Sialylated IgG induces the transcription factor REST in alveolar macrophages to protect against lung inflammation and severe influenza disease.

While most respiratory viral infections resolve with little harm to the host, severe symptoms arise when infection triggers an aberrant inflammatory response that damages lung tissue. Host regulators of virally induced lung inflammation have not been well defined. Here, we show that enrichment for sialylated, but not asialylated immunoglobulin G (IgG), predicted mild influenza disease in humans and was broadly protective against heterologous influenza viruses in a murine challenge model.

Multidimensional profiling of human T cells reveals high CD38 expression, marking recent thymic emigrants and age-related naive T cell remodeling.

Thymic involution is a key factor in human immune aging, leading to reduced thymic output and a decline in recent thymic emigrant (RTE) naive T cells in circulation. Currently, the precise definition of human RTEs and their corresponding cell surface markers lacks clarity. Analysis of single-cell RNA-seq/ATAC-seq data distinguished RTEs by the expression of SOX4, IKZF2, and TOX and CD38 protein, whereby surface CD38 expression universally identified CD8 and CD4 RTEs.

CD4 T cells exhibit distinct transcriptional phenotypes in the lymph nodes and blood following mRNA vaccination in humans.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and mRNA vaccination induce robust CD4 T cell responses. Using single-cell transcriptomics, here, we evaluated CD4 T cells specific for the SARS-CoV-2 spike protein in the blood and draining lymph nodes (dLNs) of individuals 3 months and 6 months after vaccination with the BNT162b2 mRNA vaccine. We analyzed 1,277 spike-specific CD4 T cells, including 238 defined using Trex, a deep learning-based reverse epitope mapping method to predict antigen specificity.

Structural Mapping of Polyclonal IgG Responses to HA After Influenza Virus Vaccination or Infection.

Cellular and molecular characterization of immune responses elicited by influenza virus infection and seasonal vaccination have informed efforts to improve vaccine efficacy, breadth, and longevity. Here, we use negative stain electron microscopy polyclonal epitope mapping (nsEMPEM) to structurally characterize the humoral IgG antibody responses to hemagglutinin (HA) from human patients vaccinated with a seasonal quadrivalent flu vaccine or infected with influenza A viruses. Our data show that both vaccinated and infected patients had humoral IgGs targeting highly conserved regions on both H1 and H3 subtype HAs, including the stem and anchor, which are targets for universal influenza vaccine design.

Quantitative SARS-CoV-2 RT-PCR and Bronchoalveolar Cytokine Concentrations Redefine the COVID-19 Phenotypes in Critically Ill Patients.

Rationale: Recent studies suggest that both hypo- and hyperinflammatory acute respiratory distress syndrome (ARDS) phenotypes characterize severe COVID-19-related pneumonia. The role of lung Severe Acute Respiratory Syndrome - Coronavirus 2 (SARS-CoV-2) viral load in contributing to these phenotypes remains unknown.

Objectives: To redefine COVID-19 ARDS phenotypes when considering quantitative SARS-CoV-2 RT-PCR in the bronchoalveolar lavage of intubated patients.

Emergency medicine residency pathways for MD/PhD trainees: A national cross-sectional study of physician-scientist training programs.

Background: Combined clinical and research training is common in residency programs outside emergency medicine (EM), and these pathways are particularly valuable for combined MD/PhD graduates planning to pursue a career as a physician-scientist. However, EM departments may not know what resources to provide these trainees during residency to create research-focused, productive, future faculty, and trainees may not know which programs support their goal of becoming a physician-scientist in EM. The objective of this study was to describe research training and resources available to MD/PhD graduates in EM residency training with a focus on dedicated research pathways.

Predicting severe disease in patients diagnosed with seasonal influenza in the emergency department.

Objectives: We sought to develop an evidence-based tool to risk stratify patients diagnosed with seasonal influenza in the emergency department (ED).

Methods: We performed a single-center retrospective cohort study of all adult patients diagnosed with influenza in a large tertiary care ED between 2008 and 2018. We evaluated demographics, triage vital signs, chest x-ray and laboratory results obtained in the ED.

Assessment of antibodies in the upper and lower human respiratory tract at steady state and after respiratory viral infection.

Objectives: There is an increasing appreciation for the need to study mucosal antibody responses in humans. Our aim was to determine the utility of different types of samples from the human respiratory tract, specifically nasopharyngeal (NP) swabs obtained for diagnostic purposes and bronchoalveolar lavage (BAL) obtained in outpatient and inpatient settings.

Methods: We analysed antibody levels in plasma and NP swabs from 67 individuals with acute influenza as well as plasma and BAL from individuals undergoing bronchoscopy, including five control subjects as well as seven moderately and seven severely ill subjects with a respiratory viral infection.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways.

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes.

Persons with HIV Develop Spike-Specific Lymph Node Germinal Center Responses following SARS-CoV-2 Vaccination.

COVID-19 disproportionately affects persons with HIV (PWH) in worldwide locations with limited access to SARS-CoV-2 vaccines. PWH exhibit impaired immune responses to some, but not all, vaccines. Lymph node (LN) biopsies from PWH demonstrate abnormal LN structure, including dysregulated germinal center (GC) architecture.

The salivary and nasopharyngeal microbiomes are associated with SARS-CoV-2 infection and disease severity.

Emerging evidence suggests the oral and upper respiratory microbiota may play important roles in modulating host immune responses to viral infection. As the host microbiome may be involved in the pathophysiology of coronavirus disease 2019 (COVID-19), we investigated associations between the oral and nasopharyngeal microbiome and COVID-19 severity. We collected saliva (n = 78) and nasopharyngeal swab (n = 66) samples from a COVID-19 cohort and characterized the microbiomes using 16S ribosomal RNA gene sequencing.

Immune phenotypes that are associated with subsequent COVID-19 severity inferred from post-recovery samples.

Severe COVID-19 causes profound immune perturbations, but pre-infection immune signatures contributing to severe COVID-19 remain unknown. Genome-wide association studies (GWAS) identified strong associations between severe disease and several chemokine receptors and molecules from the type I interferon pathway. Here, we define immune signatures associated with severe COVID-19 using high-dimensional flow cytometry.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer and coronary disease pathways.

Identification of the plasma proteomic changes of Coronavirus disease 2019 (COVID-19) is essential to understanding the pathophysiology of the disease and developing predictive models and novel therapeutics. We performed plasma deep proteomic profiling from 332 COVID-19 patients and 150 controls and pursued replication in an independent cohort (297 cases and 76 controls) to find potential biomarkers and causal proteins for three COVID-19 outcomes (infection, ventilation, and death). We identified and replicated 1,449 proteins associated with any of the three outcomes (841 for infection, 833 for ventilation, and 253 for death) that can be query on a web portal ( https://covid.

Germinal centre-driven maturation of B cell response to mRNA vaccination.

Germinal centres (GC) are lymphoid structures in which B cells acquire affinity-enhancing somatic hypermutations (SHM), with surviving clones differentiating into memory B cells (MBCs) and long-lived bone marrow plasma cells (BMPCs). SARS-CoV-2 mRNA vaccination induces a persistent GC response that lasts for at least six months in humans. The fate of responding GC B cells as well as the functional consequences of such persistence remain unknown.

Harnessing the Potential of Multiomics Studies for Precision Medicine in Infectious Disease.

The field of infectious diseases currently takes a reactive approach and treats infections as they present in patients. Although certain populations are known to be at greater risk of developing infection (eg, immunocompromised), we lack a systems approach to define the true risk of future infection for a patient. Guided by impressive gains in "omics" technologies, future strategies to infectious diseases should take a precision approach to infection through identification of patients at intermediate and high-risk of infection and deploy targeted preventative measures (ie, prophylaxis).

Germinal centre-driven maturation of B cell response to SARS-CoV-2 vaccination.

Germinal centres (GC) are lymphoid structures where vaccine-responding B cells acquire affinity-enhancing somatic hypermutations (SHM), with surviving clones differentiating into memory B cells (MBCs) and long-lived bone marrow plasma cells (BMPCs) . Induction of the latter is a hallmark of durable immunity after vaccination . SARS-CoV-2 mRNA vaccination induces a robust GC response in humans , but the maturation dynamics of GC B cells and propagation of their progeny throughout the B cell diaspora have not been elucidated.

Increased complement activation is a distinctive feature of severe SARS-CoV-2 infection.

Complement activation has been implicated in the pathogenesis of severe SARS-CoV-2 infection. However, it remains to be determined whether increased complement activation is a broad indicator of critical illness (and thus, no different in COVID-19). It is also unclear which pathways are contributing to complement activation in COVID-19, and if complement activation is associated with certain features of severe SARS-CoV-2 infection, such as endothelial injury and hypercoagulability.

Comprehensive Immunologic Evaluation of Bronchoalveolar Lavage Samples from Human Patients with Moderate and Severe Seasonal Influenza and Severe COVID-19.

Infection with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) or seasonal influenza may lead to respiratory failure requiring intubation and mechanical ventilation. The pathophysiology of this respiratory failure is attributed to local immune dysregulation, but how the immune response to viral infection in the lower airways of the human lung differs between individuals with respiratory failure and those without is not well understood. We used quantitative multiparameter flow cytometry and multiplex cytokine assays to evaluate matched blood and bronchoalveolar lavage (BAL) samples from control human subjects, subjects with symptomatic seasonal influenza who did not have respiratory failure, and subjects with severe seasonal influenza or SARS-CoV-2 infection with respiratory failure.

Longitudinal metabolomics of human plasma reveals prognostic markers of COVID-19 disease severity.

There is an urgent need to identify which COVID-19 patients will develop life-threatening illness so that medical resources can be optimally allocated and rapid treatment can be administered early in the disease course, when clinical management is most effective. To aid in the prognostic classification of disease severity, we perform untargeted metabolomics on plasma from 339 patients, with samples collected at six longitudinal time points. Using the temporal metabolic profiles and machine learning, we build a predictive model of disease severity.