Abstract
AbstractPreeclampsia is a hypertensive disorder of pregnancy, which complicates up to 15 % of US deliveries. It is an idiopathic disorder with complex disease genetics 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 features and control mothers with uncomplicated pregnancies. The study was conducted at Women & Infants Hospital of Rhode Island (WIH). 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. The main outcomes are variants associated with severe preeclampsia and demonstration of the genetic architecture of preeclampsia. 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 the exome-wide sequence variants, combined with these 13 identified network genes, we generated a polygenetic risk score for severe preeclampsia with an AUC of 0.57. 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. The unique genes identified in the cluster associated with severe preeclampsia were able to increase the predictive power of the polygenic risk score.
Publisher
Cold Spring Harbor Laboratory