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Reliable pre-eclampsia pathways based on multiple independent microarray data sets
Author(s) -
Kaoru Kawasaki,
Eiji Kondoh,
Yoshitsugu Chigusa,
Mari Ujita,
Ryusuke Murakami,
Haruta Mogami,
J.B. Brown,
Yasushi Okuno,
Ikuo Konishi
Publication year - 2014
Publication title -
molecular human reproduction
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.143
H-Index - 122
eISSN - 1460-2407
pISSN - 1360-9947
DOI - 10.1093/molehr/gau096
Subject(s) - biology , eclampsia , microarray analysis techniques , microarray , gene expression profiling , gene expression , computational biology , biological pathway , gene , bioinformatics , genetics , pregnancy
Pre-eclampsia is a multifactorial disorder characterized by heterogeneous clinical manifestations. Gene expression profiling of preeclamptic placenta have provided different and even opposite results, partly due to data compromised by various experimental artefacts. Here we aimed to identify reliable pre-eclampsia-specific pathways using multiple independent microarray data sets. Gene expression data of control and preeclamptic placentas were obtained from Gene Expression Omnibus. Single-sample gene-set enrichment analysis was performed to generate gene-set activation scores of 9707 pathways obtained from the Molecular Signatures Database. Candidate pathways were identified by t-test-based screening using data sets, GSE10588, GSE14722 and GSE25906. Additionally, recursive feature elimination was applied to arrive at a further reduced set of pathways. To assess the validity of the pre-eclampsia pathways, a statistically-validated protocol was executed using five data sets including two independent other validation data sets, GSE30186, GSE44711. Quantitative real-time PCR was performed for genes in a panel of potential pre-eclampsia pathways using placentas of 20 women with normal or severe preeclamptic singleton pregnancies (n = 10, respectively). A panel of ten pathways were found to discriminate women with pre-eclampsia from controls with high accuracy. Among these were pathways not previously associated with pre-eclampsia, such as the GABA receptor pathway, as well as pathways that have already been linked to pre-eclampsia, such as the glutathione and CDKN1C pathways. mRNA expression of GABRA3 (GABA receptor pathway), GCLC and GCLM (glutathione metabolic pathway), and CDKN1C was significantly reduced in the preeclamptic placentas. In conclusion, ten accurate and reliable pre-eclampsia pathways were identified based on multiple independent microarray data sets. A pathway-based classification may be a worthwhile approach to elucidate the pathogenesis of pre-eclampsia.

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