title: Proteomics and systems biology for understanding diabetic nephropathy.
abstract: 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.
authors.affiliation: Department of Internal Medicine, University of Texas Medical Branch, Galveston, TX 77555-1060, USA.
authors.forename: Jonathan M
authors.initials: JM
authors.lastname: Starkey
authors.forename: Ronald G
authors.initials: RG
authors.lastname: Tilton
mesh_terms: D000818:Animals; D015415:Biomarkers / Q000032:analysis; D003928:Diabetic Nephropathies / Q000175:diagnosis / Q000378:metabolism* / Q000503:physiopathology / Q000628:therapy; D006801:Humans; D007668:Kidney / Q000378:metabolism* / Q000503:physiopathology; D010641:Phenotype; D011379:Prognosis; D011506:Proteins / Q000032:analysis*; D040901:Proteomics / Q000379:methods; D049490:Systems Biology; D057170:Translational Research, Biomedical
chemical_list: D015415:Biomarkers; D011506:Proteins