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Peptidomic Identification of Serum Peptides Diagnosing Preeclampsia

Overview of attention for article published in PLOS ONE, June 2013
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Title
Peptidomic Identification of Serum Peptides Diagnosing Preeclampsia
Published in
PLOS ONE, June 2013
DOI 10.1371/journal.pone.0065571
Pubmed ID
Authors

Qiaojun Wen, Linda Y. Liu, Ting Yang, Cantas Alev, Shuaibin Wu, David K. Stevenson, Guojun Sheng, Atul J. Butte, Xuefeng B. Ling

Abstract

We sought to identify serological markers capable of diagnosing preeclampsia (PE). We performed serum peptide analysis (liquid chromatography mass spectrometry) of 62 unique samples from 31 PE patients and 31 healthy pregnant controls, with two-thirds used as a training set and the other third as a testing set. Differential serum peptide profiling identified 52 significant serum peptides, and a 19-peptide panel collectively discriminating PE in training sets (n = 21 PE, n = 21 control; specificity = 85.7% and sensitivity = 100%) and testing sets (n = 10 PE, n = 10 control; specificity = 80% and sensitivity = 100%). The panel peptides were derived from 6 different protein precursors: 13 from fibrinogen alpha (FGA), 1 from alpha-1-antitrypsin (A1AT), 1 from apolipoprotein L1 (APO-L1), 1 from inter-alpha-trypsin inhibitor heavy chain H4 (ITIH4), 2 from kininogen-1 (KNG1), and 1 from thymosin beta-4 (TMSB4). We concluded that serum peptides can accurately discriminate active PE. Measurement of a 19-peptide panel could be performed quickly and in a quantitative mass spectrometric platform available in clinical laboratories. This serum peptide panel quantification could provide clinical utility in predicting PE or differential diagnosis of PE from confounding chronic hypertension.

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Geographical breakdown

Country Count As %
Unknown 54 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 18 33%
Student > Master 6 11%
Student > Ph. D. Student 3 6%
Student > Postgraduate 3 6%
Professor > Associate Professor 3 6%
Other 6 11%
Unknown 15 28%
Readers by discipline Count As %
Medicine and Dentistry 14 26%
Agricultural and Biological Sciences 11 20%
Biochemistry, Genetics and Molecular Biology 3 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 4%
Psychology 2 4%
Other 4 7%
Unknown 18 33%