Open AccessIdentification of Diabetic Nephropathy in Patients Undergoing Kidney Biopsy through Blood and Urinary Profiles of d-Serine
Author(s) -
Yukimasa Iwata,
Hiroki Okushima,
Atsushi Hesaka,
Masataka Kawamura,
Ryoichi Imamura,
Shiro Takahara,
Masaru Horio,
Youko Tanaka,
Tatsuhiko Ikeda,
Maiko Nakane,
Masashi Mita,
Terumasa Hayashi,
Yoshitaka Isaka,
Tomonori Kimura
Publication year - 2021
Publication title -
kidney360
Language(s) - English
Resource type - Journals
ISSN - 2641-7650
DOI - 10.34067/kid.0004282021
Subject(s) - diabetic nephropathy , medicine , urinary system , kidney , kidney disease , nephropathy , urology , excretion , urine , endocrinology , gastroenterology , diabetes mellitus
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 μ M 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 μ M, 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.