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Discovery
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Sally Woodman, PhD

Immune Correlates of Protection: A Vaccine’s Biological Benchmark

We know vaccines protect us against infection. Measuring how they do this can explain how they do this.

In the development of novel vaccines understanding the protection they elicit and how to predict if they will protect against disease resulting from subsequent exposure to infection is critical.

What is immune protection?

On exposure to natural infection the body mounts an immune response to target the threat and protect itself. Protection implies the induction of immunological mechanisms to prevent or reduce the severity of disease on subsequent re-exposure to the pathogen. This protective response is a complex system involving many aspects of the immune system working in concert. The aim of vaccination is to drive an immune response eliciting the protection without the presence of disease. Depending on the response generated towards a vaccine the degree of protection can vary from protecting from severe disease to complete sterilising immunity (1).

What are correlates of protection and why they so important?

Understanding the relationship between the immune response and patient symptoms on exposure to a pathogen is key to the development of novel vaccines, with identifying immune markers which predict the protective effects being a critical phase in this process. These biomarkers are measurable characteristics which can be used as an indicator of biological processes or an organism’s disease state. In the field of vaccinology measurable immune responses to the vaccine which are statistically shown to be associated with protection against the pathogen are called correlates of protection (COP).  Reliable COP allow changes in the biomarker of interest to be utilised in determining if an individual will be protected when they are exposed to disease rather than embarking on lengthy trials reliant on the participants natural exposure to infection. Identifying reliable correlates of protection speeds up the vaccine development process. COP not only identify those candidate vaccines which are likely to result in effective protection at an early stage, reducing the waste of time and resources on unsuccessful candidates, but also connect preclinical animal models with clinical trials, aid in the transition from early and late phase trials and support the faster evidence-based progression towards licencing.  (2-4).

The flu vaccine is an exemplar of established COP accelerating vaccine development. The rate of mutation of the influenza virus means vaccines are required to undergo an equally fast pace of evolution with strategic COP-based vaccine design and delivery mechanisms being employed. Novel vaccines are judged based on their ability to trigger a strong enough immune response, with haemagglutination inhibition antibody titre currently being the ’gold standard’ for predicting protection (5). Lessons learned from this fast pace of vaccine development are being applied to new and emerging diseases using general predictive rules (3).

Inevitably, antibody levels wane over time; therefore understanding the appropriate level required to elicit full protection should also be considered and helps to inform the requirement and timing of booster vaccinations. It is also worth noting that due to the multifaceted nature of the immune response there will likely be more than one mechanism of protection in play. Consequently, as antibody levels wane over time other aspects of the immune response persist, T cell mediated immunity for example, meaning that a lack of antibodies in the blood does not necessarily mean a loss of protection.

How do we identify correlates of protection?

Correlates of protection are generally identified by comparing the immune response of those protected by the vaccine and so called ‘breakthrough cases’, where clinical disease manifests despite prior vaccination. In the case of the COVID-19 pandemic, the numerous vaccines developed have proven very effective with low incidences of breakthrough cases making the identification of potential correlates of protection a slow process. As a result, comparisons with previously published data relating to both natural infection and vaccine studies have been drawn (6).

A study of healthcare workers exposed to SARS-COV-2 showed that an increase in antibodies against the spike and nucleocapsid proteins correlated with protection from infection indicating that such biomarkers are of particular interest (7). This was confirmed in a recent study by Oxford/ AstraZeneca in a comparison of 171 cases vs 1404 participants that did not develop clinical infection. The model, which considered the participants perceived risk of infection, indicates that levels of neutralising antibodies, alongside binding antibodies which recognise the spike protein, correlated with incidence of symptomatic infection with protection ranging from 50-90% (8).

Yet it is still difficult to determine if these antibodies are relevant in predicting the level of protection from all COVID-19 vaccines. In the race to develop vaccines many different technologies have been utilised, each stimulating a unique profile of immune response. Many of these vaccines have shown that cell-mediated immunity is also important at driving protection. In fact B cells cannot make good antibody responses if they do not get help from T cells. This means that readouts including those investigating T cell mediated immune responses and cytokine profiles may prove more relevant COP for these vaccines. Standardisation of such techniques would be required prior to uptake by licencing bodies. To be truly valuable, the ideal corelate of protection would work across multiple vaccine platforms.

Sally Woodman is a senior scientist within the Cell Biology team at Charles River Laboratories, Portishead. She is involved in pre-clinical research studies exploring immune modulation within the fields of immune-oncology and autoimmunity. Before joining Charles River she completed a PhD at the Royal Veterinary College developing novel biotherapeutics against S. aureus infection in cattle.

References:

  1. Department of Immunization, Vaccine and Biologicals. Correlates of vaccine-induced protection: methods and implications. World Health Organisation. https://apps.who.int/iris/bitstream/handle/10665/84288/WHO_IVB_13.01_eng.pdf;sequence=1 (2013).
  2. Callaway, E. Scientists identify long-sought marker for COVID vaccine success. https://doi.org/10.1038/d41586-021-01778-2 (2021)
  3. Van Els, C., Mjaaland, S., Naess, L., Sarkadi, J., Gonczol, E., Korsholm, K. S., Hansen, J., de Jonge, J., Kersten, G., Warner, J., Semper, A., Kruiswijk, C. & Oftung, F. Fast vaccine design and development based on correlates of protection (COPs). Hum Vaccin Immunother, 10(7) 1935-1948. (2014).
  4. Plotkin, S. A. Correlates of protection induced by vaccination. Clin Vaccine Immunol, 17(7) 1055-1065. (2010).
  5. Trombetta, C. M. & Montomoli, E. Influenza immunology evaluation and correlates of protection: a focus on vaccines. Expert Rev Vaccines. 15(8) 967-976 (2016).
  6. Khoury, D. S., Cromer, D., Reynaldi, A., Schlub, T. E., Wheatley, A. K., Juno, J. A., Subbarao, K., Kent, S, J,. Triccas, J. A. & Davenport, M. P. Neutralising antibody levels are highly predictive of immune protection from symptomatic SARS-CoV-2 infection. Nature Medicine, 27 1205-1211 (2021).
  7. Lumley, S. F., O’Donnell, D., Stoesser, N. E., Matthews, P. C., Howarth, A., Hatch, S. B., Marsden, B. D., Cox, S., James, T., Warren, F., Peck, L. J., Ritter, T. G., Toledo, Z., Warren, L., Axten, D., Cornall, R. J., Jones, Y., Stuart, D. I., Screaton, G., Ebner, D., Hoosdally, S., Chand, M., Crook, D. W., O’Donnell, A., Conlon, C. P., Pouwels, K. B., Walker, S., Peto, T. E. A., Hopkines, S., Walker, T. M., Jeffery, K. & Eyre, D. W. Antibody status and Incidence of SARS-Cov2 Infection in Health Care Workers. N Engl J Med 384 533-540 (2021).
  8. Feng, S., Phillips, D. J., White, T., Sayal, H., Aley, P. K., Bibi, S., Dold, C., Fuskova, M., Gilbert, S. C., Hirsch, I., Humphries, H. E., Jepson, B., Kelly, E. J., Plested, E., Shoemaker, K., Thomas, K. M., Vekemans, J., Villafana, T. L., Lambe, T. & Pollard, A. J., Preprint at: https://www.medrxiv.org/content/10.1101/2021.06.21.21258528v1.full (2021).