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Molecular subclasses of preeclampsia characterized by a longitudinal maternal proteomics study: Distinct biomarkers, disease pathways and options for prevention

  • Nándor Gábor Than
  • , Roberto Romero
  • , Dániel Györffy
  • , Máté Posta
  • , Gaurav Bhatti
  • , Bogdan Done
  • , Piya Chaemsaithong
  • , Eunjung Jung
  • , Manaphat Suksai
  • , Francesca Gotsch
  • , Dahiana M. Gallo
  • , Mariachiara Bosco
  • , Bomi Kim
  • , Yeon Mee Kim
  • , Tinnakorn Chaiworapongsa
  • , Simona W. Rossi
  • , András Szilágyi
  • , Offer Erez
  • , Adi L. Tarca
  • , Zoltán Papp
  • Institute of Enzymology
  • Maternity Private Clinic of Obstetrics and Gynecology
  • Genesis Theranostix Group
  • Semmelweis University
  • Eunice Kennedy Shriver National Institute of Child Health and Human Development
  • University of Michigan Medical School
  • Michigan State University
  • Wayne State University School of Medicine
  • Detroit Medical Center
  • Pázmány Péter Catholic University
  • Universidad del Valle, Cali
  • Inje University Paik Hospital
  • HaEmek Medical Center
  • Wayne State University College of Engineering

Research output: Contribution to journalArticlepeer-review

31 Citations (Scopus)

Abstract

Objectives: The heterogeneous nature of preeclampsia is a major obstacle to early screening and prevention, and a molecular taxonomy of disease is needed. We have previously identified four subclasses of preeclampsia based on first-trimester plasma proteomic profiles. Herein, we expanded this approach by using a more comprehensive panel of proteins profiled in longitudinal samples. Methods: Proteomic data collected longitudinally from plasma samples of women who developed preeclampsia (n=109) and of controls (n=90) were available from our previous report on 1,125 proteins. Consensus clustering was performed to identify subgroups of patients with preeclampsia based on data from five gestational-age intervals by using select interval-specific features. Demographic, clinical, and proteomic differences among clusters were determined. Differentially abundant proteins were used to identify cluster-specific perturbed KEGG pathways. Results: Four molecular clusters with different clinical phenotypes were discovered by longitudinal proteomic profiling. Cluster 1 involves metabolic and prothrombotic changes with high rates of early-onset preeclampsia and small-for-gestational-age neonates; Cluster 2 includes maternal anti-fetal rejection mechanisms and recurrent preeclampsia cases; Cluster 3 is associated with extracellular matrix regulation and comprises cases of mostly mild, late-onset preeclampsia; and Cluster 4 is characterized by angiogenic imbalance and a high prevalence of early-onset disease. Conclusions: This study is an independent validation and further refining of molecular subclasses of preeclampsia identified by a different proteomic platform and study population. The results lay the groundwork for novel diagnostic and personalized tools of prevention.

Original languageEnglish
Pages (from-to)51-68
Number of pages18
JournalJournal of Perinatal Medicine
Volume51
Issue number1
DOIs
Publication statusPublished - 1 Jan 2023
Externally publishedYes

Keywords

  • great obstetrical syndromes
  • liquid biopsy
  • omics
  • personalized medicine
  • prenatal diagnosis
  • screening

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