Literature DB >> 33223406

SH3YL1 protein as a novel biomarker for diabetic nephropathy in type 2 diabetes mellitus.

Gyu S Choi1, Hye S Min2, Jin J Cha1, Ji E Lee2, Jung Y Ghee1, Ji A Yoo1, Ki T Kim3, Young S Kang1, Sang Y Han4, Yun S Bae5, Sae R Lee5, Jung Y Yoo5, Sung H Moon6, Soo J Lee6, Dae R Cha7.   

Abstract

BACKGROUND AND AIMS: Oxidative stress contributes to development of diabetic nephropathy. We implicated SH3YL1 in oxidative stress-induced inflammation and examined whether SH3YL1 could be used as a new biomarker of diabetic nephropathy. METHODS AND
RESULTS: In this study, we investigated the relationship between plasma level of SH3YL1 and diabetic nephropathy in patients with type 2 diabetes. In addition, we examined the physiological role of SH3YL1 in db/db mice and cultured podocytes. Plasma SH3YL1 concentration was significantly higher in patients with diabetes than in controls, even in normoalbuminuric patients, and was markedly increased in the macroalbuminuria group. Plasma SH3YL1 level was positively correlated with systolic blood pressure, HOMA-IR, postprandial blood glucose, plasma level of retinol binding protein 4 (RBP 4), and urinary albumin excretion (UAE) and was inversely correlated with BMI. Regression analysis showed that plasma level of RBP 4, UAE, and BMI were the only independent determinants of plasma SH3YL1 concentration. In db/db mice, plasma and renal SH3YL1 levels were significantly increased in mice with diabetes compared with control mice. In cultured podocytes, high glucose and angiotensin II stimuli markedly increased SH3YL1 synthesis.
CONCLUSION: These findings suggest that plasma level of SH3YL1 offers a promising new biomarker for diabetic nephropathy.
Copyright © 2020 The Italian Diabetes Society, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Biomarker; Diabetic nephropathy; SH3YL1

Year:  2020        PMID: 33223406     DOI: 10.1016/j.numecd.2020.09.024

Source DB:  PubMed          Journal:  Nutr Metab Cardiovasc Dis        ISSN: 0939-4753            Impact factor:   4.222


  1 in total

1.  Bioinformatics prediction and experimental verification of key biomarkers for diabetic kidney disease based on transcriptome sequencing in mice.

Authors:  Jing Zhao; Kaiying He; Hongxuan Du; Guohua Wei; Yuejia Wen; Jiaqi Wang; Xiaochun Zhou; Jianqin Wang
Journal:  PeerJ       Date:  2022-09-20       Impact factor: 3.061

  1 in total

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