A proteomic analysis of placental tissue from patients with early-onset preeclampsia (EOPE) has uncovered key protein interactions and pathways that could serve as biomarkers and therapeutic targets. The study used tandem mass tag (TMT)-based quantitative proteomics to analyze 15 EOPE and 15 control samples, revealing significant differences in protein expression that highlight pathways potentially driving EOPE’s progression.
“My main inspiration for this work came from the challenges I faced in understanding the molecular mechanisms underlying preeclampsia,” says Jing Li, corresponding author, and Obstetrician and Clinical Researcher at Affiliated Hospital of Qingdao University, China. “I aimed to use a proteomics approach to identify proteins that might be associated with early-onset preeclampsia, allowing for a more comprehensive exploration of potential biomarkers and therapeutic targets.”
The analysis identified 59 differentially expressed proteins: 25 proteins were upregulated, while 34 were downregulated in EOPE-affected tissues compared with controls. Six key proteins, including SLC16A3, ERO1A, and PAPPA2, were validated as consistently different in EOPE samples through parallel reaction monitoring (PRM), lending confidence to the findings.
Pathway analysis of these proteins pointed to estrogen signaling and cardiomyopathy-related pathways as significant contributors to EOPE pathogenesis. This aligns with current research on EOPE’s potential links to systemic regulatory imbalances.
“Proteomics provides insights into the interactions between proteins, creating a network of relationships that can be crucial for understanding complex biological systems,” says Li. “When combined with bioinformatics analyses, this technique offers a wealth of information that can deepen our understanding of the mechanisms involved in early-onset preeclampsia.”
However, Li also highlights challenges in proteomics. “One of the tricky challenges I encountered was that the correlation between the significant proteins I identified was not as strong as I had hoped,” Li says. “This made it difficult to pinpoint ideal cellular signaling pathways to support and inspire the next steps in my research. But I believe it’s essential to respect the realities of scientific investigation, acknowledging that not every finding leads directly to clear pathways or conclusions.” Indeed, Li emphasizes that each insight was incremental: “The results were more gradual and required careful interpretation. This experience underscored the complexity of biological systems and the importance of patience in scientific inquiry.”
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