1
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Pisanic N, Antar AAR, Hetrich MK, Demko ZO, Zhang X, Spicer K, Kruczynski KL, Detrick B, Clarke W, Knoll MD, Thomas DL, Dawood FS, Veguilla V, Karron RA, Manabe YC, Heaney CD. Early, Robust Mucosal Secretory Immunoglobulin A but not Immunoglobulin G Response to Severe Acute Respiratory Syndrome Coronavirus 2 Spike in Oral Fluid Is Associated With Faster Viral Clearance and Coronavirus Disease 2019 Symptom Resolution. J Infect Dis 2025; 231:121-130. [PMID: 39269503 PMCID: PMC11793072 DOI: 10.1093/infdis/jiae447] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 08/22/2024] [Accepted: 09/11/2024] [Indexed: 09/15/2024] Open
Abstract
BACKGROUND Efforts are underway to support the development of novel mucosal coronavirus disease 2019 (COVID-19) vaccines. However, there is limited consensus about the complementary role of mucosal immunity in disease progression and how to evaluate immunogenicity of mucosal vaccines. This study investigated the role of oral mucosal antibody responses in viral clearance and COVID-19 symptom duration. METHODS Participants with polymerase chain reaction (PCR)-confirmed severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection provided oral fluid for testing with SARS-CoV-2 antibody multiplex assays, nasal swabs for reverse-transcription PCR, and symptom information at up to 8 follow-ups from April 2020 to February 2022. RESULTS High and moderate oral fluid anti-spike (S) secretory IgA (SIgA) postinfection was associated with significantly faster viral clearance and symptom resolution across age groups with effect sizes equivalent to prior COVID-19 vaccine immunity at the time of infection. Those with high and moderate anti-S SIgA cleared the virus 14 (95% confidence interval [CI], 10-18) days and recovered 9-10 (95% CI, 6-14) days earlier. Delayed and higher anti-S IgG was associated with significantly longer time to clearance and recovery. Experiencing symptoms >4 weeks was associated with lower anti-receptor-binding domain SIgA 15-30 days after infection onset (P < .001). CONCLUSIONS Robust mucosal SIgA early postinfection appears to support faster clearance of SARS-CoV-2 and recovery from COVID-19 symptoms. This research underscores the importance of harmonizing mucosal immune response assays to evaluate new mucosal vaccines.
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Affiliation(s)
- Nora Pisanic
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Annukka A R Antar
- Division of Infectious Diseases, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Marissa K Hetrich
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Zoe O Demko
- Division of Infectious Diseases, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Xueyan Zhang
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Kristoffer Spicer
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Kate L Kruczynski
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Barbara Detrick
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - William Clarke
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Maria Deloria Knoll
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - David L Thomas
- Division of Infectious Diseases, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of Pathology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
| | - Fatimah S Dawood
- COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Vic Veguilla
- COVID-19 Response, Centers for Disease Control and Prevention, Atlanta, Georgia
| | - Ruth A Karron
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Yukari C Manabe
- Division of Infectious Diseases, Department of Medicine, School of Medicine, Johns Hopkins University, Baltimore, Maryland
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
- Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
| | - Christopher D Heaney
- Department of Environmental Health and Engineering, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland
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2
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Dhakal S, Yin A, Escarra-Senmarti M, Demko ZO, Pisanic N, Johnston TS, Trejo-Zambrano MI, Kruczynski K, Lee JS, Hardick JP, Shea P, Shapiro JR, Park HS, Parish MA, Caputo C, Ganesan A, Mullapudi SK, Gould SJ, Betenbaugh MJ, Pekosz A, Heaney CD, Antar AAR, Manabe YC, Cox AL, Karaba AH, Andrade F, Zeger SL, Klein SL. Application of machine learning algorithms to identify serological predictors of COVID-19 severity and outcomes. COMMUNICATIONS MEDICINE 2024; 4:249. [PMID: 39592832 PMCID: PMC11599591 DOI: 10.1038/s43856-024-00658-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/25/2023] [Accepted: 10/29/2024] [Indexed: 11/28/2024] Open
Abstract
BACKGROUND Critically ill hospitalized patients with COVID-19 have greater antibody titers than those with mild to moderate illness, but their association with recovery or death from COVID-19 has not been characterized. METHODS In a cohort study of 178 COVID-19 patients, 73 non-hospitalized and 105 hospitalized patients, mucosal swabs and plasma samples were collected at hospital enrollment and up to 3 months post-enrollment (MPE) to measure virus RNA, cytokines/chemokines, binding antibodies, ACE2 binding inhibition, and Fc effector antibody responses against SARS-CoV-2. The association of demographic variables and more than 20 serological antibody measures with intubation or death due to COVID-19 was determined using machine learning algorithms. RESULTS Predictive models reveal that IgG binding and ACE2 binding inhibition responses at 1 MPE are positively and anti-Spike antibody-mediated complement activation at enrollment is negatively associated with an increased probability of intubation or death from COVID-19 within 3 MPE. CONCLUSIONS At enrollment, serological antibody measures are more predictive than demographic variables of subsequent intubation or death among hospitalized COVID-19 patients.
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Affiliation(s)
- Santosh Dhakal
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Diagnostic Medicine/Pathobiology, College of Veterinary Medicine, Kansas State University, Manhattan, KS, USA
| | - Anna Yin
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Zoe O Demko
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Nora Pisanic
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Trevor S Johnston
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Kate Kruczynski
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - John S Lee
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Justin P Hardick
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Patrick Shea
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Janna R Shapiro
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Han-Sol Park
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Maclaine A Parish
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Christopher Caputo
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Abhinaya Ganesan
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Sarika K Mullapudi
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Stephen J Gould
- Department of Biological Chemistry, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Michael J Betenbaugh
- Department of Chemical and Biomolecular Engineering, Advanced Mammalian Biomanufacturing Innovation Center, Johns Hopkins University, Baltimore, MD, USA
| | - Andrew Pekosz
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Christopher D Heaney
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Annukka A R Antar
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Yukari C Manabe
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Andrea L Cox
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Andrew H Karaba
- Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Felipe Andrade
- Division of Rheumatology, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Scott L Zeger
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Sabra L Klein
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
- Division of Infectious Diseases, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, MD, USA.
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
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3
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Gigot C, Pisanic N, Spicer K, Davis MF, Kruczynski K, Gregory Rivera M, Koehler K, Hall DJ, Hall DJ, Heaney CD. SARS-CoV-2 antibody prevalence by industry, workplace characteristics, and workplace infection prevention and control measures, North Carolina, USA, 2021 to 2022. Ann Work Expo Health 2024; 68:881-889. [PMID: 39102901 PMCID: PMC11427537 DOI: 10.1093/annweh/wxae067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2024] [Accepted: 07/16/2024] [Indexed: 08/07/2024] Open
Abstract
The COVID-19 pandemic has disproportionately affected workers in certain industries and occupations, and the workplace can be a high-risk setting for SARS-CoV-2 transmission. In this study, we measured SARS-CoV-2 antibody prevalence and identified work-related risk factors in a population primarily working at industrial livestock operations. We used a multiplex salivary SARS-CoV-2 IgG assay to determine infection-induced antibody prevalence among 236 adult (≥18 yr) North Carolina residents between February 2021 and August 2022. We used the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System (NIOCCS) to classify employed participants' industry. Most participants (55%, 95% confidence interval [CI] 49% to 62%) were infection-induced IgG positive, including 71% (95% CI 60% to 83%) of animal slaughtering and processing industry workers, 1.5 to 4.3 times North Carolina general population infection-induced seroprevalence estimates during overlapping time periods. Considering self-reported diagnostic test positivity and vaccination history in addition to antibodies, the proportion of participants with evidence of prior infection increased slightly to 61% (95% CI 55% to 67%), including 75% (95% CI 64% to 87%) of animal slaughtering and processing workers. Participants with more than 1000 compared to 10 or fewer coworkers at their jobsite had higher odds of prior infection (adjusted odds ratio 4.5, 95% CI 1.0 to 21.0). This study contributes evidence of the severe and disproportionate impacts of COVID-19 on animal slaughtering and processing workers and workers in large congregate settings.
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Affiliation(s)
- Carolyn Gigot
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Nora Pisanic
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Kristoffer Spicer
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Meghan F Davis
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Johns Hopkins P.O.E. Total Worker Health(R) Center in Mental Health, Baltimore, MD, United States
- Division of Infectious Diseases and Department of Molecular and Comparative Pathobiology, Johns Hopkins School of Medicine, Baltimore, MD, United States
| | - Kate Kruczynski
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Magdielis Gregory Rivera
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Kirsten Koehler
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - D J Hall
- Rural Empowerment Association for Community Help, Warsaw, NC, United States
| | - Devon J Hall
- Rural Empowerment Association for Community Help, Warsaw, NC, United States
| | - Christopher D Heaney
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Department of International Health, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
- Community Science and Innovation for Environmental Justice Initiative, Center for a Livable Future, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
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4
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Mallory M, Munt JE, Narowski TM, Castillo I, Cuadra E, Pisanic N, Fields P, Powers JM, Dickson A, Harris R, Wargowsky R, Moran S, Allabban A, Raphel K, McCaffrey TA, Brien JD, Heaney CD, Lafleur JE, Baric RS, Premkumar L. COVID-19 point-of-care tests can identify low-antibody individuals: In-depth immunoanalysis of boosting benefits in a healthy cohort. SCIENCE ADVANCES 2024; 10:eadi1379. [PMID: 38865463 PMCID: PMC11168476 DOI: 10.1126/sciadv.adi1379] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2023] [Accepted: 05/08/2024] [Indexed: 06/14/2024]
Abstract
The recommended COVID-19 booster vaccine uptake is low. At-home lateral flow assay (LFA) antigen tests are widely accepted for detecting infection during the pandemic. Here, we present the feasibility and potential benefits of using LFA-based antibody tests as a means for individuals to detect inadequate immunity and make informed decisions about COVID-19 booster immunization. In a health care provider cohort, we investigated the changes in the breadth and depth of humoral and T cell immune responses following mRNA vaccination and boosting in LFA-positive and LFA-negative antibody groups. We show that negative LFA antibody tests closely reflect the lack of functional humoral immunity observed in a battery of sophisticated immune assays, while positive results do not necessarily reflect adequate immunity. After booster vaccination, both groups gain depth and breadth of systemic antibodies against evolving SARS-CoV-2 and related viruses. Our findings show that LFA-based antibody tests can alert individuals about inadequate immunity against COVID-19, thereby increasing booster shots and promoting herd immunity.
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Affiliation(s)
- Michael Mallory
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Jennifer E. Munt
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Tara M. Narowski
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Izabella Castillo
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Edwing Cuadra
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
| | - Nora Pisanic
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - John M. Powers
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Alexandria Dickson
- Department of Molecular Microbiology and Immunology, Saint Louis University, Saint Louis, MO, USA
| | - Rohan Harris
- Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA
| | - Richard Wargowsky
- Department of Medicine, Division of Genomic Medicine, The George Washington University Medical Center, Washington, DC, USA
| | - Seamus Moran
- Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA
| | - Ahmed Allabban
- Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA
| | - Kristin Raphel
- Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA
| | - Timothy A. McCaffrey
- Department of Medicine, Division of Genomic Medicine, The George Washington University Medical Center, Washington, DC, USA
| | - James D. Brien
- Department of Molecular Microbiology and Immunology, Saint Louis University, Saint Louis, MO, USA
| | - Christopher D. Heaney
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Department of International Health, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - John E. Lafleur
- Department Emergency Medicine, George Washington University School of Medicine, Washington, DC, USA
| | - Ralph S. Baric
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
- Department of Epidemiology, UNC Chapel Hill School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Lakshmanane Premkumar
- Department of Microbiology and Immunology, University of North Carolina School of Medicine, Chapel Hill, NC, USA
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5
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Gigot C, Pisanic N, Spicer K, Davis MF, Kruczynski K, Rivera MG, Koehler K, Hall DJ, Hall DJ, Heaney CD. SARS-CoV-2 antibody prevalence by industry, workplace characteristics, and workplace infection prevention and control measures, North Carolina, 2021 to 2022. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.06.24303821. [PMID: 38496588 PMCID: PMC10942491 DOI: 10.1101/2024.03.06.24303821] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Background The COVID-19 pandemic has disproportionately affected workers in certain industries and occupations, and the workplace can be a high risk setting for SARS-CoV-2 transmission. In this study, we measured SARS-CoV-2 antibody prevalence and identified work-related risk factors in a population primarily working at industrial livestock operations. Methods We used a multiplex salivary SARS-CoV-2 IgG antibody assay to determine infection-induced antibody prevalence among 236 adult (≥18 years) North Carolina residents between February 2021 and August 2022. We used the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System (NIOCCS) to classify employed participants' industry and compared infection-induced IgG prevalence by participant industry and with the North Carolina general population. We also combined antibody results with reported SARS-CoV-2 molecular test positivity and vaccination history to identify evidence of prior infection. We used logistic regression to estimate odds ratios of prior infection by potential work-related risk factors, adjusting for industry and date. Results Most participants (55%) were infection-induced IgG positive, including 71% of animal slaughtering and processing industry workers, which is 1.5 to 4.3 times higher compared to the North Carolina general population, as well as higher than molecularly-confirmed cases and the only other serology study we identified of animal slaughtering and processing workers. Considering questionnaire results in addition to antibodies, the proportion of participants with evidence of prior infection increased slightly, to 61%, including 75% of animal slaughtering and processing workers. Participants with more than 1000 compared to 10 or fewer coworkers at their jobsite had higher odds of prior infection (adjusted odds ratio [aOR] 4.5, 95% confidence interval [CI] 1.0 to 21.0). Conclusions This study contributes evidence of the severe and disproportionate impacts of COVID-19 on animal processing and essential workers and workers in large congregate settings. We also demonstrate the utility of combining non-invasive biomarker and questionnaire data for the study of workplace exposures.
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Affiliation(s)
- Carolyn Gigot
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Nora Pisanic
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kristoffer Spicer
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Meghan F. Davis
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Johns Hopkins P.O.E. Total Worker Health(R) Center in Mental Health, Baltimore, Maryland, USA
- Division of Infectious Diseases and Department of Molecular and Comparative Pathobiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Kate Kruczynski
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Magdielis Gregory Rivera
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Kirsten Koehler
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - D. J. Hall
- Rural Empowerment Association for Community Help, Warsaw, North Carolina, USA
| | - Devon J. Hall
- Rural Empowerment Association for Community Help, Warsaw, North Carolina, USA
| | - Christopher D. Heaney
- Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Department of International Health Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Community Science and Innovation for Environmental Justice Initiative, Center for a Livable Future, Department of Environmental Health and Engineering, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
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6
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Klein S, Dhakal S, Yin A, Escarra-Senmarti M, Demko Z, Pisanic N, Johnston T, Trejo-Zambrano M, Kruczynski K, Lee J, Hardick J, Shea P, Shapiro J, Park HS, Parish M, Caputo C, Ganesan A, Mullapudi S, Gould S, Betenbaugh M, Pekosz A, Heaney CD, Antar A, Manabe Y, Cox A, Karaba A, Andrade F, Zeger S. Application of machine learning models to identify serological predictors of COVID-19 severity and outcomes. RESEARCH SQUARE 2023:rs.3.rs-3463155. [PMID: 38014049 PMCID: PMC10680931 DOI: 10.21203/rs.3.rs-3463155/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
Critically ill people with COVID-19 have greater antibody titers than those with mild to moderate illness, but their association with recovery or death from COVID-19 has not been characterized. In 178 COVID-19 patients, 73 non-hospitalized and 105 hospitalized patients, mucosal swabs and plasma samples were collected at hospital enrollment and up to 3 months post-enrollment (MPE) to measure virus RNA, cytokines/chemokines, binding antibodies, ACE2 binding inhibition, and Fc effector antibody responses against SARS-CoV-2. The association of demographic variables and >20 serological antibody measures with intubation or death due to COVID-19 was determined using machine learning algorithms. Predictive models revealed that IgG binding and ACE2 binding inhibition responses at 1 MPE were positively and C1q complement activity at enrollment was negatively associated with an increased probability of intubation or death from COVID-19 within 3 MPE. Serological antibody measures were more predictive than demographic variables of intubation or death among COVID-19 patients.
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Affiliation(s)
- Sabra Klein
- Johns Hopkins Bloomberg School of Public Health
| | | | - Anna Yin
- Johns Hopkins Bloomberg School of Public Health
| | | | | | | | | | | | | | - John Lee
- Johns Hopkins Bloomberg School of Public Health
| | | | | | | | | | | | | | | | | | | | | | | | | | | | - Yukari Manabe
- Division of Infectious Diseases, Department of Medicine, The Johns Hopkins School of Medicine
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7
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Brown AC, Koshute PT, Cowley HP, Robinette MS, Gravelyn SR, Patel SV, Ju EY, Frommer CT, Zambidis AE, Schneider EJ, Zhao MY, Mugo BK, Clarke W, Kruczynski K, Pisanic N, Heaney CD, Colella TA. A Saliva-Based Serological and Behavioral Analysis of SARS-CoV-2 Antibody Prevalence in Howard County, Maryland. Microbiol Spectr 2023; 11:e0276522. [PMID: 37289070 PMCID: PMC10433989 DOI: 10.1128/spectrum.02765-22] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2022] [Accepted: 05/10/2023] [Indexed: 06/09/2023] Open
Abstract
The objective of the study was to estimate severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) seroprevalence in the Howard County, Maryland, general population and demographic subpopulations attributable to natural infection or coronavirus disease 2019 (COVID-19) vaccination and to identify self-reported social behaviors that may affect the likelihood of recent or past SARS-CoV-2 infection. A cross-sectional, saliva-based serological study of 2,880 residents of Howard County, Maryland, was carried out from July through September 2021. Natural SARS-CoV-2 infection prevalence was estimated by inferring infections among individuals according to anti-nucleocapsid immunoglobin G levels and calculating averages weighted by sample proportions of various demographics. Antibody levels between BNT162b2 (Pfizer-BioNTech) and mRNA-1273 (Moderna) recipients were compared. Antibody decay rate was calculated by fitting exponential decay curves to cross-sectional indirect immunoassay data. Regression analysis was carried out to identify demographic factors, social behaviors, and attitudes that may be linked to an increased likelihood of natural infection. The estimated overall prevalence of natural infection in Howard County, Maryland, was 11.9% (95% confidence interval, 9.2% to 15.1%), compared with 7% reported COVID-19 cases. Antibody prevalence indicating natural infection was highest among Hispanic and non-Hispanic Black participants and lowest among non-Hispanic White and non-Hispanic Asian participants. Participants from census tracts with lower average household income also had higher natural infection rates. After accounting for multiple comparisons and correlations between participants, none of the behavior or attitude factors had significant effects on natural infection. At the same time, recipients of the mRNA-1273 vaccine had higher antibody levels than those of BNT162b2 vaccine recipients. Older study participants had overall lower antibody levels compared with younger study participants. The true prevalence of SARS-CoV-2 infection is higher than the number of reported COVID-19 cases in Howard County, Maryland. A disproportionate impact of infection-induced SARS-CoV-2 positivity was observed across different ethnic/racial subpopulations and incomes, and differences in antibody levels across different demographics were identified. Taken together, this information may inform public health policy to protect vulnerable populations. IMPORTANCE We employed a highly innovative noninvasive multiplex oral fluid SARS-CoV-2 IgG assay to ascertain our seroprevalence estimates. This laboratory-developed test has been applied in NCI's SeroNet consortium, possesses high sensitivity and specificity according to FDA Emergency Use Authorization guidelines, correlates strongly with SARS-CoV-2 neutralizing antibody responses, and is Clinical Laboratory Improvement Amendments-approved by the Johns Hopkins Hospital Department of Pathology. It represents a broadly scalable public health tool to improve understanding of recent and past SARS-CoV-2 exposure and infection without drawing any blood. To our knowledge, this is the first application of a high-performance salivary SARS-CoV-2 IgG assay to estimate population-level seroprevalence, including identifying COVID-19 disparities. We also are the first to report differences in SARS-CoV-2 IgG responses by COVID-19 vaccine manufacturers (BNT162b2 [Pfizer-BioNTech] and mRNA-1273 [Moderna]). Our findings demonstrate remarkable consistency with those of blood-based SARS-CoV-2 IgG assays in terms of differences in the magnitude of SARS-CoV-2 IgG responses between COVID-19 vaccines.
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Affiliation(s)
- Alan C. Brown
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Phillip T. Koshute
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Hannah P. Cowley
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | | | - Sarah R. Gravelyn
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Shraddha V. Patel
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Eunice Y. Ju
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Carolyn T. Frommer
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | | | - Eric J. Schneider
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Martina Y. Zhao
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | - Benny K. Mugo
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
| | | | - Kate Kruczynski
- Johns Hopkins Environmental Health Microbiology and Immunology Laboratory (JH-EHMIL), Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Nora Pisanic
- Johns Hopkins Environmental Health Microbiology and Immunology Laboratory (JH-EHMIL), Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Christopher D. Heaney
- Johns Hopkins Environmental Health Microbiology and Immunology Laboratory (JH-EHMIL), Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Teresa A. Colella
- Johns Hopkins University Applied Physics Laboratory, Laurel, Maryland, USA
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Mallory M, Munt JE, Narowski TM, Castillo I, Cuadra E, Pisanic N, Fields P, Powers JM, Dickson A, Harris R, Wargowsky R, Moran S, Allabban A, Raphel K, McCaffrey TA, Brien JD, Heaney CD, Lafleur JE, Baric RS, Premkumar L. Longitudinal Analysis of Humoral and Cellular Immune Response Following SARS-CoV-2 Vaccination Supports Utilizing Point-Of-Care Tests to Enhance COVID-19 Booster Uptake. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.04.03.23287498. [PMID: 37066219 PMCID: PMC10104219 DOI: 10.1101/2023.04.03.23287498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
Individuals with weaker neutralizing responses show reduced protection with SARS-CoV-2 variants. Booster vaccines are recommended for vaccinated individuals, but the uptake is low. We present the feasibility of utilizing point-of-care tests (POCT) to support evidence-based decision-making around COVID-19 booster vaccinations. Using infectious virus neutralization, ACE2 blocking, spike binding, and TCR sequencing assays, we investigated the dynamics of changes in the breadth and depth of blood and salivary antibodies as well as T-cell clonal response following mRNA vaccination in a cohort of healthcare providers. We evaluated the accuracy of two POCTs utilizing either blood or saliva to identify those in whom humoral immunity was inadequate. >4 months after two doses of mRNA vaccine, SARS-CoV-2 binding and neutralizing Abs (nAbs) and T-cell clones declined 40-80%, and 2/3rd lacked Omicron nAbs. After the third mRNA booster, binding and neutralizing Abs increased overall in the systemic compartment; notably, individuals with previously weak nAbs gained sharply. The third dose failed to stimulate secretory IgA, but salivary IgG closely tracked systemic IgG levels. Vaccine boosting increased Ab breadth against a divergent bat sarbecovirus, SHC014, although the TCR-beta sequence breadth was unchanged. Post 3rd booster dose, Ab avidity increased for the Wuhan and Delta strains, while avidity against Omicron and SHC014 increased to levels seen for Wuhan after the second dose. Negative results on POCTs strongly correlated with a lack of functional humoral immunity. The third booster dose helps vaccinees gain depth and breadth of systemic Abs against evolving SARS-CoV-2 and related viruses. Our findings show that POCTs are useful and easy-to-access tools to inform inadequate humoral immunity accurately. POCTs designed to match the circulating variants can help individuals with booster vaccine decisions and could serve as a population-level screening platform to preserve herd immunity. One Sentence Summary SARS-CoV-2 point-of-care antibody tests are valuable and easy-to-access tools to inform inadequate humoral immunity and to support informed decision-making regarding the current and future booster vaccination.
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