Protein Network Analysis of Whole Exome Sequencing of Severe Preeclampsia.

Autor:	Schuster J; Pediatrics, Women and Infants Hospital, Providence, RI, United States.; Pediatrics, Warren Alpert Medical School, Brown University, Providence, RI, United States., Tollefson GA; Pediatrics, Women and Infants Hospital, Providence, RI, United States., Zarate V; Pediatrics, Women and Infants Hospital, Providence, RI, United States., Agudelo A; Pediatrics, Women and Infants Hospital, Providence, RI, United States., Stabila J; Pediatrics, Women and Infants Hospital, Providence, RI, United States., Ragavendran A; Center for Computation and Visualization, Brown University, Providence, RI, United States.; Computational Biology of Human Disease, Brown University, Providence, RI, United States., Padbury J; Pediatrics, Women and Infants Hospital, Providence, RI, United States.; Pediatrics, Warren Alpert Medical School, Brown University, Providence, RI, United States.; Center for Computational Molecular Biology, Brown University, Providence, RI, United States., Uzun A; Pediatrics, Women and Infants Hospital, Providence, RI, United States.; Pediatrics, Warren Alpert Medical School, Brown University, Providence, RI, United States.; Computational Biology of Human Disease, Brown University, Providence, RI, United States.; Center for Computational Molecular Biology, Brown University, Providence, RI, United States.
Jazyk:	angličtina
Zdroj:	Frontiers in genetics [Front Genet] 2022 Jun 02; Vol. 12, pp. 765985. Date of Electronic Publication: 2022 Jun 02 (Print Publication: 2021).
DOI:	10.3389/fgene.2021.765985
Abstrakt:	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. Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. (Copyright © 2022 Schuster, Tollefson, Zarate, Agudelo, Stabila, Ragavendran, Padbury and Uzun.)
Databáze:	MEDLINE
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