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Mathematical Modeling of Influenza Severity in Outbred Mice

Award Number: R21AI153882
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: 11/25/2020
PERIOD OF PERFORMANCE END DATE: 10/31/2023

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Mathematical Modeling of Influenza Severity in Outbred Mice - PROJECT SUMMARY In the United States, pulmonary influenza infection occurs annually in 5-20% of the population with mortality in the range of 30,000 deaths. The recent 2009 influenza H1N1 pandemic illustrated the potential for higher infection rates, which were reported to be as high as 45% in certain age groups. The 2017-18 influenza season had the highest pediatric mortalities since the 2009 pandemic. Influenza infection is known to result in a broad spectrum of disease phenotypes in humans, although severe pneumonia is relatively rare. Despite this, severe disease often requires advanced supportive care in the young, including previously healthy children. Host factors involved in determining the outcome of influenza infection are unclear and children are known to be at higher risk of severe disease. First life exposure to influenza is also thought to dictate life-long immunity. Little is known about the effects of young age and gender on influenza responses and severity. This underscores the importance of understanding influenza pathogenesis in a pediatric population. Influenza pathogenesis is likely mediated in large part by exuberant inflammatory host responses in the lung. It is likely that predictive soluble inflammatory mediators are present in severe infection. Further, predictive biomarkers or mathematical models of influenza pneumonia severity would enhance clinical decision making and patient care. We propose that machine learning and mathematical modeling of host immune endpoints will define a molecular fingerprint of severe influenza pneumonia in juveniles. This hypothesis will be tested in two Aims. Aim 1 will focus on characteristic molecular pathways related to influenza severity in juvenile animals, using outbred mice. We will utilize machine learning and new mathematical approaches for pathway and biomarker selection. Aim 2 will test mathematical models of influenza pathogenesis to elucidate new mechanisms that drive lung injury. The overall goal of the proposed study is to identify novel biomarkers and mechanistic models of influenza pneumonia severity that can be applied to children. To accomplish this we will use a broad, exploratory, and unbiased approach. Candidate biomarkers and pathways would then be evaluated in future mechanistic and translational studies in mice and humans.


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: 2024 ( Subtotal = $0 )
2024	2022	UNIVERSITY OF PITTSBURGH - OF THE COMMONWEALTH SYSTEM OF HIGHER EDUCATION	4200 FIFTH AVENUE	PITTSBURGH	PA	15260	ALLEGHENY	USA	Allergy and Infectious Diseases Research	000	2	7/3/2024	NON-COMPETING CONTINUATION	$0
														Subtotal = $0

Issue Date FY: 2022 ( Subtotal = $189,830 )
2022	2022	UNIVERSITY OF PITTSBURGH, THE	4200 5TH AVE	PITTSBURGH	PA	15260	ALLEGHENY	USA	Allergy and Infectious Diseases Research	000	2	10/20/2021	NON-COMPETING CONTINUATION	$189,830
														Subtotal = $189,830

Issue Date FY: 2021 ( Subtotal = $228,212 )
2021	2021	UNIVERSITY OF PITTSBURGH THE	3520 FIFTH AVE	PITTSBURGH	PA	15213	ALLEGHENY	USA	Allergy and Infectious Diseases Research	000	1	11/25/2020	NEW	$228,212
														Subtotal = $228,212

Grand Total All Awards = $418,042

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Mathematical Modeling of Influenza Severity in Outbred Mice

Award Number: R21AI153882

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: 11/25/2020

PERIOD OF PERFORMANCE END DATE: 10/31/2023

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