Pre‐eclampsia and future cardiovascular disease: role of circulating micro‐RNAs
Bibliographic record
Abstract
Background Women with a history of pre‐eclampsia (PE) are at increased risk of cardiovascular events later in life. The mechanisms underlying this association are incompletely understood but likely include changes in vascular function and structure. microRNAs (miRs) may play a role in vascular health and disease; therefore, we assessed profiles of circulating miRs in women who had PE, with or without subsequent cardiovascular disease. Methods We performed comprehensive profiling of circulating miRs by RNA sequencing (Qiagen, Hilden, Germany) of plasma samples from two independent cohorts: a cohort of women who presented with premature acute coronary syndrome (ACS; cohort 1: n=18 with and n=17 without history of PE) and a cohort of women without overt cardiovascular disease (cohort 2: n=20 with and n=20 without history of PE). miR profiles associated with history of PE and ACS were established based on fold change ≥ ±1.5 and P < 0.05. Targetscan 7.0 was used to predict miR targets and KEGG pathway enrichment was determined with Partek Pathway and Genomics Suite. Results Women in the two cohorts were on average 48 years of age and had prior pregnancy over 20 years before. A total of 183 and 107 miRs were found to be differentially expressed between cases and controls in cohorts 1 and 2, respectively. Five miRs (hsa‐miRs 3131, 346, 4305, 4670‐3p and 5698) were concordantly increased or decreased in both cohorts. There were 39 and 29 KEGG pathways significantly (FDR <0.05) enriched in cohorts 1 and 2, respectively, of which 23 pathways overlapped between the cohorts. Further analysis identified 13 KEGG pathways that were common between all comparisons of PE vs control in cohorts 1 and 2, and ACS vs non‐ACS across the cohorts, including cancer, Wnt signalling, TGF‐beta and focal adhesion pathways (Figure 1). Conclusions By analysing circulating miR profiles, we identified pathways that are common between women with ACS and women with history of PE. Of particular importance, pathways involved in cell growth and adhesion may provide explanations for the link between PE and future cardiovascular diseases. Support or Funding Information Funded by grants from the Canadian Vascular Network and the British Heart Foundation (Centre of Research Excellence award RE/13/5/30177) This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".