# NON-CANONICAL MECHANISMS FOR INTERFERON-LAMBDA REGULATION OF SARS-COV-2 INFECTION

> **NIH NIH R21** · OHIO STATE UNIVERSITY · 2024 · $186,279

## Abstract

PROJECT SUMMARY
As the SARS-CoV-2 pandemic continues, a better understanding of the factors that regulate broadly protective
immunity is needed. Interferon-lambda (IFN-λ) mediates antiviral protection against SARS-CoV-2 without
causing overt pathology and exacerbated disease. As such, recombinant IFN-λ is in clinical trials as a therapeutic
for COVID-19. However, the endogenous role for IFN-λ in regulating infection and functions in preventing disease
beyond antiviral programming during SARS-CoV-2 remain unknown. Our preliminary data show that mice lacking
the IFN-λ receptor (Ifnlr1-/-) have increased illness and viral burden during SARS-CoV-2 infection without
alteration of canonical antiviral gene induction associated with IFN. Instead, IFN-λ positively regulates the
induction of CD8 T cell immunity, a cellular immune response critical to mediating protection against virus
infection when neutralizing antibody responses are avoided. We further identified upregulation of cell cycle repair
and proliferation genes associated with fibrosis in Ifnlr1-/- mice. This proposal will investigate these newly
identified non-canonical functions of IFN-λ in regulating immunity against SARS-CoV-2 with the goal of informing
therapeutic use of this cytokine.

## Key facts

- **NIH application ID:** 10875449
- **Project number:** 5R21AI174050-02
- **Recipient organization:** OHIO STATE UNIVERSITY
- **Principal Investigator:** Emily Ann Hemann
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $186,279
- **Award type:** 5
- **Project period:** 2023-09-01 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10875449

## Citation

> US National Institutes of Health, RePORTER application 10875449, NON-CANONICAL MECHANISMS FOR INTERFERON-LAMBDA REGULATION OF SARS-COV-2 INFECTION (5R21AI174050-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10875449. Licensed CC0.

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