Unique microRNA Signals in Plasma Exosomes from Pregnancies Complicated by Preeclampsia
Bibliographic record
Abstract
Although preeclampsia is a common and serious complication of pregnancy, insight into its pathobiology and diagnosis is lacking. Circulating plasma exosomes, which contain RNA and other molecules and have recently become accessible for diagnostics, may be informative in this regard. We tested the hypothesis that preeclampsia may affect the miRNA cargo within circulating maternal blood exosomes. We collected plasma from 60 pregnant women at term, including 20 women with pregnancy complicated by preeclampsia, and 20 women with fetal growth restriction and 20 with healthy pregnancy, serving as controls. We isolated exosomes from the maternal plasma by continuous density gradient ultracentrifugation. Our main outcome variable was exosomal miRNA cargo, analyzed by quantitative polymerase chain reaction-based TaqMan advanced miRNA assay in a card format and the expression of differentially expressed exosomal miRNA in whole plasma from the same participants. We found that 7 miRNA species were differentially expressed in exosomes from women with preeclampsia and those from controls. In contrast, there was no significant difference in exosomal miRNA expression between women with fetal growth restriction and controls. The results were not affected by fetal sex. Only one of the preeclampsia-related, differentially expressed exosomal miRNAs was significantly different in whole plasma miRNA analysis. We concluded that unlike whole plasma miRNA, exosomes extracted from the plasma of women with preeclampsia exhibit a unique miRNA profile, suggesting that plasma exosomal miRNA could provide insight into the pathophysiology of preeclampsia, and may play a role in disease diagnostics.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".