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Protein sets define disease states and predict in vivo effects of drug treatment

Item Type:Article
Title:Protein sets define disease states and predict in vivo effects of drug treatment
Creators Name:Meierhofer, D. and Weidner, C. and Hartmann, L. and Mayr, J.A. and Han, C.T. and Schroeder, F.C. and Sauer, S.
Abstract:Gaining understanding of common complex diseases and their treatments are the main drivers for life sciences. As we show here, comprehensive protein set analyses offer new opportunities to decipher functional molecular networks of diseases and assess the efficacy and side-effects of treatments in vivo. Using mass spectrometry, we quantitatively detected several thousands of proteins and observed significant changes in protein pathways that were (dys-) regulated in diet-induced obesity mice. Analysis of the expression and post-translational modifications of proteins in various peripheral metabolic target tissues including adipose, heart, and liver tissue generated functional insights in the regulation of cell and tissue homeostasis during high-fat diet feeding and medication with two antidiabetic compounds. Protein set analyses singled out pathways for functional characterization, and indicated, for example, early-on potential cardiovascular complication of the diabetes drug rosiglitazone. In vivo protein set detection can provide new avenues for monitoring complex disease processes, and for evaluating preclinical drug candidates.
Keywords:High-Fat Diet, Hypoglycemic Agents, Inbred C57BL Mice, Liver, Myocardium, Obesity, Post-Translational Protein Processing, PPAR gamma, Proteomics, Salicylates, Thiazolidinediones, White Adipose Tissue, Animals, Mice
Source:Molecular & Cellular Proteomics
ISSN:1535-9476
Publisher:American Society for Biochemistry and Molecular Biology (U.S.A.)
Volume:12
Number:7
Page Range:1965-1979
Date:1 July 2013
Official Publication:https://doi.org/10.1074/mcp.M112.025031
PubMed:View item in PubMed

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