Background: The risk of cardiovascular disease in type 1 diabetes remains extremely high, despite marked advances in blood glucose control and even the widespread use of cholesterol synthesis inhibitors. Thus, a deeper understanding of insulin regulation of cholesterol metabolism, and its disruption in type 1 diabetes, could reveal better treatment strategies.
Methods: To define the mechanisms by which insulin controls plasma cholesterol levels, we knocked down the insulin receptor, FoxO1, and the key bile acid synthesis enzyme, CYP8B1.
The gut-microbe-derived metabolite trimethylamine N-oxide (TMAO) is increased by insulin resistance and associated with several sequelae of metabolic syndrome in humans, including cardiovascular, renal, and neurodegenerative disease. The mechanism by which TMAO promotes disease is unclear. We now reveal the endoplasmic reticulum stress kinase PERK (EIF2AK3) as a receptor for TMAO: TMAO binds to PERK at physiologically relevant concentrations; selectively activates the PERK branch of the unfolded protein response; and induces the transcription factor FoxO1, a key driver of metabolic disease, in a PERK-dependent manner.
View Article and Find Full Text PDFInsulin coordinates the complex response to feeding, affecting numerous metabolic and hormonal pathways. Forkhead box protein O1 (FoxO1) is one of several signaling molecules downstream of insulin; FoxO1 drives gluconeogenesis and is suppressed by insulin. To determine the role of FoxO1 in mediating other actions of insulin, we studied mice with hepatic deletion of the insulin receptor, FoxO1, or both.
View Article and Find Full Text PDFDespite the well-documented association between insulin resistance and cardiovascular disease, the key targets of insulin relevant to the development of cardiovascular disease are not known. Here, using non-biased profiling methods, we identify the enzyme flavin-containing monooxygenase 3 (Fmo3) to be a target of insulin. FMO3 produces trimethylamine N-oxide (TMAO), which has recently been suggested to promote atherosclerosis in mice and humans.
View Article and Find Full Text PDFGenome annotations are accumulating rapidly and depend heavily on automated annotation systems. Many genome centers offer annotation systems but no one has compared their output in a systematic way to determine accuracy and inherent errors. Errors in the annotations are routinely deposited in databases such as NCBI and used to validate subsequent annotation errors.
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