Correspondence

Global multi-stakeholder endorsement of the MAFLD definition

The novel term Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is proposed to replace non-alcoholic fatty liver disease (NAFLD) to highlight the close association with the metabolic syndrome. MASLD encompasses patients with liver steatosis and at least one of five cardiometabolic risk factors which implies that these patients are at increased risk of cardiovascular disease (CVD). Indeed, the prevalence of CVD in MASLD patients is increased and CVD is recognized as the most common cause of death in MASLD patients.

We here present an update on the pathophysiology of CVD in MASLD, discuss the risk factors, and suggest screening for CVD in patients with MASLD. Currently, there is no FDA-approved pharmacological treatment for MASLD, and no specific treatment recommended for CVD in patients with MASLD. Thus, the treatment strategy is based on weight loss and a reduction and treatment of CVD risk factors.

We recommend screening of MASLD patients for CVD using the SCORE2 system with guidance to specific treatment algorithms. In all patients with CVD risk factors, lifestyle intervention to induce weight loss through diet and exercise is recommended. Especially a Mediterranean diet may improve hyperlipidemia and if further treatment is needed, statins should be used as first-line treatment. Further, anti-hypertensive drugs should be used to treat hypertension.

With the epidemic of obesity and type 2 diabetes mellitus (T2DM) the risk of MASLD and CVD is expected to increase, and preventive measures, screening, and effective treatments are highly needed to reduce morbidity and mortality in MASLD patients.

Metabolic (dysfunction)-associated steatohepatitis (MASH) is the advanced stage of metabolic (dysfunction)-associated fatty liver disease (MAFLD) lacking approved clinical drugs. Adenosine A1 receptor (A₁R), belonging to the G-protein-coupled receptors (GPCRs) superfamily, is mainly distributed in the central nervous system and major peripheral organs with wide-ranging physiological functions; however, the exact role of hepatic A₁R in MAFLD remains unclear. Here, we report that liver-specific depletion of A₁R aggravates while overexpression attenuates diet-induced metabolic-associated fatty liver (MAFL)/MASH in mice. Mechanistically, activation of hepatic A₁R promotes the competitive binding of sterol-regulatory element binding protein (SREBP) cleavage-activating protein (SCAP) to sequestosome 1 (SQSTM1), rather than protein kinase A (PKA) leading to SCAP degradation in lysosomes. Reduced SCAP hinders SREBP1c/2 maturation and thus suppresses de novo lipogenesis and inflammation. Higher hepatic A₁R expression is observed in patients with MAFL/MASH and high-fat diet (HFD)-fed mice, which is supposed to be a physiologically adaptive response because A₁R agonists attenuate MAFL/MASH in an A₁R-dependent manner. These results highlight that hepatic A₁R is a potential target for MAFL/MASH therapy.

With the rising tide of fatty liver disease related to metabolic dysfunction worldwide, the association of this common liver disease with chronic kidney disease (CKD) has become increasingly evident. In 2020, the more inclusive term metabolic dysfunction-associated fatty liver disease (MAFLD) was proposed to replace the old term non-alcoholic fatty liver disease (NAFLD). In 2023, a modified Delphi process was led by three large pan-national liver associations. There was consensus to change the fatty liver disease nomenclature and definition to include the presence of at least one of five common cardiometabolic risk factors as diagnostic criteria. The name chosen to replace NAFLD was metabolic dysfunction-associated steatotic liver disease (MASLD). The change of nomenclature from NAFLD to MAFLD and then MASLD has resulted in a reappraisal of the epidemiological trends and associations with the risk of developing CKD. The observed association between MAFLD/MASLD and CKD and our understanding that CKD can be an epiphenomenon linked to underlying metabolic dysfunction support the notion that individuals with MASLD are at substantially higher risk of incident CKD than those without MASLD. This narrative review provides an overview of the literature on (a) the evolution of criteria for diagnosing this highly prevalent metabolic liver disease, (b) the epidemiological evidence linking MASLD to the risk of CKD, (c) the underlying mechanisms by which MASLD (and factors strongly linked with MASLD) may increase the risk of developing CKD, and (d) the potential drug treatments that may benefit both MASLD and CKD.

Machine learning (ML) approaches are beneficial when automatic identification of relevant features among numerous candidates is desired. We investigated the predictive ability of several ML models for new onset of diabetes mellitus.

In 10,248 subjects who received annual health examinations, 58 candidates including fatty liver index (FLI), which is calculated by using waist circumference, body mass index and levels of triglycerides and γ-glutamyl transferase, were used.

During a 10-year follow-up period (mean period: 6.9 years), 322 subjects (6.5 %) in the training group (70 %, n=7,173) and 127 subjects (6.2 %) in the test group (30 %, n=3,075) had new onset of diabetes mellitus. Hemoglobin A1c, fasting glucose and FLI were identified as the top 3 predictors by random forest feature selection with 10-fold cross-validation. When hemoglobin A1c and FLI were used as the selected features, C-statistics analogous in receiver operating characteristic curve analysis in ML models including logistic regression, naïve Bayes, extreme gradient boosting and artificial neural network were 0.874, 0.869, 0.856 and 0.869, respectively. There was no significant difference in the discriminatory capacity among the ML models.

ML models incorporating hemoglobin A1c and FLI provide an accurate and straightforward approach for predicting the development of diabetes mellitus.