Evaluating causality of cellular senescence in non-alcoholic fatty liver disease.

Cellular senescence is a state of irreversible cell cycle arrest that has important physiological functions. However, cellular senescence is also a hallmark of ageing and has been associated with several pathological conditions. A wide range of factors including genotoxic stress, mitogens and inflammatory cytokines can induce senescence. Phenotypically, senescent cells are characterised by short telomeres, an enlarged nuclear area and damaged genomic and mitochondrial DNA. Secretion of proinflammatory proteins, also known as the senescence-associated secretory phenotype, is a characteristic of senescent cells that is thought to be the main contributor to their disease-inducing properties. In the past decade, the role of cellular senescence in the development of non-alcoholic fatty liver disease (NAFLD) and its progression towards non-alcoholic steatohepatitis (NASH) has garnered significant interest. Until recently, it was suggested that hepatocyte cellular senescence is a mere consequence of the metabolic dysregulation and inflammatory phenomena in fatty liver disease. However, recent work in rodents has suggested that senescence may be a causal factor in NAFLD development. Although causality is yet to be established in humans, current evidence suggests that targeting senescent cells has therapeutic potential for NAFLD. We aim to provide insights into the quality of the evidence supporting a causal role of cellular senescence in the development of NAFLD in rodents and humans. We will elaborate on key cellular and molecular features of senescence and discuss the efficacy and safety of novel senolytic drugs for the treatment or prevention of NAFLD.

Use of plasma metabolomics to analyze phenotype-genotype relationships in young hypercholesterolemic females.

Hypercholesterolemia is characterized by high plasma LDL cholesterol and often caused by genetic mutations in LDL receptor (LDLR), APOB, or proprotein convertase subtilisin/kexin type 9 (PCSK9). However, a substantial proportion of hypercholesterolemic subjects do not have any mutations in these canonical genes, leaving the underlying pathobiology to be determined. In this study, we investigated to determine whether combining plasma metabolomics with genetic information increases insight in the biology of hypercholesterolemia. For this proof of concept study, we combined plasma metabolites from 119 hypercholesterolemic females with genetic information on the LDL canonical genes. Using hierarchical clustering, we identified four subtypes of hypercholesterolemia, which could be distinguished along two axes represented by triglyceride and large LDL particle concentration. Subjects with mutations in LDLR or APOB preferentially clustered together, suggesting that patients with defects in the LDLR pathway show a distinctive metabolomics profile. In conclusion, we show the potential of using metabolomics to segregate hypercholesterolemic subjects into different clusters, which may help in targeting genetic analysis.