American Journal of Physiology: Renal, Fluid & Electrolyte Physiology (Abstracts) 2011-01-01

Midkine, a heparin-binding protein, is increased in the diabetic mouse kidney postmenopause.

Maggie K Diamond-Stanic, Melissa J Romero-Aleshire, Patricia B Hoyer, Kevin Greer, James B Hoying, Heddwen L Brooks

文献索引：Am. J. Physiol. Renal Physiol. 300(1) , F139-46, (2011)

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摘要

Estrogen is thought to protect against the development of chronic kidney disease, and menopause increases the development and severity of diabetic kidney disease. In this study, we used streptozotocin (STZ) to induce diabetes in the 4-vinylcyclohexene diepoxide (VCD)-treated mouse model of menopause. DNA microarrays were used to identify gene expression changes in the diabetic kidney postmenopause. An ANOVA model, CARMA, was used to isolate the menopause effect between two groups of diabetic mice, diabetic menopausal (STZ/VCD) and diabetic cycling (STZ). In this diabetic study, 8,864 genes of the possible 15,600 genes on the array were included in the ANOVA; 99 genes were identified as demonstrating a >1.5-fold up- or downregulation between the STZ/VCD and STZ groups. We randomly selected genes for confirmation by real-time PCR; midkine (Mdk), immediate early response gene 3 (IEX-1), mitogen-inducible gene 6 (Mig6), and ubiquitin-specific protease 2 (USP2) were significantly increased in the kidneys of STZ/VCD compared with STZ mice. Western blot analysis confirmed that Mdk and IEX-1 protein abundance was significantly increased in the kidney cortex of STZ/VCD compared with STZ mice. In a separate study, DNA microarrays and CARMA analysis were used to identify the effect of menopause on the nondiabetic kidney; VCD-treated mice were compared with cycling mice. Of the possible 15,600 genes on the array, 9,142 genes were included in the ANOVA; 20 genes were identified as demonstrating a >1.5-fold up- or downregulation; histidine decarboxylase and vanin 1 were among the genes identified as differentially expressed in the postmenopausal nondiabetic kidney. These data expand our understanding of how hormone status correlates with the development of diabetic kidney disease and identify several target genes for further studies.