A blood atlas of COVID-19 defines hallmarks of disease severity and specificity

COMBATdb: a database for the COVID-19 Multi-Omics Blood ATlas

Advances in our understanding of the nature of the immune response to SARS-CoV-2 infection, and how this varies within and between individuals, is important in efforts to develop targeted therapies and precision medicine approaches. Here we present a database for the COvid-19 Multi-omics Blood ATlas (COMBAT) project, COMBATdb (https://db.combat.ox.ac.uk). This enables exploration of multi-modal datasets arising from profiling of patients with different severities of illness admitted to hospital in the first phase of the pandemic in the UK prior to vaccination, compared with community cases, healthy controls, and patients with all-cause sepsis and influenza. These data include whole blood transcriptomics, plasma proteomics, epigenomics, single-cell multi-omics, immune repertoire sequencing, flow and mass cytometry, and cohort metadata. COMBATdb provides access to the processed data in a well-defined framework of samples, cell types and genes/proteins that allows exploration across the assayed modalities, with functionality including browse, search, download, calculation and visualisation via shiny apps. This advances the ability of users to leverage COMBAT datasets to understand the pathogenesis of COVID-19, and the nature of specific and shared features with other infectious diseases.

Transcriptomic clustering of critically ill COVID-19 patients

BACKGROUND

Infections caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) may cause a severe disease, termed coronavirus disease 2019 (COVID-19), with significant mortality. Host responses to this infection, mainly in terms of systemic inflammation, have emerged as key pathogenetic mechanisms and their modulation has shown a mortality benefit.

METHODS

In a cohort of 56 critically ill COVID-19 patients, peripheral blood transcriptomes were obtained at admission to an intensive care unit (ICU) and clustered using an unsupervised algorithm. Differences in gene expression, circulating microRNAs (c-miRNAs) and clinical data between clusters were assessed, and circulating cell populations estimated from sequencing data. A transcriptomic signature was defined and applied to an external cohort to validate the findings.

RESULTS

We identified two transcriptomic clusters characterised by expression of either interferon-related or immune checkpoint genes, respectively. Steroids have cluster-specific effects, decreasing lymphocyte activation in the former but promoting B-cell activation in the latter. These profiles have different ICU outcomes, despite no major clinical differences at ICU admission. A transcriptomic signature was used to identify these clusters in two external validation cohorts (with 50 and 60 patients), yielding similar results.

CONCLUSIONS

These results reveal different underlying pathogenetic mechanisms and illustrate the potential of transcriptomics to identify patient endotypes in severe COVID-19 with the aim to ultimately personalise their therapies.

Dissecting CD8+ T cell pathology of severe SARS-CoV-2 infection by single-cell immunoprofiling

Introduction

SARS-CoV-2 infection results in varying disease severity, ranging from asymptomatic infection to severe illness. A detailed understanding of the immune response to SARS-CoV-2 is critical to unravel the causative factors underlying differences in disease severity and to develop optimal vaccines against new SARS-CoV-2 variants.

Methods

We combined single-cell RNA and T cell receptor sequencing with CITE-seq antibodies to characterize the CD8⁺ T cell response to SARS-CoV-2 infection at high resolution and compared responses between mild and severe COVID-19.

Results

We observed increased CD8⁺ T cell exhaustion in severe SARS-CoV-2 infection and identified a population of NK-like, terminally differentiated CD8⁺ effector T cells characterized by expression of FCGR3A (encoding CD16). Further characterization of NK-like CD8⁺ T cells revealed heterogeneity among CD16⁺ NK-like CD8⁺ T cells and profound differences in cytotoxicity, exhaustion, and NK-like differentiation between mild and severe disease conditions.

Discussion

We propose a model in which differences in the surrounding inflammatory milieu lead to crucial differences in NK-like differentiation of CD8⁺ effector T cells, ultimately resulting in the appearance of NK-like CD8⁺ T cell populations of different functionality and pathogenicity. Our in-depth characterization of the CD8⁺ T cell-mediated response to SARS-CoV-2 infection provides a basis for further investigation of the importance of NK-like CD8⁺ T cells in COVID-19 severity.

Multi-omics identify falling LRRC15 as a COVID-19 severity marker and persistent pro-thrombotic signals in convalescence

Patients with end-stage kidney disease (ESKD) are at high risk of severe COVID-19. Here, we perform longitudinal blood sampling of ESKD haemodialysis patients with COVID-19, collecting samples pre-infection, serially during infection, and after clinical recovery. Using plasma proteomics, and RNA-sequencing and flow cytometry of immune cells, we identify transcriptomic and proteomic signatures of COVID-19 severity, and find distinct temporal molecular profiles in patients with severe disease. Supervised learning reveals that the plasma proteome is a superior indicator of clinical severity than the PBMC transcriptome. We show that a decreasing trajectory of plasma LRRC15, a proposed co-receptor for SARS-CoV-2, is associated with a more severe clinical course. We observe that two months after the acute infection, patients still display dysregulated gene expression related to vascular, platelet and coagulation pathways, including PF4 (platelet factor 4), which may explain the prolonged thrombotic risk following COVID-19.

Stress signaling boosts interferon-induced gene transcription in macrophages

Promoters of antimicrobial genes function as logic boards, integrating signals of innate immune responses. One such set of genes is stimulated by interferon (IFN) signaling, and the expression of these genes [IFN-stimulated genes (ISGs)] can be further modulated by cell stress-induced pathways. Here, we investigated the global effect of stress-induced p38 mitogen-activated protein kinase (MAPK) signaling on the response of macrophages to IFN. In response to cell stress that coincided with IFN exposure, the p38 MAPK-activated transcription factors CREB and c-Jun, in addition to the IFN-activated STAT family of transcription factors, bound to ISGs. In addition, p38 MAPK signaling induced activating histone modifications at the loci of ISGs and stimulated nuclear translocation of the CREB coactivator CRTC3. These actions synergistically enhanced ISG expression. Disrupting this synergy with p38 MAPK inhibitors improved the viability of macrophages infected with Listeria monocytogenes. Our findings uncover a mechanism of transcriptional synergism and highlight the biological consequences of coincident stress-induced p38 MAPK and IFN-stimulated signal transduction.

High-throughput functional annotation of natural products by integrated activity profiling

Determining mechanism of action (MOA) is one of the biggest challenges in natural products discovery. Here, we report a comprehensive platform that uses Similarity Network Fusion (SNF) to improve MOA predictions by integrating data from the cytological profiling high-content imaging platform and the gene expression platform Functional Signature Ontology, and pairs these data with untargeted metabolomics analysis for de novo bioactive compound discovery. The predictive value of the integrative approach was assessed using a library of target-annotated small molecules as benchmarks. Using Kolmogorov-Smirnov (KS) tests to compare in-class to out-of-class similarity, we found that SNF retains the ability to identify significant in-class similarity across a diverse set of target classes, and could find target classes not detectable in either platform alone. This confirmed that integration of expression-based and image-based phenotypes can accurately report on MOA. Furthermore, we integrated untargeted metabolomics of complex natural product fractions with the SNF network to map biological signatures to specific metabolites. Three examples are presented where SNF coupled with metabolomics was used to directly functionally characterize natural products and accelerate identification of bioactive metabolites, including the discovery of the azoxy-containing biaryl compounds parkamycins A and B. Our results support SNF integration of multiple phenotypic screening approaches along with untargeted metabolomics as a powerful approach for advancing natural products drug discovery.

Anti-chemokine antibodies after SARS-CoV-2 infection correlate with favorable disease course

Infection by SARS-CoV-2 leads to diverse symptoms, which can persist for months. While antiviral antibodies are protective, those targeting interferons and other immune factors are associated with adverse COVID-19 outcomes. Instead, we discovered that antibodies against specific chemokines are omnipresent after COVID-19, associated with favorable disease, and predictive of lack of long COVID symptoms at one year post infection. Anti-chemokine antibodies are present also in HIV-1 infection and autoimmune disorders, but they target different chemokines than those in COVID-19. Monoclonal antibodies derived from COVID- 19 convalescents that bind to the chemokine N-loop impair cell migration. Given the role of chemokines in orchestrating immune cell trafficking, naturally arising anti-chemokine antibodies associated with favorable COVID-19 may be beneficial by modulating the inflammatory response and thus bear therapeutic potential.

One-Sentence Summary

Naturally arising anti-chemokine antibodies associate with favorable COVID-19 and predict lack of long COVID.

Biosafety protection and workflow of clinical microbiology laboratory under COVID-19: A review

This paper mainly discusses how to do a good job of daily biosafety protection measures in clinical microbiology laboratories during the epidemic of COVID-19, so as to ensure the safe development of routine clinical microbiology testing items. According to the microbiological and epidemiological characteristics of the novel coronavirus, this paper analyzed the potential risks of the laboratory from the perspective of personal protection before, during, and after testing. Combined with the actual work situation, the improved biosafety protection measures and optimized work flow are introduced to ensure the safety of medical staff and the smooth development of daily work. Danyang People's Hospital of Jiangsu Province, clinical microbiology laboratory of clinical laboratory in strict accordance with the relevant laws and regulations, technical specifications and the expert consensus, combined with their own conditions, the biosafety measures to perfect the working process was optimized, effectively prevent the laboratory exposure, and maintain strict working condition for a long time, continue to improve. We found that the biosafety protection measures of clinical microbiology laboratory have good prevention and control effect on preventing infection of medical staff, which will greatly reduce the risk of infection of medical staff, form good working habits, and provide reference for biosafety protection of microbiology laboratory during the epidemic of COVID-19.

An immune dysfunction score for stratification of patients with acute infection based on whole-blood gene expression

Dysregulated host responses to infection can lead to organ dysfunction and sepsis, causing millions of global deaths each year. To alleviate this burden, improved prognostication and biomarkers of response are urgently needed. We investigated the use of whole-blood transcriptomics for stratification of patients with severe infection by integrating data from 3149 samples from patients with sepsis due to community-acquired pneumonia or fecal peritonitis admitted to intensive care and healthy individuals into a gene expression reference map. We used this map to derive a quantitative sepsis response signature (SRSq) score reflective of immune dysfunction and predictive of clinical outcomes, which can be estimated using a 7- or 12-gene signature. Last, we built a machine learning framework, SepstratifieR, to deploy SRSq in adult and pediatric bacterial and viral sepsis, H1N1 influenza, and COVID-19, demonstrating clinically relevant stratification across diseases and revealing some of the physiological alterations linking immune dysregulation to mortality. Our method enables early identification of individuals with dysfunctional immune profiles, bringing us closer to precision medicine in infection.

A 9-mRNA signature measured from whole blood by a prototype PCR panel predicts 28-day mortality upon admission of critically ill COVID-19 patients

Immune responses affiliated with COVID-19 severity have been characterized and associated with deleterious outcomes. These approaches were mainly based on research tools not usable in routine clinical practice at the bedside. We observed that a multiplex transcriptomic panel prototype termed Immune Profiling Panel (IPP) could capture the dysregulation of immune responses of ICU COVID-19 patients at admission. Nine transcripts were associated with mortality in univariate analysis and this 9-mRNA signature remained significantly associated with mortality in a multivariate analysis that included age, SOFA and Charlson scores. Using a machine learning model with these 9 mRNA, we could predict the 28-day survival status with an Area Under the Receiver Operating Curve (AUROC) of 0.764. Interestingly, adding patients’ age to the model resulted in increased performance to predict the 28-day mortality (AUROC reaching 0.839). This prototype IPP demonstrated that such a tool, upon clinical/analytical validation and clearance by regulatory agencies could be used in clinical routine settings to quickly identify patients with higher risk of death requiring thus early aggressive intensive care.

Emerging features of MAIT cells and other unconventional T cell populations in human viral disease and vaccination

MAIT cells are one representative of a group of related unconventional or pre-set T cells, and are particularly abundant in humans. While these unconventional T cell types, which also include populations of Vδ2 cells and iNKT cells, recognise quite distinct ligands, they share functional features including the ability to sense "danger" by integration of cytokine signals. Since such signals are common to many human pathologies, activation of MAIT cells in particular has been widely observed. In this review we will discuss recent trends in these data, for example the findings from patients with Covid-19 and responses to novel vaccines. Covid-19 is an example where MAIT cell activation has been correlated with disease severity by several groups, and the pathways leading to activation are being clarified, but the overall role of the cells in vivo requires further exploration. Given the potential wide functional responsiveness of these cells, which ranges from tissue repair to cytotoxicity, and likely impacts on the activity of many other cell populations, defining the role of these cells - not only as sensitive biomarkers but also as mediators - across human disease remains an important task.

Age- and Severity-Associated Humoral Immunity Response in COVID-19 Patients: A Cohort Study from Wuhan, China

Age has been found to be the single most significant factor in COVID-19 severity and outcome. However, the age-related severity factors of COVID-19 have not been definitively established. In this study, we detected SARS-CoV-2-specific antibody responses and infectious disease-related blood indicators in 2360 sera from 783 COVID-19 patients, with an age range of 1−92 years. In addition, we recorded the individual information and clinical symptoms of the patients. We found that the IgG responses for S1, N, and ORF3a and the IgM for NSP7 were associated with severe COVID-19 at different ages. The IgM responses for the S-protein peptides S1-113 (aa 673−684) and S2-97 (aa 1262−1273) were associated with severe COVID-19 in patients aged <60. Furthermore, we found that the IgM for S1-113 and NSP7 may play a protective role in patients aged <60 and >80, respectively. Regarding clinical parameters, we analyzed the diagnostic ability of five clinical parameters for severe COVID-19 in six age groups and identified three-target panel, glucose, IL-6, myoglobin, IL-6, and NT proBNP as the appropriate diagnostic markers for severe COVID-19 in patients aged <41, 41−50, 51−60, 61−70, 71−80, and >80, respectively. The age-associated severity factors revealed here will facilitate our understanding of COVID-19 immunity and diagnosis, and eventually provide meaningful information for combating the pandemic.

Constructing custom-made radiotranscriptomic signatures of vascular inflammation from routine CT angiograms: a prospective outcomes validation study in COVID-19

BACKGROUND

Direct evaluation of vascular inflammation in patients with COVID-19 would facilitate more efficient trials of new treatments and identify patients at risk of long-term complications who might respond to treatment. We aimed to develop a novel artificial intelligence (AI)-assisted image analysis platform that quantifies cytokine-driven vascular inflammation from routine CT angiograms, and sought to validate its prognostic value in COVID-19.

METHODS

For this prospective outcomes validation study, we developed a radiotranscriptomic platform that uses RNA sequencing data from human internal mammary artery biopsies to develop novel radiomic signatures of vascular inflammation from CT angiography images. We then used this platform to train a radiotranscriptomic signature (C19-RS), derived from the perivascular space around the aorta and the internal mammary artery, to best describe cytokine-driven vascular inflammation. The prognostic value of C19-RS was validated externally in 435 patients (331 from study arm 3 and 104 from study arm 4) admitted to hospital with or without COVID-19, undergoing clinically indicated pulmonary CT angiography, in three UK National Health Service (NHS) trusts (Oxford, Leicester, and Bath). We evaluated the diagnostic and prognostic value of C19-RS for death in hospital due to COVID-19, did sensitivity analyses based on dexamethasone treatment, and investigated the correlation of C19-RS with systemic transcriptomic changes.

FINDINGS

Patients with COVID-19 had higher C19-RS than those without (adjusted odds ratio [OR] 2·97 [95% CI 1·43-6·27], p=0·0038), and those infected with the B.1.1.7 (alpha) SARS-CoV-2 variant had higher C19-RS values than those infected with the wild-type SARS-CoV-2 variant (adjusted OR 1·89 [95% CI 1·17-3·20] per SD, p=0·012). C19-RS had prognostic value for in-hospital mortality in COVID-19 in two testing cohorts (high [≥6·99] vs low [<6·99] C19-RS; hazard ratio [HR] 3·31 [95% CI 1·49-7·33], p=0·0033; and 2·58 [1·10-6·05], p=0·028), adjusted for clinical factors, biochemical biomarkers of inflammation and myocardial injury, and technical parameters. The adjusted HR for in-hospital mortality was 8·24 (95% CI 2·16-31·36, p=0·0019) in patients who received no dexamethasone treatment, but 2·27 (0·69-7·55, p=0·18) in those who received dexamethasone after the scan, suggesting that vascular inflammation might have been a therapeutic target of dexamethasone in COVID-19. Finally, C19-RS was strongly associated (r=0·61, p=0·00031) with a whole blood transcriptional module representing dysregulation of coagulation and platelet aggregation pathways.

INTERPRETATION

Radiotranscriptomic analysis of CT angiography scans introduces a potentially powerful new platform for the development of non-invasive imaging biomarkers. Application of this platform in routine CT pulmonary angiography scans done in patients with COVID-19 produced the radiotranscriptomic signature C19-RS, a marker of cytokine-driven inflammation driving systemic activation of coagulation and responsible for adverse clinical outcomes, which predicts in-hospital mortality and might allow targeted therapy.

FUNDING

Engineering and Physical Sciences Research Council, British Heart Foundation, Oxford BHF Centre of Research Excellence, Innovate UK, NIHR Oxford Biomedical Research Centre, Wellcome Trust, Onassis Foundation.

Serum biomarkers associated with SARS-CoV-2 severity

Immunity with SARS-CoV-2 infection during the acute phase is not sufficiently well understood to differentiate mild from severe cases and identify prognostic markers. We evaluated the immune response profile using a total of 71 biomarkers in sera from patients with SARS-CoV-2 infection, confirmed by RT-PCR and controls. We correlated biological marker levels with negative control (C) asymptomatic (A), nonhospitalized (mild cases-M), and hospitalized (severe cases-S) groups. Among angiogenesis markers, we identified biomarkers that were more frequently elevated in severe cases when compared to the other groups (C, A, and M). Among cardiovascular diseases, there were biomarkers with differences between the groups, with D-dimer, GDF-15, and sICAM-1 higher in the S group. The levels of the biomarkers Myoglobin and P-Selectin were lower among patients in group M compared to those in groups S and A. Important differences in cytokines and chemokines according to the clinical course were identified. Severe cases presented altered levels when compared to group C. This study helps to characterize biological markers related to angiogenesis, growth factors, heart disease, and cytokine/chemokine production in individuals infected with SARS-CoV-2, offering prognostic signatures and a basis for understanding the biological factors in disease severity.

Awake prone positioning for patients with COVID-19-induced acute hypoxemic respiratory failure

Whereas prone positioning of intubated patients suffering from acute respiratory distress syndrome represents the standard of care, proning non-intubated patients, so-called "awake prone positioning (APP)," has only recently gained popularity and undergone scientific evaluation. In this review, we summarize current evidence on physiological and clinical effects of APP on patients' centered outcomes, such as intubation and mortality, the safety of the technique, factors and predictors of success, practical issues for optimal implementation, and future areas of research. Current evidence supports using APP among patients suffering from acute hypoxemic respiratory failure due to COVID-19 and undergoing advanced respiratory support, such as high-flow nasal cannula, in an intensive care unit setting. Healthcare teams should aim to prone patients at least 8 h daily. Future research should focus on optimizing the tolerance of the technique and comprehensively evaluating benefits in other patient populations.

Antiplatelet therapy for patients with COVID-19: Systematic review and meta-analysis of observational studies and randomized controlled trials

Background

Hyperinflammation and coagulopathy are hallmarks of COVID-19 and synergistically contribute to illness progression. Antiplatelet agents have been proposed as candidate drugs for COVID-19 treatment on the basis of their antithrombotic and anti-inflammatory properties. A systematic review and meta-analysis that included early observational studies and recent randomized controlled trials (RCTs) was performed to summarize and compare evidence on this issue.

Methods

PubMed, Embase, and the Cochrane Central Register of Controlled Trials (CENTRAL) were searched to identify studies published up to Nov 7, 2021, and the results of registered clinical trials were followed up to Mar 30, 2022. We included RCTs and observational studies assessing the effect of antiplatelet therapy in adult patients with COVID-19. Data on baseline patient characteristics, interventions, controls, and outcomes were extracted by two independent reviewers. The primary outcome was mortality. Data were pooled using a random-effects model.

Results

Twenty-seven studies were included, of which 23 observational studies were pooled in a meta-analysis, and the remaining four RCTs (ACTIV-4B, RECOVERY, ACTIV-4a, and REMAP-CAP) were narratively synthesized. Based on 23 observational studies of 87,824 COVID-19 patients, antiplatelet treatment favors a lower risk of mortality [odds ratio (OR) 0.72, 95% confidence interval (CI) 0.61–0.85; I² = 87.0%, P < 0.01]. The narrative synthesis of RCTs showed conflicting evidence, which did not support adding antiplatelet therapy to the standard care, regardless of the baseline illness severity and concomitant anticoagulation intensity.

Conclusion

While the rationale for using antiplatelet treatment in COVID-19 patients is compelling and was supported by the combined result of early observational studies, evidence from RCTs did not confirm this approach. Several factors that could explain this inconsistency were highlighted alongside perspectives on future research directions.

DOCK2 is involved in the host genetics and biology of severe COVID-19

Identifying the host genetic factors underlying severe COVID-19 is an emerging challenge^1–5. Here we conducted a genome-wide association study (GWAS) involving 2,393 cases of COVID-19 in a cohort of Japanese individuals collected during the initial waves of the pandemic, with 3,289 unaffected controls. We identified a variant on chromosome 5 at 5q35 (rs60200309-A), close to the dedicator of cytokinesis 2 gene (DOCK2), which was associated with severe COVID-19 in patients less than 65 years of age. This risk allele was prevalent in East Asian individuals but rare in Europeans, highlighting the value of genome-wide association studies in non-European populations. RNA-sequencing analysis of 473 bulk peripheral blood samples identified decreased expression of DOCK2 associated with the risk allele in these younger patients. DOCK2 expression was suppressed in patients with severe cases of COVID-19. Single-cell RNA-sequencing analysis (n = 61 individuals) identified cell-type-specific downregulation of DOCK2 and a COVID-19-specific decreasing effect of the risk allele on DOCK2 expression in non-classical monocytes. Immunohistochemistry of lung specimens from patients with severe COVID-19 pneumonia showed suppressed DOCK2 expression. Moreover, inhibition of DOCK2 function with CPYPP increased the severity of pneumonia in a Syrian hamster model of SARS-CoV-2 infection, characterized by weight loss, lung oedema, enhanced viral loads, impaired macrophage recruitment and dysregulated type I interferon responses. We conclude that DOCK2 has an important role in the host immune response to SARS-CoV-2 infection and the development of severe COVID-19, and could be further explored as a potential biomarker and/or therapeutic target.

A genome-wide association study highlights a variant in DOCK2, which is common in East Asian populations but rare in Europeans, as a host genetic risk factor for severe COVID-19.

Cellular heterogeneity in disease severity and clinical outcome: Granular understanding of immune response is key

During an infectious disease progression, it is crucial to understand the cellular heterogeneity underlying the differential immune response landscape that will augment the precise information of the disease severity modulators, leading to differential clinical outcome. Patients with COVID-19 display a complex yet regulated immune profile with a heterogeneous array of clinical manifestation that delineates disease severity sub-phenotypes and worst clinical outcomes. Therefore, it is necessary to elucidate/understand/enumerate the role of cellular heterogeneity during COVID-19 disease to understand the underlying immunological mechanisms regulating the disease severity. This article aims to comprehend the current findings regarding dysregulation and impairment of immune response in COVID-19 disease severity sub-phenotypes and relate them to a wide array of heterogeneous populations of immune cells. On the basis of the findings, it suggests a possible functional correlation between cellular heterogeneity and the COVID-19 disease severity. It highlights the plausible modulators of age, gender, comorbidities, and hosts' genetics that may be considered relevant in regulating the host response and subsequently the COVID-19 disease severity. Finally, it aims to highlight challenges in COVID-19 disease that can be achieved by the application of single-cell genomics, which may aid in delineating the heterogeneity with more granular understanding. This will augment our future pandemic preparedness with possibility to identify the subset of patients with increased diseased severity.

Cytokine Storm Signature in Patients with Moderate and Severe COVID-19

Hypercytokinemia, found in SARS-CoV-2 infection, contributes to multiple organ dysfunctions with acute respiratory distress syndrome, shock etc. The aim of this study was to describe cytokine storm signatures in patients with acute COVID-19 and to investigate their influence on severity of the infection. Plasma levels of 47 cytokines were investigated in 73 patients with moderate and severe COVID-19 (41 and 32, respectively) and 11 healthy donors (HD). The most elevated levels comparing patients and the HD were observed for seven pro-inflammatory cytokines (IL-6, IL-8, IL-15, IL-18, IL-27, IFNγ, TNFα), three chemokines (GROα, IP-10, MIG), two anti-inflammatory cytokines (IL-1RA, IL-10), and two growth factors (G-CSF, M-CSF). The patients with severe disease had significantly higher levels of FGF-2/FGF-basic, IL-1β, and IL-7 compared to the HD. The two groups of patients differed from each other only based on the levels of EGF, eotaxin, and IL-12 p40. Pneumonia lung injury, characterized by computer tomography, positively correlated with levels of EGF, IP-10, MCP-3 levels and negatively with IL-12 p40. Pro-inflammatory factors including IL-6, TNFα, and IP-10 negatively correlated with the frequency of the circulating T-helper17-like cells (Th17-like) and follicular Th cells that are crucial to develop SARS-CoV-2-specific plasma cells and memory B cells. Obtained data on the cytokine levels illustrate their influence on progression and severity of COVID-19.

Assessing the use of a micro-sampling device for measuring blood protein levels in healthy subjects and COVID-19 patients

Background

Venous phlebotomy performed by trained personnel is critical for patient diagnosis and monitoring of chronic disease, but has limitations in resource-constrained settings, and represents an infection control challenge during outbreaks. Self-collection devices have the potential to shift phlebotomy closer to the point of care, supporting telemedicine strategies and virtual clinical trials. Here we assess a capillary blood micro-sampling device, the Tasso Serum Separator Tube (SST), for measuring blood protein levels in healthy subjects and non-hospitalized COVID-19 patients.

Methods

57 healthy controls and 56 participants with mild/moderate COVID-19 were recruited at two U.S. military healthcare facilities. Healthy controls donated Tasso SST capillary serum, venous plasma and venous serum samples at multiple time points, while COVID-19 patients donated a single Tasso SST serum sample at enrolment. Concentrations of 17 protein inflammatory biomarkers were measured in all biospecimens by Ella multi-analyte immune-assay.

Results

Tasso SST serum protein measurements in healthy control subjects were highly reproducible, but their agreements with matched venous samples varied. Most of the selected proteins, including CRP, Ferritin, IL-6 and PCT, were well-correlated between Tasso SST and venous serum with little sample type bias, but concentrations of D-dimer, IL-1B and IL-1Ra were not. Self-collection at home with delayed sample processing was associated with significant concentrations differences for several analytes compared to supervised, in-clinic collection with rapid processing. Finally, Tasso SST serum protein concentrations were significantly elevated in in non-hospitalized COVID-19 patients compared with healthy controls.

Conclusions

Self-collection of capillary blood with micro-sampling devices provides an attractive alternative to routine phlebotomy. However, concentrations of certain analytes may differ significantly from those in venous samples, and factors including user proficiency, temperature control and time lags between specimen collection and processing need to be considered for their effect on sample quality and reproducibility.

Mapping the Serum Proteome of COVID-19 Patients; Guidance for Severity Assessment

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), whose outbreak in 2019 led to an ongoing pandemic with devastating consequences for the global economy and human health. According to the World Health Organization, COVID-19 has affected more than 481 million people worldwide, with 6 million confirmed deaths. The joint efforts of the scientific community have undoubtedly increased the pace of production of COVID-19 vaccines, but there is still so much uncharted ground to cover regarding the mechanisms of SARS-CoV-2 infection, replication and host response. These issues can be approached by proteomics with unprecedented capacity paving the way for the development of more efficient strategies for patient care. In this study, we present a deep proteome analysis that has been performed on a cohort of 72 COVID-19 patients aiming to identify serum proteins assessing the dynamics of the disease at different age ranges. A panel of 53 proteins that participate in several functions such as acute-phase response and inflammation, blood coagulation, cell adhesion, complement cascade, endocytosis, immune response, oxidative stress and tissue injury, have been correlated with patient severity, suggesting a molecular basis for their clinical stratification. Eighteen protein candidates were further validated by targeted proteomics in an independent cohort of 84 patients including a group of individuals that had satisfactorily resolved SARS-CoV-2 infection. Remarkably, all protein alterations were normalized 100 days after leaving the hospital, which further supports the reliability of the selected proteins as hallmarks of COVID-19 progression and grading. The optimized protein panel may prove its value for optimal severity assessment as well as in the follow up of COVID-19 patients.

Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion

SARS-CoV-2 infection triggers profound and variable immune responses in human hosts. Chromatin remodeling has been observed in individuals severely ill or convalescing with COVID-19, but chromatin remodeling early in disease prior to anti-spike protein IgG seroconversion has not been defined. We performed the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA-seq on peripheral blood mononuclear cells (PBMCs) from outpatients with mild or moderate symptom severity at different stages of clinical illness. Early in the disease course prior to IgG seroconversion, modifications in chromatin accessibility associated with mild or moderate symptoms were already robust and included severity-associated changes in accessibility of genes in interleukin signaling, regulation of cell differentiation and cell morphology. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif accessibility for individual PBMC cell types over time. The most extensive remodeling occurred in CD14+ monocytes, where sub-populations with distinct chromatin accessibility profiles were observed prior to seroconversion. Mild symptom severity was marked by upregulation of classical antiviral pathways, including those regulating IRF1 and IRF7, whereas in moderate disease, these classical antiviral signals diminished, suggesting dysregulated and less effective responses. Together, these observations offer novel insight into the epigenome of early mild SARS-CoV-2 infection and suggest that detection of chromatin remodeling in early disease may offer promise for a new class of diagnostic tools for COVID-19.

The Dynamic Role of FOXP3+ Tregs and Their Potential Therapeutic Applications During SARS-CoV-2 Infection

Coronavirus disease 2019 (COVID-19) has been raging all around the world since the beginning of 2020, and leads to acute respiratory distress syndrome (ARDS) with strong cytokine storm which contributes to widespread tissue damage and even death in severe patients. Over-activated immune response becomes one of the characteristics of severe COVID-19 patients. Regulatory T cells (Treg) play an essential role in maintaining the immune homeostasis, which restrain excessive inflammation response. So FOXP3+ Tregs might participate in the suppression of inflammation caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Besides suppressive function, tissue resident Tregs are also responsible for tissue repair. In this review, we mainly summarize the latest research focusing on the change of FOXP3+ Tregs in the COVID-19 patients, discuss the relationship between disease severity and number change of Tregs and speculate the potential role of FOXP3+ Tregs during SARS-CoV-2 infection. Furthermore, we introduce some potential Treg-based therapies to improve patients’ outcomes, which include small molecular drugs, antibody drugs, CAR-Treg and cytokine treatment. We hope to reduce tissue damage of severe COVID-19 patients and offer better prognosis through Treg-based therapy.

A review of suspension trapping digestion method in bottom-up proteomics

The standard bottom-up proteomic workflow is comprised of sample preparation, data acquisition, and data analysis. While the latter two parts have made considerable advances in the last decade, sample preparation has remained an important challenge within the workflow due to the multi-step nature of complex biological samples, and still requires much development. Several sample preparation methods have been developed and used in the last two decades, including in-gel, in-solution, on-bead, filter-aided sample preparation, and suspension trapping, to improve reproducibility, efficiency, scalability, and reduce handling time of this process. One of the most recent methods developed and applied in proteomics studies in recent years is suspension trapping, which combines rapid detergent removal, reactor-type protein digestion, and peptide clean-up in a tip or spin column. Suspension trapping is a simple, rapid, and reproducible digestion method that can effectively handle proteins in low microgram or sub-microgram amounts. This review discusses the benefits of the suspension trapping digestion method in relation to its development and application in bottom-up proteomics studies. We also discuss recent applications of suspension trapping digestion to different sample types and the features of the suspension trapping digestion method compared with other sample preparation methods. This article is protected by copyright. All rights reserved.

Dysregulated Immune Responses in SARS-CoV-2-Infected Patients: A Comprehensive Overview

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first detected in humans more than two years ago and caused an unprecedented socio-economic burden on all countries around the world. Since then, numerous studies have attempted to identify various mechanisms involved in the alterations of innate and adaptive immunity in COVID-19 patients, with the ultimate goal of finding ways to correct pathological changes and improve disease outcomes. State-of-the-art research methods made it possible to establish precise molecular mechanisms which the new virus uses to trigger multisystem inflammatory syndrome and evade host antiviral immune responses. In this review, we present a comprehensive analysis of published data that provide insight into pathological changes in T and B cell subsets and their phenotypes, accompanying the acute phase of the SARS-CoV-2 infection. This knowledge might help reveal new biomarkers that can be utilized to recognize case severity early as well as to provide additional objective information on the effective formation of SARS-CoV-2-specific immunity and predict long-term complications of COVID-19, including a large variety of symptoms termed the 'post-COVID-19 syndrome'.

Chromogranin A plasma levels predict mortality in COVID-19

Background

Chromogranin A (CgA) and its fragment vasostatin I (VS-I) are secreted in the blood by endocrine/neuroendocrine cells and regulate stress responses. Their involvement in Coronavirus 2019 disease (COVID-19) has not been investigated.

Methods

CgA and VS-I plasma concentrations were measured at hospital admission from March to May 2020 in 190 patients. 40 age- and sex-matched healthy volunteers served as controls. CgA and VS-I levels relationship with demographics, comorbidities and disease severity was assessed through Mann Whitney U test or Spearman correlation test. Cox regression analysis and Kaplan Meier survival curves were performed to investigate the impact of the CgA and VS-I levels on in-hospital mortality.

Results

Median CgA and VS-I levels were higher in patients than in healthy controls (CgA: 0.558 nM [interquartile range, IQR 0.358–1.046] vs 0.368 nM [IQR 0.288–0.490] respectively, p = 0.0017; VS-I: 0.357 nM [IQR 0.196–0.465] vs 0.144 nM [0.144–0.156] respectively, p<0.0001). Concentration of CgA, but not of VS-I, significantly increased in patients who died (n = 47) than in survivors (n = 143) (median 0.948 nM [IQR 0.514–1.754] vs 0.507 nM [IQR 0.343–0.785], p = 0.00026). Levels of CgA were independent predictors of in-hospital mortality (hazard ratio 1.28 [95% confidence interval 1.077–1.522], p = 0.005) when adjusted for age, number of comorbidities, respiratory insufficiency degree, C-reactive protein levels and time from symptom onset to sampling. Kaplan Meier curves revealed a significantly increased mortality rate in patients with CgA levels above 0.558 nM (median value, log rank test, p = 0.001).

Conclusion

Plasma CgA levels increase in COVID-19 patients and represent an early independent predictor of mortality.

An Evolutionary Insight Into the Heterogeneous Severity Pattern of the SARS-CoV-2 Infection

The ongoing pandemic of COVID-19 has elaborated an idiosyncratic pattern of SARS-CoV-2-induced symptoms in the human host. Some populations have succumbed to the SARS-CoV-2 infection in large numbers during this pandemic, whereas others have shown a resilient side by manifesting only milder or no symptoms at all. This observation has relayed the onus of the heterogeneous pattern of SARS-CoV-2-induced critical illness among different populations to the host genetic factors. Here, the evolutionary route was explored and three genetic loci, i.e., rs10735079, rs2109069, and rs2236757, associated with COVID-19 were analyzed. Among the three, the risk allele A at genetic locus rs2236757 residing in the IFNAR2 gene was observed to have undergone recent positive selection in the African population.

Differential chromatin accessibility in peripheral blood mononuclear cells underlies COVID-19 disease severity prior to seroconversion

SARS-CoV-2 infection triggers profound and variable immune responses in human hosts. Chromatin remodeling has been observed in individuals severely ill or convalescing with COVID-19, but chromatin remodeling early in disease prior to anti-spike protein IgG seroconversion has not been defined. We performed the Assay for Transposase-Accessible Chromatin using sequencing (ATAC-seq) and RNA-seq on peripheral blood mononuclear cells (PBMCs) from outpatients with mild or moderate symptom severity at different stages of clinical illness. Early in the disease course prior to IgG seroconversion, modifications in chromatin accessibility associate with mild or moderate symptoms are already robust and include severity-associated changes in accessibility of genes in interleukin signaling, regulation of cell differentiation and cell morphology. Furthermore, single-cell analyses revealed evolution of the chromatin accessibility landscape and transcription factor motif accessibility for individual PBMC cell types over time. The most extensive remodeling occurred in CD14+ monocytes, where sub-populations with distinct chromatin accessibility profiles were observed prior to seroconversion. Mild symptom severity is marked by upregulation classical antiviral pathways including those regulating IRF1 and IRF7, whereas in moderate disease these classical antiviral signals diminish suggesting dysregulated and less effective responses. Together, these observations offer novel insight into the epigenome of early mild SARS-CoV-2 infection and suggest that detection of chromatin remodeling in early disease may offer promise for a new class of diagnostic tools for COVID-19.

MAIT Cells in Respiratory Viral Infections in Mouse and Human

Mucosal associated invariant T (MAIT) cells were first identified as specific for bacterial, mycobacterial, and fungal organisms, which detect microbially-derived biosynthetic ligands presented by MHC-related protein 1 (MR1). More recently two unexpected, additional roles have been identified for these ancient and abundant cells: a TCR-depen-dent role in tissue repair and a TCR-independent role in antiviral host defence. Data from several classes of viral disease shows their capability for activation by the cytokines interleukin (IL)-12, IL-15, IL-18, and type I interferon. MAIT cells are abundant at mucosal surfaces, particularly in the lung, and it seems likely a primary reason for their striking evolutionary conservation is an important role in early innate defence against respiratory infections, including both bacteria and viruses. Here we review evidence for their TCR-independent activation, observational human data for their activation in influenza A virus, and in vivo murine evidence of their protection against severe influenza A infection, mediated at least partially via IFN-gamma. We then survey evidence emerging from other respiratory viral infections including recent evidence for an important adjuvant role in adenovirus infection, specifically chimpanzee adenoviruses used in recent coronavirus vaccines, and data for strong associations between MAIT cell responses and adverse outcomes from coronavirus-19 (COVID-19) disease. We speculate on potential translational implications of these findings, either using corticosteroids or inhibitory ligands to suppress deleterious MAIT cell responses, or the potential utility of stimulatory MR1 ligands to boost MAIT cell frequencies to enhance innate viral defences.