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Abstract: PO1218

Metabolomic Analysis of Patients with Autosomal Dominant Polycystic Kidney Disease (ADPKD): Associations with Disease Progression and Treatment

Session Information

Category: Genetic Diseases of the Kidneys

  • 1001 Genetic Diseases of the Kidneys: Cystic

Authors

  • Sundar, Shirin, Otsuka Pharmaceutical Development & Commercialization, Rockville, Maryland, United States
  • Roth, Sharin, Otsuka Pharmaceutical Development & Commercialization, Rockville, Maryland, United States
  • Hajarnis, Sachin S., Otsuka Pharmaceutical Development & Commercialization, Rockville, Maryland, United States
  • Westcott-Baker, Lucas, Otsuka Pharmaceutical Development & Commercialization, Rockville, Maryland, United States
  • Mccormick, Linda, Otsuka Pharmaceutical Development & Commercialization, Rockville, Maryland, United States
  • Ramaswamy, Bharath, Otsuka Pharmaceutical Development & Commercialization, Rockville, Maryland, United States
  • Chapman, Arlene B., University of Chicago, Chicago, Illinois, United States
Background

ADPKD is characterized by epithelial proliferation and cyst growth. Metabolic abnormalities have been identified in murine models, but little is known about alterations in metabolic pathways in human ADPKD. We evaluated plasma metabolomic profiles in ADPKD subjects prior to and after exposure to tolvaptan (T) as compared to healthy controls to better understand metabolic alterations in ADPKD and potential associations with disease progression and treatment response.

Methods

Plasma samples were collected and analyzed at baseline and month 12 in 100 ADPKD subjects (50 in T and 50 in placebo [P] arms) enrolled in TEMPO 3:4 (NCT00428948). The protein fraction was removed, and the remaining extract split into equal parts for analysis on liquid chromatography tandem mass spectrometry and gas chromatography mass spectrometry platforms. Proprietary software (Metabolon, Inc., Durham, NC) matched ions to an in-house library of standards for metabolite identification and quantitation. Forty age- and sex-matched healthy subjects were analyzed as a control group. Linear mixed effect modeling identified associations of metabolites with ADPKD vs control, height-adjusted total kidney volume (htTKV), Mayo Imaging Classification (MIC), and T vs P.

Results

Baseline metabolic profiles differed between ADPKD and controls, with significant differences in lipid metabolism, TCA cycle, and amino acid metabolism. Baseline MIC 1C, 1D, 1E (vs 1B) were associated with accumulation of the uremic toxin pseudouridine, elevated fatty acid synthesis, and altered tryptophan metabolism, with similar findings when baseline htTKV was analyzed. Thyroxine, urea, and dimethylsulfone were decreased in T vs P at month 12, as well as other metabolites involved in lipid and amino acid metabolism.

Conclusion

We identified novel associations of amino acid and lipid metabolic pathways with ADPKD vs control and with measures of disease severity (MIC and htTKV). Metabolite intensity was differentially affected in T vs P at 12 months of treatment, supporting a role for discovery metabolomics in evaluating response to therapy.

Funding

  • Commercial Support