Defining human diabetic nephropathy on the molecular level: integration of transcriptomic profiles with biological knowledge

Abstract

Diabetic nephropathy (DN) is the most common cause for end stage renal disease (ESRD). Next to environmental factors, genetic predispositions determine the susceptibility for DN and its rate of progression to ESRD. With the availability of genome wide expression profiling we have the opportunity to define relevant pathways activated in the individual diabetic patient, integrating both environmental exposure and genetic background. In this review we summarize current understanding of how to link comprehensive gene expression data sets with biomedical knowledge and present strategies to build a transcriptional network of DN. Information about the individual disease processes of DN might allow the implementation of a personalized molecular medicine approach with mechanism-based patient management. Web based search engines like Nephromine are essential tools to facilitate access to molecular data of genomics, proteomics and metabolomics of DN.

Figure 1

Progression of renal diseases over time indicating time points for detection of the disease and treatment initiation.

Figure 2

Strategy used to define human transcriptional networks and their confirmation by functional analysis: bioinformatic approaches for gene expression data are able to define common regulatory mechanisms in DN in a stepwise approach. First, differentially regulated genes are assigned, which are then mapped to known and de-novo generated pathways. Their transcriptional control can be confirmed by a qRT-PCR of identified downstream targets and their function can be studied in (cell-type specific) transgenic mouse models.