Identifying and Enriching Disease-Specific Ignoromes

Preeclampsia is a leading cause of maternal and fetal morbidity and mortality. Currently, there is no cure for preeclampsia except delivery of the placenta, which is central to the pathogenesis of the disease. Transcriptional profiling of human placenta from pregnancies complicated by preeclampsia has been extensively performed to identify differentially expressed genes (DEGs). DEGs are identified using unbiased assays, however the decisions to investigate DEGs experimentally are biased by many factors (e.g., investigator interests, available reagents, knowledge of gene function) causing many DEGs to remain uninvestigated. An extensive body of literature and a pool of data (generated via transcriptional profiling) exist for preeclampsia, yet there is no cure making it a prime candidate for knowledge-based analysis. Our goal was to demonstrate how a PheKnowLator knowledge graph could be used to identify novel mechanistic preeclampsia mechanisms. Existing open source biomedical resources and publicly available high-throughput transcriptional profiling data were used to identify and annotate the function of currently uninvestigated preeclampsia-associated DEGs. Using the keyword “preeclampsia”, 68 publicly available human gene expression experiments deposited in the Gene Expression Omnibus were identified and reviewed. Meta-analysis of the 12 experiments meeting inclusion criteria generated a list of 549 DEGs. The relative complement of the annotation- and meta-analysis-derived lists were identified as the uninvestigated preeclampsia-associated DEGs (n = 445). Experimentally investigated DEGs were then identified from published literature based on semantic and syntactic annotations to PubMed abstracts. Using PheKnowLator-derived node embeddings to investigate relevant DEGs revealed 53 relevant and actionable mechanistic associations of preeclampsia.This is submission serves as a placeholder for a preprint that is being submitted to arXiv. As soon as a valid DOI has been produced, this submission will be updated with the preprint PDF, the DOI, and the submission authors