Lipidomics in MASLD and MetALD

Steatotic liver disease (SLD) includes the subtypes of metabolic dysfunction-associated steatotic liver disease (MASLD) and MASLD and increased alcohol intake (MetALD) (1). Differentiating MASLD from MetALD is crucial due to their distinct prognoses and management strategies (2–4). Advancements in the omics landscape —such as genomics, proteomics, and metabolomics—may enhance our understanding of steatotic liver diseases (5).

Schneider et al. explored lipidomic differences between MASLD and MetALD using the UK Biobank to identify lipidomic biomarkers to reliably distinguish these two steatotic liver disease phenotypes (6). They analyzed data from 40,534 individuals with MRI liver scans, of whom 11,217 had SLD, as well as detailed data on alcohol consumption and cardiometabolic comorbidities. Among these participants, nuclear magnetic resonance spectroscopy lipidomic profiles were available for 6,055 cases (5,539 MASLD, 462 MetALD, and 53 ALD), and the authors examined 250 plasma lipidomic and metabolomic parameters. MetALD participants had significantly elevated high-density lipoprotein (HDL)-centric lipidomic markers compared to MASLD, and other top discriminatory metabolites include acetoacetate, 3-hydroxybutyrate, apolipoprotein A1, and phosphatidylcholines. These markers exhibited a stable association with alcohol consumption during their sensitivity analysis and Mendelian randomization identified a causal relationship between alcohol consumption and levels of several of these metabolites.

This study utilized a large cohort with well-characterized liver phenotypes and a comprehensive array of lipidomic and metabolomic biomarkers. Furthermore, Mendelian randomization offers a robust approach to infer causal relationships, mitigating biases often seen in observational studies, lending credence to the argument that alcohol consumption distinctly alters lipid profiles. The study is not without limitations. There was a temporal disconnect between the lipidomic data collection and liver MRI scans. In UK Biobank, lipidomic specimens were nearly all collected in 2006–2010 (some were collected 2012–2013), while MRI scans were done 2014 or later. This potentially obscures temporal dynamics of lipid changes. The authors attempted to mitigate this by performing sensitivity analysis in the subset of participants with two metabolomic profiles to show that HDL profiles remained largely stable over time. Also, the study relies on self-reported alcohol consumption; alcohol biomarkers that distinguish MASLD and MetALD, as the authors recently showed (7), may serve as the basis for future metabolomic studies. Finally, the cohort’s predominantly European ancestry limits the generalizability of the findings to other populations.

The study highlights the complex link between alcohol consumption and lipid metabolism, particularly HDL-derived biomarkers, and hints at pathophysiologic distinctions between MASLD and MetALD. Whether these changes are mere biomarkers or active in MetALD pathogenesis remains unclear, and future studies to validate these findings across diverse populations and understand the implications of these biomarkers on disease trajectory will be crucial.