Celluloepidemiology: a novel paradigm for modeling T-cell responses on a population level.

Project Information

CELLULO-EPI

Grant agreement ID: 851752

DOI

10.3030/851752

Project closed

EC signature date 12 February 2020

Start date 1 March 2020

End date 31 August 2025

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 499 734,00

EU contribution

€ 1 499 734,00

Coordinated by

UNIVERSITEIT ANTWERPEN
Belgium

Periodic Reporting for period 4 - CELLULO-EPI (Celluloepidemiology: a novel paradigm for modeling T-cell responses on a population level.)

Reporting period: 2024-09-01 to 2025-08-31

Summary of the context and overall objectives of the project

Celluloepidemiology is a term invented to describe an interdisciplinary approach combining unique cellular immune responses against pathogens on a population level with mathematical modeling, thereby generating unique and otherwise not obtainable multidimensional T-cell profiles.

CELLULO-EPI will develop and use such a highly innovative model to simulate how T-cells against pathogens evolve in a synthetic population as a function of age, gender, time since infection and other relevant variables. This model will be parameterized and fitted by cross sectional T-cell data against a wide set of pathogens from 500 individuals (sampled again after 1 year), unique data from individuals with known first infections with chikungunya and longitudinal data from individuals receiving de novo yellow fever vaccination or re-exposed to chickenpox.

The insights of CELLULO-EPI will be pivotal for public health. One important example: Varicella-zoster virus (VZV) causes chickenpox but also shingles after VZV reactivation. Vaccination can prevent chickenpox, but the predicted increase in shingles incidence has blocked chickenpox vaccination in many EU-countries. Indeed, re-exposure to chickenpox is hypothesized to protect against shingles through boosting of T-cells. Unfortunately, none of the available epidemiological or immunological tools allow for adequate validation of the boosting hypothesis. However, CELLULO-EPI will be able to solve this persisting VZV vaccination dilemma. Furthermore, CELLULO-EPI will also redefine infectious disease epidemiology, for example by allowing us to back-calculate the time since last exposure.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

We have been able to recruit > 600 participants and obtained PBMC and serum from these individuals.
- We have analysed a large cohort of > 600 participants for which we performed cytof mass cytometry to obtain best T-cell markers to analyse T-cell responses against SARS-CoV-2, VZV and parvovirus B19.
- We used these markers on a novel flow cytometer allowing in-depth high-throughput T-cell characterization for more than 600 samples (each 5 stimuli).
- We developed a R based program (including automatic gating) allowing us to appropriately and timely analyse these 3000 flow cytometry data files using the Flemish Super Computer.
- We used FLOWSOM (again supported by the Flemish Super Computer) to define T-cell subclusters.
- We used machine learning algorithms to infer fundamental immunological differences between the different population groups regarding SARS-CoV-2
- We developed mathematical models, based on agent-based models, to simulate VZV and B19 specific T cell responses throughout time
- We obtained multi-omics data that allowed defining clusters of individuals depending on different variables including CMV serostatus and faecal microbiome
- We have shown that CMV seropositivity is associated with senescent T cells
- We have shown that antigen-specific immunity declines with ageing
- We have shown that individuals with high exposure to various infections have a higher VZV-specific T cell responses
- We have shown that de novo yellow fever vaccination induces both CD4+ and CD8+ T cell responses with changing T cell phenotypes

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

- we have been able to show that T-cell based epidemiology might be a validate alternative for antibody based epidemiology
- we have shown that T cell based epidemiology can indicate the severity of the SARS-CoV-2 infection in health care workers
- we have shown that T cell receptor data modeling can differentiate individuals with recent SARS-CoV-2 infection from individuals with only common coronavirus exposure
- we have shown that certain faecal microbiome clusters are associated with less inflammation
- we have shown that even > 3 months after SARS-CoV-2 infection a higher inflammatory state remains in these convalescent patients
- we have shown that interrogation of blood TCR repertoires can indicate the faecal microbiome
- we have shown that integrative agent-based modeling can adequately simulate the T cell response against VZV and B19

ERC