Abstract
BACKGROUND: Very long-chain saturated fatty acids (VLCSFA) may influence cardiometabolic health differently from other, often detrimental, saturated fatty acids (SFA). Evidence remains inconclusive, partly because VLCSFA are metabolically derived from SFA, making it difficult to disentangle their individual effects due to potential confounding of correlated lipids. Prior studies rarely accounted for correlations with other lipids or do not consider VLCSFA-specific lipid classes. We investigated prospective associations of circulating VLCSFA (C20:0, C22:0, C24:0) across multiple plasma lipid classes with type 2 diabetes (T2D) and cardiovascular disease (CVD), accounting for confounding by correlated lipids. METHODS: We constructed two nested case-cohort studies within the European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam cohort: 1911 in the T2D case-cohort (774 cases); 1704 in the CVD case-cohort (547 cases). Plasma concentrations of VLCSFA were measured in 12 lipid classes. A data-driven network including SFA across all lipid classes was used to identify precursors and downstream lipid metabolites for each lipid class of VLCSFA. The correlated lipids were gradually incorporated in multivariable-adjusted Cox regression models between individual lipids and disease risk. RESULTS: C20:0 was distributed across more lipid classes than C22:0 and C24:0. After including all correlated precursors and downstream lipid metabolites in the model, we observed that higher C22:0 levels were linked to higher T2D risk, while associations for C20:0 and C24:0 varied by class. Ceramides C20:0 (hazard ratio [HR] per SD: 0.52, 95% CI 0.35-0.79) and C24:0 (0.46, 0.27-0.79) were inversely associated with T2D, whereas dihydroceramides C20:0 (1.36, 1.07-1.72) and sphingomyelin C24:0 (1.61, 1.15-2.26) showed positive associations. Monoglycerides and cholesteryl esters containing VLCSFA were associated to higher risk of both outcomes. Most of these relationships were not observed when the confounding or mediation by correlated lipids was not considered. CONCLUSIONS: VLCSFA show different metabolic roles in cardiometabolic diseases and highlight the importance of adjusting for confounding by correlated lipids. These findings challenge the traditional view that SFA exert uniform negative effects and suggest class-specific VLCSFA profiles may improve risk prediction of cardiometabolic diseases, guiding more precise prevention strategies.