Systems Vaccinology Introduction PDF
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Universiteit Gent
Valentino D’Onofrio
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This document provides an introduction to Systems Vaccinology, a field that combines systems biology principles with vaccinology. It discusses the complex immune system, innate and adaptive immunity, vaccine immunogenicity, and methods like transcriptomics, proteomics, and metabolomics. The document aims to explore how understanding the immune system's response to vaccination can lead to better vaccine design and efficacy.
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Systems Vaccinology Valentino D’Onofrio, PhD Clinical Research Coordinator CEVAC Overview 1. 2. The diverse immune system The complex immune system A. B. I. Innate immunity Communication to adaptive immunity Adaptive immunity I. II. Cellular Humoral A. B. Regulatory requirements Knowledg...
Systems Vaccinology Valentino D’Onofrio, PhD Clinical Research Coordinator CEVAC Overview 1. 2. The diverse immune system The complex immune system A. B. I. Innate immunity Communication to adaptive immunity Adaptive immunity I. II. Cellular Humoral A. B. Regulatory requirements Knowledge gaps A. B. C. D. E. Transcriptomics Proteomics Metabolomics Systems serology Multi-omics 3. Vaccine immunogenicity 4. 5. 6. Systems Biology Systems Vaccinology Systems vaccinology – Methods 7. 8. 9. Systems Vaccinology to predict vaccine protection Systems Vaccinology to study mechanisms of action & adverse events Pitfalls The diverse immune system • Evolution has selected for diversity • Several factors play a role in this diversity. • E.g. Biological sex: o Male mammals experience trauma more frequent o Balance and homeostasis needed o Female mammals need to protect child o Stronger reactions but attenuated during pregnancy The complex immune system • • Well organised system of barriers, cells & soluble factors Communication & interaction Lymphatics The complex immune system • • Well organised system of barriers, cells & soluble factors Communication & interaction The complex immune system • Complex interplay leading to antiviral defense or pathogenesis Cells of the immune system COMMUNICATION BETWEEN INNATE AND ADAPTIVE Innate immune system Toll-like receptors (TLR) are activated by pathogen-associated molecular patterns (PAMPs), such as LPS Innate immune system Detection of bacteria/virus via PAMPs & TLR Phagocytes • Neutrophils • Monocytes • Macrophages à Detect, engulf, attack, kill à Produce inflammatory cytokines Natural Killer Cells à Engulf & kill Dendritic cells à Antigen presentation à Communication with Adaptive Innate immune system Innate immune system Innate to adaptive immune system Adaptive immune system - Cellular Adaptive immune system - Cellular Adaptive immune system - Cellular Antigen recognition – T cell receptor: MHC Class I (CD8+) & Class II (CD4+) CD8+ T cell MHC Class II CD4+ T cell MHC Class I T cell receptor Adaptive immune system - Cellular Antigen recognition – T cell receptor: MHC Class I (CD8+) Adaptive immune system - Cellular Antigen recognition – T cell receptor: MHC Class II (CD4+) Adaptive immune system - Cellular T cell receptor diversity Adaptive immune system - Humoral Adaptive immune system - Humoral Adaptive immune system - Humoral Antigen recognition – B cell receptor Adaptive immune system - Humoral B cell receptor diversity Adaptive immune system B & T cell receptor diversity Overview 1. 2. 3. The diverse immune system The complex immune system Innate immunity 4. Adaptive immunity 5. Vaccine immunogenicity 6. 7. 8. Systems Biology Systems Vaccinology Systems vaccinology – Methods A. Communication to adaptive immunity A. B. Cellular Humoral A. B. Regulatory requirements Knowledge gaps A. B. C. D. E. Transcriptomics Proteomics Metabolomics Systems serology Multi-omics 9. Systems Vaccinology to predict vaccine protection 10. Systems Vaccinology to study mechanisms of action & adverse events 11. Pitfalls 5 – 15 years • • • • • • First in Human Safety Immunogenicity • • • Dose & Schedule finding Safety Immunogenicity • • • Efficacy Safety Immunogenicity Regulatory submission • Ag definition and purification Formulation selection Immunology in animal models Mechanisms of action Toxicology 5 – 15 years Regulatory submission • Phase 4 & Post-market surveillance Clinical trial phases Vaccine Immunogenicity Vaccine Immunogenicity Almost all licensed vaccines mediate protection via humoral response Vaccine Immunogenicity Clinical Vaccine Development “To date, immunological parameters other than those that measure the humoral immune response have not played a pivotal or major role in vaccine licensure, so the focus is usually on determination of antibody levels.” Should include a description of the magnitude of the immune response, including assessment of functional antibody (neutralization or opsonophagocytosis). Total IgG or functional antibody measurement? • Dependent on correlate of protection • Known: only relevant antibody should be measured • Unknown: focus on functional, if possible efficacy trial Vaccine Immunogenicity Correlate of protection is a type and amount of immunological response that correlates with vaccine-induced protection against an infectious disease and that is considered predictive of clinical efficacy Plotkin SA (2023) Recent updates on correlates of vaccine-induced protection. Front. Immunol. 13:1081107. doi: 10.3389/fimmu.2022.1081107 Vaccine Immunogenicity Clinical Vaccine Development Case-by-case basis: • T-cell dependent response • Cross-reactivity • Antibody avidity • Factors influencing immune response à Decision lies with sponsor/investigator but should take into account existing knowledge about à Immune response to natural infection à Charachteristics of microorganism à Vaccine content Vaccine Immunogenicity First vaccine in 1796. • Many vaccines are empirically made • Immunology & Vaccinology share common origing but different trajectories • Largely ignorant about mechanisms of action of vaccines • Uninterested in immune regulation Molecular biology has led to increased knowledge innate immunity • ’Traditional’ scientific method • Hypothesis creation & experimental validation • Reductionist approach • Focus on specific parts Increased interest (scientific & regulatory) in • Cellular immune responses • Cytokine & gene expression profiles (innate reaction) àEMA ‘Guideline on the clinical evaluation of new vaccines’ Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010 Oct 29;33(4):516-29. doi: 10.1016/j.immuni.2010.10.006. PMID: 21029962; PMCID: PMC3001343. Overview 1. 2. 3. The diverse immune system The complex immune system Innate immunity 4. Adaptive immunity 5. Vaccine immunogenicity 6. 7. 8. Systems Biology Systems Vaccinology Systems vaccinology – Methods A. Communication to adaptive immunity A. B. Cellular Humoral A. B. Regulatory requirements Knowledge gaps A. B. C. D. E. Transcriptomics Proteomics Metabolomics Systems serology Multi-omics 9. Systems Vaccinology to predict vaccine protection 10. Systems Vaccinology to study mechanisms of action & adverse events 11. Pitfalls Systems Biology Interdisciplinary approach that systematically describes complex interactions between all parts in a biological system, with a view to elucidating new biological rules, capable of predicting the behaviour of the biological system. • Studying structure, dynamics & interactions of the whole system 1. Data collection from different parts of the system 2. Data analysis & integration 3. Creation of mathematical models that describe or predict response • Goal is to understnad the nature of biological networks • Access, integrate and communicate information from genome to environment and back • Need for high througput data + modeling on genes, mRNAs, proteins, … • Omics-technologies • Computational methods Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010 Oct 29;33(4):516-29. doi: 10.1016/j.immuni.2010.10.006. PMID: 21029962; PMCID: PMC3001343. Systems Vaccinology Applying the principles of systems biology to vaccinology • To study and understand perturbation induced by vaccination to the immune system & immune responses • By integrating omics-techniques 2 main applications: 1. Identfication of early immune markers Molecular signatures, such as patterns of gene expression after vaccination provide an idea of the pathways that becomes activated. This can be correlated with the development of protective imunity and help prospectively determine vaccine efficacy. 2. Study mechanisms of action and adverse effects by determination of activation of innate immune response Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010 Oct 29;33(4):516-29. doi: 10.1016/j.immuni.2010.10.006. PMID: 21029962; PMCID: PMC3001343. Systems Vaccinology Overview 1. 2. 3. The diverse immune system The complex immune system Innate immunity 4. Adaptive immunity 5. Vaccine immunogenicity 6. 7. 8. Systems Biology Systems Vaccinology Systems vaccinology – Methods A. Communication to adaptive immunity A. B. Cellular Humoral A. B. Regulatory requirements Knowledge gaps A. B. C. D. E. Transcriptomics Proteomics Metabolomics Systems serology Multi-omics 9. Systems Vaccinology to predict vaccine protection 10. Systems Vaccinology to study mechanisms of action & adverse events 11. Pitfalls Systems Vaccinology Methods • • Transcriptomics • Bulk • Single Cell • TCR/BCR repertoire Proteomics • • • • • Metabolomics Epigenetics Multi-omics Systems Serology Computational immunology Transcriptomics RNA sequencing PaxGene pre-post vaccine Stimulated PBMCs Total RNA = mRNA + rRNA. 80% rRNA: needfor removel Barcoding Transcriptomics RNA sequencing Transcriptomics RNA sequencing Count Matrix: Count the number of mRNA strains of genes in the sample DEG – Volcano Plot & Hierarchial Clustering Pathway Analyses & Gene-Ontology Enrichment Transcriptomics RNA sequencing Bulk Single Cell Spatial Transcriptomics RNA sequencing Transcriptomics RNA sequencing Transcriptomics RNA sequencing Transcriptomics Single-cell technologies Transcriptomics Antigen-specific T cells T cells = 14% of PBMCs 0,05% - 2% of T cells = antigen-specific 1 milion PBMCs = 140 000 T cells = max. 280 antigen-specific T cells Antigen presentation by MHC Capture antigen-specific cells using antigen-specific MHC molecules HLA type needs to be known! (Dextramer technology) Proteomics Clinical characterization of inflammatory response Cytokine measurements Multiplex panels for detection of inflammatory markers Similar analyses to (bulk) RNA sequencing Phenotypical level Biomarker identification Structural biology Design of antigens in correct conformation e.g. RSV pre-fusion protein Immunopeptidomics Metabolomics Impact of lipids, bile acids, … on immune response and or disease e.g. Phospholipis dynamics during COVID-19 infection results in different clinical outcomes Epigenetics sc ATAC sequencing Chromatin accessability as proxy for gene regulatory networks: • Determine open genes • Transcriptional Start Site & Motif analysis • Transcription factor binding Multi-Omics Multi-Omics CITE-seq Multi-Omics Multi-Omics System Serology Antibody subclasses and glycosylation tune interaction with Fc receptors System Serology Are all neutralizing/functional antibodies protective? Systems serology to interrogate humoral immunity • Flexible high-througput assays • Antibody engineering Computational Immunology Computational Immunology Computational Immunology Automated analysis of flow cytometry data Manual gating results in selection of specific subset populations Overview 1. 2. 3. The diverse immune system The complex immune system Innate immunity 4. Adaptive immunity 5. Vaccine immunogenicity 6. 7. 8. Systems Biology Systems Vaccinology Systems vaccinology – Methods A. Communication to adaptive immunity A. B. Cellular Humoral A. B. Regulatory requirements Knowledge gaps A. B. C. D. E. Transcriptomics Proteomics Metabolomics Systems serology Multi-omics 9. Systems Vaccinology to predict vaccine protection 10. Systems Vaccinology to study mechanisms of action & adverse events 11. Pitfalls Systems Vaccinology Applying the principles of systems biology to vaccinology • To study and understand perturbation induced by vaccination to the immune system & immune responses • By integrating omics-techniques 2 main applications: 1. Identfication of early immune markers Molecular signatures, such as patterns of gene expression after vaccination provide an idea of the pathways that becomes activated. This can be correlated with the development of protective imunity and help prospectively determine vaccine efficacy. 2. Study mechanisms of action and adverse effects by determination of activation of innate immune response Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010 Oct 29;33(4):516-29. doi: 10.1016/j.immuni.2010.10.006. PMID: 21029962; PMCID: PMC3001343. Predictive vaccine efficacy Complex immune system • Multiple lineages • Anatomically distinct 2 critical features 1. Blood and PBMCs are easily accessible • Easy sampling • Provide snapshot of lineages and differentiation state • Represent migrated immune cells • What we see in blood reflects overall response (?) 2. Immune cells are uniquely sensitive • Vaccination modifies gene expression • Easy comparison of gene expression pre- and post-vaccination Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010 Oct 29;33(4):516-29. doi: 10.1016/j.immuni.2010.10.006. PMID: 21029962; PMCID: PMC3001343. Predictive vaccine efficacy • • • • 3000 samples 820 vaccinated adults 28 studies 13 vaccines à Is there a universal vaccination-induced signature that predicts antibody responses? Predictive vaccine efficacy Hagan, T., Gerritsen, B., Tomalin, L.E. et al. Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses. Nat Immunol 23, 1788–1798 (2022). https://doi.org/10.1038/s41590-022-01328-6 Predictive vaccine efficacy Cluster 1: Up D1 & D3 Innate BTMs & TLR signalling Mainly viral vector & adjuvanted vaccines Cluster 2: NK cells Down on D1 Cluster 3 & 4: Cell cycle & plasmablast Peak on D7. Meningococcal & pneumococcal vaccine Hagan, T., Gerritsen, B., Tomalin, L.E. et al. Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses. Nat Immunol 23, 1788–1798 (2022). https://doi.org/10.1038/s41590-022-01328-6 Predictive vaccine efficacy Correlation on Day 1 across vaccines is high. Yellow fever vaccine is substantially different: • Downregulation of innate pathways on Day 1 • Early expression of B and T cell modules • Late antiviral IFN signalling on day 3 and 7 Hagan, T., Gerritsen, B., Tomalin, L.E. et al. Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses. Nat Immunol 23, 1788–1798 (2022). https://doi.org/10.1038/s41590-022-01328-6 Predictive vaccine efficacy BTMs that are capable of predicting antibody response in influenza, are not able to predict for other vaccines Using BTMs at day of peak response increases predicitive power Differential kinetics are confounding factor à Universal predictive signatue should be used with vaccine-specific timepoints Hagan, T., Gerritsen, B., Tomalin, L.E. et al. Transcriptional atlas of the human immune response to 13 vaccines reveals a common predictor of vaccine-induced antibody responses. Nat Immunol 23, 1788–1798 (2022). https://doi.org/10.1038/s41590-022-01328-6 Predictive vaccine efficacy Integration into clinical trials Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010 Oct 29;33(4):516-29. doi: 10.1016/j.immuni.2010.10.006. PMID: 21029962; PMCID: PMC3001343. Systems Vaccinology Applying the principles of systems biology to vaccinology • To study and understand perturbation induced by vaccination to the immune system & immune responses • By integrating omics-techniques 2 main applications: 1. Identfication of early immune markers Molecular signatures, such as patterns of gene expression after vaccination provide an idea of the pathways that becomes activated. This can be correlated with the development of protective imunity and help prospectively determine vaccine efficacy. 2. Study mechanisms of action and adverse effects by determination of activation of innate immune response Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010 Oct 29;33(4):516-29. doi: 10.1016/j.immuni.2010.10.006. PMID: 21029962; PMCID: PMC3001343. Mechanisms of action Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010 Oct 29;33(4):516-29. doi: 10.1016/j.immuni.2010.10.006. PMID: 21029962; PMCID: PMC3001343. Mechanisms of action Adjuvant research O'Hagan DT, van der Most R, Lodaya RN, Coccia M, Lofano G. "World in motion" - emulsion adjuvants rising to meet the pandemic challenges. NPJ Vaccines. 2021 Dec 21;6(1):158. doi: 10.1038/s41541-021-00418-0. Erratum in: NPJ Vaccines. 2023 Feb 2;8(1):7. PMID: 34934069; PMCID: PMC8692316. • • Adverse events 3 studies 123 adults • Varicella zoster vaccine • Yellow fever vaccine • Adjuvanted Hep B vaccine • Adjuvanted or non-adjuvanted TIV à Are there biomarkers that predict reactogenicity? • • T°, Pulse CRP, PTX3 Adverse events Subtle changes after vaccination Weiner J, Lewis DJM, Maertzdorf J, Mollenkopf HJ, Bodinham C, Pizzoferro K, Linley C, Greenwood A, Mantovani A, Bottazzi B, Denoel P, Leroux-Roels G, Kester KE, Jonsdottir I, van den Berg R, Kaufmann SHE, Del Giudice G. Characterization of potential biomarkers of reactogenicity of licensed antiviral vaccines: randomized controlled clinical trials conducted by the BIOVACSAFE consortium. Sci Rep. 2019 Dec 30;9(1):20362. • • Adverse events Inflammatory response aTIV vs. TIV most pronounced Follow-up study: does this relate to Reactogenicity (ongoing) Predicting reactogenicity can help design early phase clinical trials Weiner J, Lewis DJM, Maertzdorf J, Mollenkopf HJ, Bodinham C, Pizzoferro K, Linley C, Greenwood A, Mantovani A, Bottazzi B, Denoel P, Leroux-Roels G, Kester KE, Jonsdottir I, van den Berg R, Kaufmann SHE, Del Giudice G. Characterization of potential biomarkers of reactogenicity of licensed antiviral vaccines: randomized controlled clinical trials conducted by the BIOVACSAFE consortium. Sci Rep. 2019 Dec 30;9(1):20362. Pitfalls Low input, high througput: no output? • Human interpretation of results for total and biologically relevant understanding Conceptual problems • • Gene expression = truly relevant change? • Co-expression • No gene silencing, gene always ‘on’ • Causality determination needed • Literature & pre-existing knowledge, combining multiple datasets Blood = ‘perfect’ picture of total immune system? • Lymph nodes • Tissue immunology Technical problems • • • Artifacts, technical errors, doublets, empty droplets Genetic & environmental heterogeneity in humans (age, gender, exposure) Data management & big data Cultural problems • Close collaboration between biologists & bioinformaticians needed Pulendran B, Li S, Nakaya HI. Systems vaccinology. Immunity. 2010 Oct 29;33(4):516-29. doi: 10.1016/j.immuni.2010.10.006. PMID: 21029962; PMCID: PMC3001343. Key Points Human immunity is complex & diverse • Immunogenicity not only determined by humoral response • More insights needed in mechanisms of action – Innate & Cellular Systems biology applied to vaccinology • Holistic approach • Incorporation of omic-techniques Systems Vaccinology • Gene signatures for prediction of protection/efficacy • Mechanisms of action • Adverse Events & inflammtory reaction