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Extracellular vesicles alter trophoblast function in pregnancies complicated by COVID-19

GSE268230 Homo sapiens Expression profiling by high throughput sequencing 129 samples 2025/04/17 GPL24676GPL30882
Summary
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and resulting coronavirus disease (COVID-19) causes placental dysfunction, which increases the risk of adverse pregnancy outcomes. While abnormal placental pathology resulting from COVID-19 is common, direct infection of the placenta is rare. This suggests that pathophysiology associated with maternal COVID-19, rather than direct placental infection, is responsible for placental dysfunction and alteration of the placental transcriptome. We hypothesized that maternal circulating extracellular vesicles (EVs), altered by COVID-19 during pregnancy, contribute to placental dysfunction. To examine this hypothesis, we characterized maternal circulating EVs from pregnancies complicated by COVID-19 and tested their effects on trophoblast cell physiology in vitro. We found that the gestational timing of COVID-19 is a major determinant of circulating EV function and cargo. In vitro trophoblast exposure to EVs isolated from patients with an active infection at the time of delivery, but not EVs isolated from Controls, altered key trophoblast functions including hormone production and invasion. Thus, circulating EVs from participants with an active infection, both symptomatic and asymptomatic cases, can disrupt vital trophoblast functions. EV cargo differed between participants with COVID-19 and Controls, which may contribute to the disruption of the placental transcriptome and morphology. Our findings show that COVID-19 can have effects throughout pregnancy on circulating EVs and circulating EVs are likely to participate in placental dysfunction induced by COVID-19.
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NCBI GEO page ↗ Paper (PMID 40205960) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
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