# Deciphering mechanisms of COVID-19 induced anosmia > **NIH NIH R01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2020 · $202,500 ## Abstract Project Summary/Abstract In this Competitive Revision proposal, we seek to investigate the non-cell autonomous effects of Covid- 19 infections in olfaction. Our preliminary data suggest that induction of pro-inflammatory/antiviral pathways result in disruption of inter-chromosomal genomic interactions, and downregulation of Olfactory Receptor (OR) gene expression. Since antiviral responses are expected be elicited upon Covid-19 infection, we hypothesize that disruptions in nuclear architecture and OR expression account for the reported olfactory deficits in infected patients. Thus, we propose to analyze human autopsies of the olfactory epithelium, to decipher whether Covid- 19 infections disrupt genomic interactions required for OR transcription. We will complement our studies in human autopsies with experiments using mice infected with SARS-CoV-2. RNA-seq, in situ HiC and immunohistochemistry experiments in human and mice will reveal the molecular mechanisms by which Covid- 19 induces olfactory dysfunction. Our experiments will provide critical insight to the mechanisms by which the virus hijacks molecular and physiological processes of the host cell, opening new potential avenues for the prevention, diagnosis and treatment of Covid-19 infection. ## Key facts - **NIH application ID:** 10176800 - **Project number:** 3R01DC018744-01S1 - **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES - **Principal Investigator:** Stavros Lomvardas - **Activity code:** R01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2020 - **Award amount:** $202,500 - **Award type:** 3 - **Project period:** 2020-07-01 → 2021-06-30 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10176800 ## Citation > US National Institutes of Health, RePORTER application 10176800, Deciphering mechanisms of COVID-19 induced anosmia (3R01DC018744-01S1). Retrieved via AI Analytics 2026-06-08 from https://api.ai-analytics.org/grant/nih/10176800. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*