Clinical and laboratory characteristics according to retinopathy status.

<p>Values represent mean (SE)</p><p>^a For p value comparison according to retinopathy status (four groups, non-parametric test, Wilcoxon's test, adjusted for multiple comparisons according to Holm)</p><p>^b Alone or in combination</p><p>Clinical and laboratory characteristics according to retinopathy status.</p

Kaplan-Meier analysis relating time to retinopathy (any versus severe versus DME) to duration of diabetes (individual survival curves are labeled).

<p>Kaplan-Meier analysis relating time to retinopathy (any versus severe versus DME) to duration of diabetes (individual survival curves are labeled).</p

The role of insulin resistance in experimental diabetic retinopathy—Genetic and molecular aspects

<div><p>Background</p><p>Diabetic retinopathy is characterized by defects in the retinal neurovascular unit. The underlying mechanisms of impairment–including reactive intermediates and growth-factor dependent signalling pathways and their possible interplay are incompletely understood. This study aims to assess the relative role of hyperglycemia and hyperinsulinemia alone or in combination on the gene expression patterning in the retina of animal models of diabetes.</p><p>Material and methods</p><p>As insulinopenic, hyperglycemic model reflecting type 1 diabetes, male STZ-Wistar rats (60mg/kg BW; i.p. injection at life age week 7) were used. Male obese ZDF rats (fa/fa) were used as type-2 diabetes model characterized by persisting hyperglycemia and transient hyperinsulinemia. Male obese ZF rats (fa/fa) were used reflecting euglycemia and severe insulin resistance. All groups were kept till an age of 20 weeks on respective conditions together with appropriate age-matched controls. Unbiased gene expression analysis was performed per group using Affymetrix gene arrays. Bioinformatics analysis included analysis for clustering and differential gene expression, and pathway and upstream activator analysis. Gene expression differences were confirmed by microfluidic card PCR technology.</p><p>Results</p><p>The most complex genetic regulation in the retina was observed in ZDF rats with a strong overlap to STZ-Wistar rats. Surprisingly, systemic insulin resistance alone in ZF rats without concomitant hyperglycemia did not induce any significant change in retinal gene expression pattern. Pathway analysis indicate an overlap between ZDF rats and STZ-treated rats in pathways like complement system activation, acute phase response signalling, and oncostatin-M signalling. Major array gene expression changes could be confirmed by subsequent PCR. An analysis of upstream transcriptional regulators revealed interferon-γ, interleukin-6 and oncostatin-M in STZ and ZDF rats. CONCLUSIONS: Systemic hyperinsulinaemia without hyperglycemia does not result in significant gene expression changes in retina. In contrast, persistent systemic hyperglycemia boosts much stronger expression changes with a limited number of known and new key regulators.</p></div

Multiple logistic regression analysis, any retinopathy.

<p>Multiple logistic regression analysis, any retinopathy.</p

Multiple regression analysis, macula edema.

<p>Multiple regression analysis, macula edema.</p

Multiple regression analysis, severe retinopathy.

<p>Multiple regression analysis, severe retinopathy.</p

Gene array expression in retina.

<p><b>A</b>, Principal Component Analysis on raw expression data showing the first two principal components; <b>B</b>, Venn diagram of overlap in regulated gene number between the three different animal models.</p

Plasma biomarkers and metabolites at the end of the study.

<p>Shown are mean ± SD values obtained at fasting stage at the end of study.</p

Comparison of microarray gene expression with confirmatory realtime PCR.

<p>From the initial micro array 49 differentially regulated genes were selected for further confirmation by real-time PCR and normalized in the PCR to the mean of three reference genes (18s, actb, gapdh). Genes were initially selected to cover a full range from highly up-regulated (positive fc values) to down-regulated (negative fc values) genes observed between ZDF obese and lean rats. Shown are fold changes (fc) and probabilities corrected for multiple testing by a Benjamini-Hochberg false discovery rate (FDR) methodology (p(FDR)).</p

Top upstream regulators predict to explain the gene expression differences in retina between obese and lean ZDF rats or STZ treatet and non-teated Wistar rats.

<p>Molecules are sorted by the modulation z-score in ZDF rats.</p