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Cowling BJ, Okoli GN. Influenza Vaccine Effectiveness and Progress Towards a Universal Influenza Vaccine. Drugs 2024; 84:1013-1023. [PMID: 39167316 PMCID: PMC11438668 DOI: 10.1007/s40265-024-02083-8] [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] [Accepted: 08/04/2024] [Indexed: 08/23/2024]
Abstract
At various times in recent decades, surges have occurred in optimism about the potential for universal influenza vaccines that provide strong, broad, and long-lasting protection and could substantially reduce the disease burden associated with seasonal influenza epidemics as well as the threat posed by pandemic influenza. Each year more than 500 million doses of seasonal influenza vaccine are administered around the world, with most doses being egg-grown inactivated subunit or split-virion vaccines. These vaccines tend to have moderate effectiveness against medically attended influenza for influenza A(H1N1) and influenza B, and somewhat lower for influenza A(H3N2) where differences between vaccine strains and circulating strains can occur more frequently due to antigenic drift and egg adaptations in the vaccine strains. Several enhanced influenza vaccine platforms have been developed including cell-grown antigen, the inclusion of adjuvants, or higher antigen doses, to improve immunogenicity and protection. During the COVID-19 pandemic there was unprecedented speed in development and roll-out of relatively new vaccine platforms, including mRNA vaccines and viral vector vaccines. These new platforms present opportunities to improve protection for influenza beyond existing products. Other approaches continue to be explored. Incremental improvements in influenza vaccine performance should be achievable in the short to medium term.
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Affiliation(s)
- Benjamin J Cowling
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China.
- Laboratory of Data Discovery for Health Limited, Hong Kong Science and Technology Park, New Territories, Hong Kong Special Administrative Region, Hong Kong, China.
| | - George N Okoli
- WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
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Chen L, Hua J, He X. Bioinformatics analysis identifies a key gene HLA_DPA1 in severe influenza-associated immune infiltration. BMC Genomics 2024; 25:257. [PMID: 38454348 PMCID: PMC10918912 DOI: 10.1186/s12864-024-10184-7] [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: 07/07/2023] [Accepted: 03/04/2024] [Indexed: 03/09/2024] Open
Abstract
BACKGROUND Severe influenza is a serious global health issue that leads to prolonged hospitalization and mortality on a significant scale. The pathogenesis of this infectious disease is poorly understood. Therefore, this study aimed to identify the key genes associated with severe influenza patients necessitating invasive mechanical ventilation. METHODS The current study utilized two publicly accessible gene expression profiles (GSE111368 and GSE21802) from the Gene Expression Omnibus database. The research focused on identifying the genes exhibiting differential expression between severe and non-severe influenza patients. We employed three machine learning algorithms, namely the Least Absolute Shrinkage and Selection Operator regression model, Random Forest, and Support Vector Machine-Recursive Feature Elimination, to detect potential key genes. The key gene was further selected based on the diagnostic performance of the target genes substantiated in the dataset GSE101702. A single-sample gene set enrichment analysis algorithm was applied to evaluate the participation of immune cell infiltration and their associations with key genes. RESULTS A total of 44 differentially expressed genes were recognized; among them, we focused on 10 common genes, namely PCOLCE2, HLA_DPA1, LOC653061, TDRD9, MPO, HLA_DQA1, MAOA, S100P, RAP1GAP, and CA1. To ensure the robustness of our findings, we employed overlapping LASSO regression, Random Forest, and SVM-RFE algorithms. By utilizing these algorithms, we were able to pinpoint the aforementioned 10 genes as potential biomarkers for distinguishing between both cases of influenza (severe and non-severe). However, the gene HLA_DPA1 has been recognized as a crucial factor in the pathological condition of severe influenza. Notably, the validation dataset revealed that this gene exhibited the highest area under the receiver operating characteristic curve, with a value of 0.891. The use of single-sample gene set enrichment analysis has provided valuable insights into the immune responses of patients afflicted with severe influenza that have further revealed a categorical correlation between the expression of HLA_DPA1 and lymphocytes. CONCLUSION The findings indicated that the HLA_DPA1 gene may play a crucial role in the immune-pathological condition of severe influenza and could serve as a promising therapeutic target for patients infected with severe influenza.
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Affiliation(s)
- Liang Chen
- Department of Infectious Diseases, Taikang Xianlin Drum Tower Hospital, Affiliated Hospital of Medical College of Nanjing University, No 188, Lingshan North Road, Qixia District, Nanjing, 210046, China.
| | - Jie Hua
- Department of Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
| | - Xiaopu He
- Department of Geriatric Gastroenterology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, China
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Keay S, Poljak Z, Alberts F, O’Connor A, Friendship R, O’Sullivan TL, Sargeant JM. Does Vaccine-Induced Maternally-Derived Immunity Protect Swine Offspring against Influenza a Viruses? A Systematic Review and Meta-Analysis of Challenge Trials from 1990 to May 2021. Animals (Basel) 2023; 13:3085. [PMID: 37835692 PMCID: PMC10571953 DOI: 10.3390/ani13193085] [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: 08/05/2023] [Revised: 09/21/2023] [Accepted: 09/26/2023] [Indexed: 10/15/2023] Open
Abstract
It is unclear if piglets benefit from vaccination of sows against influenza. For the first time, methods of evidence-based medicine were applied to answer the question: "Does vaccine-induced maternally-derived immunity (MDI) protect swine offspring against influenza A viruses?". Challenge trials were reviewed that were published from 1990 to April 2021 and measured at least one of six outcomes in MDI-positive versus MDI-negative offspring (hemagglutination inhibition (HI) titers, virus titers, time to begin and time to stop shedding, risk of infection, average daily gain (ADG), and coughing) (n = 15). Screening and extraction of study characteristics was conducted in duplicate by two reviewers, with data extraction and assessment for risk of bias performed by one. Homology was defined by the antigenic match of vaccine and challenge virus hemagglutinin epitopes. Results: Homologous, but not heterologous MDI, reduced virus titers in piglets. There was no difference, calculated as relative risks (RR), in infection incidence risk over the entire study period; however, infection hazard (instantaneous risk) was decreased in pigs with MDI (log HR = -0.64, 95% CI: -1.13, -0.15). Overall, pigs with MDI took about a ½ day longer to begin shedding virus post-challenge (MD = 0.51, 95% CI: 0.03, 0.99) but the hazard of infected pigs ceasing to shed was not different (log HR = 0.32, 95% CI: -0.29, 0.93). HI titers were synthesized qualitatively and although data on ADG and coughing was extracted, details were insufficient for conducting meta-analyses. Conclusion: Homology of vaccine strains with challenge viruses is an important consideration when assessing vaccine effectiveness. Herd viral dynamics are complex and may include concurrent or sequential exposures in the field. The practical significance of reduced weaned pig virus titers is, therefore, not known and evidence from challenge trials is insufficient to make inferences on the effects of MDI on incidence risk, time to begin or to cease shedding virus, coughing, and ADG. The applicability of evidence from single-strain challenge trials to field practices is limited. Despite the synthesis of six outcomes, challenge trial evidence does not support or refute vaccination of sows against influenza to protect piglets. Additional research is needed; controlled trials with multi-strain concurrent or sequential heterologous challenges have not been conducted, and sequential homologous exposure trials were rare. Consensus is also warranted on (1) the selection of core outcomes, (2) the sizing of trial populations to be reflective of field populations, (3) the reporting of antigenic characterization of vaccines, challenge viruses, and sow exposure history, and (4) on the collection of non-aggregated individual pig data.
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Affiliation(s)
- Sheila Keay
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada; (Z.P.); (F.A.); (R.F.); (T.L.O.); (J.M.S.)
| | - Zvonimir Poljak
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada; (Z.P.); (F.A.); (R.F.); (T.L.O.); (J.M.S.)
| | - Famke Alberts
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada; (Z.P.); (F.A.); (R.F.); (T.L.O.); (J.M.S.)
| | - Annette O’Connor
- Department of Large Animal Clinical Sciences, College of Veterinary Medicine, Michigan State University, East Lansing, MI 48824, USA;
| | - Robert Friendship
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada; (Z.P.); (F.A.); (R.F.); (T.L.O.); (J.M.S.)
| | - Terri L. O’Sullivan
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada; (Z.P.); (F.A.); (R.F.); (T.L.O.); (J.M.S.)
| | - Jan M. Sargeant
- Department of Population Medicine, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada; (Z.P.); (F.A.); (R.F.); (T.L.O.); (J.M.S.)
- Centre for Public Health and Zoonoses, Ontario Veterinary College, University of Guelph, Guelph, ON N1G 2W1, Canada
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Fu J, Zhu F, Xu CJ, Li Y. Metabolomics meets systems immunology. EMBO Rep 2023; 24:e55747. [PMID: 36916532 PMCID: PMC10074123 DOI: 10.15252/embr.202255747] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2022] [Revised: 12/24/2022] [Accepted: 02/24/2023] [Indexed: 03/16/2023] Open
Abstract
Metabolic processes play a critical role in immune regulation. Metabolomics is the systematic analysis of small molecules (metabolites) in organisms or biological samples, providing an opportunity to comprehensively study interactions between metabolism and immunity in physiology and disease. Integrating metabolomics into systems immunology allows the exploration of the interactions of multilayered features in the biological system and the molecular regulatory mechanism of these features. Here, we provide an overview on recent technological developments of metabolomic applications in immunological research. To begin, two widely used metabolomics approaches are compared: targeted and untargeted metabolomics. Then, we provide a comprehensive overview of the analysis workflow and the computational tools available, including sample preparation, raw spectra data preprocessing, data processing, statistical analysis, and interpretation. Third, we describe how to integrate metabolomics with other omics approaches in immunological studies using available tools. Finally, we discuss new developments in metabolomics and its prospects for immunology research. This review provides guidance to researchers using metabolomics and multiomics in immunity research, thus facilitating the application of systems immunology to disease research.
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Affiliation(s)
- Jianbo Fu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Feng Zhu
- College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China
| | - Cheng-Jian Xu
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
| | - Yang Li
- Centre for Individualised Infection Medicine (CiiM), a joint venture between the Helmholtz Centre for Infection Research (HZI) and Hannover Medical School (MHH), Hannover, Germany.,TWINCORE Centre for Experimental and Clinical Infection Research, a joint venture between the Helmholtz Centre for Infection Research (HZI) and the Hannover Medical School (MHH), Hannover, Germany.,Department of Internal Medicine and Radboud Center for Infectious Diseases, Radboud University Medical Center, Nijmegen, The Netherlands
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Chen L, Hua J, He X. Co-expression network analysis identifies potential candidate hub genes in severe influenza patients needing invasive mechanical ventilation. BMC Genomics 2022; 23:703. [PMID: 36243706 PMCID: PMC9569050 DOI: 10.1186/s12864-022-08915-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Accepted: 09/26/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Influenza is a contagious disease that affects people of all ages and is linked to considerable mortality during epidemics and occasional outbreaks. Moreover, effective immunological biomarkers are needed for elucidating aetiology and preventing and treating severe influenza. Herein, we aimed to evaluate the key genes linked with the disease severity in influenza patients needing invasive mechanical ventilation (IMV). Three gene microarray data sets (GSE101702, GSE21802, and GSE111368) from blood samples of influenza patients were made available by the Gene Expression Omnibus (GEO) database. The GSE101702 and GSE21802 data sets were combined to create the training set. Hub indicators for IMV patients with severe influenza were determined using differential expression analysis and Weighted correlation network analysis (WGCNA) from the training set. The receiver operating characteristic curve (ROC) was also used to evaluate the hub genes from the test set's diagnostic accuracy. Different immune cells' infiltration levels in the expression profile and their correlation with hub gene markers were examined using single-sample gene set enrichment analysis (ssGSEA). RESULTS In the present study, we evaluated a total of 447 differential genes. WGCNA identified eight co-expression modules, with the red module having the strongest correlation with IMV patients. Differential genes were combined to obtain 3 hub genes (HLA-DPA1, HLA-DRB3, and CECR1). The identified genes were investigated as potential indicators for patients with severe influenza who required IMV using the least absolute shrinkage and selection operator (LASSO) approach. The ROC showed the diagnostic value of the three hub genes in determining the severity of influenza. Using ssGSEA, it has been revealed that the expression of key genes was negatively correlated with neutrophil activation and positively associated with adaptive cellular immune response. CONCLUSION We evaluated three novel hub genes that could be linked to the immunopathological mechanism of severe influenza patients who require IMV treatment and could be used as potential biomarkers for severe influenza prevention and treatment.
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Affiliation(s)
- Liang Chen
- Department of Infectious Diseases, Nanjing Lishui People's Hospital, Zhongda Hospital Lishui Branch, Southeast University, Nanjing, China
| | - Jie Hua
- Department of Gastroenterology, Liyang People's Hospital, Liyang Branch Hospital of Jiangsu Province Hospital, Nanjing, China
| | - Xiaopu He
- Department of Geriatric Gastroenterology, The First Affiliated Hospital With Nanjing Medical University, No.300 Guangzhou Road, Nanjing city, 210029, Jiangsu Province, China.
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Fulop T, Larbi A, Pawelec G, Cohen AA, Provost G, Khalil A, Lacombe G, Rodrigues S, Desroches M, Hirokawa K, Franceschi C, Witkowski JM. Immunosenescence and Altered Vaccine Efficiency in Older Subjects: A Myth Difficult to Change. Vaccines (Basel) 2022; 10:vaccines10040607. [PMID: 35455356 PMCID: PMC9030923 DOI: 10.3390/vaccines10040607] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2022] [Revised: 04/05/2022] [Accepted: 04/08/2022] [Indexed: 12/14/2022] Open
Abstract
Organismal ageing is associated with many physiological changes, including differences in the immune system of most animals. These differences are often considered to be a key cause of age-associated diseases as well as decreased vaccine responses in humans. The most often cited vaccine failure is seasonal influenza, but, while it is usually the case that the efficiency of this vaccine is lower in older than younger adults, this is not always true, and the reasons for the differential responses are manifold. Undoubtedly, changes in the innate and adaptive immune response with ageing are associated with failure to respond to the influenza vaccine, but the cause is unclear. Moreover, recent advances in vaccine formulations and adjuvants, as well as in our understanding of immune changes with ageing, have contributed to the development of vaccines, such as those against herpes zoster and SARS-CoV-2, that can protect against serious disease in older adults just as well as in younger people. In the present article, we discuss the reasons why it is a myth that vaccines inevitably protect less well in older individuals, and that vaccines represent one of the most powerful means to protect the health and ensure the quality of life of older adults.
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Affiliation(s)
- Tamas Fulop
- Research Center on Aging, Geriatric Division, Department of Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (A.K.); (G.L.)
- Correspondence: (T.F.); (S.R.)
| | - Anis Larbi
- Singapore Immunology Network (SIgN), Agency for Science Technology and Research (A*STAR), Immunos Building, Singapore 138648, Singapore;
| | - Graham Pawelec
- Department of Immunology, University of Tübingen, 72072 Tübingen, Germany;
- Health Sciences North Research Institute, Sudbury, ON P3E 2H2, Canada
| | - Alan A. Cohen
- Groupe de Recherche PRIMUS, Department of Family Medicine, University of Sherbrooke, 3001 12e Ave N, Sherbrooke, QC J1H 5N4, Canada;
| | | | - Abedelouahed Khalil
- Research Center on Aging, Geriatric Division, Department of Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (A.K.); (G.L.)
| | - Guy Lacombe
- Research Center on Aging, Geriatric Division, Department of Medicine, Faculty of Medicine and Health Sciences, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada; (A.K.); (G.L.)
| | - Serafim Rodrigues
- Ikerbasque, The Basque Foundation for Science, 48009 Bilbao, Spain;
- BCAM—The Basque Center for Applied Mathematics, 48009 Bilbao, Spain
- Correspondence: (T.F.); (S.R.)
| | - Mathieu Desroches
- MathNeuro Team, Inria Sophia Antipolis Méditerranée, CEDEX, 06902 Sophia Antipolis, France;
- The Jean Alexandre Dieudonné Laboratory, Université Côte d’Azur, CEDEX 2, 06108 Nice, France
| | - Katsuiku Hirokawa
- Institute of Health and Life Science, Tokyo Medical and Dental University, Tokyo 113-8510, Japan;
| | - Claudio Franceschi
- IRCCS Institute of Neurological Sciences of Bologna, Alma Mater Studiorum University of Bologna, 40126 Bologna, Italy;
- Department of Applied Mathematics and Laboratory of Systems Biology of Healthy Aging, Lobachevsky State University, 603000 Nizhny Novgorod, Russia
| | - Jacek M. Witkowski
- Department of Pathophysiology, Medical University of Gdansk, 80-210 Gdansk, Poland;
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Special Issue—Immunity to Influenza Viruses. Viruses 2022; 14:v14020319. [PMID: 35215910 PMCID: PMC8880793 DOI: 10.3390/v14020319] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2022] [Accepted: 02/01/2022] [Indexed: 11/24/2022] Open
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Rescigno M. Unraveling the long-term effect of influenza vaccines. Cell 2021; 184:3845-3847. [PMID: 34297927 DOI: 10.1016/j.cell.2021.06.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
The past decade has witnessed the emergence of highly sophisticated vaccines; still their mechanism of action is not fully understood. Wimmers et al. use advanced techniques to evaluate the immune landscape induced by flu vaccines and show that their effect on the immune system can last even 6 months from administration.
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Affiliation(s)
- Maria Rescigno
- IRCCS Humanitas Research Hospital, Via Manzoni 56, 20089 Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, Via Rita Levi Montalcini, 20090 Pieve Emanuele, Milan, Italy.
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