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Predictive fitness models for influenza vaccine strain selection

Award Number: R01AI165820
ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 01/13/2022
PERIOD OF PERFORMANCE END DATE: 12/31/2026

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Predictive fitness models for influenza vaccine strain selection - Project summary The human flu virus undergoes fast antigenic evolution driven by the challenge of the host immune system. Circulating viruses are a moving quasi-species of high genetic and antigenic diversity, which is structured in distinct clades representing niches with separate avenues of escape from human herd immunity. Specifically, viral-immune co-evolution follows a Red Queen’s dynamical pattern of competing lineages, which is further modulated by global transmission patterns, host population structure, and herd-immunity acquired by previous infections and vaccination. This process poses a challenge for vaccine strain selection: to determine a single strain from each of the four seasonal lineages to provide the best protection from the viruses that are expected to dominate almost a year in advance. Here we posit that shape and dynamics of the global viral population can be understood and predicted from the underlying human population immunity. In this project, we will develop a comprehensive and objective computational approach to provide a mechanistic understanding of the influenza virus-host immune interaction on the host level, to quantify the selection imposed on the virus on the global evolutionary scales. Specifically, we will build biophysical models, both for the B-cell and T-cell driven immune recognition of epitopes in a host, to accurately characterize the immune structure of the human population to best represent the fitness effects acting on the virus on the global scale. For the model of B-cell immune recognition (Aim 1), we will leverage diverse antigenic human serology assays to prepare a detailed map of antigenic effects of mutations and epistatic interactions. The data will be cross-mapped on the dataset of sequences of globally circulating viruses and our detailed phylogenies for each of the four seasonal lineages. The T-cell immune recognition (Aim 2) will be based on computational machine learning predictions of epitopes, combined with novel biophysically motivated models for prediction of immunodominant antigens. Host population geographically diverse HLA diversity will be accounted for estimating selective pressures imposed on the population of the virus. These components, together with a component describing the selective pressure due to previous vaccinations, will be used to optimize a joint fitness model (Aim 3). Information theoretic approaches will be used to optimize and evaluate the predictive power of the combined model. We will objectively quantify the significance of each of the components and validate the predictions on the historical sequence and epidemiological data. With the resulting fitness model we will define principled criteria for vaccine strain selection, to optimize the coverage and efficacy of the vaccine in the future populations of the of seasonal human influenza viruses.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2025 ( Subtotal = $602,331 )
2025	2025	ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI	1 GUSTAVE L LEVY PL	NEW YORK	NY	10029	NEW YORK	USA	Allergy and Infectious Diseases Research	000	4	12/19/2024	NON-COMPETING CONTINUATION	$602,331
														Subtotal = $602,331

Issue Date FY: 2024 ( Subtotal = $602,331 )
2024	2024	ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI	1 GUSTAVE L LEVY PL	NEW YORK	NY	10029	NEW YORK	USA	Allergy and Infectious Diseases Research	001	3	5/21/2024	NON-COMPETING CONTINUATION	$60,232
2024	2024	ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI	1 GUSTAVE L LEVY PL	NEW YORK	NY	10029	NEW YORK	USA	Allergy and Infectious Diseases Research	000	3	12/13/2023	NON-COMPETING CONTINUATION	$542,099
														Subtotal = $602,331

Issue Date FY: 2023 ( Subtotal = $598,951 )
2023	2023	ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI	ONE GUSTAVE L LEVY PL	NEW YORK	NY	10029	NEW YORK	USA	Allergy and Infectious Diseases Research	000	2	12/20/2022	NON-COMPETING CONTINUATION	$598,951
														Subtotal = $598,951

Issue Date FY: 2022 ( Subtotal = $601,250 )
2022	2022	ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI	ONE GUSTAVE L LEVY PL	NEW YORK	NY	10029	NEW YORK	USA	Allergy and Infectious Diseases Research	000	1	1/12/2022	NEW	$601,250
														Subtotal = $601,250

Grand Total All Awards = $2,404,863

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Predictive fitness models for influenza vaccine strain selection

Award Number: R01AI165820

ORGANIZATION: NATIONAL INSTITUTE OF ALLERGY & INFECTIOUS DISEASES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 01/13/2022

PERIOD OF PERFORMANCE END DATE: 12/31/2026

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