Abstract: SA-PO0599
Metabolomic Profiling of Plasma Reveals Disease-Specific Signatures and Biomarkers in ADPKD
Session Information
- Cystic Kidney Diseases: Clinical Research
November 08, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Genetic Diseases of the Kidneys
- 1201 Genetic Diseases of the Kidneys: Monogenic Kidney Diseases
Authors
- Ali, Hamad, Kuwait University Health Sciences Center, Safat, Kuwait
- Abu-Farha, Mohamed, ADPKD National Clinic, Mubarak Al-Kabeer Hospital, Kuwait, Kuwait
- Bahbahani, Yousif, ADPKD National Clinic, Mubarak Al-Kabeer Hospital, Kuwait, Kuwait
- Al Rajab, Heba, ADPKD National Clinic, Mubarak Al-Kabeer Hospital, Kuwait, Kuwait
- Almutawa, Sarah F A M A, ADPKD National Clinic, Mubarak Al-Kabeer Hospital, Kuwait, Kuwait
- Bahbahani, Hamad Mahdi, ADPKD National Clinic, Mubarak Al-Kabeer Hospital, Kuwait, Kuwait
- Almomen, Mohammad, ADPKD National Clinic, Mubarak Al-Kabeer Hospital, Kuwait, Kuwait
- Ayoub, Medhat N., ADPKD National Clinic, Mubarak Al-Kabeer Hospital, Kuwait, Kuwait
- Abubaker, Jehad, Dasman Diabetes Institute, Kuwait City, Al Asimah Governate, Kuwait
- Al-Mulla, Fahd, Dasman Diabetes Institute, Kuwait City, Al Asimah Governate, Kuwait
Background
Autosomal Dominant Polycystic Kidney Disease (ADPKD) is the most common inherited kidney disorder, characterized by progressive cyst development, renal enlargement, and decline in kidney function. Early detection remains a clinical challenge due to the lack of sensitive and specific biomarkers. Metabolomic profiling offers a promising approach to identify novel biomarkers and uncover disease-related metabolic dysregulation.
Methods
This pilot cross-sectional study analyzed plasma from clinical and genetic diagnosed ADPKD patients (n=8) and healthy controls (n=14) using LC-HRMS with the Biocrates Absolute IDQ-p400 HR kit. Data were processed and analyzed via PCA, Wilcoxon testing, random forest classification, and pathway enrichment.
Results
Multivariate statistical analysis demonstrated clear separation between ADPKD and control groups, highlighting distinct plasma metabolomic profiles. The analysis found important alterations in certain metabolites in the body. Some were higher than usual, like specific fats called lysophosphatidylcholines (LPC(16:0), LPC-O(16:1)) and triglycerides (TG(55:8), TG(55:9)), as well as a metabolite called sarcosine. Others were lower than normal, including taurine, arginine, and several types of cholesteryl esters. Random forest analysis pinpointed key discriminative metabolites, with sarcosine and LPC(16:0) ranking highest. Pathway enrichment indicated significant dysregulation in amino acid metabolism, transcription and translation regulation, and SLC-mediated transmembrane transport.
Conclusion
This pilot study reveals a distinct metabolic signature associated with ADPKD and identifies potential biomarkers with diagnostic relevance. These findings enhance our understanding of disease-related metabolic remodeling and highlight promising targets for future clinical validation and therapeutic exploration.