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.

Prediction of low pulse oxygen saturation in COVID-19 using remote monitoring post hospital discharge.

BACKGROUND: Monitoring systems have been developed during the COVID-19 pandemic enabling clinicians to remotely monitor physiological measures including pulse oxygen saturation (SpO2), heart rate (HR), and breathlessness in patients after discharge from hospital. These data may be leveraged to understand how symptoms vary over time in COVID-19 patients. There is also potential to use remote monitoring systems to predict clinical deterioration allowing early identification of patients in need of intervention. METHODS: A remote monitoring system was used to monitor 209 patients diagnosed with COVID-19 in the period following hospital discharge. This system consisted of a patient-facing app paired with a Bluetooth-enabled pulse oximeter (measuring SpO2 and HR) linked to a secure portal where data were available for clinical review. Breathlessness score was entered manually to the app. Clinical teams were alerted automatically when SpO2 < 94 %. In this study, data recorded during the initial ten days of monitoring were retrospectively examined, and a random forest model was developed to predict SpO2 < 94 % on a given day using SpO2 and HR data from the two previous days and day of discharge. RESULTS: Over the 10-day monitoring period, mean SpO2 and HR increased significantly, while breathlessness decreased. The coefficient of variation in SpO2, HR and breathlessness also decreased over the monitoring period. The model predicted SpO2 alerts (SpO2 < 94 %) with a mean cross-validated. sensitivity of 66 ± 18.57 %, specificity of 88.31 ± 10.97 % and area under the receiver operating characteristic of 0.80 ± 0.11. Patient age and sex were not significantly associated with the occurrence of asymptomatic SpO2 alerts. CONCLUSION: Results indicate that SpO2 alerts (SpO2 < 94 %) on a given day can be predicted using SpO2 and heart rate data captured on the two preceding days via remote monitoring. The methods presented may help early identification of patients with COVID-19 at risk of clinical deterioration using remote monitoring.

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.

Dynamic Change and Clinical Relevance of Postinfectious SARS-CoV-2 Antibody Responses.

BACKGROUND: Although reports suggest that most individuals with coronavirus disease 2019 (COVID-19) develop detectable antibodies postinfection, the kinetics, durability, and relative differences between immunoglobulin M (IgM) and immunoglobulin G (IgG) responses beyond the first few weeks after symptom onset remain poorly understood. METHODS: Within a large, well-phenotyped, diverse, prospective cohort of subjects with and without severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) polymerase chain reaction (PCR)-confirmed infection and historical controls derived from cohorts with high prevalence of viral coinfections and samples taken during prior flu seasons, we measured SARS-CoV-2 serological responses (both IgG and IgM) using commercially available assays. We calculated sensitivity, specificity, and relationship with disease severity and mapped the kinetics of antibody responses over time using generalized additive models. RESULTS: We analyzed 1001 samples from 752 subjects, 327 with confirmed SARS-CoV-2 (29.7% with severe disease) spanning a period of 90 days from symptom onset. Sensitivity was lower (44.1%-47.1%) early (<10 days) after symptom onset but increased to >80% after 10 days. IgM positivity increased earlier than IgG-targeted assays, but positivity peaked between days 32 and 38 post-onset of symptoms and declined thereafter, a dynamic that was confirmed when antibody levels were analyzed, with a more rapid decline observed with IgM. Early (<10 days) IgM but not IgG levels were significantly higher in those who subsequently developed severe disease (signal/cutoff 4.20 [0.75-17.93] vs 1.07 [0.21-5.46]; P = .048). CONCLUSIONS: This study suggests that postinfectious antibody responses in those with confirmed COVID-19 begin to decline relatively early postinfection and suggests a potential role for higher IgM levels early in infection in the prediction of subsequent disease severity.