Research Article

Dissecting the human plasma proteome and inflammatory response biomarkers

  1. Sudipto Saha1,3,
  2. Scott H. Harrison1,3,
  3. Jake Yue Chen Professor1,2,3,*

Article first published online: 22 DEC 2008

DOI: 10.1002/pmic.200800507

Issue

PROTEOMICS

PROTEOMICS

Volume 9, Issue 2, pages 470–484, No. 2 January 2009

Additional Information

How to Cite

Saha, S., Harrison, S. H. and Chen, J. Y. (2009), Dissecting the human plasma proteome and inflammatory response biomarkers. Proteomics, 9: 470–484. doi: 10.1002/pmic.200800507

Author Information

  1. 1

    School of Informatics, Indiana University – Purdue University, Indianapolis, IN, USA

  2. 2

    Department of Computer & Information Science, Purdue University, Indianapolis, IN, USA

  3. 3

    Indiana Center for Systems Biology and Personalized Medicine, Indianapolis, IN, USA

*School of Informatics, Indiana University – Purdue University, 719 N Indiana Ave, WK Suite 190, Indianapolis, IN 46202-3103, USA Fax: +1-319-9374158

Publication History

  1. Issue published online: 13 JAN 2009
  2. Article first published online: 22 DEC 2008
  3. Manuscript Received: 16 JUN 2008

Funded by

  • National Cancer Institute. Grant Number: U24CA126480-01

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Keywords:

  • Biomarkers;
  • Drug targets;
  • Inflammatory response;
  • Mass spectrometry;
  • Plasma proteome

Abstract

A central focus of clinical proteomics is to search for biomarkers in plasma for diagnostic and therapeutic use. We studied a set of plasma proteins accessed from the Healthy Human Individual's Integrated Plasma Proteome (HIP2) database, a larger set of curated human proteins, and a subset of inflammatory proteins, for overlap with sets of known protein biomarkers, drug targets, and secreted proteins. Most inflammatory proteins were found to occur in plasma, and over three times the level of biomarkers were found in inflammatory plasma proteins and their interacting protein neighbors compared to the sets of plasma and curated human proteins. Percentage overlaps with Gene Ontology terms were similar between the curated human set and plasma protein set, yet the set of inflammatory plasma proteins had a distinct ontology-based profile. Most of the major hub proteins within protein-protein interaction networks of tissue-specific sets of inflammatory proteins were found to occur in disease pathways. The present study presents a systematic approach for profiling a plasma subproteome's relationship to both its potential range of clinical application and its overlap with complex disease.

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