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NASH is the progressive form of non-alcoholic fatty liver disease (NAFLD) which affects 25% of adults in the US. We are interested in identifying genetic markers for specific cell populations in the liver and hypothesize that cells undergo genetic reprogramming to handle the molecular stresses of the NASH disease state.

Using previously published single-cell RNA sequencing datasets from mouse liver whole tissue, we identified the top 25 most highly variable genes per cell type in NASH liver tissue. Using R-programming language, datasets from both healthy and diseases livers were deconvoluted, normalized, linearized and dimensionally reduced to create a 3D map of cell clusters according to changes in gene expression. Subsequently, cell clusters were labeled according to the most differentially expressed gene per cell type. The final graph demonstrated that the most statistically significant differences in the emergence of the disease phenotype came from genetic markers associated with T-cells and dendritic cells.

The meta-analysis led to a depiction of 13 cell clusters with varying degrees of involvement in NASH pathogenesis. The top two statistically significant cell populations were T-cells and dendritic cells with the most differentially expressed genes Trbc2 and Cst3, respectively. Our results support our hypothesis as both T-cells and dendritic cells are cell populations that can be involved in inflammation during disease states. In future studies, merging datasets from different papers can help to strengthen our previous associations and be used to create algorithms for predicting disease course as well as possible therapies for patients with NASH.