Abstract: FR-PO738
Serum Global Metabolic Profiling Identifies Key Metabolic Networks Dysregulated in Autosomal Dominant Polycystic Kidney Disease
Session Information
- Cystic Kidney Diseases: Clinical/Translational
November 08, 2019 | Location: Exhibit Hall, Walter E. Washington Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: Genetic Diseases of the Kidneys
- 1001 Genetic Diseases of the Kidneys: Cystic
Authors
- Valencia, Tania M., Regulus Therapeutics, San Diego, California, United States
- Flaten, Andrea N., UT Southwestern Medical Center, Dallas, Texas, United States
- Patel, Vishal, University of Texas Southwestern Medical Center, Dallas, Texas, United States
- Wallace, Darren P., University of Kansas Medical Center, Kansas City, Kansas, United States
- Lee, Edmund, Regulus Therapeutics, San Diego, California, United States
Background
Autosomal dominant polycystic kidney disease (ADPKD) is a monogenetic disorder, caused by mutations in either the PKD1 or PKD2 gene, that eventually leads to end-stage renal disease. Despite this prognosis, treatment options for ADPKD are limited. Total kidney volume has been qualified by both FDA and EMA as a prognostic enrichment biomarker for selecting patients at high risk for progressive decline in renal function for inclusion in interventional clinical trials for ADPKD. However, an ADPKD-specific, easily-accessible and reliable biofluid biomarker for identification, stratification and monitoring of disease progression is lacking.
Methods
As several signaling and metabolic pathways are known to be dysregulated during ADPKD progression, we examined the global metabolic profiles of serum samples from a Pkd2-KO mouse model of ADPKD (n=6) and WT normal (n=6) mice; as well as ADPKD patients (n=22) and healthy volunteers (n=15) to investigate whether a metabolic profile could be established to aid in assessing disease progression. Dysregulated metabolites were identified and interrogated for their correlation to BUN, eGFR or HtTKV.
Results
Global metabolic profiling carried out in mouse and human serum samples detected a total of 841 and 1156 metabolites, respectively. In human serum samples, principal component analysis showed a clear separation of serum global metabolic profiles between ADPKD and healthy populations. Sex and age were also contributing factors, accounting for 20% and 25% of the metabolite differences observed between the respective human populations. As anticipated, serum creatine and urea were among the dysregulated metabolites increased in ADPKD samples and were highly correlated to eGFR (R2=0.949) and BUN (R2=-0.078), respectively. Importantly, we have identified a targeted list of serum metabolites (including those involved in lipid metabolism) that showed differential abundance in both human and mouse ADPKD compared to their respective healthy cohorts.
Conclusion
Our comprehensive evaluation of the global metabolic profiles of serum samples from a mouse model of ADPKD as well as ADPKD patients have identified significant dysregulation in several key metabolic networks. Our results point to the potential use of serum metabolites as translational biomarkers for ADPKD.
Funding
- Commercial Support –