Research Abstracts Online
January - December 2011
University of Minnesota Twin Cities
PI: Michael Mauer
Microarray Studies of Skin Fibroblasts in Type I Diabetes Diabetic Nephropathy
Diabetic nephropathy (DN) is the leading cause of kidney failure and was responsible for 44% of all the new cases of kidney failure in the United States in 2001. These researchers are studying cultured skin fibroblast (SF) and renal proximal tubular epithelial cells (PTEC) from type 1 diabetic patients in order to better understand the differences in behavior of these in patients with and without DN. They are testing the hypothesis that there are inherent cellular differences between type 1 diabetic patients with or without DN and that these differences are genetically determined and are associated with altered gene expression.
There is accumulating evidence that genetic factors convey risk or protection from DN. The evidence is originally derived from observation of familial clustering of DN risk. However, the genes that may be involved in the pathogenesis of DN are unknown. One approach is to study cells in vitro, which, after several passages in tissue culture, can be assumed to better reflect intrinsic rather than environmental factors. This group’s goal is to use microarray techniques to test for gene expression differences in total RNA isolated from SF from Type 1 D patients that have been structurally and functionally polarized into two groups: one a “fast-track” group (high risk of DN) and one a “slow-track” group (low risk of DN). There is accumulating evidence that epigenetic factors may also convey risk or protection from DN. To address this, this group is studying cultured cells from identical twins discordant for Type 1 D. Since they are genetically identical, differences in cell behavior can be attributed to epigenetic mechanisms and genome wide gene expression, DNA methylation and microRNA studies are being carried out and histone modification studies are planned. The group uses Galaxy and other software resources available through MSI to analyze their data.
Luiza Caramori, Faculty Collaborator
Youngki Kim, Faculty Collaborator
Jhuma Saha, Research Associate
Paul Walker, Research Associate