Topological data analysis identifies distinct biomarker phenotypes during the inflammatory phase of COVID-19 (preprint)

OBJECTIVES: The relationships between baseline clinical phenotypes and the cytokine milieu of the peak inflammatory phase of coronavirus 2019 (COVID-19) are not yet well understood. We used Topological Data Analysis (TDA), a dimensionality reduction technique to identify patterns of inflammation associated with COVID-19 severity and clinical characteristics. DESIGN: Exploratory analysis from a multi-center prospective cohort study. SETTING: Eight military hospitals across the United States between April 2020 and January 2021. PATIENTS: Adult ([≥]18 years of age) SARS-CoV-2 positive inpatient and outpatient participants were enrolled with plasma samples selected from the putative inflammatory phase of COVID-19, defined as 15-28 days post symptom onset. INTERVENTIONS: None. MEASUREMENTS AND MAIN RESULTS: Concentrations of 12 inflammatory protein biomarkers were measured using a broad dynamic range immunoassay. TDA identified 3 distinct inflammatory protein expression clusters. Peak severity (outpatient, hospitalized, ICU admission or death), Charlson Comorbidity Index (CCI), and body mass index (BMI) were evaluated with logistic regression for associations with each cluster. The study population (n=129, 33.3% female, median 41.3 years of age) included 77 outpatient, 31 inpatient, 16 ICU-level, and 5 fatal cases. Three distinct clusters were found that differed by peak disease severity (p <0.001), age (p <0.001), BMI (p<0.001), and CCI (p=0.001). CONCLUSIONS: Exploratory clustering methods can stratify heterogeneous patient populations and identify distinct inflammation patterns associated with comorbid disease, obesity, and severe illness due to COVID-19.

A betacoronavirus multiplex microsphere immunoassay detects early SARS-CoV-2 seroconversion and antibody cross reactions (preprint)

Sensitive and specific SARS-CoV-2 antibody assays remain critical for community and hospital-based SARS-CoV-2 surveillance. Here, we developed and applied a multiplex microsphere-based immunoassay (MMIA) for COVD-19 antibody studies that incorporates spike protein trimers of SARS-CoV-2, SARS-CoV-1, MERS-CoV, and the seasonal human betacoronaviruses, HCoV-HKU1 and HCoV-OC43, that enables measurement of off-target pre-existing cross-reactive antibodies. The MMIA performances characteristics are: 98% sensitive and 100% specific for human subject samples collected as early as 10 days from symptom onset. The MMIA permitted the simultaneous identification of SARS-CoV-2 seroconversion and the induction of SARS-CoV-2 IgG antibody cross reactions to SARS-CoV-1 and MERS-CoV. Further, synchronous increases of HCoV-OC43 IgG antibody levels was detected with SARS-CoV-2 seroconversion in a subset of subjects for whom early infection sera were available prior to their SARS-CoV-2 seroconversion, suggestive of an HCoV-OC43 memory response triggered by SARS-CoV-2 infection.

A betacoronavirus multiplex microsphere immunoassay detects early SARS-CoV-2 seroconversion and controls for pre-existing seasonal human coronavirus antibody cross-reactivity (preprint)

With growing concern of persistent or multiple waves of SARS-CoV-2 in the United States, sensitive and specific SARS-CoV-2 antibody assays remain critical for community and hospital-based SARS-CoV-2 surveillance. Here, we describe the development and application of a multiplex microsphere-based immunoassay (MMIA) for COVD-19 antibody studies, utilizing serum samples from non-human primate SARS-CoV-2 infection models, an archived human sera bank and subjects enrolled at five U.S. military hospitals. The MMIA incorporates prefusion stabilized spike glycoprotein trimers of SARS-CoV-2, SARS-CoV-1, MERS-CoV, and the seasonal human coronaviruses HCoV-HKU1 and HCoV-OC43, into a multiplexing system that enables simultaneous measurement of off-target pre-existing cross-reactive antibodies. We report the sensitivity and specificity performances for this assay strategy at 98% sensitivity and 100% specificity for subject samples collected as early as 10 days after the onset of symptoms. In archival sera collected prior to 2019 and serum samples from subjects PCR negative for SARS-CoV-2, we detected seroprevalence of 72% and 98% for HCoV-HKU1 and HCoV-0C43, respectively. Requiring only 1.25 uL of sera, this approach permitted the simultaneous identification of SARS-CoV-2 seroconversion and polyclonal SARS-CoV-2 IgG antibody responses to SARS-CoV-1 and MERS-CoV, further demonstrating the presence of conserved epitopes in the spike glycoprotein of zoonotic betacoronaviruses. Application of this serology assay in observational studies with serum samples collected from subjects before and after SARS-CoV-2 infection will permit an investigation of the influences of HCoV-induced antibodies on COVID-19 clinical outcomes.

Additional analyses exploring the hypothesized transdifferentiation of plasmablasts to developing neutrophils in severe COVID-19 (preprint)

We thank Alquicira-Hernandez et al. for their reanalysis of our single-cell transcriptomic dataset profiling peripheral immune responses to severe COVID-19. We agree that careful analysis of single-cell sequencing data is important for generating cogent hypotheses but find several aspects of their criticism of our analysis to be problematic. Here we respond briefly to misunderstandings and inaccuracies in their commentary that may have led to misinformed interpretation of our results.

Abnormal Antibodies to Self-Carbohydrates in SARS-CoV-2 Infected Patients (preprint)

SARS-CoV-2 is a deadly virus that is causing the global pandemic coronavirus disease 2019 (COVID-19). Our immune system plays a critical role in preventing, clearing, and treating the virus, but aberrant immune responses can contribute to deleterious symptoms and mortality. Many aspects of immune responses to SARS-CoV-2 are being investigated, but little is known about immune responses to carbohydrates. Since the surface of the virus is heavily glycosylated, pre-existing antibodies to glycans could potentially recognize the virus and influence disease progression. Furthermore, antibody responses to carbohydrates could be induced, affecting disease severity and clinical outcome. In this study, we used a carbohydrate antigen microarray with over 800 individual components to profile serum anti-glycan antibodies in COVID-19 patients and healthy control subjects. In COVID-19 patients, we observed abnormally high IgG and IgM antibodies to numerous self-glycans, including gangliosides, N-linked glycans, LacNAc-containing glycans, blood group H, and sialyl Lewis X. Some of these anti-glycan antibodies are known to play roles in autoimmune diseases and neurological disorders, which may help explain some of the unusual and prolonged symptoms observed in COVID-19 patients. The detection of antibodies to self-glycans has important implications for using convalescent serum to treat patients, developing safe and effective SARS-CoV-2 vaccines, and understanding the risks of infection. In addition, this study provides new insight into the immune responses to SARS-CoV-2 and illustrates the importance of including host and viral carbohydrate antigens when studying immune responses to viruses.

Antibody Response to a Nucleocapsid Epitope as a Marker for COVID-19 Disease Severity (preprint)

Characterization of antibody response to SARS-CoV-2 is urgently needed to predict COVID-19 disease trajectories. Ineffective antibodies or antibody-dependent enhancement (ADE) could derail patient immune responses, for example. ELISA and coronavirus antigen microarray (COVAM) analysis epitope-mapped plasma from 86 COVID-19 patients. The experiments identified antibodies to a 21-residue epitope from nucleocapsid (termed Ep9) associated with severe disease, including ICU stay, requirement for ventilators, and death. Furthermore, anti-Ep9 antibodies correlate both with various comorbidities and ADE hallmarks, including increased IL-6 levels and early IgG response. Importantly, anti-Ep9 antibodies can be detected within five days post-symptom onset and sometimes within one day. The results lay the groundwork for a new type of COVID-19 diagnostic for the early prediction of disease severity to guide more effective therapeutic interventions.

Early induction of SARS-CoV-2 specific T cells associates with rapid viral clearance and mild disease in COVID-19 patients (preprint)

Virus-specific humoral and cellular immunity act synergistically to protect the host from viral infection. We interrogated the dynamic changes of virological and immunological parameters in 12 patients with symptomatic acute SARS-CoV-2 infection from disease onset to convalescence or death. We quantified SARS-CoV-2 viral RNA in the respiratory tract in parallel with antibodies and circulating T cells specific for various structural (NP, M, ORF3a and spike) and non-structural proteins (ORF7/8, NSP7 and NSP13). We observed that while rapid induction and quantity of humoral responses were associated with increased disease severity, an early induction of SARS-CoV-2 specific T cells was present in patients with mild disease and accelerated viral clearance. These findings provide further support for a protective role of SARS-CoV-2 specific T cells over antibodies during SARS-CoV-2 infection with important implications in vaccine design and immune-monitoring.