Plasma lipidomics, choline metabolites, and metabolic-associated steatotic liver disease (MASLD): A Coronary Artery...

Metabolic-associated steatotic liver disease (MASLD) is marked by accumulation of hepatic triacylglycerols (TAG), but many other lipids have been implicated. Choline metabolism has been shown to be related to MASLD, specifically through phosphatidylcholines (PC) role in hepatic TAG removal through very low density lipoproteins (VLDL). There are a lack of population-based studies with integrated data on lipidomics, choline metabolites, and MASLD. We tested associations between the plasma lipidome, choline metabolites, and MASLD using data from the Coronary Artery Risk Development in Young Adults (CARDIA) Study. The analytic sample included 1,039 participants with data on choline metabolite, lipidomic, and liver attenuation data [mean (SD) age: 45 (4); 57% female; 57% White race]. MASLD (n = 234) was defined as mean CT-derived liver attenuation < 51HU. Plasma lipidomics and choline metabolites were quantified from stored fasting plasma using liquid-chromatography and infusion-mass spectrometry. In logistic regression adjusted for sociodemographics, lifestyle, and clinical variables, total TAGs, diacylglycerols (DAG), and dihydroceramides (DCER) were positively, and lactosylceramides (LCER) were inversely, associated with MASLD. Species-level results revealed diverging MASLD associations for PCs, based on FA composition. In choline metabolite models, betaine was inversely associated with MASLD. A lipidomic risk score (LRS) derived from penalized regression of MASLD on lipid species was associated positively with choline, and inversely with betaine. We contribute population-based results to a growing literature relating lipidomics and MASLD. In our data, FA composition is biologically relevant to MASLD, particularly for PCs and TAGs. Our results link choline metabolites to both the plasma lipidome and to incident MASLD, furthering efforts in biomarker development and supporting mechanistic evidence using population-level data.