Specific Lipidomic Shifts in Chronic Lymphocytic Leukemia at Diagnosis

Background: Chronic lymphocytic leukemia (CLL) is the most common adult leukemia and is characterized by dysregulated apoptosis and metabolic reprogramming, including alterations in lipid metabolism. However, the plasma lipidome of newly diagnosed, treatment-naïve CLL patients remains insufficiently characterized. This study aimed to define disease-specific plasma lipidomic alterations, identify discriminatory lipid species, and investigate associated metabolic pathways. Methods: The study cohort consisted of 41 participants (median age 75 years, range: 40–86), including 30 newly diagnosed, treatment-naïve CLL patients (median age 75 years, range: 40–86) and 11 age- and sex-matched healthy controls (median age 75 years, range: 41–85). Targeted lipidomic profiling was performed on plasma samples using liquid chromatography with tandem mass spectrometry (LC-MS/MS). Data processing was conducted in R using LipidSigR. Statistical analyses employed the Wilcoxon–Mann–Whitney test with Benjamini–Hochberg correction. To address data dimensionality, Boruta machine learning and pathway enrichment analyses were applied. Gene–lipid associations were further explored using GATOm, followed by Metascape analysis to identify enriched biological processes. Results: A total of 124 lipid species from five major classes (phosphatidylcholines, lysophosphatidylcholines, sphingomyelins, ether-linked phosphatidylcholines, and acylcarnitines) were quantified. CLL patients exhibited significant enrichment of acylcarnitines, saturated phosphatidylcholines, and sphingolipids compared with controls. Principal component analysis showed partial separation by disease status. Machine learning identified carnitines and ether-linked phospholipids as key discriminators. Integrated gene–lipid analyses revealed significant enrichment of lipid metabolism-related pathways, particularly glycerolipid and phosphatidylcholine metabolism, as well as lipid catabolism, ether lipid metabolism, and fatty acid metabolism. Conclusions: Treatment-naïve CLL patients display distinct plasma lipidomic signatures indicative of disease-specific metabolic reprogramming. Integrated lipidomic and predictive pathway analyses suggest disruptions in lipid metabolic pathways and highlight carnitines and ether-linked phospholipids as biological markers warranting further investigation as potential CLL biomarkers.