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

Meierhofer, David; Weidner, Christopher; Hartmann, Ludger; Mayr, Johannes A.; Han, Chung-Ting; Schroeder, Frank C.; Sauer, Sascha

doi:10.1074/mcp.M112.025031

アイテム詳細

登録内容を編集ファイル形式で保存

一時保存へ追加

タグ情報を表示リリース履歴を表示詳細要約

公開

学術論文

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

MPS-Authors

/persons/resource/persons50427

Meierhofer, David
Mass Spectrometry (Head: David Meierhofer), Scientific Service (Head: Christoph Krukenkamp), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50629

Weidner, Christopher
Nutrigenomics and Gene Regulation (Sascha Sauer), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50193

Hartmann, Ludger
Animal Unit (Head: Ludger Hartmann), Scientific Service (Head: Manuela B. Urban), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50191

Han, Chung-Ting
Nutrigenomics and Gene Regulation (Sascha Sauer), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

/persons/resource/persons50512

Sauer, Sascha
Nutrigenomics and Gene Regulation (Sascha Sauer), Independent Junior Research Groups (OWL), Max Planck Institute for Molecular Genetics, Max Planck Society;

External Resource

There are no locators available

Fulltext (restricted access)

There are currently no full texts shared for your IP range.

フルテキスト (公開)

Meierhofer.pdf
(出版社版), 5MB

付随資料 (公開)

There is no public supplementary material available

引用

Meierhofer, D., Weidner, C., Hartmann, L., Mayr, J. A., Han, C.-T., Schroeder, F. C., & Sauer, S. (2013). Protein sets define disease states and predict in vivo effects of drug treatment. Molecular and Cellular Proteomics, 12(7), 1965-1979. doi:10.1074/mcp.M112.025031.

引用: https://hdl.handle.net/11858/00-001M-0000-0019-10F8-C

要旨

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 thousand proteins and observed significant changes in protein pathway (dys-) regulated in diet-induced obesity mice. Analysis of the expression and posttranslational 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 and medication with two anti-diabetic 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.