ArticlePloS one2015
Large scale aggregate microarray analysis reveals three distinct molecular subclasses of human preeclampsia.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers, 1 of them a synthesis that pooled it.
What it found
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Who cites it
68 citing papers in PubMed, 1 synthesis or guideline pooled it, 123 citations in OpenAlex.
- A review of omics approaches to study preeclampsia.Placenta · 2020Pooled it
- Gene expression in term placentas is regulated more by spinal or epidural anesthesia than by late-onset preeclampsia or gestational diabetes mellitus.Scientific reports · 2016Trial
- Determinants of Placental Versus Maternal Preeclampsia.Hypertension (Dallas, Tex. : 1979) · 2026Article
- Large-Scale Proteomics Reveals New Candidate Biomarkers for Late-Onset Preeclampsia.Hypertension (Dallas, Tex. : 1979) · 2026Article
- Placenta-Derived Proteins in Preeclampsia: A Human In Vivo Study.Hypertension (Dallas, Tex. : 1979) · 2025Article
- Localization and quantification of placentalPhysiological genomics · 2025Article
- Multi-omic insights of preeclampsia and cardiovascular health outcomes.Communications medicine · 2025Review
- Vaping in Pregnancy: Unraveling Molecular Drivers of Preeclampsia and Fetal Growth Restriction.International journal of molecular sciences · 2025Article
- Integrated multi-omics analysis reveals immunovascular mechanisms of the placenta-maternal brain axis and lifespan neurobehavior changes in a mouse model of preeclampsia.Neuroscience · 2025Article
- Senescent Syncytiotrophoblast Secretion During Early Onset Preeclampsia.Hypertension (Dallas, Tex. : 1979) · 2025Article
- NADLife science alliance · 2024Article
- Placental differences between severe fetal growth restriction and hypertensive disorders of pregnancy requiring early preterm delivery: morphometric analysis of the villous tree supported by artificial intelligence.American journal of obstetrics and gynecology · 2024Article
- Proteomic Profiles of Maternal Plasma Extracellular Vesicles for Prediction of Preeclampsia.American journal of reproductive immunology (New York, N.Y. : 1989) · 2024Article
- A genome scale transcriptional regulatory model of the human placenta.Science advances · 2024Article
- The role of the placenta-brain axis in psychoneuroimmune programming.Brain, behavior, & immunity - health · 2024Article
- The GATA transcriptional program dictates cell fate equilibrium to establish the maternal-fetal exchange interface and fetal development.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Classification of preeclampsia according to molecular clusters with the goal of achieving personalized prevention.Journal of reproductive immunology · 2024Review
- Molecular epidemiology of pregnancy using omics data: advances, success stories, and challenges.Journal of translational medicine · 2024Review
- High placental expression of FLT1, LEP, PHYHIP and IL3RA - In persons of African ancestry with severe preeclampsia.Placenta · 2023Article
- Defining trophoblast injury patterns in the transcriptomes of dysfunctional placentas.Placenta · 2023Article
8 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
backgroundPreeclampsia (PE) is a life-threatening hypertensive pathology of pregnancy affecting 3-5% of all pregnancies. To date, PE has no cure, early detection markers, or effective treatments short of the removal of what is thought to be the causative organ, the placenta, which may necessitate a preterm delivery. Additionally, numerous small placental microarray studies attempting to identify "PE-specific" genes have yielded inconsistent results. We therefore hypothesize that preeclampsia is a multifactorial disease encompassing several pathology subclasses, and that large cohort placental gene expression analysis will reveal these groups.
resultsTo address our hypothesis, we utilized known bioinformatic methods to aggregate 7 microarray data sets across multiple platforms in order to generate a large data set of 173 patient samples, including 77 with preeclampsia. Unsupervised clustering of these patient samples revealed three distinct molecular subclasses of PE. This included a "canonical" PE subclass demonstrating elevated expression of known PE markers and genes associated with poor oxygenation and increased secretion, as well as two other subclasses potentially representing a poor maternal response to pregnancy and an immunological presentation of preeclampsia.
conclusionOur analysis sheds new light on the heterogeneity of PE patients, and offers up additional avenues for future investigation. Hopefully, our subclassification of preeclampsia based on molecular diversity will finally lead to the development of robust diagnostics and patient-based treatments for this disorder.
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