Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis

TY - JOUR

T1 - Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis

AU - Cohen, Clemens D

AU - Lindenmeyer, Maja T

AU - Eichinger, Felix

AU - Hahn, Alexander

AU - Seifert, Martin

AU - Moll, Anton G

AU - Schmid, Holger

AU - Kiss, Eva

AU - Gröne, Elisabeth

AU - Gröne, Hermann-Josef

AU - Kretzler, Matthias

AU - Werner, Thomas

AU - Nelson, Peter J

PY - 2008/8/13

Y1 - 2008/8/13

N2 - 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.METHODOLOGY/PRINCIPAL FINDINGS: 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probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data.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/SIGNIFICANCE: 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.

AB - 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.METHODOLOGY/PRINCIPAL FINDINGS: 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/SIGNIFICANCE: 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.

KW - Antigens, CD

KW - Antigens, Differentiation, Myelomonocytic

KW - DNA Probes

KW - Diabetic Nephropathies

KW - Disease Progression

KW - Extracellular Matrix Proteins

KW - Humans

KW - Neoplasm Proteins

KW - Oligonucleotide Array Sequence Analysis

KW - Polymorphism, Single Nucleotide

KW - Sensitivity and Specificity

KW - Suppressor of Cytokine Signaling Proteins

KW - Vascular Endothelial Growth Factor A

KW - Journal Article

KW - Research Support, Non-U.S. Gov't

U2 - 10.1371/journal.pone.0002937

DO - 10.1371/journal.pone.0002937

M3 - SCORING: Journal article

C2 - 18698414

VL - 3

SP - e2937

JO - PLOS ONE

JF - PLOS ONE

SN - 1932-6203

IS - 8

ER -