated with mitochondrial dysfunction.

Multiscale integration of human and single-cell variations reveals unadjuvanted vaccine high responders are naturally adjuvanted

Advances in multimodal single cell analysis can empower high-resolution dissection of human vaccination responses. The resulting data capture multiple layers of biological variations, including molecular and cellular states, vaccine formulations, inter- and intra-subject differences, and responses unfolding over time. Transforming such data into biological insight remains a major challenge. Here we present a systematic framework applied to multimodal single cell data obtained before and after influenza vaccination without adjuvants or pandemic H5N1 vaccination with the AS03 adjuvant. Our approach pinpoints responses shared across or unique to specific cell types and identifies adjuvant specific signatures, including pro-survival transcriptional states in B lymphocytes that emerged one day after vaccination. We also reveal that high antibody responders to the unadjuvanted vaccine have a distinct baseline involving a rewired network of cell type specific transcriptional states. Remarkably, the status of certain innate immune cells in this network in high responders of the unadjuvanted vaccine appear "naturally adjuvanted": they resemble phenotypes induced early in the same cells only by vaccination with AS03. Furthermore, these cell subsets have elevated frequency in the blood at baseline and increased cell-intrinsic phospho-signaling responses after LPS stimulation ex vivo in high compared to low responders. Our findings identify how variation in the status of multiple immune cell types at baseline may drive robust differences in innate and adaptive responses to vaccination and thus open new avenues for vaccine development and immune response engineering in humans.

Multiomics integration of 22 immune-mediated monogenic diseases reveals an emergent axis of human immune health

Monogenic diseases are often studied in isolation due to their rarity. Here we utilize multiomics to assess 22 monogenic immune-mediated conditions with age- and sex-matched healthy controls. Despite clearly detectable disease-specific and "pan-disease" signatures, individuals possess stable personal immune states over time. Temporally stable differences among subjects tend to dominate over differences attributable to disease conditions or medication use. Unsupervised principal variation analysis of personal immune states and machine learning classification distinguishing between healthy controls and patients converge to a metric of immune health (IHM). The IHM discriminates healthy from multiple polygenic autoimmune and inflammatory disease states in independent cohorts, marks healthy aging, and is a pre-vaccination predictor of antibody responses to influenza vaccination in the elderly. We identified easy-to-measure circulating protein biomarker surrogates of the IHM that capture immune health variations beyond age. Our work provides a conceptual framework and biomarkers for defining and measuring human immune health.

Inflammatory and interferon gene expression signatures in patients with mitochondrial disease

Background: People with mitochondrial disease (MtD) are susceptible to metabolic decompensation and neurological symptom progression in response to an infection. Increasing evidence suggests that mitochondrial dysfunction may cause chronic inflammation, which may promote hyperresponsiveness to pathogens and neurodegeneration. Methods: We collected whole blood from a cohort of MtD patients and healthy controls and performed RNAseq to examine transcriptomic differences. We performed GSEA analyses to compare our findings against existing studies to identify commonly dysregulated pathways. Results: Gene sets involved in inflammatory signaling, including type I interferons, interleukin-1β and antiviral responses, are enriched in MtD patients compared to controls. Monocyte and dendritic cell gene clusters are also enriched in MtD patients, while T cell and B cell gene sets are negatively enriched. The enrichment of antiviral response corresponds with an independent set of MELAS patients, and two mouse models of mtDNA dysfunction. Conclusions: Through the convergence of our results, we demonstrate translational evidence of systemic peripheral inflammation arising from MtD, predominantly through antiviral response gene sets. This provides key evidence linking mitochondrial dysfunction to inflammation, which may contribute to the pathogenesis of primary MtD and other chronic inflammatory disorders associated with mitochondrial dysfunction.

Influenza vaccination reveals sex dimorphic imprints of prior mild COVID-19

Acute viral infections can have durable functional impacts on the immune system long after recovery, but how they affect homeostatic immune states and responses to future perturbations remain poorly understood1-4. Here we use systems immunology approaches, including longitudinal multimodal single-cell analysis (surface proteins, transcriptome and V(D)J sequences) to comparatively assess baseline immune statuses and responses to influenza vaccination in 33 healthy individuals after recovery from mild, non-hospitalized COVID-19 (mean, 151 days after diagnosis) and 40 age- and sex-matched control individuals who had never had COVID-19. At the baseline and independent of time after COVID-19, recoverees had elevated T cell activation signatures and lower expression of innate immune genes including Toll-like receptors in monocytes. Male individuals who had recovered from COVID-19 had coordinately higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared with healthy male individuals and female individuals who had recovered from COVID-19, in part because male recoverees had monocytes with higher IL-15 responses early after vaccination coupled with elevated prevaccination frequencies of 'virtual memory'-like CD8+ T cells poised to produce more IFNγ after IL-15 stimulation. Moreover, the expression of the repressed innate immune genes in monocytes increased by day 1 to day 28 after vaccination in recoverees, therefore moving towards the prevaccination baseline of the healthy control individuals. By contrast, these genes decreased on day 1 and returned to the baseline by day 28 in the control individuals. Our study reveals sex-dimorphic effects of previous mild COVID-19 and suggests that viral infections in humans can establish new immunological set-points that affect future immune responses in an antigen-agnostic manner.

Sex and prior exposure jointly shape innate immune responses to a live herpesvirus vaccine

Background

Both sex and prior exposure to pathogens are known to influence responses to immune challenges, but their combined effects are not well established in humans, particularly in early innate responses critical for shaping subsequent outcomes.

Methods

We employed systems immunology approaches to study responses to a replication-defective, herpes simplex virus (HSV) 2 vaccine in men and women either naive or previously exposed to HSV.

Results

Blood transcriptomic and cell population profiling showed substantial changes on day 1 after vaccination, but the responses depended on sex and whether the vaccinee was naive or previously exposed to HSV. The magnitude of early transcriptional responses was greatest in HSV naive women where type I interferon (IFN) signatures were prominent and associated negatively with vaccine-induced neutralizing antibody titers, suggesting that a strong early antiviral response reduced the uptake of this replication-defective virus vaccine. While HSV seronegative vaccine recipients had upregulation of gene sets in type I IFN (IFN-α/β) responses, HSV2 seropositive vaccine recipients tended to have responses focused more on type II IFN (IFN-γ) genes.

Conclusions

These results together show that prior exposure and sex interact to shape early innate responses that then impact subsequent adaptive immune phenotypes.

Funding

Intramural Research Program of the NIH, the National Institute of Allergy and Infectious Diseases, and other institutes supporting the Trans-NIH Center for Human Immunology, Autoimmunity, and Inflammation. The vaccine trial was supported through a clinical trial agreement between the National Institute of Allergy and Infectious Diseases and Sanofi Pasteur. Clinical trial number: NCT01915212.

Adaptive immune responses to SARS-CoV-2 persist in the pharyngeal lymphoid tissue of children

Most studies of adaptive immunity to SARS-CoV-2 infection focus on peripheral blood, which may not fully reflect immune responses at the site of infection. Using samples from 110 children undergoing tonsillectomy and adenoidectomy during the COVID-19 pandemic, we identified 24 samples with evidence of previous SARS-CoV-2 infection, including neutralizing antibodies in serum and SARS-CoV-2-specific germinal center and memory B cells in the tonsils and adenoids. Single-cell B cell receptor (BCR) sequencing indicated virus-specific BCRs were class-switched and somatically hypermutated, with overlapping clones in the two tissues. Expanded T cell clonotypes were found in tonsils, adenoids and blood post-COVID-19, some with CDR3 sequences identical to previously reported SARS-CoV-2-reactive T cell receptors (TCRs). Pharyngeal tissues from COVID-19-convalescent children showed persistent expansion of germinal center and antiviral lymphocyte populations associated with interferon (IFN)-γ-type responses, particularly in the adenoids, and viral RNA in both tissues. Our results provide evidence for persistent tissue-specific immunity to SARS-CoV-2 in the upper respiratory tract of children after infection.

Pan-vaccine analysis reveals innate immune endotypes predictive of antibody responses to vaccination

Several studies have shown that the pre-vaccination immune state is associated with the antibody response to vaccination. However, the generalizability and mechanisms that underlie this association remain poorly defined. Here, we sought to identify a common pre-vaccination signature and mechanisms that could predict the immune response across 13 different vaccines. Analysis of blood transcriptional profiles across studies revealed three distinct pre-vaccination endotypes, characterized by the differential expression of genes associated with a pro-inflammatory response, cell proliferation, and metabolism alterations. Importantly, individuals whose pre-vaccination endotype was enriched in pro-inflammatory response genes known to be downstream of nuclear factor-kappa B showed significantly higher serum antibody responses 1 month after vaccination. This pro-inflammatory pre-vaccination endotype showed gene expression characteristic of the innate activation state triggered by Toll-like receptor ligands or adjuvants. These results demonstrate that wide variations in the transcriptional state of the immune system in humans can be a key determinant of responsiveness to vaccination.

Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses

Systems vaccinology has defined molecular signatures and mechanisms of immunity to vaccination. However, comparative analysis of immunity to different vaccines is lacking. We integrated transcriptional data of over 3,000 samples, from 820 adults across 28 studies of 13 vaccines and analyzed vaccination-induced signatures of antibody responses. Most vaccines induced signatures of innate immunity and plasmablasts at days 1 and 7, respectively, after vaccination. However, the yellow fever vaccine induced an early transient signature of T and B cell activation at day 1, followed by delayed antiviral/interferon and plasmablast signatures that peaked at days 7 and 14-21, respectively. Thus, there was no evidence for a 'universal signature' that predicted antibody response to all vaccines. However, accounting for the asynchronous nature of responses, we defined a time-adjusted signature that predicted antibody responses across vaccines. These results provide a transcriptional atlas of immunity to vaccination and define a common, time-adjusted signature of antibody responses.

The Immune Signatures data resource, a compendium of systems vaccinology datasets

Vaccines are among the most cost-effective public health interventions for preventing infection-induced morbidity and mortality, yet much remains to be learned regarding the mechanisms by which vaccines protect. Systems immunology combines traditional immunology with modern 'omic profiling techniques and computational modeling to promote rapid and transformative advances in vaccinology and vaccine discovery. The NIH/NIAID Human Immunology Project Consortium (HIPC) has leveraged systems immunology approaches to identify molecular signatures associated with the immunogenicity of many vaccines. However, comparative analyses have been limited by the distributed nature of some data, potential batch effects across studies, and the absence of multiple relevant studies from non-HIPC groups in ImmPort. To support comparative analyses across different vaccines, we have created the Immune Signatures Data Resource, a compendium of standardized systems vaccinology datasets. This data resource is available through ImmuneSpace, along with code to reproduce the processing and batch normalization starting from the underlying study data in ImmPort and the Gene Expression Omnibus (GEO). The current release comprises 1405 participants from 53 cohorts profiling the response to 24 different vaccines. This novel systems vaccinology data release represents a valuable resource for comparative and meta-analyses that will accelerate our understanding of mechanisms underlying vaccine responses.

Influenza vaccination and single cell multiomics reveal sex dimorphic immune imprints of prior mild COVID-19

Viral infections can have profound and durable functional impacts on the immune system. There is an urgent need to characterize the long-term immune effects of SARS-CoV-2 infection given the persistence of symptoms in some individuals and the continued threat of novel variants. Here we use systems immunology, including longitudinal multimodal single cell analysis (surface proteins, transcriptome, and V(D)J sequences) from 33 previously healthy individuals after recovery from mild, non-hospitalized COVID-19 and 40 age- and sex-matched healthy controls with no history of COVID-19 to comparatively assess the post-infection immune status (mean: 151 days after diagnosis) and subsequent innate and adaptive responses to seasonal influenza vaccination. Identification of both sex-specific and -independent temporally stable changes, including signatures of T-cell activation and repression of innate defense/immune receptor genes (e.g., Toll-like receptors) in monocytes, suggest that mild COVID-19 can establish new post-recovery immunological set-points. COVID-19-recovered males had higher innate, influenza-specific plasmablast, and antibody responses after vaccination compared to healthy males and COVID-19-recovered females, partly attributable to elevated pre-vaccination frequencies of a GPR56 expressing CD8+ T-cell subset in male recoverees that are "poised" to produce higher levels of IFNγ upon inflammatory stimulation. Intriguingly, by day 1 post-vaccination in COVID-19-recovered subjects, the expression of the repressed genes in monocytes increased and moved towards the pre-vaccination baseline of healthy controls, suggesting that the acute inflammation induced by vaccination could partly reset the immune states established by mild COVID-19. Our study reveals sex-dimorphic immune imprints and in vivo functional impacts of mild COVID-19 in humans, suggesting that prior COVID-19, and possibly respiratory viral infections in general, could change future responses to vaccination and in turn, vaccines could help reset the immune system after COVID-19, both in an antigen-agnostic manner.

OMiCC: An expanded and enhanced platform for meta-analysis of public gene expression data

OMiCC (OMics Compendia Commons) is a biologist-friendly web platform that facilitates data reuse and integration. Users can search over 40,000 publicly available gene expression studies, annotate and curate samples, and perform meta-analysis. Since the initial publication, we have incorporated RNA-seq datasets, compendia sharing, RESTful API support, and an additional meta-analysis method based on random effects. Here, we provide a step-by-step guide for using OMiCC.

For complete details on the use and execution of this protocol, please refer to Shah et al. (2016).

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OMiCC (OMics Compendia Commons) is a free web-based tool for gene expression data reuse

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Search publicly available studies to perform sample group comparisons to explore a disease

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In meta-analysis, multiple studies are combined to identify coherent signals

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OMiCC supports crowd-sharing and users can share their own analyses with the community

Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.

Peroxisome proliferator activated receptor-γ agonist pioglitazone improves vascular and metabolic dysfunction in systemic lupus erythematosus

OBJECTIVES

Premature cardiovascular events in systemic lupus erythematosus (SLE) contribute to morbidity and mortality, with no effective preventive strategies described to date. Immune dysregulation and metabolic disturbances appear to play prominent roles in the induction of vascular disease in SLE. The peroxisome proliferator activated receptor-gamma agonist pioglitazone (PGZ suppresses vascular damage and immune dysregulation in murine lupus and improves endothelial dysfunction in other inflammatory diseases. We hypothesised that PGZ could improve vascular dysfunction and cardiometabolic parameters in SLE.

METHODS

Eighty SLE subjects with mild to severe disease activity were randomised to a sequence of PGZ followed by placebo for 3 months, or vice versa, in a double-blind, cross-over design with a 2-month wash-out period. Primary endpoints were parameters of endothelial function and arterial inflammation, measured by multimodal assessments. Additional outcome measures of disease activity, neutrophil dysregulation, metabolic disturbances and gene expression studies were performed.

RESULTS

Seventy-two subjects completed the study. PGZ was associated with a significant reduction in Cardio-Ankle Vascular Index (a measure of arterial stiffness) compared with placebo. Various metabolic parameters improved with PGZ, including insulin resistance and lipoprotein profiles. Circulating neutrophil extracellular trap levels also significantly decreased with PGZ compared with placebo. Most adverse events experienced while on PGZ were mild and resolved with reduction in PGZ dose.

CONCLUSION

PGZ was well tolerated and induced significant improvement in vascular stiffness and cardiometabolic parameters in SLE. The results suggest that PGZ should be further explored as a modulator of cardiovascular disease risk in SLE.

TRIAL REGISTRATION NUMBER

NCT02338999.

Considering innate immune responses in SARS-CoV-2 infection and COVID-19

During the COVID-19 pandemic, much of the media focus has been on adaptive immunity, particularly antibody levels and memory T cells. However, immunologists have been striving to decipher how SARS-CoV-2 infection impacts our first line of defence, namely the innate immune system. In early 2022, Program staff from the NIAID at the NIH organized a workshop focusing on the innate immune response to SARS-CoV-2 infection and during COVID-19, which was chaired by Ralph Baric, Jenny Ting and John Lambris. Following the meeting, Nature Reviews Immunology invited some of the organizers and speakers to share their thoughts on the key discussion points.

Immunopathological signatures in multisystem inflammatory syndrome in children and pediatric COVID-19

Pediatric Coronavirus Disease 2019 (pCOVID-19) is rarely severe; however, a minority of children infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) might develop multisystem inflammatory syndrome in children (MIS-C), with substantial morbidity. In this longitudinal multi-institutional study, we applied multi-omics (analysis of soluble biomarkers, proteomics, single-cell gene expression and immune repertoire analysis) to profile children with COVID-19 (n = 110) and MIS-C (n = 76), along with pediatric healthy controls (pHCs; n = 76). pCOVID-19 was characterized by robust type I interferon (IFN) responses, whereas prominent type II IFN-dependent and NF-κB-dependent signatures, matrisome activation and increased levels of circulating spike protein were detected in MIS-C, with no correlation with SARS-CoV-2 PCR status around the time of admission. Transient expansion of TRBV11-2 T cell clonotypes in MIS-C was associated with signatures of inflammation and T cell activation. The association of MIS-C with the combination of HLA A*02, B*35 and C*04 alleles suggests genetic susceptibility. MIS-C B cells showed higher mutation load than pCOVID-19 and pHC. These results identify distinct immunopathological signatures in pCOVID-19 and MIS-C that might help better define the pathophysiology of these disorders and guide therapy.

Normalizing and denoising protein expression data from droplet-based single cell profiling

Multimodal single-cell profiling methods that measure protein expression with oligo-conjugated antibodies hold promise for comprehensive dissection of cellular heterogeneity, yet the resulting protein counts have substantial technical noise that can mask biological variations. Here we integrate experiments and computational analyses to reveal two major noise sources and develop a method called "dsb" (denoised and scaled by background) to normalize and denoise droplet-based protein expression data. We discover that protein-specific noise originates from unbound antibodies encapsulated during droplet generation; this noise can thus be accurately estimated and corrected by utilizing protein levels in empty droplets. We also find that isotype control antibodies and the background protein population average in each cell exhibit significant correlations across single cells, we thus use their shared variance to correct for cell-to-cell technical noise in each cell. We validate these findings by analyzing the performance of dsb in eight independent datasets spanning multiple technologies, including CITE-seq, ASAP-seq, and TEA-seq. Compared to existing normalization methods, our approach improves downstream analyses by better unmasking biologically meaningful cell populations. Our method is available as an open-source R package that interfaces easily with existing single cell software platforms such as Seurat, Bioconductor, and Scanpy and can be accessed at "dsb [ https://cran.r-project.org/package=dsb ]".

Robust, persistent adaptive immune responses to SARS-CoV-2 in the oropharyngeal lymphoid tissue of children

SARS-CoV-2 infection triggers adaptive immune responses from both T and B cells. However, most studies focus on peripheral blood, which may not fully reflect immune responses in lymphoid tissues at the site of infection. To evaluate both local and systemic adaptive immune responses to SARS-CoV-2, we collected peripheral blood, tonsils, and adenoids from 110 children undergoing tonsillectomy/adenoidectomy during the COVID-19 pandemic and found 24 with evidence of prior SARS-CoV-2 infection, including detectable neutralizing antibodies against multiple viral variants. We identified SARS-CoV-2-specific germinal center (GC) and memory B cells; single cell BCR sequencing showed that these virus-specific B cells were class-switched and somatically hypermutated, with overlapping clones in the adenoids and tonsils. Oropharyngeal tissues from COVID-19-convalescent children showed persistent expansion of GC and anti-viral lymphocyte populations associated with an IFN-γ-type response, with particularly prominent changes in the adenoids, as well as evidence of persistent viral RNA in both tonsil and adenoid tissues of many participants. Our results show robust, tissue-specific adaptive immune responses to SARS-CoV-2 in the upper respiratory tract of children weeks to months after acute infection, providing evidence of persistent localized immunity to this respiratory virus.

Pre-existing chromatin accessibility and gene expression differences among naive CD4+ T cells influence effector potential

CD4+ T cells have a remarkable potential to differentiate into diverse effector lineages following activation. Here, we probe the heterogeneity present among naive CD4+ T cells before encountering their cognate antigen to ask whether their effector potential is modulated by pre-existing transcriptional and chromatin landscape differences. Single-cell RNA sequencing shows that key drivers of variability are genes involved in T cell receptor (TCR) signaling. Using CD5 expression as a readout of the strength of tonic TCR interactions with self-peptide MHC, and sorting on the ends of this self-reactivity spectrum, we find that pre-existing transcriptional differences among naive CD4+ T cells impact follicular helper T (TFH) cell versus non-TFH effector lineage choice. Moreover, our data implicate TCR signal strength during thymic development in establishing differences in naive CD4+ T cell chromatin landscapes that ultimately shape their effector potential.

A local regulatory T cell feedback circuit maintains immune homeostasis by pruning self-activated T cells

A fraction of mature T cells can be activated by peripheral self-antigens, potentially eliciting host autoimmunity. We investigated homeostatic control of self-activated T cells within unperturbed tissue environments by combining high-resolution multiplexed and volumetric imaging with computational modeling. In lymph nodes, self-activated T cells produced interleukin (IL)-2, which enhanced local regulatory T cell (Treg) proliferation and inhibitory functionality. The resulting micro-domains reciprocally constrained inputs required for damaging effector responses, including CD28 co-stimulation and IL-2 signaling, constituting a negative feedback circuit. Due to these local constraints, self-activated T cells underwent transient clonal expansion, followed by rapid death ("pruning"). Computational simulations and experimental manipulations revealed the feedback machinery's quantitative limits: modest reductions in Treg micro-domain density or functionality produced non-linear breakdowns in control, enabling self-activated T cells to subvert pruning. This fine-tuned, paracrine feedback process not only enforces immune homeostasis but also establishes a sharp boundary between autoimmune and host-protective T cell responses.

Pre-vaccination and early B cell signatures predict antibody response to SARS-CoV-2 mRNA vaccine

SARS-CoV-2 mRNA vaccines are highly effective, although weak antibody responses are seen in some individuals with correlates of immunity that remain poorly understood. Here we longitudinally dissected antibody, plasmablast, and memory B cell (MBC) responses to the two-dose Moderna mRNA vaccine in SARS-CoV-2-uninfected adults. Robust, coordinated IgA and IgG antibody responses were preceded by bursts of spike-specific plasmablasts after both doses, but earlier and more intensely after dose two. Distinct antigen-specific MBC populations also emerged post-vaccination with varying kinetics. We identified antigen non-specific pre-vaccination MBC and post-vaccination plasmablasts after dose one and their spike-specific counterparts early after dose two that correlated with subsequent antibody levels. These baseline and response signatures can thus provide early indicators of serological efficacy and explain response variability in the population.

Immune dysregulation and autoreactivity correlate with disease severity in SARS-CoV-2-associated multisystem inflammatory syndrome in children

Multisystem inflammatory syndrome in children (MIS-C) is a life-threatening post-infectious complication occurring unpredictably weeks after mild or asymptomatic SARS-CoV-2 infection. We profiled MIS-C, adult COVID-19, and healthy pediatric and adult individuals using single-cell RNA sequencing, flow cytometry, antigen receptor repertoire analysis, and unbiased serum proteomics, which collectively identified a signature in MIS-C patients that correlated with disease severity. Despite having no evidence of active infection, MIS-C patients had elevated S100A-family alarmins and decreased antigen presentation signatures, indicative of myeloid dysfunction. MIS-C patients showed elevated expression of cytotoxicity genes in NK and CD8+ T cells and expansion of specific IgG-expressing plasmablasts. Clinically severe MIS-C patients displayed skewed memory T cell TCR repertoires and autoimmunity characterized by endothelium-reactive IgG. The alarmin, cytotoxicity, TCR repertoire, and plasmablast signatures we defined have potential for application in the clinic to better diagnose and potentially predict disease severity early in the course of MIS-C.

Post-infectious inflammatory disease in MIS-C features elevated cytotoxicity signatures and autoreactivity that correlates with severity

Multisystem inflammatory syndrome in children (MIS-C) is a life-threatening post-infectious complication occurring unpredictably weeks after mild or asymptomatic SARS-CoV2 infection in otherwise healthy children. Here, we define immune abnormalities in MIS-C compared to adult COVID-19 and pediatric/adult healthy controls using single-cell RNA sequencing, antigen receptor repertoire analysis, unbiased serum proteomics, and in vitro assays. Despite no evidence of active infection, we uncover elevated S100A-family alarmins in myeloid cells and marked enrichment of serum proteins that map to myeloid cells and pathways including cytokines, complement/coagulation, and fluid shear stress in MIS-C patients. Moreover, NK and CD8 T cell cytotoxicity genes are elevated, and plasmablasts harboring IgG1 and IgG3 are expanded. Consistently, we detect elevated binding of serum IgG from severe MIS-C patients to activated human cardiac microvascular endothelial cells in culture. Thus, we define immunopathology features of MIS-C with implications for predicting and managing this SARS-CoV2-induced critical illness in children.

Prevalence and pathogenicity of autoantibodies in patients with idiopathic CD4 lymphopenia

BACKGROUNDIdiopathic CD4 lymphopenia (ICL) is defined by persistently low CD4+ cell counts (<300 cells/μL) in the absence of a causal infection or immune deficiency and can manifest with opportunistic infections. Approximately 30% of ICL patients develop autoimmune disease. The prevalence and breadth of their autoantibodies, however, and their potential contribution to pathogenesis of ICL remain unclear.METHODSWe hybridized 34 and 51 ICL patients' sera to a 9,000-human-proteome array and to a 128-known-autoantigen array, respectively. Using a flow-based method, we characterized the presence of anti-lymphocyte Abs in the whole cohort of 72 patients, as well as the Ab functional capability of inducing Ab-dependent cell-mediated cytotoxicity (ADCC), complement deposition, and complement-dependent cytotoxicity (CDC). We tested ex vivo the activation of the classical complement pathway on ICL CD4+ T cells.RESULTSAll ICL patients had a multitude of autoantibodies mostly directed against private (not shared) targets and unrelated quantitatively or qualitatively to the patients' autoimmune disease status. The targets included lymphocyte intracellular and membrane antigens, confirmed by the detection by flow of IgM and IgG (mostly IgG1 and IgG4) anti-CD4+ cell Abs in 50% of the patients, with half of these cases triggering lysis of CD4+ T cells. We also detected in vivo classical complement activation on CD4+ T cells in 14% of the whole cohort.CONCLUSIONOur data demonstrate that a high prevalence of autoantibodies in ICL, some of which are specific for CD4+ T cells, may contribute to pathogenesis, and may represent a potentially novel therapeutic target.TRIAL REGISTRATIONClinicalTrials.gov NCT00867269.FUNDINGNIAID and National Institute of Arthritis and Musculoskeletal and Skin Diseases of the NIH.

Time-resolved systems immunology reveals a late juncture linked to fatal COVID-19

COVID-19 exhibits extensive patient-to-patient heterogeneity. To link immune response variation to disease severity and outcome over time, we longitudinally assessed circulating proteins as well as 188 surface protein markers, transcriptome, and T cell receptor sequence simultaneously in single peripheral immune cells from COVID-19 patients. Conditional-independence network analysis revealed primary correlates of disease severity, including gene expression signatures of apoptosis in plasmacytoid dendritic cells and attenuated inflammation but increased fatty acid metabolism in CD56^dimCD16^hi NK cells linked positively to circulating interleukin (IL)-15. CD8⁺ T cell activation was apparent without signs of exhaustion. Although cellular inflammation was depressed in severe patients early after hospitalization, it became elevated by days 17–23 post symptom onset, suggestive of a late wave of inflammatory responses. Furthermore, circulating protein trajectories at this time were divergent between and predictive of recovery versus fatal outcomes. Our findings stress the importance of timing in the analysis, clinical monitoring, and therapeutic intervention of COVID-19.

An immune-based biomarker signature is associated with mortality in COVID-19 patients

Immune and inflammatory responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) contribute to disease severity of coronavirus disease 2019 (COVID-19). However, the utility of specific immune-based biomarkers to predict clinical outcome remains elusive. Here, we analyzed levels of 66 soluble biomarkers in 175 Italian patients with COVID-19 ranging from mild/moderate to critical severity and assessed type I IFN-, type II IFN-, and NF-κB-dependent whole-blood transcriptional signatures. A broad inflammatory signature was observed, implicating activation of various immune and nonhematopoietic cell subsets. Discordance between IFN-α2a protein and IFNA2 transcript levels in blood suggests that type I IFNs during COVID-19 may be primarily produced by tissue-resident cells. Multivariable analysis of patients' first samples revealed 12 biomarkers (CCL2, IL-15, soluble ST2 [sST2], NGAL, sTNFRSF1A, ferritin, IL-6, S100A9, MMP-9, IL-2, sVEGFR1, IL-10) that when increased were independently associated with mortality. Multivariate analyses of longitudinal biomarker trajectories identified 8 of the aforementioned biomarkers (IL-15, IL-2, NGAL, CCL2, MMP-9, sTNFRSF1A, sST2, IL-10) and 2 additional biomarkers (lactoferrin, CXCL9) that were substantially associated with mortality when increased, while IL-1α was associated with mortality when decreased. Among these, sST2, sTNFRSF1A, IL-10, and IL-15 were consistently higher throughout the hospitalization in patients who died versus those who recovered, suggesting that these biomarkers may provide an early warning of eventual disease outcome.

Autoantibodies against type I IFNs in patients with life-threatening COVID-19

Interindividual clinical variability in the course of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is vast. We report that at least 101 of 987 patients with life-threatening coronavirus disease 2019 (COVID-19) pneumonia had neutralizing immunoglobulin G (IgG) autoantibodies (auto-Abs) against interferon-ω (IFN-ω) (13 patients), against the 13 types of IFN-α (36), or against both (52) at the onset of critical disease; a few also had auto-Abs against the other three type I IFNs. The auto-Abs neutralize the ability of the corresponding type I IFNs to block SARS-CoV-2 infection in vitro. These auto-Abs were not found in 663 individuals with asymptomatic or mild SARS-CoV-2 infection and were present in only 4 of 1227 healthy individuals. Patients with auto-Abs were aged 25 to 87 years and 95 of the 101 were men. A B cell autoimmune phenocopy of inborn errors of type I IFN immunity accounts for life-threatening COVID-19 pneumonia in at least 2.6% of women and 12.5% of men.

Porcine dermal collagen mesh (Permacol™) as a bioprosthesis in the ligation of intersphincteric tract (BioLIFT) procedure

BACKGROUND

Ligation of intersphincteric tract (LIFT) is a sphincter-saving technique used to treat anal fistulas. Incorporation of a bioprosthesis in LIFT (BioLIFT) aims to improve healing. The use of cross-linked porcine dermal collagen mesh Permacol™ in BioLIFT has never been investigated. The aim of this study was to compare the healing rates and outcome of LIFT and BioLIFT for complex anal fistulas using the Permacol™ biological mesh.

METHODS

A retrospective analysis of all patients having LIFT or BioLIFT for complex fistulas from January 2010 to November 2019 was performed in a tertiary referral centre. Patient data from a prospectively collected database of all patients having LIFT or BioLIFT were analyzed.

RESULTS

LIFT and BioLIFT were performed in 48 (82.8%) and 10 (17.2%) patients, respectively. All BioLIFT patients had previous interventions for their fistulas compared to 30 (62.5%) of patients who had LIFT, p = 0.023. The primary healing rate for LIFT was 87.5% (42/48) compared to 80% (8/10) in BioLIFT, (p = 0.42). Eight (13.8%) patients developed complications, 6 (12.5%) in the LIFT group vs 2 (20%) in the BioLIFT group (p = 0.62). On univariate analysis, the number of previous operations was predictive of complications (p = 0.03). BioLIFT was not associated with complication (OR = 1.75, 95% CI: 0.30-10.3, p = 0.54) or primary healing (OR = 0.57, 95% CI: 0.97-3.36, p = 0.54). There was no significant difference in recurrence (LIFT 12.5% vs BioLIFT 0%, p = 0.58). Kaplan-Meier analysis found no difference in time to recurrence between the two groups (p = 0.65).

CONCLUSION

Permacol™ mesh in BioLIFT is feasible and achieves a high primary healing rate of 80%. Prospective evidence is needed to establish the benefits of BioLIFT and determine whether Permacol™ is superior to the non-cross-linked porcine submucosal mesh.

Emergency surgery comparison of right versus left acute colonic diverticulitis: A 10-year outcome analysis

INTRODUCTION

The difference in outcome between right (RCD) and left colonic diverticulitis (LCD) is not well established. The aim of this study was to analyse the presentation and surgical outcome of RCD versus left-sided disease following emergency surgery.

METHOD

We conducted a retrospective review of patients presenting with acute diverticulitis over a 10-year period from 2004 to 2014 to a tertiary unit. Patient demographics, Hinchey classification, need for emergency surgery, perioperative outcome and recurrence were evaluated.

RESULTS

In total 360 patients presented with acute diverticulitis, 218 (61%) were right-sided and 142 (39%) were left-sided. The mean age (57 yrs vs 68 yrs) and median length of stay (4 days vs 5 days) were significantly less in RCD (p < 0.001). The need for emergency surgery was similar between RCD and LCD (30.7% vs 23.2%, p = 0.12). Sixty-seven (31%) patients with RCD required emergency surgery, 42 (62.7%) of these were based on a presumptive diagnosis of appendicitis and underwent laparoscopic appendicectomy only. Operative morbidity (10.4% vs 51.5%, p < 0.001) and mortality were significantly higher in LCD (1.5% v 15.2%, p = 0.007). Subgroup analysis of non-appendicectomy, RCD patients, showed LCD were more likely to require surgery (11.5% vs 23.2%, p = 0.003). There was no difference in recurrence (p = 0.6).

CONCLUSION

Right colonic diverticulitis patients are younger and disease course is more benign compared to LCD. Presentation can be confused with appendicitis without proper imaging. In the rare cases where emergency surgery is required, RCD is associated with a lower operative morbidity and mortality compared to left-sided disease.

Multimodal immune phenotyping of maternal peripheral blood in normal human pregnancy

Changes in maternal immunity during pregnancy can result in an altered immune state, and as a natural perturbation, this provides an opportunity to understand functional interactions of the immune system in vivo. We report characterization of maternal peripheral immune phenotypes for 33 longitudinally sampled normal pregnancies, using clinical measurements of complete blood counts and major immune cell populations, as well as high parameter flow cytometry for 30 leukocyte antigens characterizing 79 cell populations, and monitoring of 1305 serum proteins using the SomaLogic platform. Cellular analyses characterized transient changes in T cell polarization and more persistent alterations in T and B cell subset frequencies and activation. Serum proteomic analysis identified a potentially novel set of 7 proteins that are predictive of gestational age: DDR1, PLAU, MRC1, ACP5, ROBO2, IGF2R, and GNS. We further show that gestational age can be predicted from the parameters obtained by complete blood count tests and clinical flow cytometry characterizing 5 major immune cell populations. Inferring gestational age from this routine clinical phenotyping data could be useful in resource-limited settings that lack obstetric ultrasound. Overall, both the cellular and proteomic analyses validate previously reported phenotypic immunological changes of pregnancy and uncover potentially new alterations and predictive markers.

Improving Vaccine-Induced Immunity: Can Baseline Predict Outcome?

Immune signatures measured at baseline and immediately prior to vaccination may predict the immune response to vaccination. Such pre-vaccine assessment might allow not only population-based, but also more personalized vaccination strategies (‘precision vaccination’). If baseline immune signatures are predictive, the underlying mechanism they reflect may also determine vaccination outcome. Thus, baseline signatures might contribute to identifying interventional targets to be modulated prior to vaccination in order to improve vaccination responses. This concept has the potential to transform vaccination strategies and usher in a new approach to improve global health.

Extensive baseline variability in immune responses (e.g., antibody titers) among individuals in given populations is increasingly being appreciated as a major contributor to vaccine response heterogeneity.

The concept of ‘baseline may predict outcome’ has recently been reported for human influenza virus, yellow fever virus, and hepatitis B virus, as well as malaria vaccination. This concept might also apply to other vaccines.

The ability to predict who might respond to immunization (and to what extent) might offer avenues for optimization of current vaccination strategies.

We posit that this simple concept might be useful and significant for vaccine design: if ‘baseline determines outcome, then altering baseline prior to vaccination could alter outcome’.

This approach could potentially lead to tailored (precision) vaccines ensuring that the majority, or all individuals vaccinated, respond by eliciting a protective immune response (i.e., devoid of non-responder individuals). Presumably, this approach might also allow the administration of fewer vaccine doses, potentially arriving at one vaccine dose only.

Cancer prognosis with shallow tumor RNA sequencing

Disrupted molecular pathways are often robustly associated with disease outcome in cancer^1-3. Although biologically informative transcriptional pathways can be revealed by RNA sequencing (RNA-seq) at up to hundreds of folds reduction in conventionally used coverage^4-6, it remains unknown how low-depth sequencing datasets perform in the challenging context of developing transcriptional signatures to predict clinical outcomes. Here we assessed the possibility of cancer prognosis with shallow tumor RNA-seq, which would potentially enable cost-effective assessment of much larger numbers of samples for deeper biological and predictive insights. By statistically modeling the relative risk of an adverse outcome for thousands of subjects in The Cancer Genome Atlas^7-13, we present evidence that subsampled tumor RNA-seq data with a few hundred thousand reads per sample provide sufficient information for outcome prediction in several types of cancer. Analysis of predictive models revealed robust contributions from pathways known to be associated with outcomes. Our findings indicate that predictive models of outcomes in cancer may be developed with dramatically increases in sample numbers at low cost, thus potentially enabling the development of more realistic predictive models that incorporate diverse variables and their interactions. This strategy could also be used, for example, in longitudinal analysis of multiple regions of a tumor alongside treatment for quantitative modeling and prediction of outcome in personalized oncology.

Differential Expression of the Transcription Factor GATA3 Specifies Lineage and Functions of Innate Lymphoid Cells

Lymphoid tissue inducer (LTi) cells are regarded as a subset of innate lymphoid cells (ILCs). However, these cells are not derived from the ILC common progenitor, which generates other ILC subsets and is defined by the expression of the transcription factor PLZF. Here, we examined transcription factor(s) determining the fate of LTi progenitors versus non-LTi ILC progenitors. Conditional deletion of Gata3 resulted in the loss of PLZF⁺ non-LTi progenitors but not the LTi progenitors that expressed the transcription factor RORγt. Consistently, PLZF⁺ non-LTi progenitors expressed high amounts of GATA3, whereas GATA3 expression was low in RORγt⁺ LTi progenitors. The generation of both progenitors required the transcriptional regulator Id2, which defines the common helper-like innate lymphoid progenitor (ChILP), but not cytokine signaling. Nevertheless, low GATA3 expression was necessary for the generation of functionally mature LTi cells. Thus, differential expression of GATA3 determines the fates and functions of distinct ILC progenitors.

Overexpression of T-bet in HIV infection is associated with accumulation of B cells outside germinal centers and poor affinity maturation

Nearly all chronic human infections are associated with alterations in the memory B cell (MBC) compartment, including a large expansion of CD19hiT-bethi MBC in the peripheral blood of HIV-infected individuals with chronic viremia. Despite their prevalence, it is unclear how these B cells arise and whether they contribute to the inefficiency of antibody-mediated immunity in chronic infectious diseases. We addressed these questions by characterizing T-bet-expressing B cells in lymph nodes (LN) and identifying a strong T-bet signature among HIV-specific MBC associated with poor immunologic outcome. Confocal microscopy and quantitative imaging revealed that T-bethi B cells in LN of HIV-infected chronically viremic individuals distinctly accumulated outside germinal centers (GC), which are critical for optimal antibody responses. In single-cell analyses, LN T-bethi B cells of HIV-infected individuals were almost exclusively found among CD19hi MBC and expressed reduced GC-homing receptors. Furthermore, HIV-specific B cells of infected individuals were enriched among LN CD19hiT-bethi MBC and displayed a distinct transcriptome, with features similar to CD19hiT-bethi MBC in blood and LN GC B cells (GCBC). LN CD19hiT-bethi MBC were also related to GCBC by B cell receptor (BCR)-based phylogenetic linkage but had lower BCR mutation frequencies and reduced HIV-neutralizing capacity, consistent with diminished participation in GC-mediated affinity selection. Thus, in the setting of chronic immune activation associated with HIV viremia, failure of HIV-specific B cells to enter or remain in GC may help explain the rarity of high-affinity protective antibodies.

IFN-mediated negative feedback supports bacteria class-specific macrophage inflammatory responses

Despite existing evidence for tuning of innate immunity to different classes of bacteria, the molecular mechanisms used by macrophages to tailor inflammatory responses to specific pathogens remain incompletely defined. By stimulating mouse macrophages with a titration matrix of TLR ligand pairs, we identified distinct stimulus requirements for activating and inhibitory events that evoked diverse cytokine production dynamics. These regulatory events were linked to patterns of inflammatory responses that distinguished between Gram-positive and Gram-negative bacteria, both in vitro and after in vivo lung infection. Stimulation beyond a TLR4 threshold and Gram-negative bacteria-induced responses were characterized by a rapid type I IFN-dependent decline in inflammatory cytokine production, independent of IL-10, whereas inflammatory responses to Gram-positive species were more sustained due to the absence of this IFN-dependent regulation. Thus, disparate triggering of a cytokine negative feedback loop promotes tuning of macrophage responses in a bacteria class-specific manner and provides context-dependent regulation of inflammation dynamics.

ImmuneRegulation: a web-based tool for identifying human immune regulatory elements

Humans vary considerably both in their baseline and activated immune phenotypes. We developed a user-friendly open-access web portal, ImmuneRegulation, that enables users to interactively explore immune regulatory elements that drive cell-type or cohort-specific gene expression levels. ImmuneRegulation currently provides the largest centrally integrated resource on human transcriptome regulation across whole blood and blood cell types, including (i) ∼43,000 genotyped individuals with associated gene expression data from ∼51,000 experiments, yielding genetic variant-gene expression associations on ∼220 million eQTLs; (ii) 14 million transcription factor (TF)-binding region hits extracted from 1945 ChIP-seq studies; and (iii) the latest GWAS catalog with 67,230 published variant-trait associations. Users can interactively explore associations between queried gene(s) and their regulators (cis-eQTLs, trans-eQTLs or TFs) across multiple cohorts and studies. These regulators may explain genotype-dependent gene expression variations and be critical in selecting the ideal cohorts or cell types for follow-up studies or in developing predictive models. Overall, ImmuneRegulation significantly lowers the barriers between complex immune regulation data and researchers who want rapid, intuitive and high-quality access to the effects of regulatory elements on gene expression in multiple studies to empower investigators in translating these rich data into biological insights and clinical applications, and is freely available at https://immuneregulation.mssm.edu.

eNetXplorer: an R package for the quantitative exploration of elastic net families for generalized linear models

Background

Regularized generalized linear models (GLMs) are popular regression methods in bioinformatics, particularly useful in scenarios with fewer observations than parameters/features or when many of the features are correlated. In both ridge and lasso regularization, feature shrinkage is controlled by a penalty parameter λ. The elastic net introduces a mixing parameter α to tune the shrinkage continuously from ridge to lasso. Selecting α objectively and determining which features contributed significantly to prediction after model fitting remain a practical challenge given the paucity of available software to evaluate performance and statistical significance.

Results

eNetXplorer builds on top of glmnet to address the above issues for linear (Gaussian), binomial (logistic), and multinomial GLMs. It provides new functionalities to empower practical applications by using a cross validation framework that assesses the predictive performance and statistical significance of a family of elastic net models (as α is varied) and of the corresponding features that contribute to prediction. The user can select which quality metrics to use to quantify the concordance between predicted and observed values, with defaults provided for each GLM. Statistical significance for each model (as defined by α) is determined based on comparison to a set of null models generated by random permutations of the response; the same permutation-based approach is used to evaluate the significance of individual features. In the analysis of large and complex biological datasets, such as transcriptomic and proteomic data, eNetXplorer provides summary statistics, output tables, and visualizations to help assess which subset(s) of features have predictive value for a set of response measurements, and to what extent those subset(s) of features can be expanded or reduced via regularization.

Conclusions

This package presents a framework and software for exploratory data analysis and visualization. By making regularized GLMs more accessible and interpretable, eNetXplorer guides the process to generate hypotheses based on features significantly associated with biological phenotypes of interest, e.g. to identify biomarkers for therapeutic responsiveness. eNetXplorer is also generally applicable to any research area that may benefit from predictive modeling and feature identification using regularized GLMs. The package is available under GPL-3 license at the CRAN repository, https://CRAN.R-project.org/package=eNetXplorer.

Electronic supplementary material

The online version of this article (10.1186/s12859-019-2778-5) contains supplementary material, which is available to authorized users.

Resident Macrophages Cloak Tissue Microlesions to Prevent Neutrophil-Driven Inflammatory Damage

Neutrophils are attracted to and generate dense swarms at sites of cell damage in diverse tissues, often extending the local disruption of organ architecture produced by the initial insult. Whether the inflammatory damage resulting from such neutrophil accumulation is an inescapable consequence of parenchymal cell death has not been explored. Using a combination of dynamic intravital imaging and confocal multiplex microscopy, we report here that tissue-resident macrophages rapidly sense the death of individual cells and extend membrane processes that sequester the damage, a process that prevents initiation of the feedforward chemoattractant signaling cascade that results in neutrophil swarms. Through this "cloaking" mechanism, the resident macrophages prevent neutrophil-mediated inflammatory damage, maintaining tissue homeostasis in the face of local cell injury that occurs on a regular basis in many organs because of mechanical and other stresses. VIDEO ABSTRACT.

Immune regulation by glucocorticoids can be linked to cell type-dependent transcriptional responses

A functional genomics approach uncovers previously undescribed cell type–dependent responses that can be linked to the immunoregulatory actions of glucocorticoids in humans.

Glucocorticoids remain the most widely used immunosuppressive and anti-inflammatory drugs, yet substantial gaps exist in our understanding of glucocorticoid-mediated immunoregulation. To address this, we generated a pathway-level map of the transcriptional effects of glucocorticoids on nine primary human cell types. This analysis revealed that the response to glucocorticoids is highly cell type dependent, in terms of the individual genes and pathways affected, as well as the magnitude and direction of transcriptional regulation. Based on these data and given their importance in autoimmunity, we conducted functional studies with B cells. We found that glucocorticoids impair upstream B cell receptor and Toll-like receptor 7 signaling, reduce transcriptional output from the three immunoglobulin loci, and promote significant up-regulation of the genes encoding the immunomodulatory cytokine IL-10 and the terminal-differentiation factor BLIMP-1. These findings provide new mechanistic understanding of glucocorticoid action and emphasize the multifactorial, cell-specific effects of these drugs, with potential implications for designing more selective immunoregulatory therapies.

Immune regulation by glucocorticoids can be linked to cell-lineage-specific transcriptional responses

Glucocorticoids remain the most widely used class of immunosuppressive and anti-inflammatory drugs, yet significant gaps exist in our understanding of glucocorticoid-mediated immunoregulation. We have studied the transcriptional response to glucocorticoids, by total RNA sequencing and small-RNA sequencing, in nine human primary cell populations: B cells, CD4+ T cells, monocytes, neutrophils, endothelial cells, myoblasts, osteoblasts, fibroblasts, and preadipocytes. Our results suggest that the human response to glucocorticoids displays cell-lineage dependency, in terms of the individual genes and pathways that are differentially affected, as well as the magnitude and direction of transcriptional regulation. While decreased expression of genes that function in critical immune pathways is widespread, increased expression of negative regulators of immune activation is also common. Despite the critical role of B cells in many diseases for which glucocorticoids are used, glucocorticoid effects on human B cells are particularly poorly understood. We have identified significant transcriptional and functional changes in key molecules involved in B cell receptor signaling, intracellular Toll-like receptor signaling, B cell activation, differentiation, and antibody production. We have validated these results at the RNA and protein levels in vivo, by assaying B cells isolated from healthy human volunteers given a single intravenous dose of a glucocorticoid. Overall, our results illustrate the ability of an unbiased, genome-wide approach to uncover previously undescribed, cell-type-dependent transcriptional responses that can be linked to the immunoregulatory actions of glucocorticoids in humans.

Transcriptional Response of Respiratory Epithelium to Nontuberculous Mycobacteria

The incidence of pulmonary nontuberculous mycobacteria (NTM) disease is increasing, but host responses in respiratory epithelium infected with NTM are not fully understood. In this work, we aimed to identify infection-relevant gene expression signatures of NTM infection of the respiratory epithelium. We infected air-liquid interface (ALI) primary respiratory epithelial cell cultures with Mycobacterium avium subsp. avium (MAC) or Mycobacterium abscessus subsp. abscessus (MAB). We used cells from four different donors to obtain generalizable data. Differentiated respiratory epithelial cells at the ALI were infected with MAC or MAB at a multiplicity of infection of 100:1 or 1,000:1, and RNA sequencing was performed at Days 1 and 3 after infection. In response to infection, we found down-regulation of ciliary genes but upregulation of genes associated with cytokines/chemokines, such as IL-32, and cholesterol biosynthesis. Inflammatory response genes tended to be more upregulated by MAB than by MAC infection. Primary respiratory epithelial cell infection with NTM at the ALI identified ciliary function, cholesterol biosynthesis, and cytokine/chemokine production as major host responses to infection. Some of these pathways may be amenable to therapeutic manipulation.

Systematic Analysis of Cell-to-Cell Expression Variation of T Lymphocytes in a Human Cohort Identifies Aging and Genetic Associations

Cell-to-cell expression variation (CEV) is a prevalent feature of even well-defined cell populations, but its functions, particularly at the organismal level, are not well understood. Using single-cell data obtained via high-dimensional flow cytometry of T cells as a model, we introduce an analysis framework for quantifying CEV in primary cell populations and studying its functional associations in human cohorts. Analyses of 840 CEV phenotypes spanning multiple baseline measurements of 14 proteins in 28 T cell subpopulations suggest that the quantitative extent of CEV can exhibit substantial subject-to-subject differences and yet remain stable within healthy individuals over months. We linked CEV to age and disease-associated genetic polymorphisms, thus implicating CEV as a biomarker of aging and disease susceptibility and suggesting that it might play an important role in health and disease. Our dataset, interactive figures, and software for computing CEV with flow cytometry data provide a resource for exploring CEV functions.

Role of hepatic trisectionectomy in advanced hepatocellular carcinoma

BACKGROUND

Advanced hepatocellular carcinoma (HCC) with underlying cirrhosis poses a major operative challenge. Patients have a dismal prognosis without curative resection. The role of hepatic trisectionectomy in these patients is not established. The aim of this study was to analyze and compare the perioperative outcome and prognosis of patients undergoing trisectionectomy with hepatic resection of a lesser extent.

METHODS

From 2000 to 2014, 48 patients underwent hepatic trisectionectomy for HCC with background cirrhosis or chronic hepatitis (Group A). Another (Group B) 520 patients underwent liver resection of a lesser extent. Patient demographics, clinicopathological data, perioperative outcome and long-term survival were compared between the 2 groups.

RESULTS

Intraoperative bloodloss, operating time and total hospital stay were significantly higher in trisectionectomy patients. Tumors were larger and more advanced in group A. The morbidity rate was 43.8% in group A compared to 27.5% in group B, p = 0.027. In-hospital mortality was 6.3% for group A. Group A had a significantly shorter time to recurrence (4.5months vs 6.2months, p = 0.036), as well as a poorer disease-free survival (DFS) than group B (6.3 months vs 15.7 months, p = 0.02). Overall survival was comparable. Tumor number, size, albumin, INR, microvascular invasions and positive resection margins were predictors of disease-free survival.

CONCLUSION

Hepatic trisectionectomy may be associated with a higher morbidity and lower DFS. However, these patients would not be suitable candidates for ablative therapy or liver transplantation. With careful patient selection and meticulous surgical technique, trisectionectomy is feasible and gives these patients the only hope of cure.

Appropriate timing for surgery after neoadjuvant chemoradiation for esophageal cancer

Optimal interval between neoadjuvant chemoradiotherapy (CRT) and surgery is not elucidated for esophageal squamous carcinoma. The aim of this study is to evaluate the impact of this time interval on patient outcome. Patients treated with neoadjuvant CRT followed by surgery between 2002 and 2009 were analyzed. Patients were divided into two groups based on the median interval to surgery (64 days): A </= 64 days (n = 54) and B > 64 days (n = 53). A second analysis was performed by re-classifying patients into three interval groups: A* ≤ 40 days (n = 16); B* 41-80 days (n = 60); C* > 80 days (n = 31). Operative outcome, pathological data, and long-term survival were analyzed. One hundred and seven (n = 107) patients were analyzed. Five patients (9.4%) in group B had an anastomotic leak compared with no leakage from group A (P < 0.021). The complete pathological response was comparable in groups A and B (35% vs. 24.5%, p = 0.23). R0 was significantly lower in group A* (A*: 56.3%, B*: 90%, C*: 74.2%, P = 0.006). In patients with R0 resection, 5-year survival was significantly better in group A than B (71.7% vs. 51%, P = 0.032) and in group A* (A* 100% vs. B* 60.2% & C* 48.3%; A* vs. B*, P = 0.036; A* vs. C*, P = 0.019). Complete pathological response was an independent predictor of survival. Early surgery with R0 resection following neoadjuvant CRT may lead to a better outcome. Further prospective studies are still necessary to provide better insight into the issue. At present, timing of surgery should be individualized and performed at the earliest opportunity.

Combining gene expression data from inflamed tissue and machine learning for blood biomarker discovery

Inflammation is common in virtually all diseases. Since immune cells travel through the blood to inflamed tissues, peripheral blood reflects inflammation at distant sites. However, blood biomarkers are hard to detect in global gene expression data since blood is not the site of perturbation and statistical corrections for multiple testing reduce sensitivity. We hypothesized that combining transcriptional signatures from inflamed tissue and machine learning would be useful to derive blood biomarkers. We first tested this in the mouse model of influenza infection. We identified a set of early genes in the lungs associated with lethality after infection. We then tested their differential abundance early in the blood of mice infected with a range of influenza doses. We applied elastic net to build a biomarker able to predict disease outcome (4 classes: early lethal, late lethal, non-lethal vs. non-infected; accuracy on training and validation sets: 91% and 79%). We next confirmed our hypothesis in lung cancer and breast cancer in humans. We identified sets of genes associated with tumors but not with tumor-free tissues and tested their differential abundance in the blood of patients compared to healthy controls. Using elastic net, we built two blood biomarkers to classify subjects according to disease status (case vs. control; accuracy on training and validation sets in breast cancer: 92% and 67%; in lung cancer: 89% and 78%). In conclusion, combining inflamed tissue signatures and machine learning, we were able to derive blood biomarkers for three different diseases in two different species. We expect that this novel strategy can be applied in other diseases as well.

This work was supported by the Intramural Research Program of NIAID, NIH.