Non-alcoholic fatty liver disease (NAFLD) is a liver manifestation of metabolic syndrome, and is estimated to affect one billion individuals worldwide. An increased intake of a high-fat diet (HFD) and sugar-sweetened beverages are risk-factors for NAFLD development, but how their combined intake promotes progression to a more severe form of liver injury is unknown. Here we show that fructose metabolism via ketohexokinase (KHK) C isoform increases endoplasmic reticulum (ER) stress in a dose dependent fashion, so when fructose is coupled with a HFD intake it leads to unresolved ER stress. Conversely, a liver-specific knockdown of KHK in C57BL/6J male mice consuming fructose on a HFD is adequate to improve the NAFLD activity score and exert a profound effect on the hepatic transcriptome. Overexpression of KHK-C in cultured hepatocytes is sufficient to induce ER stress in fructose free media. Upregulation of KHK-C is also observed in genetically obesity ob/ob, db/db and lipodystrophic FIRKO male mice, whereas KHK knockdown in these mice improves metabolic function. Additionally, in over 100 inbred strains of male or female mice hepatic KHK expression correlates positively with adiposity, insulin resistance, and liver triglycerides. Similarly, in 241 human subjects and their controls, hepatic Khk expression is upregulated in early, but not late stages of NAFLD. In summary, we describe a novel role of KHK-C in triggering ER stress, which offers a mechanistic understanding of how the combined intake of fructose and a HFD propagates the development of metabolic complications.

Mouse models have been used extensively to study human coronary artery disease (CAD) or atherosclerosis and to test therapeutic targets. However, whether mouse and human share similar genetic factors and pathogenic mechanisms of atherosclerosis has not been thoroughly investigated in a data-driven manner. We conducted a cross-species comparison study to better understand atherosclerosis pathogenesis between species by leveraging multiomics data. Specifically, we compared genetically driven and thus CAD-causal gene networks and pathways, by using human GWAS of CAD from the CARDIoGRAMplusC4D consortium and mouse GWAS of atherosclerosis from the Hybrid Mouse Diversity Panel (HMDP) followed by integration with functional multiomics human (STARNET and GTEx) and mouse (HMDP) databases. We found that mouse and human shared >75% of CAD causal pathways. Based on network topology, we then predicted key regulatory genes for both the shared pathways and species-specific pathways, which were further validated through the use of single cell data and the latest CAD GWAS. In sum, our results should serve as a much-needed guidance for which human CAD-causal pathways can or cannot be further evaluated for novel CAD therapies using mouse models.