# Fluomics: The Next Generation

> **NIH NIH U19** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2021 · $2,648,626

## Abstract

Influenza A virus is a major human respiratory pathogen, and available vaccines and antivirals are of
limited efficacy. In order to identify novel targets for therapeutic intervention during influenza virus infection, we
have assembled an interdisciplinary team that uses a highly integrated systems level approach to identify and
validate key genes/networks involved in virus pathogenesis. The overarching theme of our multidisciplinary
proposal “FluOMICS: The NEXT Generation” is to obtain multiple OMICS-based systems level measurements
and integrate them using modeling approaches and machine learning algorithms to identify and validate 1)
host-virus networks that modulate influenza A virus disease severity, 2) biomarkers in blood that reflect the
activation states of these networks and 3) novel host targets for therapeutic interventions. Our underlying main
hypothesis is that host networks involved in viral replication and early host responses regulate disease
outcomes and represent targets for therapeutic intervention. The proposed studies leverage on our previous
collaborations that generated global datasets and models that predict severity of disease caused by three
influenza virus strains with different levels of virulence. While our previous studies gave many novel insights in
influenza pathogenesis, they likely provide a narrow window on the determinants of disease severity in
humans. Thus, it is necessary expand beyond the specific virus strains that were used to study pathogenesis,
and explore a broader context of viral and host perturbations linked to clinical outcomes. In order to identify
clinically relevant networks involved in influenza virus pathogenesis we propose to integrate into predictive and
comprehensive models global responses during influenza virus infection in three systems 1) human blood from
a human cohort of patients with documented influenza virus infection and diverse clinical outcomes (Project
1); 2) mouse blood and tissues from experimentally infected animals under a variety of conditions and
perturbations resulting in diverse disease outcomes (Project 1) and 3) relevant primary human cells (Project
2). Samples will be processed and send to the Technology Core for global transcriptomics, proteomics and
metabolomics analysis. OMICS data sets will be integrated and compared by the Modeling Core to generate
network models of disease, uncover blood biomarkers and identify key drivers as targets for therapeutic
intervention. Predicted network regulators will be used as a source for subsequent iterative rounds of
perturbations to refine existing and to identify new network disease models. Data and models will be managed
and disseminated by the Data Management and Bioinformatics Core. We expect that these studies will
uncover and validate novel pathogenic networks, blood biomarkers associated with them, and specific
therapeutic targets to revert pathogenic networks. In summary, our modeling approaches will find correlates
an...

## Key facts

- **NIH application ID:** 10080700
- **Project number:** 5U19AI135972-04
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Adolfo Garcia-Sastre
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $2,648,626
- **Award type:** 5
- **Project period:** 2018-01-20 → 2022-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10080700

## Citation

> US National Institutes of Health, RePORTER application 10080700, Fluomics: The Next Generation (5U19AI135972-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10080700. Licensed CC0.

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