TY - JOUR
T1 - Predicting albuminuria response to spironolactone treatment with urinary proteomics in patients with type 2 diabetes and hypertension
AU - Lindhardt, Morten
AU - Persson, Frederik
AU - Oxlund, Christina
AU - Jacobsen, Ib A
AU - Zürbig, Petra
AU - Mischak, Harald
AU - Rossing, Peter
AU - Heerspink, Hiddo J L
N1 - © The Authors 2017. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.
PY - 2018/2/1
Y1 - 2018/2/1
N2 - Background The mineralocorticoid receptor antagonist spironolactone significantly reduces albuminuria in patients with diabetes. Prior studies have shown large between-patient variability in albuminuria treatment response. We previously developed and validated a urinary proteomic classifier that predicts onset and progression of chronic kidney disease. Here, we tested whether the proteomic classifier based on 273 urinary peptides (CKD273) predicts albuminuria response to spironolactone treatment. Methods We performed a post hoc analysis in a double-blind randomized clinical trial with allocation to either spironolactone 12.5-50 mg/day (n = 57) or placebo (n = 54) for 16 weeks. Patients were diagnosed with type 2 diabetes and resistant hypertension. Treatment was an adjunct to renin-Angiotensin system inhibition. Primary endpoint was the percentage change in urine albumin to creatinine ratio (UACR). Capillary electrophoresis mass spectrometry was used to quantify urinary peptides at baseline. The previously validated combination of 273 known urinary peptides was used as proteomic classifier. Results Spironolactone reduced UACR relative to placebo by 50%, although with a large between-patient variability in UACR response (5th to 95th percentile, 7 to 312%). An interaction was detected between CKD273 and treatment assignment (β = â '1.09, P = 0.026). Higher values of CKD273 at baseline were associated with a larger reduction in UACR in the spironolactone group (β = â '0.70, P = 0.049), but not in the placebo group (β = 0.39, P = 0.25). Stratified in tertiles of baseline CKD273, reduction in UACR was greater in the highest tertile, 63% (95% confidence interval: 35-79%), as compared with the two other tertiles combined, 16% (â '17 to 40%) (P = 0.011). Conclusions A urinary proteomics classifier can be used to identify individuals with type 2 diabetes who are more likely to show an albuminuria-lowering response to spironolactone treatment. These results suggest that urinary proteomics may be a valuable tool to tailor therapy, but confirmation in a larger clinical trial is required.
AB - Background The mineralocorticoid receptor antagonist spironolactone significantly reduces albuminuria in patients with diabetes. Prior studies have shown large between-patient variability in albuminuria treatment response. We previously developed and validated a urinary proteomic classifier that predicts onset and progression of chronic kidney disease. Here, we tested whether the proteomic classifier based on 273 urinary peptides (CKD273) predicts albuminuria response to spironolactone treatment. Methods We performed a post hoc analysis in a double-blind randomized clinical trial with allocation to either spironolactone 12.5-50 mg/day (n = 57) or placebo (n = 54) for 16 weeks. Patients were diagnosed with type 2 diabetes and resistant hypertension. Treatment was an adjunct to renin-Angiotensin system inhibition. Primary endpoint was the percentage change in urine albumin to creatinine ratio (UACR). Capillary electrophoresis mass spectrometry was used to quantify urinary peptides at baseline. The previously validated combination of 273 known urinary peptides was used as proteomic classifier. Results Spironolactone reduced UACR relative to placebo by 50%, although with a large between-patient variability in UACR response (5th to 95th percentile, 7 to 312%). An interaction was detected between CKD273 and treatment assignment (β = â '1.09, P = 0.026). Higher values of CKD273 at baseline were associated with a larger reduction in UACR in the spironolactone group (β = â '0.70, P = 0.049), but not in the placebo group (β = 0.39, P = 0.25). Stratified in tertiles of baseline CKD273, reduction in UACR was greater in the highest tertile, 63% (95% confidence interval: 35-79%), as compared with the two other tertiles combined, 16% (â '17 to 40%) (P = 0.011). Conclusions A urinary proteomics classifier can be used to identify individuals with type 2 diabetes who are more likely to show an albuminuria-lowering response to spironolactone treatment. These results suggest that urinary proteomics may be a valuable tool to tailor therapy, but confirmation in a larger clinical trial is required.
KW - Journal Article
U2 - 10.1093/ndt/gfw406
DO - 10.1093/ndt/gfw406
M3 - Journal article
C2 - 28064163
SN - 0931-0509
VL - 33
SP - 296
EP - 303
JO - Nephrology, Dialysis, Transplantation
JF - Nephrology, Dialysis, Transplantation
IS - 2
ER -
