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Abstract Post-acute sequelae of SARS-CoV-2 (PASC) is a significant public health concern. We describe Patient Reported Outcomes (PROs) on 590 participants prospectively assessed from hospital admission for COVID-19 through one year after discharge. Modeling identified 4 PRO clusters based on reported deficits (minimal, physical, mental/cognitive, and multidomain), supporting heterogenous clinical presentations in PASC, with sub-phenotypes associated with female sex and distinctive comorbidities. During the acute phase of disease, a higher respiratory SARS-CoV-2 viral burden and lower Receptor Binding Domain and Spike antibody titers were associated with both the physical predominant and the multidomain deficit clusters. A lower frequency of circulating B lymphocytes by mass cytometry (CyTOF) was observed in the multidomain deficit cluster. Circulating fibroblast growth factor 21 (FGF21) was significantly elevated in the mental/cognitive predominant and the multidomain clusters. Future efforts to link PASC to acute anti-viral host responses may help to better target treatment and prevention of PASC.

Abstract Many deep learning-based methods have been proposed to handle complex single-cell data. Deep learning approaches may also prove useful to jointly analyze single-cell RNA sequencing (scRNA-seq) and single-cell T cell receptor sequencing (scTCR-seq) data for novel discoveries. We developed scNAT, a deep learning method that integrates paired scRNA-seq and scTCR-seq data to represent data in a unified latent space for downstream analysis. We demonstrate that scNAT is capable of removing batch effects, and identifying cell clusters and a T cell migration trajectory from blood to cerebrospinal fluid in multiple sclerosis.

Summary: Infection with West Nile virus (WNV) drives a wide range of responses, from asymptomatic to flu-like symptoms/fever or severe cases of encephalitis and death. To identify cellular and molecular signatures distinguishing WNV severity, we employed systems profiling of peripheral blood from asymptomatic and severely ill individuals infected with WNV. We interrogated immune responses longitudinally from acute infection through convalescence employing single-cell protein and transcriptional profiling complemented with matched serum proteomics and metabolomics as well as multi-omics analysis. At the acute time point, we detected both elevation of pro-inflammatory markers in innate immune cell types and reduction of regulatory T cell activity in participants with severe infection, whereas asymptomatic donors had higher expression of genes associated with anti-inflammatory CD16+ monocytes. Therefore, we demonstrated the potential of systems immunology using multiple cell-type and cell-state-specific analyses to identify correlates of infection severity and host cellular activity contributing to an effective anti-viral response.

BACKGROUND While B cell depletion is associated with attenuated antibody responses to SARS-CoV-2 mRNA vaccination, responses vary among individuals. Thus, elucidating the factors that affect immune responses after repeated vaccination is an important clinical need.METHODS We evaluated the quality and magnitude of the T cell, B cell, antibody, and cytokine responses to a third dose of BNT162b2 or mRNA-1273 mRNA vaccine in patients with B cell depletion.RESULTS In contrast with control individuals (n = 10), most patients on anti-CD20 therapy (n = 48) did not demonstrate an increase in spike-specific B cells or antibodies after a third dose of vaccine. A third vaccine elicited significantly increased frequencies of spike-specific non-naive T cells. A small subset of B cell–depleted individuals effectively produced spike-specific antibodies, and logistic regression models identified time since last anti-CD20 treatment and lower cumulative exposure to anti-CD20 mAbs as predictors of those having a serologic response. B cell–depleted patients who mounted an antibody response to 3 vaccine doses had persistent humoral immunity 6 months later.CONCLUSION These results demonstrate that serial vaccination strategies can be effective for a subset of B cell–depleted patients.FUNDING The NIH (R25 NS079193, P01 AI073748, U24 AI11867, R01 AI22220, UM 1HG009390, P01 AI039671, P50 CA121974, R01 CA227473, U01CA260507, 75N93019C00065, K24 AG042489), NIH HIPC Consortium (U19 AI089992), the National Multiple Sclerosis Society (CA 1061-A-18, RG-1802-30153), the Nancy Taylor Foundation for Chronic Diseases, Erase MS, the Robert Leet and Clara Guthrie Patterson Trust, and the Claude D. Pepper Older Americans Independence Center at Yale (P30 AG21342).

As part of a biomarker discovery effort in peripheral blood, we acquired an immunological profile of cell-surface markers from healthy control and untreated subjects with relapsing–remitting MS (RRMS). Fresh blood from each subject was screened ex vivo using a panel of 50 fluorescently labelled monoclonal antibodies distributed amongst 56 pools of four antibodies each. From these 56 pools, we derived an immunological profile consisting of 1018 ‘features’ for each subject in our analysis using a systematic gating strategy. These profiles were interrogated in an analysis with a screening phase (23 patients) and an extension phase (15 patients) to identify cell populations in peripheral blood whose frequency is altered in untreated RRMS subjects. A population of CD8lowCD4− cells was identified as being reduced in frequency in untreated RRMS subjects (P = 0.0002), and this observation was confirmed in an independent sample of subjects from the Comprehensive Longitudinal Investigation of MS at the Brigham & Womens Hospital (P = 0.002). This reduction in the frequency of CD8lowCD4− cells is also observed in 38 untreated subjects with a clinically isolated demyelination syndrome (CIS) (P = 0.0006). We also show that these differences may be due to a reduction in the CD8lowCD56࠽−CD4− subset of CD8low cells, which have a natural killer cell profile. Similarities between untreated CIS and RRMS subjects extend to broader immunological profiles: consensus clustering of our data suggests that there are three distinct populations of untreated RRMS subjects and that these distinct phenotypic categories are already present in our sample of untreated CIS subjects. Thus, our large-scale immunophenotyping approach has yielded robust evidence for a reduction of CD8lowCD4− cells in both CIS and RRMS in the absence of treatment as well as suggestive evidence for the existence of immunologically distinct subsets of subjects with a demyelinating disease. [ABSTRACT FROM AUTHOR]

Maintenance of peripheral tolerance by CD4+Foxp3+ regulatory T cells (Tregs) is essential for regulating autoreactive T cells. The loss of function of Foxp3 leads to autoimmune disease in both animals and humans. An example is the rare, X-linked recessive disorder known as IPEX (Immune Dysregulation, Polyendocrinopathy, Enteropathy X-linked) syndrome. In more common human autoimmune diseases, defects in Treg function are accompanied with aberrant effector cytokines such as IFNγ. It has recently become appreciated that Tregs plays an important role in not only maintaining immune homeostasis but also in establishing the tissue microenvironment and homeostasis of non-lymphoid tissues. Tissue resident Tregs show profiles that are unique to their local environments which are composed of both immune and non-immune cells. Core tissue-residence gene signatures are shared across different tissue Tregs and are crucial to homeostatic regulation and maintaining the tissue Treg pool in a steady state. Through interaction with immunocytes and non-immunocytes, tissue Tregs exert a suppressive function via conventional ways involving contact dependent and independent processes. In addition, tissue resident Tregs communicate with other tissue resident cells which allows Tregs to adopt to their local microenvironment. These bidirectional interactions are dependent on the specific tissue environment. Here, we summarize the recent advancements of tissue Treg studies in both human and mice, and discuss the molecular mechanisms that maintain tissue homeostasis and prevent pathogenesis.

B cell depletion in patients with relapsing-remitting multiple sclerosis (RRMS) markedly prevents new MRI-detected lesions and disease activity, suggesting the hypothesis that altered B cell function leads to the activation of T cells driving disease pathogenesis. Here, we performed comprehensive analyses of CD40 ligand– (CD40L-) and IL-21–stimulated memory B cells from patients with MS and healthy age-matched controls, modeling the help of follicular helper T cells (Tfh cells), and found a differential gene expression signature in multiple B cell pathways. Most striking was the impaired TIGIT expression on MS-derived B cells mediated by dysregulation of the transcription factor TCF4. Activated circulating Tfh cells (cTfh cells) expressed CD155, the ligand of TIGIT, and TIGIT on B cells revealed their capacity to suppress the proliferation of IL-17–producing cTfh cells via the TIGIT/CD155 axis. Finally, CCR6+ cTfh cells were significantly increased in patients with MS, and their frequency was inversely correlated with that of TIGIT+ B cells. Together, these data suggest that the dysregulation of negative feedback loops between TIGIT+ memory B cells and cTfh cells in MS drives the activated immune system in this disease.

Summary: Background: Better understanding of the association between characteristics of patients hospitalized with coronavirus disease 2019 (COVID-19) and outcome is needed to further improve upon patient management. Methods: Immunophenotyping Assessment in a COVID-19 Cohort (IMPACC) is a prospective, observational study of 1164 patients from 20 hospitals across the United States. Disease severity was assessed using a 7-point ordinal scale based on degree of respiratory illness. Patients were prospectively surveyed for 1 year after discharge for post-acute sequalae of COVID-19 (PASC) through quarterly surveys. Demographics, comorbidities, radiographic findings, clinical laboratory values, SARS-CoV-2 PCR and serology were captured over a 28-day period. Multivariable logistic regression was performed. Findings: The median age was 59 years (interquartile range [IQR] 20); 711 (61%) were men; overall mortality was 14%, and 228 (20%) required invasive mechanical ventilation. Unsupervised clustering of ordinal score over time revealed distinct disease course trajectories. Risk factors associated with prolonged hospitalization or death by day 28 included age ≥ 65 years (odds ratio [OR], 2.01; 95% CI 1.28–3.17), Hispanic ethnicity (OR, 1.71; 95% CI 1.13–2.57), elevated baseline creatinine (OR 2.80; 95% CI 1.63– 4.80) or troponin (OR 1.89; 95% 1.03–3.47), baseline lymphopenia (OR 2.19; 95% CI 1.61–2.97), presence of infiltrate by chest imaging (OR 3.16; 95% CI 1.96–5.10), and high SARS-CoV2 viral load (OR 1.53; 95% CI 1.17–2.00). Fatal cases had the lowest ratio of SARS-CoV-2 antibody to viral load levels compared to other trajectories over time (p=0.001). 589 survivors (51%) completed at least one survey at follow-up with 305 (52%) having at least one symptom consistent with PASC, most commonly dyspnea (56% among symptomatic patients). Female sex was the only associated risk factor for PASC. Interpretation: Integration of PCR cycle threshold, and antibody values with demographics, comorbidities, and laboratory/radiographic findings identified risk factors for 28-day outcome severity, though only female sex was associated with PASC. Longitudinal clinical phenotyping offers important insights, and provides a framework for immunophenotyping for acute and long COVID-19. Funding: NIH.

For over a decade the term “Big data” has been used to describe the rapid increase in volume, variety and velocity of information available, not just in medical research but in almost every aspect of our lives. As scientists, we now have the capacity to rapidly generate, store and analyse data that, only a few years ago, would have taken many years to compile. However, “Big data” no longer means what it once did. The term has expanded and now refers not to just large data volume, but to our increasing ability to analyse and interpret those data. Tautologies such as “data analytics” and “data science” have emerged to describe approaches to the volume of available information as it grows ever larger. New methods dedicated to improving data collection, storage, cleaning, processing and interpretation continue to be developed, although not always by, or for, medical researchers. Exploiting new tools to extract meaning from large volume information has the potential to drive real change in clinical practice, from personalized therapy and intelligent drug design to population screening and electronic health record mining. As ever, where new technology promises “Big Advances,” significant challenges remain. Here we discuss both the opportunities and challenges posed to biomedical research by our increasing ability to tackle large datasets. Important challenges include the need for standardization of data content, format, and clinical definitions, a heightened need for collaborative networks with sharing of both data and expertise and, perhaps most importantly, a need to reconsider how and when analytic methodology is taught to medical researchers. We also set “Big data” analytics in context: recent advances may appear to promise a revolution, sweeping away conventional approaches to medical science. However, their real promise lies in their synergy with, not replacement of, classical hypothesis-driven methods. The generation of novel, data-driven hypotheses based on interpretable models will always require stringent validation and experimental testing. Thus, hypothesis-generating research founded on large datasets adds to, rather than replaces, traditional hypothesis driven science. Each can benefit from the other and it is through using both that we can improve clinical practice.

The central nervous system (CNS) of patients with multiple sclerosis (MS) is the site where disease pathology is evident. Damaged CNS tissue is commonly associated with immune cell infiltration. This infiltrate often includes B cells that are found in multiple locations throughout the CNS, including the cerebrospinal fluid (CSF), parenchyma and the meninges, frequently forming tertiary lymphoid structures in the latter. Several groups, including our own, have shown that B cells from distinct locations within the MS CNS are clonally related and display the characteristics of an antigen-driven response. However, the antigen(s) driving this response have yet to be conclusively defined. To explore the antigen specificity of the MS B cell response, we produced recombinant human immunoglobulin (rIgG) from a series of expanded B cell clones that we isolated from the CNS tissue of six MS brains. The specificity of these MS-derived rIgG and control rIgG derived from non-MS tissues was then examined using multiple methodologies that included testing individual candidate antigens, screening with high-throughput antigen arrays and evaluating binding to CNS-derived cell lines. We report that while several MS-derived rIgG recognized particular antigens, including neurofilament light and a protocadherin isoform, none were unique to MS, as non-MS-derived rIgG used as controls invariably displayed similar binding specificities. We conclude that while MS CNS resident B cells display the characteristics of an antigen-driven B cell response, the antigen(s) driving this response remain at large.

Genome-wide association studies have revealed a large number of genetic associations with autoimmune diseases. Despite this progress, the mechanisms underlying the contribution of allelic variants to the onset of immune-related diseases remain mostly unknown. Our recent meta-analysis of genome-wide association studies of multiple sclerosis (MS) identified a new susceptibility locus tagged by a single nucleotide polymorphism, rs17824933 (p = 3.8 x 10-9), that is found in a block of linkage disequilibrium containing the CD6 gene. Because CD6 plays an important role in maintenance of T cell activation and proliferation, we examined the biologic phenotypes of the risk-associated allele. In this article, we report that the MS susceptibility allele in CD6 is associated with decreased expression of full-length CD6 in CD4+ and CD8+ T cells. As a consequence, proliferation is diminished during long-term activation of CD4+ T cells from subjects with the risk allele. Selective knockdown of full-length CD6 using exon 5-specific small interfering RNA induces a similar proliferation defect of CD4+ T cells from subjects homozygous for the protective allele. Exon 5 encodes for the extracellular binding site of the CD6 ligand ALCAM, which is required for CD6 stimulation. In CD4+ T cells from subjects with the risk allele, exon 5 is consistently underexpressed, thereby providing a mechanism by which the allele affects proliferation of CD4+ T cells. These findings indicate that the MS risk allele in the CD6 locus is associated with altered proliferation of CD4+ T cells and demonstrate the influence of a disease-related allelic variant on important immunological characteristics. [ABSTRACT FROM AUTHOR]

CD4+ T helper 1 (TH1) cells are important mediators of inflammation and are regulated by numerous pathways, including the negative immune receptor Tim-3. We found that Tim-3 is constitutively expressed on cells of the innate immune system in both mice and humans, and that it can synergize with Toll-like receptors. Moreover, an antibody agonist of Tim-3 acted as an adjuvant during induced immune responses, and Tim-3 ligation induced distinct signaling events in T cells and dendritic cells; the latter finding could explain the apparent divergent functions of Tim-3 in these cell types. Thus, by virtue of differential expression on innate versus adaptive immune cells, Tim-3 can either promote or terminate TH1 immunity and may be able to influence a range of inflammatory conditions. [ABSTRACT FROM AUTHOR]