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Ceramides surpass LDL-cholesterol in predicting cardiovascular mortality in diabetic and non-diabetic patients
Journal article   Open access   Peer reviewed

Ceramides surpass LDL-cholesterol in predicting cardiovascular mortality in diabetic and non-diabetic patients

Andreas Leiherer, Axel Muendlein, Christoph Saely, Thomas Plattner, Barbara Larcher, Arthur Mader, Alexander Vonbank, Reijo Laaksonen, Peter Fraunberger and Heinz Drexel
Atherosclerosis, v 407, 119608
Aug 2025
DOI: https://doi.org/10.1016/j.atherosclerosis.2025.119608
url
https://doi.org/10.1016/j.atherosclerosis.2025.119608View
Published, Version of Record (VoR)Maybe Open Access (Publisher Bronze),  Open

Abstract

Background and Aims: The power of cardiovascular risk prediction is biased by comorbidities (including T2DM), medical treatment, and age, which impact cholesterol levels. Consequently, when applying LDL-C, the true cardiovascular risk of such confounded patients is often underestimated. However, it is not clear whether this constraint for risk prediction may likewise apply to other lipid risk markers in particular ceramides. Methods: In this observational cohort study, we recorded cardiovascular mortality for 16 years in 1195 patients. Their median age was 67 years, all of them had a high preexisting cardiovascular risk, 51% were taking statins, and 30% had T2DM. Results: We found a U-shaped association between cardiovascular mortality and LDL-C. We thus stratified the population according to the vertex into high (≥150mg/dL) and lower LDL-C (<150mg/dL) and also according to the T2DM status. A Cox regression analysis revealed that LDL-C failed to predict cardiovascular mortality in any subgroup. In contrast, no U-shaped but a linear association was found for ceramide-based markers. They were able to significantly predict cardiovascular mortality after stratification and even after multivariate adjustment. Conclusions: We thus propose that ceramide-based predictors rather than LDL-C should be applied for a more accurate cardiovascular risk prediction in diabetic and other high-risk patients.

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