Literature DB >> 21126025

Quantitative analysis of the intra- and inter-individual variability of the normal urinary proteome.

Nagarjuna Nagaraj1, Matthias Mann.   

Abstract

Urine is a readily and noninvasively obtainable body fluid. Mass spectrometry (MS)-based proteomics has shown that urine contains thousands of proteins. Urine is a potential source of biomarkers for diseases of proximal and distal tissues but it is thought to be more variable than the more commonly used plasma. By LC-MS/MS analysis on an LTQ-Orbitrap without prefractionation we characterized the urinary proteome of seven normal human donors over three consecutive days. Label-free quantification of triplicate single runs covered the urinary proteome to a depth of more than 600 proteins. The median coefficient of variation (cv) of technical replicates was 0.18. Interday variability was markedly higher with a cv of 0.48 and the overall variation of the urinary proteome between individuals was 0.66. Thus technical variability in our data was 7.5%, whereas intrapersonal variability contributed 45.5% and interpersonal variability contributed 47.1% to total variability. Determination of the normal fluctuation of individual urinary proteins should be useful in establishing significance thresholds in biomarker studies. Our data also allowed definition of a common and abundant set of 500 proteins that were readily detectable in all studied individuals. This core urinary proteome has a high proportion of secreted, membrane, and relatively high-molecular weight proteins.

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Year:  2011        PMID: 21126025     DOI: 10.1021/pr100835s

Source DB:  PubMed          Journal:  J Proteome Res        ISSN: 1535-3893            Impact factor:   4.466


  88 in total

1.  Identification of glycoproteins containing specific glycans using a lectin-chemical method.

Authors:  Yan Li; Punit Shah; Angelo M De Marzo; Jennifer E Van Eyk; Qianqian Li; Daniel W Chan; Hui Zhang
Journal:  Anal Chem       Date:  2015-04-20       Impact factor: 6.986

2.  Comprehensive Analysis of Individual Variation in the Urinary Proteome Revealed Significant Gender Differences.

Authors:  Chen Shao; Mindi Zhao; Xizhao Chen; Haidan Sun; Yehong Yang; Xiaoping Xiao; Zhengguang Guo; Xiaoyan Liu; Yang Lv; Xiangmei Chen; Wei Sun; Di Wu; Youhe Gao
Journal:  Mol Cell Proteomics       Date:  2019-03-20       Impact factor: 5.911

3.  Stone former urine proteome demonstrates a cationic shift in protein distribution compared to normal.

Authors:  Ann M Kolbach-Mandel; Neil S Mandel; Brian R Hoffmann; Jack G Kleinman; Jeffrey A Wesson
Journal:  Urolithiasis       Date:  2017-03-17       Impact factor: 3.436

4.  Rapid verification of candidate serological biomarkers using gel-based, label-free multiple reaction monitoring.

Authors:  Hsin-Yao Tang; Lynn A Beer; Kurt T Barnhart; David W Speicher
Journal:  J Proteome Res       Date:  2011-07-26       Impact factor: 4.466

5.  Simple Tip-Based Sample Processing Method for Urinary Proteomic Analysis.

Authors:  David J Clark; Yingwei Hu; Michael Schnaubelt; Yi Fu; Sean Ponce; Shao-Yung Chen; Yangying Zhou; Punit Shah; Hui Zhang
Journal:  Anal Chem       Date:  2019-04-08       Impact factor: 6.986

6.  Urinary proteome analysis of irritable bowel syndrome (IBS) symptom subgroups.

Authors:  Young Ah Goo; Kevin Cain; Monica Jarrett; Lynne Smith; Joachim Voss; Ernie Tolentino; Joyce Tsuji; Yihsuan S Tsai; Alexandre Panchaud; David R Goodlett; Robert J Shulman; Margaret Heitkemper
Journal:  J Proteome Res       Date:  2012-10-26       Impact factor: 4.466

Review 7.  High-sensitivity analytical approaches for the structural characterization of glycoproteins.

Authors:  William R Alley; Benjamin F Mann; Milos V Novotny
Journal:  Chem Rev       Date:  2013-03-27       Impact factor: 60.622

Review 8.  Proteomic studies of urinary biomarkers for prostate, bladder and kidney cancers.

Authors:  Steven L Wood; Margaret A Knowles; Douglas Thompson; Peter J Selby; Rosamonde E Banks
Journal:  Nat Rev Urol       Date:  2013-02-26       Impact factor: 14.432

Review 9.  Current state of the art for enhancing urine biomarker discovery.

Authors:  Michael Harpole; Justin Davis; Virginia Espina
Journal:  Expert Rev Proteomics       Date:  2016-06       Impact factor: 3.940

10.  Sources of technical variability in quantitative LC-MS proteomics: human brain tissue sample analysis.

Authors:  Paul D Piehowski; Vladislav A Petyuk; Daniel J Orton; Fang Xie; Ronald J Moore; Manuel Ramirez-Restrepo; Anzhelika Engel; Andrew P Lieberman; Roger L Albin; David G Camp; Richard D Smith; Amanda J Myers
Journal:  J Proteome Res       Date:  2013-04-10       Impact factor: 4.466

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