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- Title
Identification of Novel Urinary Biomarkers for Predicting Renal Prognosis in Patients With Type 2 Diabetes by Glycan Profiling in a Multicenter Prospective Cohort Study: U-CARE Study 1.
- Authors
Koki Mise; Mariko Imamura; Satoshi Yamaguchi; Sanae Teshigawara; Atsuhito Tone; Uchida, Haruhito A.; Jun Eguchi; Atsuko Nakatsuka; Daisuke Ogawa; Michihiro Yoshida; Masao Yamada; Kenichi Shikata; Jun Wada; Mise, Koki; Imamura, Mariko; Yamaguchi, Satoshi; Teshigawara, Sanae; Tone, Atsuhito; Eguchi, Jun; Nakatsuka, Atsuko
- Abstract
<bold>Objective: </bold>Because quantifying glycans with complex structures is technically challenging, little is known about the association of glycosylation profiles with the renal prognosis in diabetic kidney disease (DKD).<bold>Research Design and Methods: </bold>In 675 patients with type 2 diabetes, we assessed the baseline urinary glycan signals binding to 45 lectins with different specificities. The end point was a decrease of estimated glomerular filtration rate (eGFR) by ≥30% from baseline or dialysis for end-stage renal disease.<bold>Results: </bold>During a median follow-up of 4.0 years, 63 patients reached the end point. Cox proportional hazards analysis revealed that urinary levels of glycans binding to six lectins were significantly associated with the outcome after adjustment for known indicators of DKD, although these urinary glycans, except that for DBA, were highly correlated with baseline albuminuria and eGFR. Hazard ratios for these lectins were (+1 SD for the glycan index) as follows: SNA (recognizing glycan Siaα2-6Gal/GalNAc), 1.42 (95% CI 1.14-1.76); RCA120 (Galβ4GlcNAc), 1.28 (1.01-1.64); DBA (GalNAcα3GalNAc), 0.80 (0.64-0.997); ABA (Galβ3GalNAc), 1.29 (1.02-1.64); Jacalin (Galβ3GalNAc), 1.30 (1.02-1.67); and ACA (Galβ3GalNAc), 1.32 (1.04-1.67). Adding these glycan indexes to a model containing known indicators of progression improved prediction of the outcome (net reclassification improvement increased by 0.51 [0.22-0.80], relative integrated discrimination improvement increased by 0.18 [0.01-0.35], and the Akaike information criterion decreased from 296 to 287).<bold>Conclusions: </bold>The urinary glycan profile identified in this study may be useful for predicting renal prognosis in patients with type 2 diabetes. Additional investigation of glycosylation changes and urinary glycan excretion in DKD is needed.
- Subjects
BIOLOGICAL tags; GLYCAN analysis; PEOPLE with diabetes; URINALYSIS; DIAGNOSIS; PHYSIOLOGY; MEDICAL care
- Publication
Diabetes Care, 2018, Vol 41, Issue 8, p1765
- ISSN
0149-5992
- Publication type
journal article
- DOI
10.2337/dc18-0030