Using total plasma triacylglycerol to assess hepatic de novo lipogenesis as an alternative to VLDL triacylglycerol

Nutritional regulation of hepatic de novo lipogenesis in humans

PURPOSE OF REVIEW

De novo lipogenesis (DNL) is a metabolic process occurring mainly within the liver, in humans. Insulin is a primary signal for promoting DNL; thus, nutritional state is a key determinant for upregulation of the pathway. However, the effects of dietary macronutrient composition on hepatic DNL remain unclear. Nor is it clear if a nutrition-induced increase in DNL results in accumulation of intra-hepatic triglyceride (IHTG); a mechanism often proposed for pathological IHTG. Here, we review the latest evidence surrounding the nutritional regulation of hepatic DNL.

RECENT FINDINGS

The role of carbohydrate intake on hepatic DNL regulation has been well studied, with only limited data on the effects of fats and proteins. Overall, increasing carbohydrate intake typically results in an upregulation of DNL, with fructose being more lipogenic than glucose. For fat, it appears that an increased intake of n-3 polyunsaturated fatty acids downregulates DNL, whilst, in contrast, an increased dietary protein intake may upregulate DNL.

SUMMARY

Although DNL is upregulated with high-carbohydrate or mixed-macronutrient meal consumption, the effects of fat and protein remain unclear. Additionally, the effects of different phenotypes (including sex, age, ethnicity, and menopause status) in combination with different diets (enriched in different macronutrients) on hepatic DNL requires elucidation.

Dysregulation of hepatic metabolism with obesity: factors influencing glucose and lipid metabolism

The liver is a key metabolic organ that undertakes a multitude of physiological processes over the course of a day, including intrahepatic lipid and glucose metabolism which plays a key role in the regulation of systemic lipid and glucose concentrations. It serves as an intermediary organ between exogenous (dietary) and endogenous energy supply to extrahepatic organs. Thus, perturbations in hepatic metabolism can impact widely on metabolic disease risk. For example, the accumulation of intra-hepatocellular TAG (IHTG), for which adiposity is almost invariably a causative factor may result in dysregulation of metabolic pathways. Accumulation of IHTG is likely due to an imbalance between fatty acid delivery, synthesis and removal (via oxidation or export as TAG) from the liver; insulin plays a key role in all of these processes.

Diagnostic management of nonalcoholic fatty liver disease: a transformational period in the development of diagnostic and predictive tools-a narrative review

NAFLD is an emerging healthcare epidemic that is causing predictable adverse consequences for healthcare systems, societies and individuals. Whilst NAFLD is recognized as a multi-system disease with compound pathways that are both benign and pernicious in their unfolding; NASH is generally understood as a deleterious follow-on condition with path-specific tendencies that progress to cirrhosis, HCC and liver transplantation. Recent evidence is beginning to challenge this interpretation demanding more attention to the personalized nature of the disease and its pathogenesis across multiple different cohorts. This means that we need better diagnostic and prognostic tools not only to capture those 'at risk' disease phenotypes; but for better stratification and monitoring of patients according to their treatment strategies. With the advent of pipeline therapies for NASH underway, the medical profession looks to adopt more accurate non-invasive diagnostic tools that can help to delineate and eliminate NASH histology. This review looks at the search for the killer application revealing this particular moment in time as a transformational period; one that is pushing the boundaries of technology to integrate diverse panels of species through sensitive profiling and multi-omics approaches that cast wide, yet powerful diagnostic nets that have the potential to elucidate pathway specific biomarkers that are personalized and predictable.