Tackling the complexity of nonalcoholic steatohepatitis treatment: challenges and opportunities based on systems biology and machine learning approaches

Nonalcoholic fatty liver disease (NAFLD) is regarded as the most frequent cause of chronic liver damage (1,2). The natural history of the disease presents a complex scenario of potential progression into severe clinical outcomes, including nonalcoholic steatohepatitis (NASH), NASH-fibrosis, cirrhosis, and hepatocellular carcinoma (1,2). In addition, NAFLD is closely associated with comorbidities of the metabolic syndrome (MetS), including type 2 diabetes, obesity, arterial hypertension, and dyslipidemia, which together aggravate the morbidity and mortality associated with the disease.