Evidence map›Paper›PMID 41080949›Full record

ArticleFrontiers in medicine2025

Untargeted metabolomics reveals distinct biomarkers and metabolic alterations in familial and non-genetic hypercholesterolemia in Saudi patients.

Hadiah Bassam Al Mahdi, Noor Ahmad Shaik, Zuhier Awan, Hussam Daghistani, Faisal Alandejani, Kawthar Saad Alghamdi, Ahmad A Obaid, Rawabi Zahed, Reem Nabil Hassan, Sherif Edris and 2 more

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Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

12 authors.

Hadiah Bassam Al MahdiDepartment of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
Noor Ahmad ShaikDepartment of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Zuhier AwanDepartment of Clinical Biochemistry, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Hussam DaghistaniDepartment of Clinical Biochemistry, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Faisal AlandejaniDepartment of Clinical Biochemistry, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Kawthar Saad AlghamdiDepartment of Biology, College of Science, University of Hafr Al Batin, Hafar Al Batin, Saudi Arabia.
Ahmad A ObaidDepartment of Physiology, Faculty of Medicine, Umm Al-Qura University, Makkah, Saudi Arabia.
Rawabi ZahedDepartment of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
Reem Nabil HassanDepartment of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
Sherif EdrisDepartment of Biological Sciences, Faculty of Science, King Abdulaziz University, Jeddah, Saudi Arabia.
Babajan BanaganapalliDepartment of Genetic Medicine, Faculty of Medicine, King Abdulaziz University, Jeddah, Saudi Arabia.
Abdulrahman MujalliDepartment of Clinical Laboratory Sciences, Faculty of Applied Medical Sciences, Umm Al-Qura University, Makkah, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Familial 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. Methods: A 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. Results: Metabolic 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- Conclusion: This 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.

Indexed as

biomarkerscholic acidfamilial hypercholesterolemiaKEGG databaseuntargeted metabolomics

Identifiers

PMID41080949
PMCPMC12511148

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