Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis.
BACKGROUND
Diabetic nephropathy (DN) is a complex and chronic metabolic disease that evolves into a progressive fibrosing renal disorder. Effective transcriptomic profiling of slowly evolving disease processes such as DN can be problematic. The changes that occur are often subtle and can escape detection by conventional oligonucleotide DNA array analyses.


RESULTS
We examined microdissected human renal tissue with or without DN using Affymetrix oligonucleotide microarrays (HG-U133A) by standard Robust Multi-array Analysis (RMA). Subsequent gene ontology analysis by Database for Annotation, Visualization and Integrated Discovery (DAVID) showed limited detection of biological processes previously identified as central mechanisms in the development of DN (e.g. inflammation and angiogenesis). This apparent lack of sensitivity may be associated with the gene-oriented averaging of oligonucleotide probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data. We then examined the same CEL file data using a different methodology to determine how well it could correlate transcriptomic data with observed biology. ChipInspector (CI) is based on single probe analysis and de novo gene annotation that bypasses probe set definitions. Both methods, RMA and CI, used at default settings yielded comparable numbers of differentially regulated genes. However, when verified by RT-PCR, the single probe based analysis demonstrated reduced background noise with enhanced sensitivity and fewer false positives.


CONCLUSIONS
Using a single probe based analysis approach with de novo gene annotation allowed an improved representation of the biological processes linked to the development and progression of DN. The improved analysis was exemplified by the detection of Wnt signaling pathway activation in DN, a process not previously reported to be involved in this disease.
Cohen
Clemens D
CD
Nephrology Clinic and Institute of Physiology with Center of Integrative Human Physiology, University Hospital and University, Zurich, Switzerland.
Lindenmeyer
Maja T
MT
Eichinger
Felix
F
Hahn
Alexander
A
Seifert
Martin
M
Moll
Anton G
AG
Schmid
Holger
H
Kiss
Eva
E
Gröne
Elisabeth
E
Gröne
Hermann-Josef
HJ
Kretzler
Matthias
M
Werner
Thomas
T
Nelson
Peter J
PJ
D015703:Antigens, CD / Q000235:genetics; D015214:Antigens, Differentiation, Myelomonocytic / Q000235:genetics; D015342:DNA Probes; D003928:Diabetic Nephropathies / Q000235:genetics*; D018450:Disease Progression; D016326:Extracellular Matrix Proteins / Q000235:genetics; D006801:Humans; D009363:Neoplasm Proteins / Q000235:genetics; D020411:Oligonucleotide Array Sequence Analysis; D020641:Polymorphism, Single Nucleotide; D012680:Sensitivity and Specificity; D050826:Suppressor of Cytokine Signaling Proteins / Q000235:genetics; D042461:Vascular Endothelial Growth Factor A / Q000235:genetics; D000097382:CD68 Molecule
D015703:Antigens, CD; D015214:Antigens, Differentiation, Myelomonocytic; D015342:DNA Probes; D016326:Extracellular Matrix Proteins; D009363:Neoplasm Proteins; D050826:Suppressor of Cytokine Signaling Proteins; D042461:Vascular Endothelial Growth Factor A; C067980:CD68 antigen, human; D000097382:CD68 Molecule; C106643:SOCS2 protein, human; C122166:SPON2 protein, human