Open AccessIntegrative analysis provides multi‐omics evidence for the pathogenesis of placenta percreta
Author(s) -
Jiang Qingyuan,
Dai Lei,
Chen Na,
Li Junshu,
Gao Yan,
Zhao Jing,
Ding Li,
Xie Chengbin,
Yi Xiaolian,
Deng Hongxin,
Wang Xiaodong
Publication year - 2020
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.15973
Subject(s) - biology , microrna , pathogenesis , gene , placenta percreta , computational biology , placenta , bioinformatics , genetics , pregnancy , immunology , fetus
Pernicious placenta previa with placenta percreta (PP) is a catastrophic condition during pregnancy. However, the underlying pathogenesis remains unclear. In the present study, the placental tissues of normal cases and PP tissues of pernicious placenta previa cases were collected to determine the expression profile of protein‐coding genes, miRNAs, and lncRNAs through sequencing. Weighted gene co‐expression network analysis (WGCNA), accompanied by miRNA target prediction and correlation analysis, were employed to select potential hub protein‐coding genes and lncRNAs. The expression levels of selected protein‐coding genes, Wnt5A and MAPK13 , were determined by quantitative PCR and immunohistochemical staining, and lncRNA PTCHD1‐AS and PAPPA‐AS1 expression levels were determined by quantitative PCR and fluorescence in situ hybridization. The results indicated that 790 protein‐coding genes, 382 miRNAs, and 541 lncRNAs were dysregulated in PP tissues, compared with normal tissues. WGCNA identified coding genes in the module (ME) black and ME turquoise modules that may be involved in the pathogenesis of PP. The selected potential hub protein‐coding genes, Wnt5A and MAPK13 , were down‐regulated in PP tissues, and their expression levels were positively correlated with the expression levels of PTCHD1‐AS and PAPPA‐AS1 . Further analysis demonstrated that PTCHD1‐AS and PAPPA‐AS1 regulated Wnt5A and MAPK13 expression by interacting with specific miRNAs. Collectively, our results provided multi‐omics data to better understand the pathogenesis of PP and help identify predictive biomarkers and therapeutic targets for PP.