Liver Investigation: Testing Marker Utility in Steatohepatitis (LITMUS): Assessment & validation of imaging modality performance across the NAFLD spectrum in a prospectively recruited cohort study (the LITMUS imaging study): Study protocol

Advancements in pharmacological treatment of NAFLD/MASLD: a focus on metabolic and liver-targeted interventions

In the present narrative review, we have summarized evidence on the pharmacological treatment of non-alcoholic fatty liver disease (NAFLD)/metabolic dysfunction-associated steatotic liver disease (MASLD). We start by reviewing the epidemiology of the condition and its close association with obesity and type 2 diabetes. We then discuss how randomized-controlled trials are performed following guidance from regulatory agencies, including differences and similarities between requirements of the US Food and Drug Administration and the European Medicine Agency. Difficulties and hurdles related to limitations of liver biopsy, a large number of screening failures in recruiting patients, as well as unpredictable response rates in the placebo group are evaluated. Finally, we recapitulate the strategies employed for potential drug treatments of this orphan condition. The first is to repurpose drugs that originally targeted T2DM and/or obesity, such as pioglitazone, glucagon-like peptide 1 receptor agonists (liraglutide and semaglutide), multi-agonists (tirzepatide and retatrutide), and sodium-glucose transporter 2 inhibitors. The second is to develop drugs specifically targeting NAFLD/MASLD. Among those, we focused on resmetirom, fibroblast growth factor 21 analogs, and lanifibranor, as they are currently in Phase 3 of their clinical trial development. While many failures have characterized the field of pharmacological treatment of NAFLD/MASLD in the past, it is likely that approval of the first treatments is near. As occurs in many chronic conditions, combination therapy might lead to better outcomes. In the case of non-alcoholic steatohepatitis, we speculate that drugs treating underlying metabolic co-morbidities might play a bigger role in the earlier stages of disease, while liver-targeting molecules will become vital in patients with more advanced disease in terms of inflammation and fibrosis.

A data-driven approach to decode metabolic dysfunction-associated steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD), defined by the presence of liver steatosis together with at least one out of five cardiometabolic factors, is the most common cause of chronic liver disease worldwide, affecting around one in three people. Yet the clinical presentation of MASLD and the risk of progression to cirrhosis and adverse clinical outcomes is highly variable. It, therefore, represents both a global public health threat and a precision medicine challenge. Artificial intelligence (AI) is being investigated in MASLD to develop reproducible, quantitative, and automated methods to enhance patient stratification and to discover new biomarkers and therapeutic targets in MASLD. This review details the different applications of AI and machine learning algorithms in MASLD, particularly in analyzing electronic health record, digital pathology, and imaging data. Additionally, it also describes how specific MASLD consortia are leveraging multimodal data sources to spark research breakthroughs in the field. Using a new national-level 'data commons' (SteatoSITE) as an exemplar, the opportunities, as well as the technical challenges of large-scale databases in MASLD research, are highlighted.