Seasonal rhythms are endogenous timing mechanisms that allow animals living at temperate latitudes to synchronize their physiology to the seasons. Human viral respiratory disease is prevalent in the winter at temperate latitudes, but the role of endogenous mechanisms in these recurring annual patterns is unclear.
The common cold project is a repository of data from five US and UK viral challenge studies of the factors underlying susceptibility to the common cold. The studies were carried out at temperate latitudes (40-50oN), and across the four seasons, facilitating the investigation of associations between annual changes in day length and susceptibility to experimental viral challenges. If day length-dependent rhythms in human immunity contribute to this susceptibility, then their endogenous origin should cause them to persist when variations in temperature, humidity, and exposure to other sources of infection are eliminated. Here, we test this hypothesis by investigating whether: (i) susceptibility to infection by a respiratory virus or (ii) susceptibility to disease once infection has occurred, are associated with day length following viral challenge under controlled conditions in the Common Cold Project.
This study describes a secondary analysis of data collated by the Common Cold Project, which is a repository of data from studies of susceptibility to infection with respiratory viruses carried out in the UK (British Cold Study, BCS) and in the US (Pittsburgh Cold Studies, PCS) between 1986-2004. (Laboratory for the Study of Stress, Immunity, and Disease. (2016). Common Cold Project. Retrieved from http://www.commoncoldproject.com) The BCS and PCS were analysed separately due to discrepancies between the definition of the disease outcomes and some of the covariables.
These was extensive variability in the times of year that different viruses were tested in the BCS, and the PCS did not collect data at all in the months of January or February. Furthermore, the PCS included data from four separate experiments, Pittsburgh Cold Study 1, Pittsburgh Cold Study 2, Mind-Body Center Study, and Pittsburgh Cold Study 3).We expressed the time-dependent data as a categorical variable (season) or a continuous variable (Day length) rather than month, in order to address the missing data for January and February. Season was defined by the CCP as winter (December-February), spring (March-May), summer (June-August), fall (September-November). Pre-challenge immunity (virus-specific IgG measured at baseline) was defined as positive at antibody titres above 1:2 for rhinoviruses and at antibody titre greater than the sample median for coronavirus or respiratory syncytial virus as previously described for Common Cold Project data. The CCP continuous variables stratified by study name (PCS or BCS) are reported as mean (sd) or n (%) for continuous or categorical data, respectively . The PCS data were not independent due to their derivation from four separate iterations of the PCS. A mixed-effects logistic regression model with PCS as a random effect, was used to address this violation of the assumption of independence. The association between variables and disease outcomes were expressed as odds ratios or regression coefficients with 95% confidence intervals. All analyses were performed using R version 4.1.3 and values of p % 0.05 were considered to represent statistical significance. (R-code BCS; R-code PCS)
Univariate analysis directed the selection of parameters (p< 0.2) for inclusion as fixed effects inmultivariable models. Day length, age, and pre-challenge immunity were significantly associated with the probability of infection post-challenge, while day length, pre-challenge immunity, were associated with the probability of developing disease if infected. The majority of the participants (78%) showed signs of infection but only 32% developed clinical signs of disease, and the probability of infection was significantly higher in longer day lengths (summer), but the disease was more likely in short (winter) day lengths. The persistence of winter disease patterns in experimental conditions supports the role of endogenous seasonality in human susceptibility to viral infection.
Figure 1 Common cold infection and disease by season. The percentages of participants infected and that went on to develop clinical signs of disease in the PCS. Infection was higher in summer (June-August) in both studies, and disease was highest in winter (December-February).
Figure 2 The tilt and orbit of the Earth around )the sun generate variation in day length across the year which were associated with variation in susceptibility to common cold infection and disease in this study.
The observations of this study provide further evidence that annual rhythms in human immunity might contribute to the seasonality of viral respiratory disease. Seasonal rhythms in human immunity have broad implications for our understanding of the epidemiology of viral infections, and the mechanisms that drive outbreaks of disease. Increased understanding of the role of the host immune system in generating variations in vulnerability to viral respiratory disease could confer novel opportunities for curtailing the spread of novel pathogens, as well as for minimizing the annual impact of circulating viruses such as SARS-CoV-2 and influenza on the health services.
Co-authors on this project were Ava Clarke, Enya Nordon, Collette Murtagh, Alexandra Keogh and Lorna Lopez at Maynooth University
The data used for this article were collected by the Laboratory for the Study of Stress, Immunity, and Disease at Carnegie Mellon University under the directorship of Sheldon Cohen, PhD; and were accessed via the Common Cold Project (CCP) website (www.commoncoldproject.com). CCP data are made publicly available through a grant from the National Center for Complementary and Integrative Health (AT006694); the conduct of the studies was supported by grants from the National Institute of Mental Health (NIMH) (MH50429) and National Heart, Lung, and Blood Institute (NHLBI) (HL65111; HL65112); and secondary support was provided by a grant from the National Institutes of Health to the University of Pittsburgh Medical Center General Clinical Research Center (NCRR/GCRC 5M01 RR00056). The BCS was provided with primary funding by the National Institute of Allergy and Infectious Diseases (R01 AI23072) and the Office of Naval Research (N00014-88-K-0063). The PCS were provided with primary funding by NIMH (MH50429), NIH (NHLBI HL65111, HL65112), NIAID (R01 AI066367), NHLBI (P01 HL65111, P01 HL65112), NIAID (R01 AI066367). Clinical and regulatory assistance was supported by grants from the NIH (5M01 RR00056, UL1 RR024153, and UL1 TR0005). CW and LL were funded by ERC Grant H2020ERC/950010/FAMILY/LOPEZ. This project has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation program (grant agreement No 950010). AC and EN were funded by a Summer Program for Undergraduate Research (SPUR) scholarship from Maynooth University. AK was funded by a Health Research Board studentship (SS-2021-052) and CM was supported by an SFI Starting Grant awarded to LL. This publication has emanated from research supported in part by a grant from Science Foundation Ireland under Grant No. 15/SIRG/3324.