Untargeted metabolomics reveals distinct biomarkers and metabolic alterations in familial and non-genetic hypercholesterolemia in Saudi patients - Al Mahdi, Hadiah Bassam; Shaik, Noor Ahmad; Awan, Zuhier; Daghistani, Hussam; Alandejani, Faisal; Alghamdi, Kawthar Saad; Obaid, Ahmad A.; Zahed, Rawabi; Hassan, Reem Nabil; Edris, Sherif; Banaganapalli, Babajan; Mujalli, Abdulrahman (Frontiers in Medicine, 2025)
BackgroundFamilial hypercholesterolemia (FH) and non-genetic hypercholesterolemia (HC) are both associated with elevated low-density cholesterol (LDL-C) levels, which increase the risk of cardiovascular disease. However, their underlying metabolic disturbances differ significantly. Untargeted metabolomics offers a powerful approach for identifying disease-specific metabolic signatures and potential biomarkers, thereby contributing to precision medicine applications.MethodsA high-resolution metabolomics analysis was performed using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) on plasma samples from FH, HC, and healthy Saudi individuals. Differentially expressed metabolites were identified through univariate and multivariate analyses, followed by pathway enrichment analysis using the KEGG database.ResultsMetabolic profiling revealed distinct alterations in bile acid biosynthesis and steroid metabolism pathways in FH. Cholic acid was significantly downregulated, while 17α-hydroxyprogesterone (17α-OHP) was significantly elevated in FH. In contrast, HC was characterized by increased uric acid and choline levels, along with dysregulation in oleic acid and linoleic acid metabolism. Notably, both FH and HC groups were dysregulated in Sphinganine, D-α-hydroxyglutaric acid, and pyridoxamine.ConclusionThis study demonstrates the utility of untargeted metabolomics in distinguishing FH from HC, identifying 17α-OHP and cholic acid as potential FH biomarkers, while uric acid and choline may serve as HC-specific metabolic markers. These findings provide new insights for personalized interventions, enhancing disease stratification and therapeutic decision-making between genetic and non-genetic hypercholesterolemia.