Urinary Protein Profiles in a Rat Model for Diabetic Complications

Sep. 24, 2009

Diabetes mellitus (DM) is estimated to affect approximately 24 million people in the US and more than 150 million people worldwide. There are numerous end organ complications of diabetes, the onset of which can be delayed by early diagnosis and treatment. Although assays for diabetes are well founded, tests for its complications lack sufficient specificity and sensitivity to adequately guide these treatment options. In our study, we employed a streptozotocin (STZ) induced rat model of diabetes to determine changes in urinary protein profiles that occur during the initial response to the attendant hyperglycemia (e.g. the first two months) with the goal of developing a reliable and reproducible method of analyzing multiple urine samples as well as providing clues to early markers of disease progression. After filtration and buffer exchange, urinary proteins were digested with a specific protease and the relative amounts of several thousand peptides were compared across rat urine samples representing various times after administration of drug or sham control. Extensive data analysis, including imputation of missing values and normalization of all data was followed by ANOVA analysis to discover peptides that were significantly changing as a function of time, treatment and interaction of the two variables. The data demonstrated significant differences in protein abundance in urine before observable patho-physiological changes occur in this animal model and as function of the measured variables. These included decreases in relative abundance of major urinary protein precursor and increases in pro-alpha-collagen (2) 1 whose expression is known to be regulated by circulating levels of insulin and/or glucose. Peptides from these proteins represent potential biomarkers which can be used to stage uro-genital complications from diabetes. The expression changes of a pro-alpha (2) 1 collagen peptide was also confirmed via selected reaction monitoring. This analysis has demonstrated significant differences in protein abundance in urine before observable patho-physiological changes occur in this animal model. In addition, the techniques developed have been easily translated to human analyses to direct additional discovery efforts in human samples for diabetic complications.

Figure 1.

Volcano plots of treatment effect at 1 month (A) and 2 months (B) post STZ treatment. The t-test volcano plots arrange peptides by statistical significance. The most significant peptides are those found by ANOVA (highlighted in red (up) and green (down)) and distributed in the top right or left of the plots.

Figure 2. Box plots of illustrating abundance of pro alpha (2) 1 collagen peptide GEPGSVGAQGPPGPSGEEGK in targeted SRM analysis (A) and label free expression analysis (B). Maximum value with a treatment group is represented by blue box, median value for a treatment group by red box and minimum value for a treatment group by green.

Results from: Schlatzer, D.M., Dazard, J-E., Dharsee, M., Ewing, R.M., Ilchenko, S., Stewart, I., Christ, G., Chance, M.R. Urinary protein profiles in a rat model for diabetic complications, Mol Cell Proteomics, 2009.