1
|
Zhang H, Ouyang S, Qu Y, Li Z, Jiang Y, Peng T, Yang G, Chen T, Li B, Shen C, Zhao W. Humoral immune response characteristics of vulnerable populations against SARS-CoV-2 strains EG.5 and JN.1 after infection with strains BA.5 and XBB. Arch Virol 2025; 170:82. [PMID: 40100292 DOI: 10.1007/s00705-025-06248-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2024] [Accepted: 12/06/2024] [Indexed: 03/20/2025]
Abstract
In this study, we compared the humoral immune characteristics of children, elderly individuals, and pregnant women in Guangzhou, China, who had been infected with the SARS-CoV-2 strains BA.5 and XBB against the currently predominant strains EG.5 and JN.1. It was discovered that the neutralizing antibody titers in children, elderly individuals, and pregnant women against strains EG.5 and JN.1 were low in individuals who had been infected with strain BA.5, irrespective of their vaccination status. There was a significant positive correlation between the neutralization titers against JN.1 and EG.5 in both the acute and convalescent phases of BA.5 infection. For XBB-infected patients, the sera in the acute stage exhibited a low neutralizing titer against EG.5 and JN.1, whereas the convalescent sera demonstrated a significantly higher neutralizing titer against the two viruses, particularly in infected individuals who had been vaccinated. For XBB-infected patients, there was a strong positive correlation between the serum neutralizing antibody titers against EG.5 and JN.1 in both the acute and recovery phases. This finding provides crucial information for judging the epidemic trend of COVID-19 and the development of vaccines, especially for developing customized vaccines and immune strategies for different populations.
Collapse
Affiliation(s)
- Huan Zhang
- Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention CN, Guangzhou, China
- BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China
| | - Shi Ouyang
- Department of Infectious Diseases, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China
| | - Yunyun Qu
- The Second Affiliated Hospital of Shandong, University of Traditional Chinese Medicine, Jinan, China
| | - Zhuolin Li
- BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China
| | - Yushan Jiang
- BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China
- Department of Infectious Diseases, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China
| | - Tingting Peng
- Department of Infectious Diseases, Key Laboratory of Biological Targeting Diagnosis, Therapy and Rehabilitation of Guangdong Higher Education Institutes, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou, 510000, China
| | - Guangyan Yang
- Jinan Central People's Hospital, Jinan, Shandong, China
| | - Tao Chen
- The Second Affiliated Hospital of Shandong, University of Traditional Chinese Medicine, Jinan, China.
| | - Baisheng Li
- Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention CN, Guangzhou, China.
| | - Chenguang Shen
- BSL-3 Laboratory (Guangdong), Guangdong Provincial Key Laboratory of Tropical Disease Research, School of Public Health, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, People's Republic of China.
| | - Wei Zhao
- Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention CN, Guangzhou, China.
| |
Collapse
|
2
|
Arévalo‐Herrera M, Rincón‐Orozco B, González‐Escobar JM, Herrera‐Arévalo SM, Carrasquilla‐Agudelo E, Serna‐Ortega PA, Quiceno‐García S, Palacio‐Muñoz N, Rosero‐López B, Mondol‐Miranda E, Freyle‐Roman I, Mendoza‐Landinez B, Mora‐Guevara E, Santos‐Barbosa JC, Bohórquez‐Martínez F, Bolaños‐Cristancho N, Jiménez‐Serna M, Nieto‐Rojas MA, Suarez‐Zamora D, Quintero‐Espinosa J, Londoño‐Trujillo D, Herrera‐ Valencia S. Longitudinal Follow-Up of the Specific Antibody Response to SARS-CoV-2 Vaccination in Colombia. J Med Virol 2025; 97:e70133. [PMID: 39817585 PMCID: PMC11737005 DOI: 10.1002/jmv.70133] [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: 05/22/2024] [Revised: 11/04/2024] [Accepted: 12/06/2024] [Indexed: 01/18/2025]
Abstract
A total of 5011 adult volunteers attending vaccination centers in different regions of Colombia were enrolled in a 1-year prospective observational cohort study to evaluate the immunogenicity and effectiveness of SARS-CoV-2-based vaccines as part of a National Vaccine Program established to contain the COVID-19 pandemic. Following informed consent, 5,011 participants underwent a sociodemographic survey and PCR testing to assess SARS-CoV-2 infection. Blood samples were collected, and serum fractions were obtained from a participant subsample (n = 3441) at six-time points to assess virus-specific IgG responses to the Spike protein, its Receptor Binding Domain, and the Nucleoprotein by ELISA. Additionally, antibody-neutralizing activity was evaluated using a cPass SARS-CoV-2 neutralization kit. Most participants (95.8%; n = 4802) received between one Ad26. COV2.S (Janssen vaccine) and four vaccine doses of BNT162b2 (Pfizer/BioNTech), AZD1222 (AstraZeneca), mRNA-1273 (Moderna), CoronaVac (Sinovac), with some receiving vaccine combinations; a small group, 4.2% (n = 209), remained unvaccinated. Throughout the study, only 8.76% (n = 439) of the participants tested positive for SARS-CoV-2 by PCR. Notably, all participants seroconverted for IgG antibodies, with high seropositivity rates for S (99.8%; n = 4795), RBD (99.7%; n = 1691), and N (92.7%; n = 3072) proteins. Moreover, significant (92%-97%) neutralizing activity was observed for all four SARS-CoV-2 circulating variants. This study highlights the importance of assessing the duration of the IgG response to SARS-CoV-2 elicited by vaccination and infection, and the antibody neutralizing activity as a potential surrogate marker of protection. These findings provide important insight for further strengthening the vaccination strategies to control COVID-19.
Collapse
Affiliation(s)
| | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | | - Juliana Quintero‐Espinosa
- Fundación Santa Fe de BogotáSalud PoblacionalColombia
- Departamento de Medicina Interna, Sección de Infectología, Fundación Santa Fe de Bogotá
| | | | | |
Collapse
|
3
|
Li Y, Zhang X, Yi J, Chen Y, Liang J, Wang L, Ma J, Zhu R, Zhang X, Hu D, Jia Y, Yu X, Wang Y. Synergistic evolution: The dynamic adaptation of SARS-CoV-2 and human protective immunity in the real world. J Infect 2024; 89:106310. [PMID: 39393556 DOI: 10.1016/j.jinf.2024.106310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Revised: 09/18/2024] [Accepted: 09/30/2024] [Indexed: 10/13/2024]
Abstract
OBJECTIVES SARS-CoV-2 is continually evolving with new variants to evade protective immunity and cause new infections. This study aimed to assess infection-acquired immunity and hybrid immunity against re-infection or severe COVID-19. METHODS During 2020-2023, we collected 890 serum samples from individuals infected with SARS-CoV-2 variants including wild type, D614G, Alpha, Delta, BA.1, BA.2, BA.2.76, BA.5.2, BF.7, XBB, and EG.5. The levels of serum neutralizing antibodies (NAbs) against 18 diverse SARS-CoV-2 variants were determined using a bead-based high-throughput broad neutralizing-antibody assay. RESULTS In the initial wave of the COVID-19 pandemic, >75% of the patients demonstrated robust NAb responses against the ancestral SARS-CoV-2, during a period when vaccines were not yet available. After the emergence of the Omicron variant, the seroprevalence of anti-Omicron NAbs among the patients increased rapidly. By April 2023, when XBB variant was predominant, approximately 80% of the patients demonstrated >50% neutralization against the highly immune-evasive XBB lineages. Three serotypes of SARS-CoV-2, namely non-Omicron, Omicron, and XBB serotypes, were identified, with the strong likelihood of further changes occurring as the virus mutating. Generally, NAbs elicited by a previous serotype could not typically effectively protect against another serotype that emerges later in the evolutionary stages. CONCLUSION Our results firstly demonstrated the synergistic evolution between host immunity and SARS-CoV-2 variants in the real world, which would be helpful to develop future vaccines and public health strategies.
Collapse
Affiliation(s)
- Yunhui Li
- Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Xiaohan Zhang
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Jingkun Yi
- Department of Biomedical Informatics, State Key Laboratory of Vascular Homeostasis and Remodeling, School of Basic Medical Sciences, Peking University, Beijing 100191, China
| | - Yuan Chen
- Department of Clinical Laboratory, Peking University Ditan Teaching Hospital, Beijing 100015, China
| | - Jing Liang
- Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Li Wang
- Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Jiayue Ma
- Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China
| | - Renlong Zhu
- Department of Clinical Laboratory, Peking University Ditan Teaching Hospital, Beijing 100015, China
| | - Xiaomei Zhang
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing 102206, China
| | - Di Hu
- ProteomicsEra Medical Co., Ltd., Beijing 102206, China
| | - Yan Jia
- ProteomicsEra Medical Co., Ltd., Beijing 102206, China
| | - Xiaobo Yu
- State Key Laboratory of Medical Proteomics, Beijing Proteome Research Center, National Center for Protein Sciences-Beijing (PHOENIX Center), Beijing Institute of Lifeomics, Beijing 102206, China.
| | - Yajie Wang
- Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing 100015, China.
| |
Collapse
|
4
|
Li Y, Chen Y, Liang J, Wang Y. Immunological characteristics in elderly COVID-19 patients: a post-COVID era analysis. Front Cell Infect Microbiol 2024; 14:1450196. [PMID: 39679195 PMCID: PMC11638707 DOI: 10.3389/fcimb.2024.1450196] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2024] [Accepted: 10/14/2024] [Indexed: 12/17/2024] Open
Abstract
Background Advanced age is a primary risk factor for adverse COVID-19 outcomes, potentially attributed to immunosenescence and dysregulated inflammatory responses. In the post-pandemic era, with containment measures lifted, the elderly remain particularly susceptible, highlighting the need for intensified focus on immune health management. Methods A total of 281 elderly patients were enrolled in this study and categorized based on their clinical status at the time of admission into three groups: non-severe (n = 212), severe survivors (n = 49), and severe non-survivors (n = 20). Binary logistic regression analysis was employed to identify independent risk factors associated with disease severity and in-hospital outcomes. The diagnostic performance of risk factors was assessed using the receiver operating characteristic (ROC) curves. Kaplan-Meier survival analysis and log-rank test were utilized to compare the 30-day survival rates. Furthermore, the transcriptomic data of CD4+ T cells were extracted from Gene Expression Omnibus (GEO) database. Gene Set Enrichment Analysis (GSEA) was applied to reveal biological processes and pathways involved. Results In the comparison between severe and non-severe COVID-19 cases, significant elevations were observed in the neutrophil-to-lymphocyte ratio (NLR), C-reactive protein (CRP), and Serum Amyloid A (SAA) levels, concurrent with a notable reduction in CD8+ T cells, CD4+ T cells, natural killer (NK) cells, and monocytes (all p < 0.05). CD4+ T cells (OR: 0.997 [0.995-1.000], p<0.05) and NLR (OR: 1.03 [1.001-1.060], p<0.05) were independent risk factors affecting disease severity. The diagnostic accuracy for COVID-19 severity, as measured by the area under the curve (AUC) for CD4+ T cells and NLR, was 0.715 (95% CI: 0.645-0.784) and 0.741 (95% CI: 0.675-0.807), respectively. Moreover, patients with elevated NLR or IL-6 levels at admission exhibited significantly shorter survival times. Gene Set Enrichment Analysis (GSEA) revealed several biological pathways that are implicated in the regulation of immune responses and metabolic processes. Conclusions Lymphocytopenia and the cytokine storm onset are significant predictors of an unfavorable prognosis in elderly patients. The decrease in CD4+ T cells among elderly patients is detrimental to disease recovery, and the biological pathways regulated by these cells could potentially heighten vulnerability to SARS-CoV-2 infection, thereby exacerbating the development of associated complications.
Collapse
Affiliation(s)
| | | | | | - Yajie Wang
- Department of Clinical Laboratory, Beijing Ditan Hospital, Capital Medical University, Beijing, China
| |
Collapse
|
5
|
Rothoeft T, Maier C, Talarico A, Hoffmann A, Schlegtendal A, Lange B, Petersmann A, Denz R, Timmesfeld N, Toepfner N, Vidal-Blanco E, Pfaender S, Lücke T, Brinkmann F. Natural and hybrid immunity after SARS-CoV-2 infection in children and adolescents. Infection 2024; 52:1449-1458. [PMID: 38499828 PMCID: PMC11288991 DOI: 10.1007/s15010-024-02225-w] [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: 10/07/2023] [Accepted: 02/24/2024] [Indexed: 03/20/2024]
Abstract
PURPOSE In contrast to adults, immune protection against SARS-CoV-2 in children and adolescents with natural or hybrid immunity is still poorly understood. The aim of this study was to analyze different immune compartments in different age groups and whether humoral immune reactions correlate with a cellular immune response. METHODS 72 children and adolescents with a preceding SARS-CoV-2 infection were recruited. 37 were vaccinated with an RNA vaccine (BNT162b2). Humoral immunity was analyzed 3-26 months (median 10 months) after infection by measuring Spike protein (S), nucleocapsid (NCP), and neutralizing antibodies (nAB). Cellular immunity was analyzed using a SARS-CoV-2-specific interferon-γ release assay (IGRA). RESULTS All children and adolescents had S antibodies; titers were higher in those with hybrid immunity (14,900 BAU/ml vs. 2118 BAU/ml). NCP antibodies were detectable in > 90%. Neutralizing antibodies (nAB) were more frequently detected (90%) with higher titers (1914 RLU) in adolescents with hybrid immunity than in children with natural immunity (62.5%, 476 RLU). Children with natural immunity were less likely to have reactive IGRAs (43.8%) than adolescents with hybrid immunity (85%). The amount of interferon-γ released by T cells was comparable in natural and hybrid immunity. CONCLUSION Spike antibodies are the most reliable markers to monitor an immune reaction against SARS-CoV-2. High antibody titers of spike antibodies and nAB correlated with cellular immunity, a phenomenon found only in adolescents with hybrid immunity. Hybrid immunity is associated with markedly higher antibody titers and a higher probability of a cellular immune response than a natural immunity.
Collapse
Affiliation(s)
- T Rothoeft
- University Hospital of Pediatrics and Adolescent Medicine, St. Josef-Hospital, Ruhr-University, Bochum, Germany.
| | - C Maier
- University Hospital of Pediatrics and Adolescent Medicine, St. Josef-Hospital, Ruhr-University, Bochum, Germany
| | - A Talarico
- University Hospital of Pediatrics and Adolescent Medicine, St. Josef-Hospital, Ruhr-University, Bochum, Germany
| | - A Hoffmann
- University Hospital of Pediatrics and Adolescent Medicine, St. Josef-Hospital, Ruhr-University, Bochum, Germany
| | - A Schlegtendal
- University Hospital of Pediatrics and Adolescent Medicine, St. Josef-Hospital, Ruhr-University, Bochum, Germany
| | - B Lange
- Department of Epidemiology, Helmholtz Centre for Infection Research, Brunswick, Germany
| | - A Petersmann
- University Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Oldenburg, Oldenburg, Germany
- University Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - R Denz
- Department of Medical Informatics, Biometry and Epidemiology, Ruhr-University Bochum, Bochum, Germany
| | - N Timmesfeld
- Department of Medical Informatics, Biometry and Epidemiology, Ruhr-University Bochum, Bochum, Germany
| | - N Toepfner
- Department of Pediatrics, Faculty of Medicine, University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany
| | - E Vidal-Blanco
- Department of Molecular and Medical Virology, Ruhr University Bochum, Bochum, Germany
| | - S Pfaender
- Department of Molecular and Medical Virology, Ruhr University Bochum, Bochum, Germany
| | - T Lücke
- University Hospital of Pediatrics and Adolescent Medicine, St. Josef-Hospital, Ruhr-University, Bochum, Germany
| | - F Brinkmann
- University Hospital of Pediatrics and Adolescent Medicine, St. Josef-Hospital, Ruhr-University, Bochum, Germany
- University Children's Hospital, Lübeck, Germany
- Airway Research Center North (ARCN), German Center for Lung Research (DZL), Lübeck, Germany
| |
Collapse
|
6
|
Qu L, Xie C, Qiu M, Yi L, Liu Z, Zou L, Hu P, Jiang H, Lian H, Yang M, Yang H, Zeng H, Chen H, Zhao J, Xiao J, He J, Yang Y, Chen L, Li B, Sun J, Lu J. Characterizing Infections in Two Epidemic Waves of SARS-CoV-2 Omicron Variants: A Cohort Study in Guangzhou, China. Viruses 2024; 16:649. [PMID: 38675989 PMCID: PMC11053513 DOI: 10.3390/v16040649] [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: 03/21/2024] [Revised: 04/06/2024] [Accepted: 04/17/2024] [Indexed: 04/28/2024] Open
Abstract
BACKGROUND After the adjustment of COVID-19 epidemic policy, mainland China experienced two consecutive waves of Omicron variants within a seven-month period. In Guangzhou city, as one of the most populous regions, the viral infection characteristics, molecular epidemiology, and the dynamic of population immunity are still elusive. METHODS We launched a prospective cohort study in the Guangdong Provincial CDC from December 2022 to July 2023. Fifty participants who received the same vaccination regimen and had no previous infection were recruited. RESULTS 90% of individuals were infected with Omicron BA.5* variants within three weeks in the first wave. Thirteen cases (28.26%) experienced infection with XBB.1* variants, occurring from 14 weeks to 21 weeks after the first wave. BA.5* infections exhibited higher viral loads in nasopharyngeal sites compared to oropharyngeal sites. Compared to BA.5* infections, the XBB.1* infections had significantly milder clinical symptoms, lower viral loads, and shorter durations of virus positivity. The infection with the BA.5* variant elicited varying levels of neutralizing antibodies against XBB.1* among different individuals, even with similar levels of BA.5* antibodies. The level of neutralizing antibodies specific to XBB.1* determined the risk of reinfection. CONCLUSIONS The rapid large-scale infections of the Omicron variants have quickly established herd immunity among the population in mainland China. In the future of the COVID-19 epidemic, a lower infection rate but a longer duration can be expected. Given the large population size and ongoing diversified herd immunity, it remains crucial to closely monitor the molecular epidemiology of SARS-CoV-2 for the emergence of new variants of concern in this region. Additionally, the timely evaluation of the immune status across different age groups is essential for informing future vaccination strategies and intervention policies.
Collapse
Affiliation(s)
- Lin Qu
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (L.Q.); (M.Q.); (H.Y.)
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Chunyan Xie
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Basic Medicine and Public Health, Jinan University, Guangzhou 510632, China
| | - Ming Qiu
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (L.Q.); (M.Q.); (H.Y.)
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Lina Yi
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Zhe Liu
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Lirong Zou
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China;
| | - Pei Hu
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China;
| | - Huimin Jiang
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Huimin Lian
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Public Health, Southern Medical University, Guangzhou 510515, China
| | - Mingda Yang
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Basic Medicine and Public Health, Jinan University, Guangzhou 510632, China
| | - Haiyi Yang
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (L.Q.); (M.Q.); (H.Y.)
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Huiling Zeng
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Public Health, Guangdong Pharmaceutical University, Guangzhou 510310, China
| | - Huimin Chen
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- School of Basic Medicine and Public Health, Jinan University, Guangzhou 510632, China
| | - Jianguo Zhao
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
| | - Jianpeng Xiao
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
| | - Jianfeng He
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China;
| | - Ying Yang
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
| | - Liang Chen
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
| | - Baisheng Li
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
- Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China;
| | - Jiufeng Sun
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| | - Jing Lu
- School of Public Health, Sun Yat-sen University, Guangzhou 510080, China; (L.Q.); (M.Q.); (H.Y.)
- Guangdong Provincial Institution of Public Health, Guangzhou 511430, China; (C.X.); (L.Y.); (Z.L.); (H.J.); (H.L.); (M.Y.); (H.Z.); (H.C.); (J.Z.); (J.X.); (Y.Y.); (L.C.)
- Guangdong Workstation for Emerging Infectious Disease Control and Prevention, Guangdong Provincial Key Laboratory of Pathogen Detection for Emerging Infectious Disease Response, Guangdong Provincial Center for Disease Control and Prevention, Guangzhou 511430, China; (L.Z.); (J.H.); (B.L.)
| |
Collapse
|
7
|
McCarthy MW. Intravenous immunoglobulin as a potential treatment for long COVID. Expert Opin Biol Ther 2023; 23:1211-1217. [PMID: 38100573 DOI: 10.1080/14712598.2023.2296569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Accepted: 12/14/2023] [Indexed: 12/17/2023]
Abstract
INTRODUCTION On 31 July 2023, the United States Department of Health and Human Services announced the formation of the Office of Long COVID Research and Practice and the United States National Institutes of Health (NIH) opened enrollment for the therapeutic arm of the RECOVER initiative, a prospective, randomized study to evaluate new treatment options for long coronavirus disease 2019 (long COVID). AREAS COVERED One of the first drugs to be studied in this nationwide initiative is intravenous immunoglobulin (IVIG), which will be a treatment option for subjects enrolled in RECOVER-AUTO, a randomized trial to investigate therapeutic strategies for autonomic dysfunction related to long COVID. EXPERT OPINION IVIG is a mixture of human antibodies (human immunoglobulin) that has been widely used to treat a variety of diseases, including immune thrombocytopenia purpura, Kawasaki disease, chronic inflammatory demyelinating polyneuropathy, and certain infections such as influenza, human immunodeficiency virus, and measles. However, the role of IVIG in the treatment of post-COVID-19 conditions is uncertain. This manuscript examines what is known about IVIG in the treatment of long COVID and explores how this therapeutic agent may be used in the future to address this condition.
Collapse
|