| Literature DB >> 35428514 |
Nándor Gábor Than1, Máté Posta2, Dániel Györffy3, László Orosz4, Gergő Orosz4, Simona W Rossi5, Géza Ambrus-Aikelin6, András Szilágyi2, Sándor Nagy7, Petronella Hupuczi8, Olga Török4, Adi L Tarca9, Offer Erez10, Zoltán Papp8, Roberto Romero11.
Abstract
Preeclampsia is a syndromic disease of the mother, fetus, and placenta. The main limitation in early and accurate diagnosis of preeclampsia is rooted in the heterogeneity of this syndrome as reflected by diverse molecular pathways, symptoms, and clinical outcomes. Gaps in our knowledge preclude successful early diagnosis, personalized treatment, and prevention. The advent of "omics" technologies and systems biology approaches addresses this problem by identifying the molecular pathways associated with the underlying mechanisms and clinical phenotypes of preeclampsia. Here, we provide a brief overview on how the field has progressed, focusing on studies utilizing state-of-the-art transcriptomics and proteomics methods. Moreover, we summarize our systems biology studies involving maternal blood proteomics and placental transcriptomics, which identified early maternal and placental disease pathways and showed that their interaction influences the clinical presentation of preeclampsia. We also present an analysis of maternal blood proteomics data which revealed distinct molecular subclasses of preeclampsia and their molecular mechanisms. Maternal and placental disease pathways behind these subclasses are similar to those recently reported in studies on the placental transcriptome. These findings may promote the development of novel diagnostic tools for the distinct subtypes of preeclampsia syndrome, enabling early detection and personalized follow-up and tailored care of patients.Entities:
Keywords: Class discovery; Great obstetrical syndromes; High-dimensional biology; Liquid biopsy; Personalized medicine; Prenatal diagnosis; “Omics” sciences
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Year: 2022 PMID: 35428514 PMCID: PMC9261837 DOI: 10.1016/j.placenta.2022.03.009
Source DB: PubMed Journal: Placenta ISSN: 0143-4004 Impact factor: 3.287