Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis
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Improved elucidation of biological processes linked to diabetic nephropathy by single probe-based microarray data analysis. / Cohen, Clemens D; Lindenmeyer, Maja T; Eichinger, Felix; Hahn, Alexander; Seifert, Martin; Moll, Anton G; Schmid, Holger; Kiss, Eva; Gröne, Elisabeth; Gröne, Hermann-Josef; Kretzler, Matthias; Werner, Thomas; Nelson, Peter J.
in: PLOS ONE, Jahrgang 3, Nr. 8, 13.08.2008, S. e2937.Publikationen: SCORING: Beitrag in Fachzeitschrift/Zeitung › SCORING: Zeitschriftenaufsatz › Forschung › Begutachtung
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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probe signals, as this includes signals from cross-hybridizing probes and gene annotation that is based on out of date genomic data.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 -