Associations between host microbiome and inflammation suggest role for host microbiome in driving COVID-19 disease severity.

Systemic inflammation and innate immune activation are associated with COVID-19 disease severity. Knowledge gaps remain in the relationships between microbiome, inflammation and COVID-19 disease severity. To better characterise these associations, we performed 16SrDNA analysis of stool samples in COVID-19 subjects to explore diversity and taxanomic composition. We correlated these to host inflammatory profiles, derived from soluble plasma biomarkers measured by bead-based fluorescence and electrochemiluminescence immunoassays. Associations of microbial diversity and inflammatory biomarkers on maximal COVID-19 severity (mild, moderate v severe/critical) was explored using logistic regression and weighted gene correlation network analysis (WGCNA). Of 79 subjects, 58% were male and 88% were Caucasian with 36% experiencing mild disease, 22% moderate disease and 40% critical/severe COVID-19. Hierarchical clustering and principal component analysis (PCo) revealed distinct inflammatory clusters that were found to correlate with 4 modules of microbiome profiles. Modules 3 and 4 were associated with both older age and severe/critical disease outcomes. These modules were enriched in pathogenic and inflammatory bacteria that mapped to a pro-inflammatory biomarker cluster. In contrast, module 1 exhibited enrichment of anti-inflammatory bacteria, was associated with younger age and mild/moderate disease outcomes and mapped to a less-inflamed biomarker cluster. This study provides further insights into links between host microbiome, inflammatory responses to SARS-CoV-2 infection and clinical COVID-19 disease severity, suggesting a role for the microbiome in shaping distinct host inflammatory responses to infection.

Impact of vaccination and variants of concern on long COVID clinical phenotypes.

BACKGROUND: Defining patterns of symptoms in long COVID is necessary to advance therapies for this heterogeneous condition. Here we aimed to describe clusters of symptoms in individuals with long COVID and explore the impact of the emergence of variants of concern (VOCs) and vaccination on these clusters. METHODS: In a prospective, multi centre cohort study, individuals with symptoms persisting > 4 weeks from acute COVID-19 were divided into two groups based on timing of acute infection; pre-Alpha VOC, denoted wild type (WT) group and post-Alpha VOC (incorporating alpha and delta dominant periods) denoted VOC group. We used multiple correspondence analysis (MCA) and hierarchical clustering in the WT and VOC groups to identify symptom clusters. We then used logistic regression to explore factors associated with individual symptoms. RESULTS: A total of 417 individuals were included in the analysis, 268 in WT and 149 in VOC groups respectively. In both groups MCA identified three similar clusters; a musculoskeletal (MSK) cluster characterised by joint pain and myalgia, a cardiorespiratory cluster and a less symptomatic cluster. Differences in characteristic symptoms were only seen in the cardiorespiratory cluster where a decrease in the frequency of palpitations (10% vs 34% p = 0.008) and an increase in cough (63% vs 17% p < 0.001) in the VOC compared to WT groups was observed. Analysis of the frequency of individual symptoms showed significantly lower frequency of both chest pain (25% vs 39% p = 0.004) and palpitations (12% vs 32% p < 0.001) in the VOC group compared to the WT group. In adjusted analysis being in the VOC group was significantly associated with a lower odds of both chest pain and palpitations, but vaccination was not associated with these symptoms. CONCLUSION: This study suggests changes in long COVID phenotype in individuals infected later in the pandemic, with less palpitations and chest pain reported. Adjusted analyses suggest that these effects are mediated through introduction of variants rather than an effect from vaccination.

Development of a novel medium throughput flow-cytometry based micro-neutralisation test for SARS-CoV-2 with applications in clinical vaccine trials and antibody screening.

Quantifying neutralising capacity of circulating SARS-COV-2 antibodies is critical in evaluating protective humoral immune responses generated post-infection/post-vaccination. Here we describe a novel medium-throughput flow cytometry-based micro-neutralisation test to evaluate Neutralising Antibody (NAb) responses against live SARS-CoV-2 Wild Type and Variants of Concern (VOC) in convalescent/vaccinated populations. Flow Cytometry-Based Micro-Neutralisation Test (Micro-NT) was performed in 96-well plates using clinical isolates WT-B, WT-B.1.177.18 and/or VOCs Beta and Omicron. Plasma samples (All Ireland Infectious Diseases (AIID) Cohort) were serially diluted (8 points, half-log) from 1:20 and pre-incubated with SARS-CoV-2 (1h, 37°C). Virus-plasma mixture were added onto Vero E6 or Vero E6/TMPRSS2 cells for 18h. Percentage infected cells was analysed by automated flow cytometry following trypsinisation, fixation and SARS-CoV-2 Nucleoprotein intracellular staining. Half-maximal Neutralisation Titres (NT50) were determined using non-linear regression. Our assay was compared to Plaque Reduction Neutralisation Test (PRNT) and validated against the First WHO International Standard for anti-SARS-CoV-2 immunoglobulin. Both Micro-NT and PRNT achieved comparable NT50 values. Further validation showed adequate correlation with PRNT using a panel of secondary standards of clinical convalescent and vaccinated plasma samples. We found the assay to be reproducible through measuring both repeatability and intermediate precision. Screening 190 convalescent samples and 11 COVID-19 naive controls (AIID cohort) we demonstrated that Micro-NT has broad dynamic range differentiating NT50s <1/20 to >1/5000. We could also characterise immune-escape VOC Beta and Omicron BA.5, achieving fold-reductions in neutralising capacity similar to those published. Our flow cytometry-based Micro-NT is a robust and reliable assay to quantify NAb titres, and has been selected as an endpoint in clinical trials.

Distinct receptor binding domain IgG thresholds predict protective host immunity across SARS-CoV-2 variants and time.

SARS-CoV-2 neutralising antibodies provide protection against COVID-19. Evidence from early vaccine trials suggested binding antibody thresholds could serve as surrogate markers of neutralising capacity, but whether these thresholds predict sufficient neutralising capacity against variants of concern (VOCs), and whether this is impacted by vaccine or infection history remains unclear. Here we analyse individuals recovered from, vaccinated or with hybrid immunity against SARS-CoV-2. An NT50 ≥ 100 IU confers protection in vaccine trials, however, as VOC induce a reduction in NT50, we use NT50 ≥ 1000 IU as a cut off for WT NT50 that would retain neutralisation against VOC. In unvaccinated convalescent participants, a receptor binding domain (RBD) IgG of 456 BAU/mL predicts an NT50 against WT of 1000 IU with an accuracy of 80% (95%CI 73-86%). This threshold maintains accuracy in determining loss of protective immunity against VOC in two vaccinated cohorts. It predicts an NT50 < 100 IU against Beta with an accuracy of 80% (95%CI 67-89%) in 2 vaccine dose recipients. In booster vaccine recipients with a history of COVID-19 (hybrid immunity), accuracy is 87% (95%CI 77-94%) in determining an NT50 of <100 IU against BA.5. This analysis provides a discrete threshold that could be used in future clinical studies.

Dysregulated early transcriptional signatures linked to mast cell and interferon responses are implicated in COVID-19 severity.

Background: Dysregulated immune responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection are thought to underlie the progression of coronavirus disease 2019 (COVID-19) to severe disease. We sought to determine whether early host immune-related gene expression could predict clinical progression to severe disease. Methods: We analysed the expression of 579 immunological genes in peripheral blood mononuclear cells taken early after symptom onset using the NanoString nCounter and compared SARS-CoV-2 negative controls with SARS-CoV-2 positive subjects with mild (SARS+ Mild) and Moderate/Severe disease to evaluate disease outcomes. Biobanked plasma samples were also assessed for type I (IFN-α2a and IFN-ß), type II (IFN-γ) and type III (IFN-λ1) interferons (IFNs) as well as 10 additional cytokines using multiplex immunoassays. Results: We identified 19 significantly deregulated genes in 62 SARS-CoV-2 positive subject samples within 5 days of symptom onset and 58 SARS-CoV-2 negative controls and found that type I interferon (IFN) signalling (MX1, IRF7, IFITM1, IFI35, STAT2, IRF4, PML, BST2, STAT1) and genes encoding proinflammatory cytokines (TNF, TNFSF4, PTGS2 and IL1B) were upregulated in both SARS+ groups. Moreover, we found that FCER1, involved in mast cell activation, was upregulated in the SARS+ Mild group but significantly downregulated in the SARS+ Moderate/Severe group. In both SARS+ groups we discovered elevated interferon type I IFN-α2a, type II IFN and type III IFN λ1 plasma levels together with higher IL-10 and IL-6. These results indicate that those with moderate or severe disease are characterised by deficiencies in a mast cell response together with IFN hyper-responsiveness, suggesting that early host antiviral immune responses could be a cause and not a consequence of severe COVID-19. Conclusions: This study suggests that early host immune responses linking defects in mast cell activation with host interferon responses correlates with more severe outcomes in COVID-19. Further characterisation of this pathway could help inform better treatment for vulnerable individuals.

Performance and validation of an adaptable multiplex assay for detection of serologic response to SARS-CoV-2 infection or vaccination.

Measurement of quantitative antibody responses are increasingly important in evaluating the immune response to infection and vaccination. In this study we describe the validation of a quantitative, multiplex serologic assay utilising an electrochemiluminescence platform, which measures IgG against the receptor binding domain (RBD), spike S1 and S2 subunits and nucleocapsid antigens of SARS-CoV-2. The assay displayed a sensitivity ranging from 73 to 91% and specificity from 90 to 96% in detecting previous infection with SARS-CoV-2 depending on antigenic target and time since infection, and this assay highly correlated with commercially available assays. The within-plate coefficient of variation ranged from 3.8-3.9% and the inter-plate coefficient of variation from 11 to 13% for each antigen.

Identification of Distinct Long COVID Clinical Phenotypes Through Cluster Analysis of Self-Reported Symptoms.

Background: We aimed to describe the clinical presentation of individuals presenting with prolonged recovery from coronavirus disease 2019 (COVID-19), known as long COVID. Methods: This was an analysis within a multicenter, prospective cohort study of individuals with a confirmed diagnosis of COVID-19 and persistent symptoms >4 weeks from onset of acute symptoms. We performed a multiple correspondence analysis (MCA) on the most common self-reported symptoms and hierarchical clustering on the results of the MCA to identify symptom clusters. Results: Two hundred thirty-three individuals were included in the analysis; the median age of the cohort was 43 (interquartile range [IQR], 36-54) years, 74% were women, and 77.3% reported a mild initial illness. MCA and hierarchical clustering revealed 3 clusters. Cluster 1 had predominantly pain symptoms with a higher proportion of joint pain, myalgia, and headache; cluster 2 had a preponderance of cardiovascular symptoms with prominent chest pain, shortness of breath, and palpitations; and cluster 3 had significantly fewer symptoms than the other clusters (2 [IQR, 2-3] symptoms per individual in cluster 3 vs 6 [IQR, 5-7] and 4 [IQR, 3-5] in clusters 1 and 2, respectively; P < .001). Clusters 1 and 2 had greater functional impairment, demonstrated by significantly longer work absence, higher dyspnea scores, and lower scores in SF-36 domains of general health, physical functioning, and role limitation due to physical functioning and social functioning. Conclusions: Clusters of symptoms are evident in long COVID patients that are associated with functional impairments and may point to distinct underlying pathophysiologic mechanisms of disease.

In vivo and in vitro studies of GAD-antibody positive subjects with Type 2 diabetes: A distinct sub-phenotype.

The purpose of this study was to determine if immune mechanisms in GAD positive patients' contribute to the pathogenesis of a specific sub-type of Type 2 diabetes. GAD positive (n=8) and GAD negative (n=8) subjects diagnosed with Type 2 diabetes were matched for age, gender, body mass index, duration of diabetes and glycaemic control. All subjects underwent an insulin-modified frequently sampled intravenous glucose tolerance test to measure insulin sensitivity and insulin secretory function with minimal model analysis. In addition, BRIN-BD11 clonal beta-cells were supplemented with patients' sera to determine basal and alanine-stimulated insulin secretion and terminal complement complex (TCC) formation. Both groups were severely insulin resistant (0.56+/-0.17 vs. 0.99+/-0.3310(-4)min(-1)/(microUml(-1)) for GADneg and GADpos, respectively) but the GAD negative subjects had a higher basal (87+/-11 vs. 58+/-14pmoll(-1), p<0.05) and glucose-stimulated insulin secretion (DeltaAUCins 0.96+/-0.12 vs. 0.60+/-0.12pmol/(l(-1)min), p<0.05). In vivo measures of insulin secretion were negatively correlated with TCC formation, independent of antibody status. In conclusion, GAD positive subjects initially diagnosed with Type 2 diabetes are unable to compensate for insulin resistance due to more pronounced beta-cell impairment. TCC formation may be partly responsible for the insulin secretory dysfunction associated with this specific sub-type of Type 2 diabetes.