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.

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

Gotsch, Francesca;Bosco, Mariachiara;
2023-01-01

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.
2023
great obstetrical syndromes
liquid biopsy
omics
personalized medicine
prenatal diagnosis
screening
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1154148
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