Towards precision medicine in non-alcoholic fatty liver disease.
Sven M FrancquePublished in: Reviews in endocrine & metabolic disorders (2023)
Non-Alcoholic Fatty Liver Disease (NAFLD) refers to the accumulation of lipid laden vacuoles in hepatocytes, occurring in the context of visceral adiposity, insulin resistance and other features of the metabolic syndrome. Its more severe form (NASH, Non-Alcoholic Steatohepatitis) is becoming the leading aetiology of end-stage liver disease and hepatocellular carcinoma, and also contributes to cardiovascular disease, diabetes and extrahepatic malignancy. Management is currently limited to lifestyle modification and optimisation of the metabolic co-morbidities, with some of the drugs used for the latter also having shown some benefit for the liver. Licensed treatment modalities are currently lacking. A particular difficulty is the notorious heterogeneity of the patient population, which is poorly understood. A spectrum of disease severity associates in a non-linear way with a spectrum of severity of underlying metabolic factors. Heterogeneity of the liver in terms of mechanisms to cope with the metabolic and inflammatory stress and in terms of repair mechanisms, and a lack of knowledge hereof, further complicate the understanding of inter-individual variability. Genetic factors act as disease modifiers and potentially allow for some risk stratification, but also only explain a minor fraction of disease heterogeneity. Response to treatment shows a large variation in treatment response, again with little understanding of what is driving the absence of response in individual patients. Management can be tailored to patient's preferences in terms of diet modification, but tailoring treatment to knowledge on disease driving mechanisms in an individual patient is still in its infancy. Recent progress in analysing liver tissue as well as non-invasive tests hold, however, promise to rapidly improve our understanding of disease heterogeneity in NAFLD and provide individualised management.
Keyphrases
- insulin resistance
- cardiovascular disease
- metabolic syndrome
- healthcare
- type diabetes
- case report
- end stage renal disease
- weight loss
- machine learning
- chronic kidney disease
- ejection fraction
- newly diagnosed
- oxidative stress
- prognostic factors
- replacement therapy
- genome wide
- cardiovascular risk factors
- coronary artery disease
- body mass index
- early onset
- liver fibrosis
- dna methylation
- high fat diet
- smoking cessation
- glycemic control
- polycystic ovary syndrome
- big data
- artificial intelligence