A new study in the journal Nature describes a model that can successfully predict changes in seasonal human influenza virus from year to year.
The model, developed by German and US researchers, considers the evolutionary advantages of mutations in previous influenza strains, and the frequency of these mutations, to predict the future evolution of current strains.
Predicting the make-up of future strains of influenza is critical for vaccine design and the model could play an important role in staying one step ahead of the ever-changing influenza virus.
The Science Media Centre contacted infectious disease experts for comment on the research:
Prof Michael Baker, Department of Public Health, University of Otago, Wellington, comments:
“Seasonal influenza remains one of New Zealand’s most important infectious diseases. It is estimated to kill around 400 New Zealanders a year and hospitalises thousands more as well as causing a large amount of suffering and lost productivity. Influenza vaccine remains our major tool to combat this disease. Unfortunately, the vaccine is only moderately effective, partly because influenza virus evolves rapidly with new strains appearing each year. This antigenic drift means that the vaccine produced in batches before each season may not perfectly match the circulating viruses. Anything that can improve the fit of the vaccine to the likely strains of virus that will be circulating in the upcoming influenza season is therefore welcome.
“This published research seems promising in that regard. The test will be whether it can contribute to improved vaccine formulation and vaccine effectiveness. That assessment may take several years to emerge. Either way, the science behind this work will almost certainly improve our ability to prevent and control influenza over the next few years and may also be applicable to other rapidly evolving pathogens. The ultimate goal will be vaccines which are effective against all circulating strains of seasonal, and ultimately pandemic, influenza.”
Dr Sue Huang, Director of the WHO National Influenza Centre and Senior Science Leader, Institute of Environmental Science & Research (ESR) comments:
“The goal of vaccine strain selection is to achieve the best match between the vaccine strain and the circulating strain. There are many different influenza strains within each influenza type/subtype (i.e. A(H1N1), A(H3N2) and B) circulating in a given season.
“The real difficulty is to predict which strain will be fit enough to become the predominant strain a year into the future. The current vaccine strain selection uses assays that identify antigenic difference between the current circulating strains and vaccine strain. This method is highly effective in some years, but antigenic mismatch between the vaccine strain and the strain that ends up predominating the next flu season do occur.
“This study published in Nature provides very good insights. It tells us that when a new variant is identified and the mutation occurs on a specific gene in protein regions that are not recognized by human antibodies, this type of mutation is often deleterious to the virus because they reduce protein stability or upset evolutionarily conserved viral functions. This type of antigenic variant is therefore not fit to become the predominant strain in the next flu season. If it is selected to be a vaccine strain, it would result in a mismatch situation.
“On the other hand, if a new variant carries mutations in protein regions that are recognized by human antibodies, this type of mutation is often beneficial to the virus because they can be more effective in evading host immune response. This type of antigenic variant is fit to become predominant strain in the next flu season. If it is selected to be a vaccine strain, it would result in a good match. This new study will help to formulate better strategy in selecting vaccine strains in the future by including viral fitness considerations and cross-immunity estimations.
“An interesting perspective raised in the study is that it tries to infer fitness of the viruses based on their population genetic data and states that ‘the frequency of a strain is simply the fraction of the infected host individuals corresponding to that strain’. For a better estimation of the fitness of a strain, the population from which the virus is derived should be as representative as possible. Data from studies using a comprehensive, thorough and unbiased way to assess patients and collect samples for testing influenza, such as the ongoing SHIVERS project which our team leads, would provide a more robust basis for prediction of future predominant strains and thus result in better match between a vaccine strain and a future predominant circulating strain. This would help vaccine strain selection for both southern and northern hemispheres.”