Identification of Diabetic Nephropathy in Patients Undergoing Kidney Biopsy through Blood and Urinary Profiles of D-Serine

Abstract

Background The diagnosis of diabetic nephropathy (DN), the major cause of ESKD, requires kidney biopsy. d-Serine, present only in trace amounts in humans, is a biomarker for kidney diseases and shows potential to distinguish the origin of kidney diseases, whose diagnoses usually require kidney biopsy. We extended this concept and examined the potential of d-serine in the diagnosis of DN. Methods We enrolled patients with biopsy sample-proven DN and primary GN (minimal change disease and IgA nephropathy) and participants without kidney disease. A total of 388 participants were included in this study, and d-serine levels in blood and urine were measured using two-dimensional high-performance liquid chromatography, and urinary fractional excretion (FE) of d-serine was calculated. Using data from 259 participants, we developed prediction models for detecting DN by logistic regression analyses, and the models were validated in 129 participants. Results A d-serine blood level of >2.34 μM demonstrated a high specificity of 83% (95% CI, 70% to 93%) for excluding participants without kidney diseases. In participants with a d-serine blood level >2.34 μM, the threshold of 47% in FE of d-serine provided an optimal threshold for the detection of DN (AUC, 0.85 [95% CI, 0.76 to 0.95]; sensitivity, 79% [95% CI, 61% to 91%]; specificity, 83% [95% CI, 67% to 94%]). This plasma-high and FE-high profile of d-serine in combination with clinical factors (age, sex, eGFR, and albuminuria) correctly predicted DN with a sensitivity of 91% (95% CI, 72% to 99%) and a specificity of 79% (95% CI, 63% to 80%), and outperformed the model based on clinical factors alone in the validation dataset (P<0.02). Conclusions Analysis of d-serine in blood and urinary excretion is useful in identifying DN in patients undergoing kidney biopsy. Profiling of d-serine in patients with kidney diseases supports the suitable treatment through the auxial diagnosis of the origins of kidney diseases.