Almost every one of us has heard or read the news about the spreading coronavirus. As with any other disease, early diagnosis is important in the fight against a new virus. However, not all infected people show the same set of symptoms, and even scanners at airports designed to detect signs of infection do not always successfully identify the sick among the crowd of passengers. The question arises - why does the same virus manifest itself differently in different people? Naturally, the first answer is immunity. However, this is not the only important parameter that affects the variability of symptoms and the severity of the disease. Scientists from the Universities of California and Arizona (USA) found that the strength of resistance to viruses depends not only on what subtypes of influenza a person has had throughout his life, but also on their sequence. What exactly did scientists find out, what methods were used in the study, and how can this work help in the fight against epidemics? We will find answers to these questions in the report of the research group. Go.
Research basis
As we know, the flu manifests itself differently in different people. In addition to the human factor (immune system, taking antiviral drugs, preventive measures, etc.), an important aspect is the virus itself, or rather its subtype, which infects a particular patient. Each subtype has its own characteristics, including the degree to which different demographic groups are affected. Scientists note that the H1N1 (“swine flu”) and H3N2 (Hong Kong flu) viruses, which have become the most common at the moment, affect people of different ages in different ways: H3N2 is the cause of most severe cases of illness in the elderly, and most deaths are also attributed to it. ; H1N1 is less lethal, but most commonly affects middle-aged and young people.
Such differences can be due to both the difference in the rate of evolution of the viruses themselves, and the difference in immune imprinting* in children.
Immune imprinting* - a kind of long-term memory of the immune system, formed on the basis of experienced viral attacks on the body and its reactions to them.
In this study, researchers analyzed epidemiological data to determine whether childhood imprinting affects the epidemiology of seasonal influenza and, if so, whether it operates primarily through homosubtypic* immune memory or through a wider heterosubtypic* memory.
Homosubtypic immunity* - infection with seasonal influenza A viruses contributes to the development of immune protection against a specific subtype of the virus.
Heterosubtypic immunity* - infection with seasonal influenza A viruses contributes to the development of immune protection against sub-strains unrelated to this virus.
In other words, children's immunity and all that he has experienced leaves its mark on immunity for life. Previous studies have shown that adults have stronger immunity against the types of viruses they were infected with as children. It has also recently been found that imprinting protects against new avian influenza virus subtypes of the same haemagglutinin phylogenetic group (hemagglutinin, HA) as during the first infection in childhood.
Until recently, narrow cross-protective immunity, specific to variants of the same HA subtype, was considered the main way to protect against seasonal influenza. However, there is new evidence suggesting that the memory of other influenza antigens (eg, neuraminidase, NA) may also influence the formation of immunity. Since 1918, three subtypes of HA have been recorded in humans: H1, H2, and H3. At the same time, H1 and H2 belong to phylogenetic group 1, and H3 belong to group 2.
Given the fact that imprinting most likely causes multiple changes in immune memory, it can be assumed that these changes have a certain hierarchy.
Scientists note that since 1977, two subtypes of influenza A, H1N1 and H3N2, have been seasonally circulating among the population. At the same time, differences in the demographics of infection and in symptoms were quite obvious, but poorly understood. These differences may be due to childhood imprinting: older people were almost certainly exposed to H1N1 in childhood (from 1918 to 1975 this was the only subtype circulating in humans). Therefore, these individuals are currently better protected against current seasonal variants of this virus subtype. Similarly, in young adults, the highest likelihood of childhood imprinting is for the more modern H3N2 (image #1), consistent with the relatively low number of clinically reported cases of H3N2 in this demographic.
Image No. 1: variants of models of the dependence of immunity on imprinting in childhood and the factor of viral evolution.
On the other hand, these differences may be related to the evolution of the virus subtypes themselves. Thus, H3N2 demonstrates a faster drifting* its antigenic phenotype than H1N1.
Drift of antigens* - changes in immunoforming surface factors of viruses.
For this reason, H3N2 may be better able to avoid pre-existing immunity in immunologically experienced (previously ill) adults, while H1N1 may be relatively limited in its effect solely on immunologically inexperienced (previously ill) children.
To test all possible hypotheses, the scientists analyzed the epidemiological data, creating likelihood functions for each version of the statistical models, which were compared using the Akaike Information Criterion (AIC).
An additional analysis of the hypothesis was also carried out, in which the differences are not due to imprinting, in the evolution of viruses.
Preparation for research
Hypothesis modeling used data from the Arizona State Department of Health (ADHS), namely 9510 cases of seasonal H1N1 and H3N2 throughout the state. Approximately 76% of the registered cases were recorded in hospitals and laboratories, the rest of the cases were not specified in the laboratories. We also know that about half of the laboratory-diagnosed cases were severe enough to result in hospitalization.
The data used in the study refer to a period of 22 years from the 1993–1994 flu season to the 2014–2015 flu season. It is worth noting that sample sizes increased dramatically after the 2009 pandemic, so this period was excluded from the sample (Table 1).
Table 1: epidemiological data from 1993 to 2015 regarding reported cases of H1N1 and H3N2 viruses.
It is also important to consider that, since 2004, US commercial laboratories have been required to share all data regarding virus infection of patients with public health authorities. However, most of the analyzed cases (9150/9451) were observed from the 2004-2005 season, after this rule came into force.
Of all 9510 cases, 58 were excluded because they were people with a year of birth before 1918 (their imprinting status cannot be unequivocally determined), and 1 more case because of an incorrectly indicated year of birth. Thus, 9541 cases were included in the analysis models.
At the first stage of modeling, the probabilities of imprinting to the H1N1, H2N2 or H3N2 viruses, specific to the year of birth, were determined. These probabilities reflect the nature of the impact of influenza A on children and its prevalence over the years.
Most people born between the 1918 and 1957 pandemics were first infected with the H1N1 subtype. People born between the 1957 and 1968 pandemics were virtually all infected with the H2N2 subtype (1А). And since 1968, H3N2 has been the dominant subtype of the virus, causing the majority of people in the younger demographic to become infected.
Despite the prevalence of H3N2, H1N1 has still circulated seasonally in the population since 1977, causing imprinting in a subset of people born since the mid-1970s (1А).
If imprinting at the HA subtype level creates the likelihood of infection during seasonal influenza, then exposure to HA subtypes H1 or H3 in early childhood should provide lifelong immunity to more modern variants of the same HA subtype. If imprinted immunity works more against certain types of NA (neuraminidase), then lifelong protection will be characteristic of N1 or N2 (1V).
If imprinting is based on a broader HA, i.e. If there is protection against a wider range of subtypes, then H1 and H2 imprinted individuals should be protected against contemporary seasonal H1N1. At the same time, people with H3 imprinting will only be protected from current seasonal H3N2 (1V).
Scientists note that the collinearity (roughly speaking, parallelism) of the predictions of various imprinting models (1D—1I) was inevitable given the limited diversity of influenza antigenic subtypes circulating in the population over the past century.
The most important role in differentiating between imprinting at the level of the HA subtype, the NA subtype, or the level of the HA group is played by middle-aged people who first became infected with H2N2 (1V).
Each of the models tested used a linear combination of age-related infection (1S), and infection associated with the year of birth (1D—1F), to obtain the distribution of H1N1 or H3N2 cases (1G - 1I).
In total, 4 models were created: the simplest one contained only the age factor, and more complex models were supplemented with imprinting factors at the HA subtype level, at the NA subtype level, or at the HA group level.
The age factor curve is in the form of a step function in which the relative risk of infection was set to 1 in the 0–4 age group. In addition to the primary age group, there were also the following: 5–10, 11–17, 18–24, 25–31, 32–38, 39–45, 46–52, 53–59, 60–66, 67–73, 74– 80, 81+.
Models that contained the effects of imprinting assumed that the proportion of people in each birth year with protective childhood imprinting was proportional to the reduction in risk of infection.
Also, the factor of viral evolution was taken into account in the simulation. For this, data were used that described the annual antigenic progress, which was defined as the average antigenic distance between strains of a certain viral line (H1N1 before 2009, H1N1 after 2009 and H3N2). The "antigenic distance" between two strains of influenza is used as an indicator of similarity in antigenic phenotype and potential immune cross-protection.
In order to assess the impact of antigenic evolution on the epidemic age distribution, a test was made of changes in the proportion of cases in children during seasons when strong antigenic changes occurred.
If the level of antigenic drift is a decisive factor in the age-related risk of infection, then the proportion of cases observed in children should be negatively associated with annual antigenic progress. In other words, strains that have not undergone significant antigenic changes from the previous season should be unable to escape pre-existing immunity in adults with immunological experience. Such strains will be more active among the population with no immunological experience, that is, among children.
Results of the study
An analysis of the data over the years showed that seasonal H3N2 was the main cause of infection among the older population, while H1N1 affected middle-aged people and young people (image #2).
Image #2: Distribution of H1N1 and H3N2 influenza by age over different time periods.
This pattern was present both in the data before the 2009 pandemic and after it.
The data showed that imprinting at the NA subtype level predominates over imprinting at the HA subtype level (ΔAIC = 34.54). At the same time, imprinting at the level of the HA group was almost completely absent (ΔAIC = 249.06), as was the complete absence of imprinting (ΔAIC = 385.42).
Image #3: Assessing the fit of models to study data.
Visual assessment of the conformity of models (3C и 3D) confirmed that models containing imprinting effects at narrow levels of NA or HA subtypes provided the best fit to the data used in the study. The fact that the model lacking imprinting cannot be supported by data suggests that imprinting is a critical aspect of developing immunity in the adult population against seasonal influenza subtypes. However, imprinting works very narrowly, that is, it affects only a certain subtype, and not a whole range of subtypes of influenza.
Table 2: Evaluation of the fit of the models to the study data.
After adjusting for demographic age distribution, the estimated age-related risk was highest in children and the elderly, consistent with the accumulation of immune memory in childhood and the decline in immune function in the elderly (by 3А approximate curve from the best model is shown). Imprinting parameter scores were less than one, indicating some relative risk reduction (Table 2). In the best model, the estimated relative risk reduction from childhood imprinting was greater for H1N1 (0.34, 95% CI 0.29–0.42) than for H3N2 (0.71, 95% CI 0.62–0.82).
To test the influence of viral evolution on the age distribution of infection risk, the researchers looked for a decrease in the proportion of infections among children during periods associated with antigenic change, when strains with high antigenic drift were more effective in infecting immunologically experienced adults.
Data analysis showed a small negative but nonsignificant association between the annual increase in antigenic activity and the proportion of H3N2 cases seen in children (4А).
Image #4: Impact of viral evolution on age-related risk factor for infection.
However, no clear relationship was found between antigenic changes and the proportion of cases observed in children over 10 years of age and in adults. If viral evolution played a major role in this distribution, the result would be clearer evidence of evolutionary influence among adults, and not just when comparing adults and children under 10 years of age.
Furthermore, if the degree of virus evolution is dominant for subtype-specific differences in epidemic age distribution, then when the H1N1 and H3N2 subtypes show the same annual antigen spread, their age distributions of infections should appear more similar.
For a more detailed acquaintance with the nuances of the study, I recommend looking at .
Finale
In this work, scientists analyzed the epidemiological data of cases of infection with H1N1, H3N2 and H2N2. Data analysis showed a clear relationship between imprinting in childhood and the degree of risk of infection in adulthood. In other words, if a child was infected in the 50s when H1N1 was circulating and H3N2 was absent, then in adulthood the chance of H3N2 infection would be much greater than the chance of catching H1N1.
The main conclusion of this study is that it is important not only what a person suffered from in childhood, but also in what sequence. Immune memory, which is formed throughout life, actively “records” the data of the first viral infections, which contributes to a more effective counteraction to them in adulthood.
Scientists hope that their work will allow them to better predict which age groups are more susceptible to the effects of a particular influenza subtype. This knowledge can help prevent the spread of epidemics, especially if a limited number of vaccines need to be distributed to the population.
This study is not aimed at finding super cures for any type of flu, although that would be great. It is aimed at what is much more real and important at the moment - preventing the spread of infection. If we cannot immediately get rid of the virus, then we must have all possible tools to contain it. One of the most faithful allies of any epidemic is the careless attitude towards it both on the part of the state as a whole and of each person in particular. Panic, of course, is not needed, because it can only make things worse, but precautions never hurt.
Thank you for your attention, stay curious, take care of yourself and your loved ones and have a great weekend everyone! 🙂
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Source: habr.com