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bioRxiv · 10.64898/2026.03.10.710888

Multi-omic profiling of early pregnancy small and large plasma extracellular vesicles reveals placental, metabolic, and structural adaptation signatures

Abstract

Early human pregnancy is a critical period characterized by rapid growth and extensive maternal-fetal communication that influence maternal and fetal outcomes. Circulating extracellular vesicles (EVs) have the capacity to capture cargo that reflect these processes in real-time; however, signatures of EV subtypes during early pregnancy are poorly defined. Here we quantified mitochondrial DNA (mtDNA) and performed transcriptomic and proteomic profiling of small ([~]100 nm) and large ([~]200 nm) plasma EVs from n=10 normal pregnancies (11-15 weeks) to define subtype-specific molecular signatures. mtDNA and mitochondrial protein content were more abundant in large EVs (lEVs). lEVs also contained a more complex set of long RNAs enriched for placental, immune, and mitochondrial-related transcripts compared with small EVs (sEVs). Proteomic profiling showed enrichment of canonical EV markers and extracellular matrix proteins in sEVs, whereas lEVs were preferentially associated with pregnancy-specific proteins, including proteins related to placental hormone production. MicroRNAs (miRNAs) accounted for [~]25% of small RNAs in both EV subtypes with miR-223 and miR-16 enriched in lEVs and miR-639 enriched in sEVs. These data together, support a model where small and large plasma EVs have distinct, yet complementary signatures reporting systemic adaptations during the critical 11-15 week transition period. This work establishes a foundational framework for future studies linking EV signatures to placental dysfunction and adverse outcomes.

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Abney, K., Hollingsworth, T., Schneider, A., Brown, E. M., Fazelinia, H., Spruce, L., Leite, R., Parry, S., Schwartz, N., Conine, C. C., Simmons, R.. 2026-03-13. Multi-omic profiling of early pregnancy small and large plasma extracellular vesicles reveals placental, metabolic, and structural adaptation signatures. https://doi.org/10.64898/2026.03.10.710888

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