Kidney Week

Abstract: FR-PO461

Validation of a Systems Biology Derived Urinary Metabolite Panel for Prediction of Albuminuria Response to Spironolactone Therapy in Type 2 Diabetes

Session Information

• Diabetic Kidney Disease: Clinical - I
  October 26, 2018 | Location: Exhibit Hall, San Diego Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Diabetic Kidney Disease

• 602 Diabetic Kidney Disease: Clinical

Authors

• Mulder, Skander, University Medical Center Groningen, Groningen, Netherlands

Skander Mulder,

• Lambers Heerspink, Hiddo Jan, University Medical Center Groningen, Groningen, Netherlands

Hiddo Jan Lambers Heerspink,

• Perco, Paul, Medical University Innsbruck, Innsbruck, Austria

Paul Perco,

• Toto, Robert D., University of Texas Southwestern Medical Center, Dallas, Texas, United States

Robert D. Toto,

• Pena, Michelle, University Medical Center Groningen, Groningen, Netherlands

Michelle Pena,

Background

The mineralocorticoid receptor antagonist spironolactone significantly reduces albuminuria in patients with diabetic kidney disease, albeit with a large between individual variability. We previously identified a panel of systems biology derived urinary metabolites for prediction of albuminuria response to spironolactone therapy.¹ Here we validate this metabolite panel in an external cohort.

Methods

Data and samples were used from a randomized placebo controlled double blind clinical trial.² Patients with diabetes, hypertension, and albuminuria (urine albumin-to-creatinine ratio ≥300 mg/g) who all received lisinopril 80 mg/day were randomly assigned to placebo (n=23) or spironolactone 25 mg/day (n=20) for 48 weeks. Urine samples were obtained at baseline, 24 and 48 weeks, and LC-MS metabolomics measurements were performed on the baseline samples. We used leave-one-out cross-validated optimism corrected ridge regression to predict albuminuria response to spironolactone.

Results

After 12 weeks of therapy, spironolactone reduced UACR relative to placebo by median -57%, with large variability (5th to 95th percentile -136% to +4%). A clear separation between the spironolactone and placebo arms was observed in the predicted treatment effect by the metabolite panel (Figure). The metabolite panel was able to predict albuminuria response to spironolactone (R² = 0.30, p-value <0.01).

Conclusion

We validated a previously identified panel of 18 urinary biogenic amines and organic acids to predict albuminuria response to spironolactone. These results suggest that this urinary metabolite panel may be used as a tool to tailor optimal therapy in diabetes and move in the direction of personalized medicine.

References
1. Pena et al. Urinary Metabolomics Predict Albuminuria Response to Spironolactone Therapy in Type 2 Diabetes. J Am Soc Nephrol 27, 2016: 557A
2. Mehdi et al. J Am Soc Nephrol. 2009 Dec;20(12):2641-50

Funding

• Commercial Support –