Diabetic nephropathy progression can be predicted by seeing differences in sugar chains in just one drop of urine! – Sugar chains in urine reflect a new progression mechanism of nephropathy
June 22(Fri), 2018
A research group led by Professor Jun Wada and Koki Mise, a researcher at the Department of Nephrology, Rheumatology, Endocrinology and Metabolism, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, found for the first time that a difference in sugar chain amounts excreted in urine can be a new biomarker to predict the future progression of kidney disease among diabetic patients. This research result was published in the electronic version of Diabetes Care, an American science journal, at 2 pm EST in the U.S. on June 21, 2018 (4 am on June 22, 2018 in Japan).
Sugar chains are essential biomacromolecules with various functions in living organisms, but their structures are complicated and hard to measure. Because of this, research on sugar chains relating to kidney disease and diabetes was lagging. In this research, lectin arrays developed by GlycoTechnica Ltd., a collaborator on this research, were used. With these arrays, the group was able to simultaneously measure several sugar chain volumes of many patients in a very short period of time using samples of just one drop of urine (20 microliters; micro meaning one/one million). Further, the group measured sugar chains in urine at many institutions and discovered that specific sugar chain volumes were higher among patients who were believed to have a greater possibility of worsening kidney functions in the future.
It is possible that a sugar chain volume increase in urine reflects an important mechanism in a worsening of diabetic nephropathy. Further research on sugar chains in urine is expected to identify treatment targets for diabetic nephropathy.
Journal: Diabetes Care
Authors: Koki Mise, Mariko Imamura, Satoshi Yamaguchi, Sanae Teshigawara, Atsuhito Tone, Haruhito A. Uchida, Jun Eguchi, Atsuko Nakatsuka, Daisuke Ogawa, Michihiro Yoshida, Masao Yamada, Kenichi Shikata and Jun Wada
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
Year of Publication: 2018
Okayama University Silicon Valley Office (OUSVO)
Contact: Mototaka Senda, Ph.D.