Feline chronic gingivostomatitis (FCGS) is an inflammatory disease that affects the oral mucosa up to 12% of domestic cats and 26.6% of feral cats. Affected cats exhibit painful ulcerative and/or proliferative lesions throughout the oral cavity, typically lateral to the palatoglossal folds, which can cause severe anorexia and weight loss. Current treatments involve surgical extraction of all or nearly all teeth to reduce antigen load and remove focal points of inflammation. However, this can be expensive, invasive, and only effective for one-third to half of the patients. Other standard treatments include immunosuppressants such as cyclosporine and corticosteroids, which may cause polyuria, polydipsia, metabolic dysfunctions, and may decrease in effectiveness over time.

We hypothesize that the inflammatory phenotype observed in FCGS is driven by the dysregulation of distinct cell types in affected cats. By applying snRNA-seq we will be able to characterize the cellular composition of FCGS oral mucosa based on the transcriptomic signatures of individual cells. This will also facilitate the deconvolution of bulk and spatial transcriptomic experiments and provide a better understanding of the tissue microenvironment in affected cats. Our findings will advance our understanding of the molecular mechanisms driving FCGS initiation and progression and potentially inform targets for future therapeutic approaches.

We propose to use snRNA-seq to investigate the underlying mechanisms driving FCGS in a cellular and spatial context. Our central hypothesis is that snRNA-seq of FCGS samples will reveal distinct cell populations and transcriptomic signatures that drive disease, thereby revealing diagnostic biomarkers and potential drug targets.