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Hsieh MJ, Tsai PH, Chiang PH, Kao ZK, Zhuang ZQ, Hsieh AR, Ho HL, Chiou SH, Liang KH, Chen YC. Genomic insights into mRNA COVID-19 vaccines efficacy: Linking genetic polymorphisms to waning immunity. Hum Vaccin Immunother 2024; 20:2399382. [PMID: 39254005 PMCID: PMC11404610 DOI: 10.1080/21645515.2024.2399382] [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: 06/25/2024] [Revised: 08/13/2024] [Accepted: 08/29/2024] [Indexed: 09/11/2024] Open
Abstract
Genetic polymorphisms have been linked to the differential waning of vaccine-induced immunity against COVID-19 following vaccination. Despite this, evidence on the mechanisms behind this waning and its implications for vaccination policy remains limited. We hypothesize that specific gene variants may modulate the development of vaccine-initiated immunity, leading to impaired immune function. This study investigates genetic determinants influencing the sustainability of immunity post-mRNA vaccination through a genome-wide association study (GWAS). Utilizing a hospital-based, test negative case-control design, we enrolled 1,119 participants from the Taiwan Precision Medicine Initiative (TPMI) cohort, all of whom completed a full mRNA COVID-19 vaccination regimen and underwent PCR testing during the Omicron outbreak. Participants were classified into breakthrough and protected groups based on PCR results. Genetic samples were analyzed using SNP arrays with rigorous quality control. Cox regression identified significant single nucleotide polymorphisms (SNPs) associated with breakthrough infections, affecting 743 genes involved in processes such as antigenic protein translation, B cell activation, and T cell function. Key genes identified include CD247, TRPV1, MYH9, CCL16, and RPTOR, which are vital for immune responses. Polygenic risk score (PRS) analysis revealed that individuals with higher PRS are at greater risk of breakthrough infections post-vaccination, demonstrating a high predictability (AUC = 0.787) in validating population. This finding confirms the significant influence of genetic variations on the durability of immune responses and vaccine effectiveness. This study highlights the importance of considering genetic polymorphisms in evaluating vaccine-induced immunity and proposes potential personalized vaccination strategies by tailoring regimens to individual genetic profiles.
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Affiliation(s)
- Min-Jia Hsieh
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Ping-Hsing Tsai
- Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Pin-Hsuan Chiang
- Big Data Center, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Zih-Kai Kao
- Department of Information Management, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Zi-Qing Zhuang
- Big Data Center, Taipei Veterans General Hospital, Taipei, Taiwan
| | - Ai-Ru Hsieh
- Department of Statistics, Tamkang University, New Taipei, Taiwan
| | - Hsiang-Ling Ho
- Department of Pathology and Laboratory Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- Department of Biotechnology and Laboratory Science in Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Shih-Hwa Chiou
- Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
- School of medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Kung-Hao Liang
- Department of Medical Research, Taipei Veterans General Hospital, Taipei, Taiwan
- Biosafety level 3 laboratory, Taipei Veterans General Hospital, Taipei, Taiwan
- Institute of Biomedical Informatics, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Institute of Food Safety and Health Risk Assessment, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Yu-Chun Chen
- Department of Family Medicine, Taipei Veterans General Hospital, Taipei, Taiwan
- Big Data Center, Taipei Veterans General Hospital, Taipei, Taiwan
- School of medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
- Department of Family Medicine, Taipei Veterans General Hospital Yuli Branch, Hualien, Taiwan
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Deng S, Xu Z, Hu J, Yang Y, Zhu F, Liu Z, Zhang H, Wu S, Jin T. The molecular mechanisms of CD8 + T cell responses to SARS-CoV-2 infection mediated by TCR-pMHC interactions. Front Immunol 2024; 15:1468456. [PMID: 39450171 PMCID: PMC11499136 DOI: 10.3389/fimmu.2024.1468456] [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: 07/30/2024] [Accepted: 09/16/2024] [Indexed: 10/26/2024] Open
Abstract
Cytotoxic CD8+ T lymphocytes (CTLs) have been implicated in the severity of COVID-19. The TCR-pMHC ternary complex, formed by the T cell receptor (TCR) and peptide-MHC (major histocompatibility complex), constitutes the molecular basis of CTL responses against SARS-CoV-2. While numerous studies have been conducted on T cell immunity, the molecular mechanisms underlying CTL-mediated immunity against SARS-CoV-2 infection have not been well elaborated. In this review, we described the association between HLA variants and different immune responses to SARS-CoV-2 infection, which may lead to varying COVID-19 outcomes. We also summarized the specific TCR repertoires triggered by certain SARS-CoV-2 CTL epitopes, which might explain the variations in disease outcomes among different patients. Importantly, we have highlighted the primary strategies used by SARS-CoV-2 variants to evade T-cell killing: disrupting peptide-MHC binding, TCR recognition, and antigen processing. This review provides valuable insights into the molecule mechanism of CTL responses during SARS-CoV-2 infection, aiding efforts to control the pandemic and prepare for future challenges.
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Affiliation(s)
- Shasha Deng
- Center of Disease Immunity and Intervention, College of Medicine, Lishui University, Lishui, China
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
| | - Zhihao Xu
- Center of Disease Immunity and Intervention, College of Medicine, Lishui University, Lishui, China
- Department of Experimental Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, United States
| | - Jing Hu
- Laboratory of Structural Immunology, the Chinese Academy of Sciences (CAS) Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Yunru Yang
- Laboratory of Structural Immunology, the Chinese Academy of Sciences (CAS) Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Fang Zhu
- Laboratory of Structural Immunology, the Chinese Academy of Sciences (CAS) Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Zhuan Liu
- Laboratory of Structural Immunology, the Chinese Academy of Sciences (CAS) Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
| | - Hongliang Zhang
- Center of Disease Immunity and Intervention, College of Medicine, Lishui University, Lishui, China
| | - Songquan Wu
- Center of Disease Immunity and Intervention, College of Medicine, Lishui University, Lishui, China
| | - Tengchuan Jin
- Center of Disease Immunity and Intervention, College of Medicine, Lishui University, Lishui, China
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of University of Science and Technology of China (USTC), Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China
- Laboratory of Structural Immunology, the Chinese Academy of Sciences (CAS) Key Laboratory of Innate Immunity and Chronic Disease, School of Basic Medical Sciences, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, China
- Institute of Health and Medicine, Hefei Comprehensive National Science Center, Hefei, Anhui, China
- Biomedical Sciences and Health Laboratory of Anhui Province, University of Science & Technology of China, Hefei, China
- Clinical Research Hospital of Chinese Academy of Sciences (Hefei), University of Science and Technology of China, Hefei, China
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Crocchiolo R, Frassati C, Gallina AM, Pedini P, Maioli S, Veronese L, Pani A, Scaglione F, D'Amico F, Crucitti L, Sacchi N, Rossini S, Picard C. Strong humoral response after Covid-19 vaccination correlates with the common HLA allele A*03:01 and protection from breakthrough infection. HLA 2024; 103:e15421. [PMID: 38433722 DOI: 10.1111/tan.15421] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2023] [Revised: 02/14/2024] [Accepted: 02/16/2024] [Indexed: 03/05/2024]
Abstract
Few data exist on the role of genetic factors involving the HLA system on response to Covid-19 vaccines. Moving from suggestions of a previous study investigating the association of some HLA alleles with humoral response to BNT162b2, we here compared the HLA allele frequencies among weak (n = 111) and strong (n = 123) responders, defined as those healthcare workers with the lowest and the highest anti-Spike antibody levels after vaccination. Individuals with clinical history of Covid-19 or positive anti-nucleocapside antibodies were excluded. We found the common HLA-A*03:01 allele as an independent predictor of strong humoral response (OR = 12.46, 95% CI: 4.41-35.21, p < 0.0001), together with younger age of vaccines (p = 0.004). Correlation between antibody levels and protection from breakthrough infection has been observed, with a 2-year cumulative incidence of 42% and 63% among strong and weak responders, respectively (p = 0.03). Due to the high frequency of HLA-A*03:01 and the need for seasonal vaccinations against SARS-CoV-2 mutants, our findings provide useful information about the inter-individual differences observed in humoral response after Covid-19 vaccine and might support further studies on the next seasonal vaccines.
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Affiliation(s)
- Roberto Crocchiolo
- Dipartimento dei Servizi, ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | | | - Anna Maria Gallina
- Italian Bone Marrow Donor Registry, E.O. Ospedali Galliera Genova, Genova, Italy
| | | | | | - Luca Veronese
- Dipartimento dei Servizi, ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | - Arianna Pani
- Dipartimento dei Servizi, ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | - Francesco Scaglione
- Dipartimento dei Servizi, ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | - Federico D'Amico
- Dipartimento dei Servizi, ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
| | - Lara Crucitti
- Hematology Department, Azienda Sanitaria Provinciale di Trapani, Castelvetrano, Italy
| | - Nicoletta Sacchi
- Italian Bone Marrow Donor Registry, E.O. Ospedali Galliera Genova, Genova, Italy
| | - Silvano Rossini
- Dipartimento dei Servizi, ASST Grande Ospedale Metropolitano Niguarda, Milano, Italy
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