Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution

Huddleston, John and Barnes, John R. and Rowe, Thomas and Xu, Xiyan and Kondor, Rebecca and Wentworth, David E. and Whittaker, Lynne and Ermetal, Burcu and Daniels, Rodney Stuart and McCauley, John W. and Fujisaki, Seiichiro and Nakamura, Kazuya and Kishida, Noriko and Watanabe, Shinji and Hasegawa, Hideki and Barr, Ian and Subbarao, Kanta and Barrat-Charlaix, Pierre and Neher, Richard A. and Bedford, Trevor. (2020) Integrating genotypes and phenotypes improves long-term forecasts of seasonal influenza A/H3N2 evolution. eLife, 9. e60067.

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Official URL: https://edoc.unibas.ch/84934/

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Seasonal influenza virus A/H3N2 is a major cause of death globally. Vaccination remains the most effective preventative. Rapid mutation of hemagglutinin allows viruses to escape adaptive immunity. This antigenic drift necessitates regular vaccine updates. Effective vaccine strains need to represent H3N2 populations circulating one year after strain selection. Experts select strains based on experimental measurements of antigenic drift and predictions made by models from hemagglutinin sequences. We developed a novel influenza forecasting framework that integrates phenotypic measures of antigenic drift and functional constraint with previously published sequence-only fitness estimates. Forecasts informed by phenotypic measures of antigenic drift consistently outperformed previous sequence-only estimates, while sequence-only estimates of functional constraint surpassed more comprehensive experimentally-informed estimates. Importantly, the best models integrated estimates of both functional constraint and either antigenic drift phenotypes or recent population growth.
Faculties and Departments:05 Faculty of Science > Departement Biozentrum > Computational & Systems Biology > Computational Modeling of Biological Processes (Neher)
UniBasel Contributors:Neher, Richard A
Item Type:Article, refereed
Article Subtype:Research Article
Publisher:eLife Sciences Publications
Note:Publication type according to Uni Basel Research Database: Journal article
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Last Modified:24 Nov 2021 13:06
Deposited On:24 Nov 2021 13:06

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