Deciphering immunological imprinting in the context of COVID-19

NewsGuard 100/100 Score

In a recent article published in the journal Immunity, researchers explained the concept of immunological imprinting and its underlying principles. They also discussed its potential role in the context of coronavirus disease 2019 (COVID-19) vaccines.

Primer: Immunological imprinting: Understanding COVID-19. Image Credit: Lightspring / ShutterstockPrimer: Immunological imprinting: Understanding COVID-19. Image Credit: Lightspring / Shutterstock

Immunological imprinting is a phenomenon where prior exposure to a viral strain (an antigen) elicits B-cell memory which confers protection against related antigens in the future. In other words, first exposure to an antigen (e.g., a viral pathogen) leaves an ever-lasting 'imprint' on the naïve immune system. Other names for immunological imprinting are antigenic imprinting, immune imprinting, and original antigenic sin (OAS).

Renowned scientist Thomas Francis Jr coined the term OAS in the context of the influenza virus in the 1960s since many epidemiological studies associated immune imprinting with the effect of childhood exposure to the influenza A virus on susceptibility to contract severe influenza infections later in life. However, it has recently garnered attention due to the advent of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

The term original antigenic "sin" seems to have a negative connotation. It points to the development of a lifelong antigenic bias following the first exposure to an antigen in childhood. Although reactivity towards the original strain is higher than towards newer strains, it is yet feasible to exploit OAS with the right vaccine formulation. Further, the researchers discussed the seemingly conflicting observations in the published scientific literature on OAS, i.e., inherently focused on the influenza virus.

In cases where OAS is examined as a bias in antibody levels after a second exposure to an antigen, the time of sampling after-re-exposure is a confounder. Further, 'biases' differs substantially, sometimes referring to a variation in antibody affinity to original vs. recall antigens or to a measurable variation in antibody titers, where quantification assays could be confounders (e.g., neutralization vs. binding assays).

Though rarely, OAS also refers to in vivo antibody recall by a secondary antigen. However, these do not show quantifiable in vitro binding to the secondary antigen though they bind the original antigen. In the past few decades, connotations of the word 'sin' in OAS have limited its utility. So, avoiding this term and using other consistently defined terms that are less prone to misinterpretation is advised.

Another noteworthy feature of immune imprinting is that all immunological reactivity differences triggered by it could not be translated into epidemiological differences. Hence, variable susceptibility to infections could easily be considered an 'epidemiological imprint' that the first antigen exposure leaves at the population level.

Some additional terms could help explain or describe observed patterns in antibody titers or the above immunological effects of OAS. First is 'antigenic seniority,' which refers to a quantitatively stratified hierarchy of antibody titers elicited in response to encounters with antigenically-related viruses in a lifetime.

As the name suggests, in this hierarchy, antigens encountered earlier hold a senior position than those encountered later in life. Cross-sectional studies use this term in the context of 'steady-state' antibody titers, and while it captures a phenomenon closely similar to Francis' OAS, it has no negative connotations.

Another term is 'back-boosting,' which refers to an elevation in antibody titers towards antigens encountered previously. Longitudinal studies used this term to describe antibody responses post-exposure to antigenically related pathogens, e.g., a modified influenza virus strain used in a vaccine or a newer strain causing re-infection.

While the titer boost, i.e., fold-difference between pre-and post-exposure titers, is greater for newer antigens, back-boosting preserves the absolute neutralizing antibody titers towards previously encountered antigens at an elevated level than towards newer ones. These terms manifest two core immunological processes: cross-reactivity and memory recall. 

Published literature often suggests that immune imprinting is a  barrier to generating protective immunity. For instance, there is evidence that childhood exposure adversely influenced the vaccine efficacy of influenza A viruses. On the contrary, childhood exposure to H1N1 substantially decreased the risk of H1N1-caused influenza and the risk of fatal H5N1 infection. However, given several mixed effects, beneficial and detrimental, of prior exposures, it is not advisable to generalize the effects of immune imprinting.

While immunological data could help understand the observed epidemiological patterns, vice versa, i.e., extrapolating immunological results to clinical outcomes is not feasible. Considering the classic seroprotection curve, either of two possibilities arise:

i) above an antibody threshold, the conferred immune protection does not increase;

ii) comparable antibody titer fold variation could have markedly varying protective effects. 

Both scenarios depend on the actual antibody titers and their relationship with immune protection.

Importantly, concerning disease severity, immune protection is multifactorial and not quantifiable by a single immunological assessment. So, while immunological data might be useful, interpreting the clinical and epidemiological inferences of exposure history entirely from variations in antibody reactivity patterns could lead to misinterpretations.

So far, neutralizing antibodies are an established correlate of protection for COVID-19 vaccines. However, that does not undermine the significance of cellular immunity, which is relatively less affected by exposure history, when considering protection from disease.

Studies have shown back-boosting of antibodies with cross-reactivity towards the spike(S) protein of several hCoVs following COVID-19 vaccination or SARS-CoV-2 infection. However, evidence suggesting that these antibodies modulate susceptibility to severe disease is sparse.

On the contrary, people primed with an ancestral SARS-CoV-2 strain (Wuhan-Hu-1-like) via vaccination or infection, who contracted an infection with an antigenically drifted variant, showed higher neutralizing antibody titers against Wuhan-Hu-1-like antigen (by back-boosting) and the new infecting variant.

However, when infected with an antigenically distant variant, e.g., Omicron, they maintained higher antibody titers against the Wuhan-Hu-1 than Omicron, illustrating antigenic seniority. Both scenarios are manifestations of recall of cross-reactive memory B cells elicited by Wuhan-Hu-1 priming.

Surprisingly, bivalent vaccines based on Omicron BA.1/BA.5 antigens elicit a higher neutralization activity towards more antigenically advanced variants. Also, an Omicron antigen-based bivalent vaccine triggers antibodies with de novo reactivity toward mutated epitopes, indicating naïve B cell recruitment to the antigen exposure site.

It is not yet possible to fully comprehend and generalize the effects of prior antigen exposure on subsequent B cells responses through cross-reactivity and recall. However, increasing antigen dosage or adding adjuvants in vaccine formulations could impede some of the limitations imposed by pre-existing memory.

Conclusions

Effects of prior antigen exposure impact immunity towards diseases. While immunological patterns, e.g., antigenic seniority, seemed significant in analyses of antibody reactivity, epidemiolocal patterns looked like the key determinants of disease susceptibility in people with varying exposure histories. Thus, there is an urgent need to carefully consider these effects using consistent terminology while extrapolating them to clinical outcomes. Nevertheless, the study provided insights that could greatly help the development of COVID-19 vaccines against antigenically progressive SARS-CoV-2 variants.

Journal reference:
Neha Mathur

Written by

Neha Mathur

Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.

Citations

Please use one of the following formats to cite this article in your essay, paper or report:

  • APA

    Mathur, Neha. (2023, April 24). Deciphering immunological imprinting in the context of COVID-19. News-Medical. Retrieved on April 23, 2024 from https://www.news-medical.net/news/20230424/Deciphering-immunological-imprinting-in-the-context-of-COVID-19.aspx.

  • MLA

    Mathur, Neha. "Deciphering immunological imprinting in the context of COVID-19". News-Medical. 23 April 2024. <https://www.news-medical.net/news/20230424/Deciphering-immunological-imprinting-in-the-context-of-COVID-19.aspx>.

  • Chicago

    Mathur, Neha. "Deciphering immunological imprinting in the context of COVID-19". News-Medical. https://www.news-medical.net/news/20230424/Deciphering-immunological-imprinting-in-the-context-of-COVID-19.aspx. (accessed April 23, 2024).

  • Harvard

    Mathur, Neha. 2023. Deciphering immunological imprinting in the context of COVID-19. News-Medical, viewed 23 April 2024, https://www.news-medical.net/news/20230424/Deciphering-immunological-imprinting-in-the-context-of-COVID-19.aspx.

Comments

The opinions expressed here are the views of the writer and do not necessarily reflect the views and opinions of News Medical.
Post a new comment
Post

While we only use edited and approved content for Azthena answers, it may on occasions provide incorrect responses. Please confirm any data provided with the related suppliers or authors. We do not provide medical advice, if you search for medical information you must always consult a medical professional before acting on any information provided.

Your questions, but not your email details will be shared with OpenAI and retained for 30 days in accordance with their privacy principles.

Please do not ask questions that use sensitive or confidential information.

Read the full Terms & Conditions.

You might also like...
Annual COVID-19 vaccine proves to be a wise investment for personal health and pocketbook