Identification of the Key Pathways and Genes in Hypoxia Pulmonary Arterial Hypertension Following Intrauterine Growth Retardation

Weifen Zhu; Ziming Zhang; Weiwei Gui; Zheng Shen; Yixin Chen; Xueyao Yin; Li Liang; Lin Li

doi:10.3389/fmolb.2022.789736

Identification of the Key Pathways and Genes in Hypoxia Pulmonary Arterial Hypertension Following Intrauterine Growth Retardation

Front Mol Biosci. 2022 Mar 31:9:789736. doi: 10.3389/fmolb.2022.789736. eCollection 2022.

Authors

Weifen Zhu¹, Ziming Zhang², Weiwei Gui¹, Zheng Shen³, Yixin Chen¹, Xueyao Yin¹, Li Liang⁴, Lin Li¹

Affiliations

¹ Department of Endocrinology, The Affiliated Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, China.
² Department of Neonatology, Children's Hospital of Zhejiang University School of Medicine, Hangzhou, China.
³ Department of Central Laboratory, Children's Hospital of Zhejiang University School of Medicine, Hangzhou, China.
⁴ Department of Pediatrics, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China.

Abstract

High-throughput sequencing and weighted gene co-expression network analysis (WGCNA) were used to identify susceptibility modules and genes in liver tissue for the hypoxic pulmonary arterial hypertension (PAH) animal model following intrauterine growth retardation (IUGR). A total of 5,000 genes were clustered into eight co-expression modules via WGCNA. Module blue was mostly significantly correlated with the IUGR-hypoxia group. Gene Ontology analysis showed that genes in the module blue were mainly enriched in the fatty acid metabolic process, lipid modification, and fatty acid catabolic process. The Kyoto Encyclopedia of Genes and Genomes enrichment analyses showed that the genes in module blue were mainly associated with fatty acid metabolism, PPAR signaling pathway, and biosynthesis of unsaturated fatty acids. In addition, the maximal clique centrality method was used to identify the hub genes in the subnetworks, and the obtained results were verified using real-time quantitative PCR. Finally, we identified that four genes including Cyp2f4, Lipc, Acadl, and Hacl1 were significantly associated with IUGR-hypoxia. Our study identified a module and several key genes that acted as essential components in the etiology of the long-term metabolic consequences in hypoxia PAH following IUGR.

Keywords: hypoxia; intrauterine growth retardation; metabolic dysfunction; pulmonary arterial hypertension; weighted gene co-expression network analysis.