Open AccessIsobaric tag for relative and absolute quantitation based quantitative proteomics reveals unique urinary protein profiles in patients with preeclampsia
Author(s) -
Ding Wenyan,
Qiu Bintao,
Cram David S.,
Chen Xiuting,
Li Shengjie,
Zhou Xiya,
Liu Juntao,
Wu Zhihong,
Song Yijun
Publication year - 2019
Publication title -
journal of cellular and molecular medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.44
H-Index - 130
eISSN - 1582-4934
pISSN - 1582-1838
DOI - 10.1111/jcmm.14459
Subject(s) - kegg , proteomics , preeclampsia , pathogenesis , hemopexin , proteome , urinary system , bioinformatics , biology , computational biology , medicine , gene ontology , pregnancy , gene , genetics , gene expression , biochemistry , heme , enzyme
Abstract Preeclampsia (PE) is one of the most significant pregnancy‐related hypertensive disorders. Currently, there are no useful markers to predict the onset of the condition in pregnant women. To provide further insights into the pathogenesis of PE and identify biomarkers of the condition, we used isobaric tags for relative and absolute quantitation (iTRAQ) proteomics coupled with 2‐D LC‐MS/MS, to analyze urinary protein profiles from 7 PE patients and 7 normotensive pregnant women. A total of 294 proteins were abnormally expressed in PE patients. Of these, 233 were significantly down‐regulated and 61 proteins were significantly up‐regulated. Bioinformatics analysis using the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) database, found that the most differentially expressed proteins (DEPs) were involved in coagulation and complement pathways, the renin‐angiotensin system and cell adhesion molecules (CAMs) pathways. We further validated three of the DEPs, including serotransferrin (TF) and complement factor B (CFB) by immunoblottingand serum paraoxonase/arylesterase 1 (PON1) by ELISA using 14 pairs of urine samples from PE patients and normal pregnant women. Taken together, our results provide the basis for further understanding the pathogenesis of PE and identifying predictive biomarkers.