TY - JOUR
T1 - Proteomics and systems biology for understanding diabetic nephropathy
AU - Starkey, Jonathan M.
AU - Tilton, Ronald G.
N1 - Funding Information:
Acknowledgments Work in our laboratory was supported by the Juvenile Diabetes Research Foundation, International (JDRF) grant award #1-2008-202 and grant Award 39-2009-643.
PY - 2012/8
Y1 - 2012/8
N2 - Like many diseases, diabetic nephropathy is defined in a histopathological context and studied using reductionist approaches that attempt to ameliorate structural changes. Novel technologies in mass spectrometry-based proteomics have the ability to provide a deeper understanding of the disease beyond classical histopathology, redefine the characteristics of the disease state, and identify novel approaches to reduce renal failure. The goal is to translate these new definitions into improved patient outcomes through diagnostic, prognostic, and therapeutic tools. Here, we review progress made in studying the proteomics of diabetic nephropathy and provide an introduction to the informatics tools used in the analysis of systems biology data, while pointing out statistical issues for consideration. Novel bioinformatics methods may increase biomarker identification, and other tools, including selective reaction monitoring, may hasten clinical validation.
AB - Like many diseases, diabetic nephropathy is defined in a histopathological context and studied using reductionist approaches that attempt to ameliorate structural changes. Novel technologies in mass spectrometry-based proteomics have the ability to provide a deeper understanding of the disease beyond classical histopathology, redefine the characteristics of the disease state, and identify novel approaches to reduce renal failure. The goal is to translate these new definitions into improved patient outcomes through diagnostic, prognostic, and therapeutic tools. Here, we review progress made in studying the proteomics of diabetic nephropathy and provide an introduction to the informatics tools used in the analysis of systems biology data, while pointing out statistical issues for consideration. Novel bioinformatics methods may increase biomarker identification, and other tools, including selective reaction monitoring, may hasten clinical validation.
KW - Bioinformatics
KW - Diabetes
KW - Diabetic nephropathy
KW - Mass spectrometry
KW - Proteomics
KW - Sytems biology
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U2 - 10.1007/s12265-012-9372-9
DO - 10.1007/s12265-012-9372-9
M3 - Article
C2 - 22581264
AN - SCOPUS:84866062801
SN - 1937-5387
VL - 5
SP - 479
EP - 490
JO - Journal of Cardiovascular Translational Research
JF - Journal of Cardiovascular Translational Research
IS - 4
ER -