AUTHOR=Schuster Jessica , Tollefson George A. , Zarate Valeria , Agudelo Anthony , Stabila Joan , Ragavendran Ashok , Padbury James , Uzun Alper TITLE=Protein Network Analysis of Whole Exome Sequencing of Severe Preeclampsia JOURNAL=Frontiers in Genetics VOLUME=12 YEAR=2022 URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.765985 DOI=10.3389/fgene.2021.765985 ISSN=1664-8021 ABSTRACT=

Preeclampsia is a hypertensive disorder of pregnancy, which complicates up to 15% of US deliveries. It is an idiopathic disorder associated with several different phenotypes. We sought to determine if the genetic architecture of preeclampsia can be described by clusters of patients with variants in genes in shared protein interaction networks. We performed a case-control study using whole exome sequencing on early onset preeclamptic mothers with severe clinical features and control mothers with uncomplicated pregnancies between 2016 and 2020. A total of 143 patients were enrolled, 61 women with early onset preeclampsia with severe features based on ACOG criteria, and 82 control women at term, matched for race and ethnicity. A network analysis and visualization tool, Proteinarium, was used to confirm there are clusters of patients with shared gene networks associated with severe preeclampsia. The majority of the sequenced patients appear in two significant clusters. We identified one case dominant and one control dominant cluster. Thirteen genes were unique to the case dominated cluster. Among these genes, LAMB2, PTK2, RAC1, QSOX1, FN1, and VCAM1 have known associations with the pathogenic mechanisms of preeclampsia. Using bioinformatic analysis, we were able to identify subsets of patients with shared protein interaction networks, thus confirming our hypothesis about the genetic architecture of preeclampsia.