Antigen Analysis of Pre-Eclamptic Plasma Antibodies Using Escherichia Coli Proteome Chips

利用大肠杆菌蛋白质组芯片对先兆子痫血浆抗体进行抗原分析

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Abstract

Pre-eclampsia is one of the main causes of perinatal mortality and morbidity. Many biomarkers for diagnosing pre-eclampsia have been found but most have low accuracy. Therefore, a potential marker that can detect pre-eclampsia with high accuracy is required. Infection has been reported as a cause of pre-eclampsia. In recent years, protein microarray chips have been recognized as a strong and robust tool for profiling antibodies for infection diagnoses. The purpose of the present study was to profile antibodies in the human plasma of healthy and pre-eclamptic pregnancies to identify suitable biomarkers. In this study, an Escherichia coli chip was probed with samples from 29 individuals (16 pre-eclamptic women and 13 healthy pregnant women) to profile plasma antibodies. Bioinformatics tools were used to analyze the results, discover conserved motifs, compare against the entire human proteome, and perform protein functional analysis. An antibody classifier was identified using k-top scoring pairs and additional samples for a blinded test were collected. The findings indicated that compared with the healthy women, the pre-eclamptic women exhibited 108 and 130 differentially immunogenic proteins against human immunoglobulins G and M, respectively. In addition, pre-eclamptic women developed more immunoglobulin G but less immunoglobulin M against bacterial surface proteins compared with healthy women. The k-top scoring pairs identified five pairs of immunogenic proteins as classifiers with a high accuracy of 90% in the blind test. [AG] [ISV] GV [AE] L [LF] and [IV] [IV] RI [AG] [AD] E were the consensus motifs observed in immunogenic proteins in the immunoglobulin G and immunoglobulin M of pre-eclamptic women, respectively, whereas GA [AG] [AL] L [LF] and [SRY] [IQML] [ILV] [ILV] [ACG] GI [GH] [AEF] [AK] [ATY] [RG] N [IV] were observed in the immunoglobulins G and immunoglobulin M of healthy women, respectively.

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