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The digital phenotype of vaccination

To the Editor — Vaccines against COVID-19 have been a remarkable public health success. However, as with all vaccines, immunologic response can vary by several orders of magnitude between individuals1. This is important since antibody levels following COVID-19 vaccination have been shown to correlate with the level of protection2. As only a miniscule fraction of the over 5 billion people vaccinated worldwide have undergone blood testing to analyze their immune response, for the majority of people the ultimate measure of their adequacy of immune protection is whether they experience a breakthrough infection and the level of its severity.

Vaccination activates the innate immune system, triggering the synthesis of inflammatory cytokines critical to launching an antigen-specific adaptive immune response. The physical manifestations of this inflammation, termed reactogenicity, has historically been tracked only by symptom surveys. Limited studies directly measuring inflammatory blood biomarkers have not only found substantial inter-individual variation in this inflammatory response, but also a strong correlation between this response and both systemic symptoms3 and humoral immune reponse4.

Systemic inflammation, even at low levels, can manifest as subtle but measurable physiological changes in multiple parameters, including temperature, heart rate, blood pressure and heart rate variability5. Because of the normal variation in these parameters that a person experiences throughout each day, as well as day-to-day, potentially meaningful changes can go undetected through occasional spot checks. Furthermore, due to the substantially large inter-individual differences, population-based cut-offs, such as a temperature of >38 °C, are especially insensitive. Because wearable sensors can now continuously track multiple physiological and behavioral parameters, we have, for the first time, the ability to detect these small individual changes and objective measures of reactogenicity.

Early proof-of-concept data from the DETECT6 study and from other studies7,8,9 confirm that consumer wearable sensors can detect the individual physiological and behavioral changes associated with the vaccination and the consequent inflammation. All three studies7,8,9 identified significant post-vaccine changes in daily summary values of physiological and behavioral parameters relative to their pre-vaccine individual baselines. The level of deviation from normal was moderate. For example, a mean increase of only 1.5 beats per minute in resting heart rate, a decrease of 1,600 daily step count and an increase of 35 min of night sleep were observed after a second mRNA vaccine dose7. Yet these findings tracked well with established knowledge of subjective assessments of reactogenicity, such as significantly greater changes in those receiving the Moderna versus the Pfizer/BioNTech vaccine and in those receiving the first dose response in people with prior COVID-19 infection (Fig. 1).

Fig. 1: Physiological and behavioral changes post vaccination.
figure 1

Monitoring physiological (resting heart rate, RHR) and behavioral (sleep) changes post vaccination to identify vaccine response. Graphs reproduced with permission from ref. 7, Springer Nature.

The potential value in identifying these small, individual changes was demonstrated by Mason et al.9 in their study of over 1,000 individuals with wearable data from a smart ring and with post-vaccination SARS-CoV-2 receptor-binding domain antibody levels. They identified a significant and direct correlation between the change in several physiological parameters and immunogenicity, with the strongest independent predictor being temperature deviation. These finding are interesting considering prior work that has found that in some but not all studies, prophylactic antipyretic therapy can diminish the immunologic response to vaccine10. The ability to measure inflammation following vaccination has the potential, after being confirmed with rigorous prospective studies, of identifying individuals who may not develop an adequate immune response after vaccination.

Beyond the potential association between physiological changes and immunogenicity, objective evidence of the real-world behavioral impact of vaccines can aid in the design of safer, better-tolerated vaccines. The limitations of capturing this information using only subjective surveys is highlighted in an analysis of reported adverse events in the placebo-controlled COVID-19 vaccine trials that found that >50% of the systemic adverse events reported could be attributed to a nocebo response11. Measurement of changes in activity type and duration, sleep quality and duration, sedentary time, posture and more, relative to a person’s baseline before vaccination, can tell a more accurate and complete story of the severity of reactogenicity.

Although we find these early data encouraging, there still is a good deal to learn before wearables can become a standard part of vaccine development and treatment. For one, the current data are based on surprisingly sparse individual data — typically just one data point a day per parameter. Ongoing studies using medical grade wearable sensors with continuous high-fidelity data capture surrounding vaccination will help clarify the value of much deeper data (for example, ClinicalTrials.gov Identifier: NCT05237024). Most importantly, there is a need for more real-world data, with simultaneous testing of humoral and cellular immunogenicity, along with subjective symptoms. The ultra-rapid development of remarkably successful mRNA vaccines against COVID-19 foretells the future potential for this technology to address not only infectious diseases, but much more. Wearable technologies, passively and longitudinally tracking individuals without interfering with their day-to-day life, can help to realize the potential of individualized care based on a person’s unique response to inflammatory stimuli.

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Acknowledgements

This work was funded by grant number UL1TR002550 from the National Center for Advancing Translational Sciences (NCATS) at the National Institutes of Health (NIH) (E.J.T.)

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Correspondence to Giorgio Quer.

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S.R.S. is employed by PhysIQ. The other authors declare no competing interests.

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Quer, G., Topol, E.J. & Steinhubl, S.R. The digital phenotype of vaccination. Nat Biotechnol (2022). https://doi.org/10.1038/s41587-022-01417-9

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