TNFα-producing CD4+ T cells dominate the SARS-CoV-2-specific T cell response in COVID-19 outpatients and are associated with durable antibodies (preprint)

SARS-CoV-2-specific CD4+ T cells are likely important in immunity against COVID-19, but our understanding of CD4+ longitudinal dynamics following infection and specific features that correlate with the maintenance of neutralizing antibodies remains limited. We characterized SARS-CoV-2-specific CD4+ T cells in a longitudinal cohort of 109 COVID-19 outpatients. The quality of the SARS-CoV-2-specific CD4+ response shifted from cells producing IFN{gamma} to TNF+ from five days to four months post-enrollment, with IFN{gamma}-IL21-TNF+ CD4+ T cells the predominant population detected at later timepoints. Greater percentages of IFN{gamma}-IL21-TNF+ CD4+ T cells on day 28 correlated with SARS-CoV-2 neutralizing antibodies measured seven months post-infection ({rho}=0.4, P=0.01). mRNA vaccination following SARS-CoV-2 infection boosted both IFN{gamma} and TNF producing, spike protein-specific CD4+ T cells. These data suggest that SARS-CoV-2-specific, TNF-producing CD4+ T cells may play an important role in antibody maintenance following COVID-19.

Differential Peripheral Blood Glycoprotein Profiles in Symptomatic and Asymptomatic COVID-19 (preprint)

Glycosylation is the most common form of post-translational modification of proteins, critically affecting their structure and function. Using liquid chromatography and mass spectrometry for high-resolution site-specific quantification of glycopeptides coupled with high-throughput artificial intelligence-powered data processing, we analyzed differential protein glyco-isoform distributions of 597 abundant serum glycopeptides and non-glycosylated peptides in 50 individuals who had been seriously ill with COVID-19 and in 22 individuals who had recovered after an asymptomatic course of COVID-19. As additional comparison reference phenotypes, we included 12 individuals with a history of infection with a common cold coronavirus, 16 patients with bacterial sepsis, and 15 healthy subjects without history of coronavirus exposure. We found statistically significant differences, at FDR<0.05, for normalized abundances of 374 of the 597 peptides and glycopeptides interrogated, between symptomatic and asymptomatic COVID-19 patients. Similar statistically significant differences were seen when comparing symptomatic COVID-19 patients to healthy controls (350 differentially abundant peptides and glycopeptides) and common cold coronavirus seropositive subjects (353 differentially abundant peptides and glycopeptides). Among healthy controls and sepsis patients, 326 peptides and glycopeptides were found to be differentially abundant, of which 277 overlapped with biomarkers that showed differential expression between symptomatic COVID-19 cases and healthy controls. Among symptomatic COVID-19 cases and sepsis patients, 101 glycopeptide and peptide biomarkers were found to be statistically significantly abundant. Using both supervised and unsupervised machine learning techniques, we found specific glycoprotein profiles to be strongly predictive of symptomatic COVID-19 infection. LASSO-regularized multivariable logistic regression and K-means clustering yielded accuracies of 100% in an independent test set and of 96% overall, respectively. Our findings are consistent with the interpretation that a majority of glycoprotein modifications observed which are shared among symptomatic COVID-19 and sepsis patients likely represent a generic consequence of a severe systemic immune and inflammatory state. However, there are glyco-isoform changes that are specific and particular to severe COVID-19 infection. These may be representative of either COVID-19-specific consequences or of susceptibility to or predisposition for a severe course of the disease. Our findings support the potential value of glycoproteomic biomarkers in the biomedical understanding, and, potentially, the clinical management of serious acute infectious conditions.

Magnitude and breadth of neutralizing antibody responses elicited by SARS-CoV-2 infection or vaccination (preprint)

Multiple SARS-CoV-2 variants that possess mutations associated with increased transmission and antibody escape have arisen over the course of the current pandemic. While the current vaccines have largely been effective against past variants, the number of mutations found on the Omicron (B.1.529) spike appear to diminish the efficacy of pre-existing immunity. Using pseudoparticles expressing the spike of several SARS-CoV-2 variants, we evaluated the magnitude and breadth of the neutralizing antibody response over time in naturally infected and in mRNA-vaccinated individuals. We observed that while boosting increases the magnitude of the antibody response to wildtype (D614), Beta, Delta and Omicron variants, the Omicron variant was the most resistant to neutralization. We further observed that vaccinated healthy adults had robust and broad antibody responses while responses were relatively reduced in vaccinated pregnant women, underscoring the importance of learning how to maximize mRNA vaccine responses in pregnant populations. Findings from this study show substantial heterogeneity in the magnitude and breadth of responses after infection and mRNA vaccination and may support the addition of more conserved viral antigens to existing SARS-CoV-2 vaccines.

Early immune responses have long-term associations with clinical, virologic, and immunologic outcomes in patients with COVID-19 (preprint)

The great majority of SARS-CoV-2 infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, mild to moderate infections are an important contributor to ongoing transmission. There remains a critical need to identify host immune biomarkers predictive of clinical and virologic outcomes in SARS-CoV-2-infected patients. Leveraging longitudinal samples and data from a clinical trial of Peginterferon Lambda for treatment of SARS-CoV-2 infected outpatients, we used host proteomics and transcriptomics to characterize the trajectory of the immune response in COVID-19 patients within the first 2 weeks of symptom onset. We define early immune signatures, including plasma levels of RIG-I and the CCR2 ligands (MCP1, MCP2 and MCP3), associated with control of oropharyngeal viral load, the degree of symptom severity, and immune memory (including SARS-CoV-2-specific T cell responses and spike (S) protein-binding IgG levels). We found that individuals receiving BNT162b2 (Pfizer-BioNTech) vaccine had similar early immune trajectories to those observed in this natural infection cohort, including the induction of both inflammatory cytokines (e.g. MCP1) and negative immune regulators (e.g. TWEAK). Finally, we demonstrate that machine learning models using 8-10 plasma protein markers measured early within the course of infection are able to accurately predict symptom severity, T cell memory, and the antibody response post-infection.

Early immune responses have long-term associations with clinical, virologic, and immunologic outcomes in patients with COVID-19 (preprint)

The great majority of SARS-CoV-2 infections are mild and uncomplicated, but some individuals with initially mild COVID-19 progressively develop more severe symptoms. Furthermore, there is substantial heterogeneity in SARS-CoV-2-specific memory immune responses following infection. There remains a critical need to identify host immune biomarkers predictive of clinical and immunologic outcomes in SARS-CoV-2-infected patients. Leveraging longitudinal samples and data from a clinical trial in SARS-CoV-2 infected outpatients, we used host proteomics and transcriptomics to characterize the trajectory of the immune response in COVID-19 patients within the first 2 weeks of symptom onset. We identify early immune signatures, including plasma RIG-I levels, early interferon signaling, and related cytokines (CXCL10, MCP1, MCP-2 and MCP-3) associated with subsequent disease progression, control of viral shedding, and the SARS-CoV-2 specific T cell and antibody response measured up to 7 months after enrollment. We found that several biomarkers for immunological outcomes are shared between individuals receiving BNT162b2 (Pfizer–BioNTech) vaccine and COVID-19 patients. Finally, we demonstrate that machine learning models using 7-10 plasma protein markers measured early within the course of infection are able to accurately predict disease progression, T cell memory, and the antibody response post-infection in a second, independent dataset.

Divergent early antibody responses define COVID-19 disease trajectories (preprint)

Serologic markers that predict severe COVID-19 disease trajectories could enable early medical interventions and reduce morbidity and mortality. We found that distinct features of IgG Fab and Fc domain structures were present within three days of a positive test that predicted two separate disease trajectories in a prospective cohort of patients with COVID-19. One trajectory was defined by early production of neutralizing antibodies and led to mild disease. A distinct trajectory, characterized by an initial period of mild symptoms followed by rapid progression to more severe outcomes, was predicted by the absence of early neutralizing antibody responses with concomitant production of afucosylated IgGs. Elevated frequencies of monocytes expressing the receptor for afucosylated IgGs, Fc{gamma}RIIIa (CD16a), were an additional antecedent in patients with the more severe outcomes. In mechanistic studies, afucosylated immune complexes in the lung triggered an inflammatory infiltrate and cytokine production that was dependent on CD16a. Finally, in healthy subjects, mRNA SARS-CoV-2 vaccination elicited neutralizing antibodies that were enriched for Fc fucosylation and sialylation and distinct from both infection-induced trajectories. These data show the importance of combined Fab and Fc domain functions in the antiviral response, define an early antibody signature in people who progressed to more severe COVID-19 outcomes and have implications for novel therapeutic strategies targeting Fc{gamma}RIIIa pathways.

New-Onset IgG Autoantibodies in Hospitalized Patients with COVID-19 (preprint)

Coronavirus Disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), is associated with a wide range of clinical manifestations, including autoimmune features and autoantibody production. We developed three different protein arrays to measure hallmark IgG autoantibodies associated with Connective Tissue Diseases (CTDs), Anti-Cytokine Antibodies (ACA), and anti-viral antibody responses in 147 hospitalized COVID-19 patients in three different centers. Autoantibodies were identified in approximately 50% of patients, but in <15% of healthy controls. When present, autoantibodies largely targeted autoantigens associated with rare disorders such as myositis, systemic sclerosis and CTD overlap syndromes. Anti-nuclear antibodies (ANA) were observed in ~25% of patients. Patients with autoantibodies tended to demonstrate one or a few specificities whereas ACA were even more prevalent, and patients often had antibodies to multiple cytokines. Rare patients were identified with IgG antibodies against angiotensin converting enzyme-2 (ACE-2). A subset of autoantibodies and ACA developed de novo following SARS-CoV-2 infection while others were transient. Autoantibodies tracked with longitudinal development of IgG antibodies that recognized SARS-CoV-2 structural proteins such as S1, S2, M, N and a subset of non-structural proteins, but not proteins from influenza, seasonal coronaviruses or other pathogenic viruses. COVID-19 patients with one or more autoantibodies tended to have higher levels of antibodies against SARS-CoV-2 Nonstructural Protein 1 (NSP1) and Methyltransferase (ME). We conclude that SARS-CoV-2 causes development of new-onset IgG autoantibodies in a significant proportion of hospitalized COVID-19 patients and are positively correlated with immune responses to SARS-CoV-2 proteins.

Symptomatic SARS-CoV-2 infections display specific IgG Fc structures (preprint)

The ongoing severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has caused a public health crisis that is exacerbated by our poor understanding of correlates of immunity. SARS-CoV-2 infection can cause Coronavirus Disease 2019 (COVID-19), with a spectrum of symptoms ranging from asymptomatic carriage to life threatening pneumonia and cytokine dysregulation [1-3]. Although antibodies have been shown in a variety of in vitro assays to promote coronavirus infections through mechanisms requiring interactions between IgG antibodies and Fc gamma receptors (Fc{gamma}Rs), the relevance of these observations to coronavirus infections in humans is not known [4-7]. In light of ongoing clinical trials examining convalescent serum therapy for COVID-19 patients and expedited SARS-CoV-2 vaccine testing in humans, it is essential to clarify the role of antibodies in the pathogenesis of COVID-19. Here we show that adults with PCR-diagnosed COVID-19 produce IgG antibodies with a specific Fc domain repertoire that is characterized by reduced fucosylation, a modification that enhances interactions with the activating Fc{gamma}R, Fc{gamma}RIIIa. Fc fucosylation was reduced when compared with SARS-CoV-2-seropositive children and relative to adults with symptomatic influenza virus infections. These results demonstrate an antibody correlate of symptomatic SARS-CoV-2 infections in adults and have implications for novel therapeutic strategies targeting Fc{gamma}RIIIa pathways.