Periodic Reporting for period 2 - ModVaccine (Cross-omics integration to identify modulators for improving vaccine efficacy)
Período documentado: 2022-07-01 hasta 2023-12-31
The problem and its importance for society
Influenza is a significant public health threat that causes about 3 to 5 million cases of severe illness and about 290,000-650,000 deaths annually worldwide. Influenza symptoms diverge from fever, muscle aches, fatigue, and headache to serious complications such as respiratory failure and death. While seasonal influenza vaccines are currently the primary prevention and the most effective strategy against influenza infection, the protection conferred upon vaccination is highly variable across the population. Vaccine efficacy is especially low in the elderly, individuals with comorbidities, or immunocompromised individuals; consequently, these individuals are poorly protected from influenza. Besides the inter-individual variation, substantial heterogeneity of the circulating influenza strains within the season and across seasons also poses difficulties in understanding human vaccine-induced responses.
To improve the efficacy of vaccinations, a better understanding of the factors that determine inter-individual variability in the immune response is required. Previous studies have assessed inter-individual variability among human immune responses, but are limited in investigating few factors such as variation in host transcriptome or other environmental factors. A simultaneous multi-layer investigation in host responses is lacking and is essential for better vaccine design, enhancing the efficacy of the vaccination, and consequently improving general public health.
Overall objectives
In line with our original proposal, we apply ‘systems immunological approaches’ to examine the host-specific factors implicated in the protection variability of the influenza vaccine.
1. We first aim to identify molecular factors and their interactions to determine vaccine-induced immune response. We use high-throughput technologies to systematically generate longitudinal multi-layer omics data in large, diverse cohorts. Thereafter, we examine multiple layers of omics with post-vaccination antibody titers (the main indicator of vaccine responsiveness). This allows us to identify the key molecular components and pathways crucial for immune responses and provide important biological insights into immunological processes in general.
2. Next, we aim to utilize the inter-individual variation in the key molecular components at pre-vaccination to construct predictive models for immune responses induced by vaccination using our extensive cross-omics data. We will validate our prediction model in independent cohorts.
3. Lastly, we aim to identify modulators that can be used for preventive or therapeutic intervention. Future pharmacological interventions can target those modulators to improve vaccine efficacy in non-responding individuals.
Since the global SARS-CoV-2 pandemic caused a lockdown for nearly two years, it had substantial impacts on research plans and activities. Therefore, while keeping the main focus on influenza, we expanded the scope of the current project to vaccination against other infectious diseases which will give a holistic view of the human immune response to vaccination. Within the ERC-ST project, we have applied a similar bioinformatics and systems immunology approach to anti-tuberculosis vaccine Bacillus Calmette–Guérin (BCG), MMR, and COVID-19 studies.
Influenza is a significant public health threat that causes about 3 to 5 million cases of severe illness and about 290,000-650,000 deaths annually worldwide. Influenza symptoms diverge from fever, muscle aches, fatigue, and headache to serious complications such as respiratory failure and death. While seasonal influenza vaccines are currently the primary prevention and the most effective strategy against influenza infection, the protection conferred upon vaccination is highly variable across the population. Vaccine efficacy is especially low in the elderly, individuals with comorbidities, or immunocompromised individuals; consequently, these individuals are poorly protected from influenza. Besides the inter-individual variation, substantial heterogeneity of the circulating influenza strains within the season and across seasons also poses difficulties in understanding human vaccine-induced responses.
To improve the efficacy of vaccinations, a better understanding of the factors that determine inter-individual variability in the immune response is required. Previous studies have assessed inter-individual variability among human immune responses, but are limited in investigating few factors such as variation in host transcriptome or other environmental factors. A simultaneous multi-layer investigation in host responses is lacking and is essential for better vaccine design, enhancing the efficacy of the vaccination, and consequently improving general public health.
Overall objectives
In line with our original proposal, we apply ‘systems immunological approaches’ to examine the host-specific factors implicated in the protection variability of the influenza vaccine.
1. We first aim to identify molecular factors and their interactions to determine vaccine-induced immune response. We use high-throughput technologies to systematically generate longitudinal multi-layer omics data in large, diverse cohorts. Thereafter, we examine multiple layers of omics with post-vaccination antibody titers (the main indicator of vaccine responsiveness). This allows us to identify the key molecular components and pathways crucial for immune responses and provide important biological insights into immunological processes in general.
2. Next, we aim to utilize the inter-individual variation in the key molecular components at pre-vaccination to construct predictive models for immune responses induced by vaccination using our extensive cross-omics data. We will validate our prediction model in independent cohorts.
3. Lastly, we aim to identify modulators that can be used for preventive or therapeutic intervention. Future pharmacological interventions can target those modulators to improve vaccine efficacy in non-responding individuals.
Since the global SARS-CoV-2 pandemic caused a lockdown for nearly two years, it had substantial impacts on research plans and activities. Therefore, while keeping the main focus on influenza, we expanded the scope of the current project to vaccination against other infectious diseases which will give a holistic view of the human immune response to vaccination. Within the ERC-ST project, we have applied a similar bioinformatics and systems immunology approach to anti-tuberculosis vaccine Bacillus Calmette–Guérin (BCG), MMR, and COVID-19 studies.
Within the ERC-ST project, we have generated multi-omics data and examined the response to influenza vaccines in various contexts. We have generated multi-omics datasets in:
• iMED: an elderly cohort of 234 donors aged 65 or more, in 2 seasons of influenza vaccination, covering up to 2 months post-vaccination.
• ZirFlu: a cohort of ˜100 compensated and non-compensated cirrhotic and healthy donors, in 2 seasons, covering up to 2 months post-vaccination.
• RA cohort: a cohort of ~ 350 rheumatoid arthritis, spondylarthritis arthritis, and healthy donors, across different seasons and longitudinal datasets.
We have analyzed and published our findings related to influenza vaccination in high-impact journals such as Cell and Cell Genomics. Within the ERC-ST project, we have also applied a similar bioinformatics and systems immunology approach to other vaccination and infectious disease studies. Our group has led and collaborated on several studies describing the human immune variation in response to BCG (3 publications), MMR (1 publication), immune variation across different ethnic populations (1 publication), SARS-CoV-2 vaccination (1 publication), COVID-19 (3 publications), and the post-COVID-19 syndrome (2 publications). Overall, we have published 19 papers, and 2 manuscripts are under review that acknowledge this ERC grant.
• iMED: an elderly cohort of 234 donors aged 65 or more, in 2 seasons of influenza vaccination, covering up to 2 months post-vaccination.
• ZirFlu: a cohort of ˜100 compensated and non-compensated cirrhotic and healthy donors, in 2 seasons, covering up to 2 months post-vaccination.
• RA cohort: a cohort of ~ 350 rheumatoid arthritis, spondylarthritis arthritis, and healthy donors, across different seasons and longitudinal datasets.
We have analyzed and published our findings related to influenza vaccination in high-impact journals such as Cell and Cell Genomics. Within the ERC-ST project, we have also applied a similar bioinformatics and systems immunology approach to other vaccination and infectious disease studies. Our group has led and collaborated on several studies describing the human immune variation in response to BCG (3 publications), MMR (1 publication), immune variation across different ethnic populations (1 publication), SARS-CoV-2 vaccination (1 publication), COVID-19 (3 publications), and the post-COVID-19 syndrome (2 publications). Overall, we have published 19 papers, and 2 manuscripts are under review that acknowledge this ERC grant.
Examining the iMED cohort, we found that an important candidate biomarker through an NK-driven mechanism that leads to a decrease in vaccine-induced antibody production in the elderly; the model is supported by experimental validation in mice. We are exploring the possibility of patenting this biomarker. Our results also show certain long-chain fatty acids as potential modulators of persistent inflammation in non-responders. Together, these results highlight the potential for stratification of vaccinees and provide candidate molecules to enhance vaccine responses in the elderly.
In the ZirFlu cohort, cirrhotic patients, with chronic hyperinflammatory conditions, unexpectedly responded better to the vaccine compared to healthy controls, irrespective of age. The distinction in immune cells, cytokines, and metabolite profiles in cirrhotic patients suggests a contribution towards the efficient humoral and cellular vaccine responses. This is unexpected since cirrhotic patients are usually considered suboptimal vaccine responders. To complement these findings, we are planning to analyze the vaccine response from patients with different comorbidities i.e. in an RA cohort. By combining these cohorts, we aim to increase our understanding of the immune response in immunocompromised individuals.
While influenza vaccine response is currently measured as the increase in antibody titers between post-vaccination and pre-vaccination states, this criterion could be influenced by the high pre-existing antibodies due to previous infection and/or vaccination and consequently fail to identify people who are truly non-protected against influenza. We are developing a reclassification concept, which includes the vaccine-induced response and the levels of pre-existing antibody titers, to better separate non-responders from responders. We identified consistent molecular signatures in truly non-protected individuals across age groups in multi-cohorts and multi-season. We are also developing a machine learning model based on these biomarkers to predict how individuals respond to influenza vaccination before administering the vaccine. This offers a personalized vaccine strategy by stratifying people based on their immune response and giving, for example, higher-dose vaccines to non-protected individuals.
To bring our novel findings to the clinical setting, we aim to develop a diagnostic test that can identify people who do not respond effectively to the influenza vaccine for personalizing vaccine administration. We are in contact with supporting staffs from Helmholtz centers for the patenting process to protect our intellectual property. We are applying for the Helmholtz Enterprise – Field Study Fellowship (HE-FSF) to identify the target customer and explore the market and the commercial aspects of our idea. We are also applying for the ERC – Proof of Concept (PoC) grant to validate our findings and inspect the manufacturing aspect of our idea. Thus, we are in the process of communicating with different stakeholders to transfer our fundamental research to clinical applications.
In the ZirFlu cohort, cirrhotic patients, with chronic hyperinflammatory conditions, unexpectedly responded better to the vaccine compared to healthy controls, irrespective of age. The distinction in immune cells, cytokines, and metabolite profiles in cirrhotic patients suggests a contribution towards the efficient humoral and cellular vaccine responses. This is unexpected since cirrhotic patients are usually considered suboptimal vaccine responders. To complement these findings, we are planning to analyze the vaccine response from patients with different comorbidities i.e. in an RA cohort. By combining these cohorts, we aim to increase our understanding of the immune response in immunocompromised individuals.
While influenza vaccine response is currently measured as the increase in antibody titers between post-vaccination and pre-vaccination states, this criterion could be influenced by the high pre-existing antibodies due to previous infection and/or vaccination and consequently fail to identify people who are truly non-protected against influenza. We are developing a reclassification concept, which includes the vaccine-induced response and the levels of pre-existing antibody titers, to better separate non-responders from responders. We identified consistent molecular signatures in truly non-protected individuals across age groups in multi-cohorts and multi-season. We are also developing a machine learning model based on these biomarkers to predict how individuals respond to influenza vaccination before administering the vaccine. This offers a personalized vaccine strategy by stratifying people based on their immune response and giving, for example, higher-dose vaccines to non-protected individuals.
To bring our novel findings to the clinical setting, we aim to develop a diagnostic test that can identify people who do not respond effectively to the influenza vaccine for personalizing vaccine administration. We are in contact with supporting staffs from Helmholtz centers for the patenting process to protect our intellectual property. We are applying for the Helmholtz Enterprise – Field Study Fellowship (HE-FSF) to identify the target customer and explore the market and the commercial aspects of our idea. We are also applying for the ERC – Proof of Concept (PoC) grant to validate our findings and inspect the manufacturing aspect of our idea. Thus, we are in the process of communicating with different stakeholders to transfer our fundamental research to clinical applications.