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In a new respiratory virus pandemic, optimizing allocation of scarce medical resources becomes an urgent challenge. Infection prognosis takes on particular importance when allocating scarce antiviral antibodies and drugs, which are most effective when administered before the onset of severe disease. During arrival of the COVID-19 pandemic to the United States in 2020, we conducted a prognostic biomarker discovery and validation effort based upon metabolomic profiling with a liquid-chromatography-mass spectrometer (LC-MS) type used clinically for rapid toxicology. We obtained urine specimens from 163 patients presenting for evaluation. We obtained LC-MS profiles in the initial cohort and used machine learning methods to define a simplified urine metabolomic signature associated with respiratory failure or death by 90 days. This signature was composed of three metabotypes linked to intestinal microbiome metabolism and anticonvulsant use, with a receiver-operator characteristic area under the curve (ROC AUC) of 89.4%. Blinded application of this signature to the subsequent validation cohort yielded a ROC AUC of 81.2%. A model trained on the two baseline metabotypes present before intubation exhibited similar performance in the validation cohort. This study demonstrates the plausibility and promise of rapid metabolome-based prognostic discovery and validation in the opening wave of a pandemic. The approach used here could be used to inform therapeutic and resource allocation decisions early in a future epidemic.IMPORTANCEIn a new respiratory virus pandemic, the ability to identify patients at greatest risk for severe disease is essential to direct scarce medical resources to those most likely to benefit from them. Tools to predict disease severity are best developed early in a pandemic, but laboratory-based resources to develop these may be limited by available technology and by infection precautions. Here, we show that an accessible metabolic profiling approach could identify a prognostic signature of severe disease in the initial wave of COVID-19, when patients presenting for care often exceeded the available doses of convalescent plasma and remdesivir. In a future pandemic, this approach, alongside efforts to identify clinical disease severity predictors, could improve patient outcomes and facilitate therapeutic trials by identifying individuals at high risk for severe disease., Competing Interests: The authors declare no conflict of interest.

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. Human dLN spike-specific CD4 + follicular helper T (T FH ) cells exhibited heterogeneous phenotypes, including germinal center CD4 + T FH cells and CD4 + IL-10 + T FH cells. Analysis of an independent cohort of SARS-CoV-2-infected individuals 3 months and 6 months after infection found spike-specific CD4 + T cell profiles in blood that were distinct from those detected in blood 3 months and 6 months after BNT162b2 vaccination. Our findings provide an atlas of human spike-specific CD4 + T cell transcriptional phenotypes in the dLNs and blood following SARS-CoV-2 vaccination or infection., (© 2024. Springer Nature America, Inc.)

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. We also examined associations between the salivary and nasopharyngeal microbiome and age, COVID-19 symptoms, and blood cytokines. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection status, but not COVID-19 severity, was associated with community-level differences in the oral and nasopharyngeal microbiomes. Salivary and nasopharyngeal microbiome alpha diversity negatively correlated with age and were associated with fever and diarrhea. Oral Bifidobacterium, Lactobacillus, and Solobacterium were depleted in patients with severe COVID-19. Nasopharyngeal Paracoccus was depleted while nasopharyngeal Proteus, Cupravidus, and Lactobacillus were increased in patients with severe COVID-19. Further analysis revealed that the abundance of oral Bifidobacterium was negatively associated with plasma concentrations of known COVID-19 biomarkers interleukin 17F and monocyte chemoattractant protein-1. Our results suggest COVID-19 disease severity is associated with the relative abundance of certain bacterial taxa., (© 2022 Wiley Periodicals LLC.)

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. We measure the cells of the peripheral immune system from individuals who recovered from mild, moderate, severe or critical COVID-19 and focused only on those immune signatures returning to steady-state. Individuals that suffered from severe COVID-19 show reduced frequencies of T cell, mucosal-associated invariant T cell (MAIT) and dendritic cell (DC) subsets and altered chemokine receptor expression on several subsets, such as reduced levels of CCR1 and CCR2 on monocyte subsets. Furthermore, we find reduced frequencies of type I interferon-producing plasmacytoid DCs and altered IFNAR2 expression on several myeloid cells in individuals recovered from severe COVID-19. Thus, these data identify potential immune mechanisms contributing to severe COVID-19., (© 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.)

Introduction: Applying an intersectional framework, we examined sex and racial inequality in COVID-19-related employment loss (ie, job furlough, layoff, and reduced pay) and food insecurity (ie, quality and quantity of food eaten, food worry, and receipt of free meals or groceries) among residents in Saint Louis County, Missouri., Methods: We used cross-sectional data from adults aged 18 or older (N = 2,146), surveyed by using landlines or cellular phones between August 12, 2020, and October 27, 2020. We calculated survey-weighted prevalence of employment loss and food insecurity for each group (Black female, Black male, White female, White male). Odds ratios for each group were estimated by using survey-weighted binary and multinomial logistic regression models., Results: Black female residents had higher odds of being laid off, as compared with White male residents (OR = 2.61, 95% CI, 1.24-5.46). Both Black female residents (OR = 4.13, 95% CI, 2.29-7.45) and Black male residents (OR = 2.41, 95% CI, 1.15-5.07) were more likely to receive free groceries, compared with White male residents. Black female (OR = 4.25, 95% CI, 2.28-7.94) and White female residents (OR = 1.93, 95% CI, 1.04-3.60) had higher odds of sometimes worrying about food compared with White male residents. Black women also had higher odds of always or nearly always worrying about food, compared with White men (OR = 2.99, 95% CI, 1.52-5.87)., Conclusion: Black women faced the highest odds of employment loss and food insecurity, highlighting the disproportionate impact of COVID-19 among people with intersectional disadvantages of being both Black and female. Interventions to reduce employment loss and food insecurity can help reduce the disproportionately negative social effects among Black women.

Background: The true prevalence of COVID-19 is difficult to estimate due to the absence of random population-based testing. To estimate current and past COVID-19 infection prevalence in a large urban area, we conducted a population-based survey in St. Louis County, Missouri., Methods: The population-based survey of active infection (PCR) and seroprevalence (IgG antibodies) of adults (≥18 years) was conducted through random-digit dialing and targeted sampling of St. Louis County residents with oversampling of Black residents. Infection prevalence of residents was estimated using design-based and raking weighting., Results: Between August 17 and October 24, 2020, 1245 residents completed a survey and underwent PCR testing; 1073 residents completed a survey and underwent PCR and IgG testing or self-reported results. Weighted prevalence estimates of residents with active infection were 1.9% (95% CI, 0.4%-3.3%) and 5.6% were ever infected (95% CI, 3.3%-8.0%). Overall infection hospitalization and fatality ratios were 4.9% and 1.4%, respectively., Conclusions: Through October 2020, the percentage of residents that had ever been infected was relatively low. A markedly higher percentage of Black and other minorities compared to White residents were infected with COVID-19. The St. Louis region remained highly vulnerable to widespread infection in late 2020., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

Background: The rapid spread of the coronavirus disease 2019 (COVID-19) has created considerable strain on the physical and mental health of healthcare workers around the world. The effects have been acute for physician trainees-a unique group functioning simultaneously as learners and care providers with limited autonomy., Objective: To investigate the longitudinal effects of physician trainee exposure to patients being tested for COVID-19 on stress, anxiety, depression, and burnout using three surveys conducted during the early phase of the pandemic., Design: Longitudinal survey study., Participants: All physician trainees (N = 1375) at an academic medical center., Main Measure: Assess the relationship between repeated exposure to patients being tested for COVID-19 and stress, anxiety, depression, and burnout., Key Results: Three hundred eighty-nine trainees completed the baseline survey (28.3%). Of these, 191 and 136 completed the ensuing surveys. Mean stress, anxiety, and burnout decreased by 21% (95% confidence interval (CI): - 28 to - 12%; P < 0.001), 25% (95% CI: - 36 to - 11%; P < 0.001), and 13% (95% CI: - 18 to - 7%; P < 0.001), respectively, per survey. However, for each survey time point, there was mean increase in stress, anxiety, and burnout per additional exposure: stress [24% (95% CI: + 12 to + 38%; P < 0.001)], anxiety [22% (95% CI: + 2 to + 46%; P = 0.026)], and burnout [18% (95% CI: + 10 to + 28%; P < 0.001)]. For depression, the association between exposure was strongest for the third survey, where mean depression scores increased by 33% per additional exposure (95% CI: + 18 to + 50%; P < 0.001)., Conclusions: Training programs should adapt to address the detrimental effects of the "pileup" of distress associated with persistent exposure through adaptive programs that allow flexibility for time off and recovery., (© 2022. The Author(s) under exclusive licence to Society of General Internal Medicine.)

Background: The COVID-19 pandemic has been accompanied by the largest mobilization of therapeutic convalescent plasma (CCP) in over a century. Initial identification of high titer units was based on dose-response data using the Ortho VITROS IgG assay. The proliferation of severe acute respiratory syndrome coronavirus 2 serological assays and non-uniform application has led to uncertainty about their interrelationships. The purpose of this study was to establish correlations and analogous cutoffs between multiple serological assays., Methods: We compared the Ortho, Abbott, Roche, an anti-spike (S) ELISA, and a virus neutralization assay. Relationships relative to FDA-approved cutoffs under the CCP emergency use authorization were identified in convalescent plasma from a cohort of 79 donors from April 2020., Results: Relative to the neutralization assay, the spearman r value of the Ortho Clinical, Abbott, Roche, anti-S ELISA assays was 0.65, 0.59, 0.45, and 0.76, respectively. The best correlative index for establishing high-titer units was 3.87 signal-to-cutoff (S/C) for the Abbott, 13.82 cutoff index for the Roche, 1:1412 for the anti-S ELISA, 1:219 by the neutralization assay, and 15.9 S/C by the Ortho Clinical assay. The overall agreement using derived cutoffs compared to a neutralizing titer of 1:250 was 78.5% for Abbott, 74.7% for Roche, 83.5% for the anti-S ELISA, and 78.5% for Ortho Clinical., Discussion: Assays based on antibodies against the nucleoprotein were positively associated with neutralizing titers and the Ortho assay, although their ability to distinguish FDA high-titer specimens was imperfect. The resulting relationships help reconcile results from the large body of serological data generated during the COVID-19 pandemic., (© 2021 AABB.)

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. We discover that a panel of metabolites measured at the time of study entry successfully determines disease severity. Through analysis of longitudinal samples, we confirm that most of these markers are directly related to disease progression and that their levels return to baseline upon disease recovery. Finally, we validate that these metabolites are also altered in a hamster model of COVID-19., Competing Interests: The A.G.-S. laboratory has received research support from Pfizer, Pharmamar, Blade Therapeutics, Avimex, Dynavax, Kenall Manufacturing, ImmunityBio, Nanocomposix, Senhwa Biosciences, and 7Hills Pharma. A.G.-S. has consulting agreements for the following companies involving cash and/or stock: Vivaldi Biosciences, Contrafect, 7 Hills Pharma, Avimex, Vaxalto, Accurius, and Esperovax. G.J.P. is a scientific advisor for Cambridge Isotope Laboratories. The Patti laboratory has a collaboration agreement with Agilent Technologies and Thermo Fisher Scientific. All other authors declare no competing interests., (© 2021 The Author(s).)

Long-lived bone marrow plasma cells (BMPCs) are a persistent and essential source of protective antibodies 1-7 . Individuals who have recovered from COVID-19 have a substantially lower risk of reinfection with SARS-CoV-2 8-10 . Nonetheless, it has been reported that levels of anti-SARS-CoV-2 serum antibodies decrease rapidly in the first few months after infection, raising concerns that long-lived BMPCs may not be generated and humoral immunity against SARS-CoV-2 may be short-lived 11-13 . Here we show that in convalescent individuals who had experienced mild SARS-CoV-2 infections (n = 77), levels of serum anti-SARS-CoV-2 spike protein (S) antibodies declined rapidly in the first 4 months after infection and then more gradually over the following 7 months, remaining detectable at least 11 months after infection. Anti-S antibody titres correlated with the frequency of S-specific plasma cells in bone marrow aspirates from 18 individuals who had recovered from COVID-19 at 7 to 8 months after infection. S-specific BMPCs were not detected in aspirates from 11 healthy individuals with no history of SARS-CoV-2 infection. We show that S-binding BMPCs are quiescent, which suggests that they are part of a stable compartment. Consistently, circulating resting memory B cells directed against SARS-CoV-2 S were detected in the convalescent individuals. Overall, our results indicate that mild infection with SARS-CoV-2 induces robust antigen-specific, long-lived humoral immune memory in humans., (© 2021. The Author(s), under exclusive licence to Springer Nature Limited.)

Antibody tests can be tools for detecting current or past severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 [coronavirus disease 2019 (COVID-19)]) infections. Independent test evaluations are needed to document the performance with different sample sets. We evaluated six lateral flow assays (LFAs) and two laboratory-based tests (EUROIMMUN-SARS-CoV-2 ELISA and Abbott-Architect-SARS-CoV-2-IgG). We tested 210 plasma samples from 89 patients diagnosed with acute COVID-19. These samples were collected at different time points after the onset of symptoms. In addition, 80 convalescent plasma samples, and 168 pre-pandemic samples collected from adults in the United States and in Africa were tested. LFA performance varied widely, and some tests with high sensitivity had low specificity. LFA sensitivities were low (18.8-40.6%) for samples collected 0 to 3 days after symptom onset, and were greater (80.3-96.4%) for samples collected > 14 days after symptom onset. These results are similar to those obtained by ELISA (15.6% and 89.1%) and chemiluminescent microparticle assay (21.4% and 93.1%). The range of test specificity was between 82.7% and 97%. The combined use of two LFAs can increase specificity to more than 99% without a major loss of sensitivity. Because of suboptimal sensitivity with early COVID-19 samples and background reactivity with some pre-pandemic samples, none of the evaluated tests alone is reliable enough for definitive diagnosis of COVID-19 infection. However, antibody testing may be useful for assessing the status of the epidemic or vaccination campaign. Some of the LFAs had sensitivities and specificities that were comparable to those of more expensive laboratory tests, and these may be useful for seroprevalence surveys in resource-limited settings.

We examine the cellular and soluble determinants of coronavirus disease 2019 (COVID-19) relative to aging by performing mass cytometry in parallel with clinical blood testing and plasma proteomic profiling of ~4,700 proteins from 71 individuals with pulmonary disease and 148 healthy donors (25-80 years old). Distinct cell populations were associated with age (GZMK + CD8 + T cells and CD25 low CD4 + T cells) and with COVID-19 (TBET - EOMES - CD4 + T cells, HLA-DR + CD38 + CD8 + T cells and CD27 + CD38 + B cells). A unique population of TBET + EOMES + CD4 + T cells was associated with individuals with COVID-19 who experienced moderate, rather than severe or lethal, disease. Disease severity correlated with blood creatinine and urea nitrogen levels. Proteomics revealed a major impact of age on the disease-associated plasma signatures and highlighted the divergent contribution of hepatocyte and muscle secretomes to COVID-19 plasma proteins. Aging plasma was enriched in matrisome proteins and heart/aorta smooth muscle cell-specific proteins. These findings reveal age-specific and disease-specific changes associated with COVID-19, and potential soluble mediators of the physiological impact of COVID-19., (© 2021. The Author(s), under exclusive licence to Springer Nature America, Inc.)

Objectives: This article investigates the association between changes in electronic health record (EHR) use during the coronavirus disease 2019 (COVID-19) pandemic on the rate of burnout, stress, posttraumatic stress disorder (PTSD), depression, and anxiety among physician trainees (residents and fellows)., Methods: A total of 222 (of 1,375, 16.2%) physician trainees from an academic medical center responded to a Web-based survey. We compared the physician trainees who reported that their EHR use increased versus those whose EHR use stayed the same or decreased on outcomes related to depression, anxiety, stress, PTSD, and burnout using univariable and multivariable models. We examined whether self-reported exposure to COVID-19 patients moderated these relationships., Results: Physician trainees who reported increased use of EHR had higher burnout (adjusted mean, 1.48 [95% confidence interval [CI] 1.24, 1.71] vs. 1.05 [95% CI 0.93, 1.17]; p  = 0.001) and were more likely to exhibit symptoms of PTSD (adjusted mean = 15.09 [95% CI 9.12, 21.05] vs. 9.36 [95% CI 7.38, 11.28]; p  = 0.035). Physician trainees reporting increased EHR use outside of work were more likely to experience depression (adjusted mean, 8.37 [95% CI 5.68, 11.05] vs. 5.50 [95% CI 4.28, 6.72]; p  = 0.035). Among physician trainees with increased EHR use, those exposed to COVID-19 patients had significantly higher burnout (2.04, p  < 0.001) and depression scores (14.13, p  = 0.003)., Conclusion: Increased EHR use was associated with higher burnout, depression, and PTSD outcomes among physician trainees. Although preliminary, these findings have implications for creating systemic changes to manage the wellness and well-being of trainees., Competing Interests: T.K. reports grants from NIMH, grants from NCATS, grants from NINR, personal fees from Pfizer, outside the submitted work. B.A.E. reports grants from National Institute of Occupational Safety and Health, from null, during the conduct of the study; grants from National Institute of Occupational Safety and Health, grants from National Institute of Health, from null, outside the submitted work., (Thieme. All rights reserved.)

Background: The COVID-19 pandemic resulted in a transformation of clinical care practices to protect both patients and providers. These changes led to a decrease in patient volume, impacting physician trainee education due to lost clinical and didactic opportunities. We measured the prevalence of trainee concern over missed educational opportunities and investigated the risk factors leading to such concerns., Methods: All residents and fellows at a large academic medical center were invited to participate in a web-based survey in May of 2020. Participants responded to questions regarding demographic characteristics, specialty, primary assigned responsibility during the previous 2 weeks (clinical, education, or research), perceived concern over missed educational opportunities, and burnout. Multivariable logistic regression was used to assess the relationship between missed educational opportunities and the measured variables., Results: 22% (301 of 1375) of the trainees completed the survey. 47% of the participants were concerned about missed educational opportunities. Trainees assigned to education at home had 2.85 [95%CI 1.33-6.45] greater odds of being concerned over missed educational opportunities as compared with trainees performing clinical work. Trainees performing research were not similarly affected [aOR = 0.96, 95%CI (0.47-1.93)]. Trainees in pathology or radiology had 2.51 [95%CI 1.16-5.68] greater odds of concern for missed educational opportunities as compared with medicine. Trainees with greater concern over missed opportunities were more likely to be experiencing burnout (p = 0.038)., Conclusions: Trainees in radiology or pathology and those assigned to education at home were more likely to be concerned about their missed educational opportunities. Residency programs should consider providing trainees with research or at home clinical opportunities as an alternative to self-study should future need for reduced clinical hours arise.