Patrick Wong's research while affiliated with Yale-New Haven Hospital and other places

T cell-B cell interaction is the key immune response to protect the host from severe viral infection. However, how T cells support B cells to exert protective humoral immunity in humans is not well understood. Here, we use COVID-19 as a model of acute viral infections and analyze CD4⁺ T cell subsets associated with plasmablast expansion and clinical outcome. Peripheral helper T cells (Tph cells; denoted as PD-1highCXCR5–CD4⁺ T cells) are significantly increased, as are plasmablasts. Tph cells exhibit “B cell help” signatures and induce plasmablast differentiation in vitro. Interestingly, expanded plasmablasts show increased CXCR3 expression, which is positively correlated with higher frequency of activated Tph cells and better clinical outcome. Mechanistically, Tph cells help B cell differentiation and produce more interferon γ (IFNγ), which induces CXCR3 expression on plasmablasts. These results elucidate a role for Tph cells in regulating protective B cell response during acute viral infection.

As the biomedical community produces datasets that are increasingly complex and high dimensional, there is a need for more sophisticated computational tools to extract biological insights. We present Multiscale PHATE, a method that sweeps through all levels of data granularity to learn abstracted biological features directly predictive of disease outcome. Built on a coarse-graining process called diffusion condensation, Multiscale PHATE learns a data topology that can be analyzed at coarse resolutions for high-level summarizations of data and at fine resolutions for detailed representations of subsets. We apply Multiscale PHATE to a coronavirus disease 2019 (COVID-19) dataset with 54 million cells from 168 hospitalized patients and find that patients who die show CD16hiCD66blo neutrophil and IFN-γ+ granzyme B+ Th17 cell responses. We also show that population groupings from Multiscale PHATE directly fed into a classifier predict disease outcome more accurately than naive featurizations of the data. Multiscale PHATE is broadly generalizable to different data types, including flow cytometry, single-cell RNA sequencing (scRNA-seq), single-cell sequencing assay for transposase-accessible chromatin (scATAC-seq), and clinical variables. Disease signatures in high-dimensional biomedical data are detected with a visualization algorithm.

Significance Chilblain diagnoses have increased during the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic and have been attributed to viral infection and a subsequent robust antiviral immune response. As a result, providers have managed these cases differently than idiopathic chilblains, which are associated with cold exposure. The relationship between pandemic chilblains and SARS-CoV-2 infection, however, remains unclear as most patients do not test positive for SARS-CoV-2–specific PCR or antibodies. To better understand this disconnect, we enrolled cases of pandemic chilblains in a study and performed detailed immune profiling of antibody and T cell responses. Additionally, we compared immunohistochemical staining of pandemic chilblains with prepandemic tissues. Our results do not support SARS-CoV-2 as the cause of the increased chilblain incidence.

Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100A hi /HLA-DR lo classical monocytes and activated LAG-3 hi T cells are hallmarks of progressive disease and highlights the abnormal MHC-II/LAG-3 interaction on myeloid and T cells, respectively. We also find skewed T cell receptor repertories in expanded effector CD8 ⁺ clones, unmutated IGHG ⁺ B cell clones, and mutated B cell clones with stable somatic hypermutation frequency over time. In conclusion, our in-depth immune profiling reveals dyssynchrony of the innate and adaptive immune interaction in progressive COVID-19.

Antibodies secreted at the mucosal surface play an integral role in immune defense by serving to neutralize the pathogen and promote its elimination at the site of entry. Secretory immunoglobulin A (IgA) is a predominant Ig isotype at mucosal surfaces whose epithelial cells express polymeric Ig receptor capable of transporting dimeric IgA to the lumen. Although the role of IgA in intestinal mucosa has been extensively studied, the cell types responsible for secreting the IgA that protects the host against pathogens in the lower respiratory tract are less clear. Here, using a mouse model of influenza virus infection, we demonstrate that intranasal, but not systemic, immunization induces local IgA secretion in the bronchoalveolar space. Using single-cell RNA sequencing, we found a heterogeneous population of IgA-expressing cells within the respiratory mucosa, including tissue-resident memory B cells, plasmablasts, and plasma cells. IgA-secreting cell establishment within the lung required CXCR3. An intranasally administered protein-based vaccine also led to the establishment of IgA-secreting cells in the lung, but not when given intramuscularly or intraperitoneally. Last, local IgA secretion correlated with superior protection against secondary challenge with homologous and heterologous virus infection than circulating antibodies alone. These results provide key insights into establishment of protective immunity in the lung based on tissue-resident IgA-secreting B cells and inform vaccine strategies designed to elicit highly effective immune protection against respiratory virus infections.

Background The underlying immunologic deficiencies enabling SARS-CoV-2 reinfection are currently unknown. We describe deep longitudinal immune profiling of a transplant recipient hospitalized twice for COVID-19. Methods A 66-year-old male renal transplant recipient was hospitalized with COVID-19 March 2020 then readmitted to the hospital with COVID-19 233 days after initial diagnosis. Virologic and immunologic investigation were performed on samples from the primary and secondary infections. Results Whole viral genome sequencing and phylogenic analysis revealed that viruses causing both infections were caused by distinct genetic lineages without evidence of immune escape mutations. Longitudinal comparison of cellular and humoral responses during primary SARS-CoV-2 infection revealed that this patient responded to the primary infection with low neutralization titer anti-SARS-CoV-2 antibodies that were likely present at the time of reinfection. Discussion The development of neutralizing antibodies and humoral memory responses in this patient failed to confer protection against reinfection, suggesting that they were below a neutralizing titer threshold or that additional factors may be required for efficient prevention of SARS-CoV-2 reinfection. Development of poorly neutralizing antibodies may have been due to profound and relatively specific reduction in naïve CD4 T-cell pools. Seropositivity alone may not be a perfect correlate of protection in immunocompromised patients.

COVID-19 manifests with a wide spectrum of clinical phenotypes that are characterized by exaggerated and misdirected host immune responses1–6. While pathological innate immune activation is well documented in severe disease¹, the impact of autoantibodies on disease progression is less defined. Here, we used a high-throughput autoantibody (AAb) discovery technique called Rapid Extracellular Antigen Profiling (REAP)⁷ to screen a cohort of 194 SARS-CoV-2 infected COVID-19 patients and healthcare workers for autoantibodies against 2,770 extracellular and secreted proteins (the “exoproteome”). We found that COVID-19 patients exhibit dramatic increases in autoantibody reactivities compared to uninfected controls, with a high prevalence of autoantibodies against immunomodulatory proteins including cytokines, chemokines, complement components, and cell surface proteins. We established that these autoantibodies perturb immune function and impair virological control by inhibiting immunoreceptor signaling and by altering peripheral immune cell composition, and found that murine surrogates of these autoantibodies exacerbate disease severity in a mouse model of SARS-CoV-2 infection. Analysis of autoantibodies against tissue-associated antigens revealed associations with specific clinical characteristics and disease severity. In summary, these findings implicate a pathological role for exoproteome-directed autoantibodies in COVID-19 with diverse impacts on immune functionality and associations with clinical outcomes.

Coronavirus disease 2019 (COVID-19) has poorer clinical outcomes in males than in females, and immune responses underlie these sex-related differences. Because immune responses are, in part, regulated by metabolites, we examined the serum metabolomes of COVID-19 patients. In male patients, kynurenic acid (KA) and a high KA-to-kynurenine (K) ratio (KA:K) positively correlated with age and with inflammatory cytokines and chemokines and negatively correlated with T cell responses. Males that clinically deteriorated had a higher KA:K than those that stabilized. KA inhibits glutamate release, and glutamate abundance was lower in patients that clinically deteriorated and correlated with immune responses. Analysis of data from the Genotype-Tissue Expression (GTEx) project revealed that the expression of the gene encoding the enzyme that produces KA, kynurenine aminotrans-ferase, correlated with cytokine abundance and activation of immune responses in older males. This study reveals that KA has a sex-specific link to immune responses and clinical outcomes in COVID-19, suggesting a positive feedback between metabolites and immune responses in males.

Recent studies have provided insights into innate and adaptive immune dynamics in coronavirus disease 2019 (COVID-19). However, the exact features of antibody responses that govern COVID-19 disease outcomes remain unclear. In this study, we analyzed humoral immune responses in 229 patients with asymptomatic, mild, moderate and severe COVID-19 over time to probe the nature of antibody responses in disease severity and mortality. We observed a correlation between anti-spike (S) immunoglobulin G (IgG) levels, length of hospitalization and clinical parameters associated with worse clinical progression. Although high anti-S IgG levels correlated with worse disease severity, such correlation was time dependent. Deceased patients did not have higher overall humoral response than discharged patients. However, they mounted a robust, yet delayed, response, measured by anti-S, anti-receptor-binding domain IgG and neutralizing antibody (NAb) levels compared to survivors. Delayed seroconversion kinetics correlated with impaired viral control in deceased patients. Finally, although sera from 85% of patients displayed some neutralization capacity during their disease course, NAb generation before 14 d of disease onset emerged as a key factor for recovery. These data indicate that COVID-19 mortality does not correlate with the cross-sectional antiviral antibody levels per se but, rather, with the delayed kinetics of NAb production. A longitudinal analysis of humoral immune responses in patients with COVID-19 with varying disease severities reveals that mortality does not correlate with antiviral antibody levels but, instead, with slower seroconversion.