Hypertensive disorders of pregnancy and cardiovascular disease risk: a Mendelian randomisation study
Bibliographic record
Abstract
OBJECTIVE: Observational studies show that hypertensive disorders of pregnancy (HDPs) are related to unfavourable maternal cardiovascular disease (CVD) risk profiles later in life. We investigated whether genetic liability to pre-eclampsia/eclampsia and gestational hypertension is associated with CVD risk factors and occurrence of CVD events. METHODS: We obtained genetic associations with HDPs from a genome-wide association study and used individual participant data from the UK Biobank to obtain genetic associations with CVD risk factors and CVD events (defined as myocardial infarction or stroke). In our primary analysis, we applied Mendelian randomisation using inverse-variance weighted regression analysis in ever pregnant women. In sensitivity analyses, we studied men and nulligravidae to investigate genetic liability to HDPs and CVD risk without the ability to experience the underlying phenotype. RESULTS: Our primary analysis included 221 155 ever pregnant women (mean age 56.8 (SD 7.9) years) with available genetic data. ORs for CVD were 1.20 (1.02 to 1.41) and 1.24 (1.12 to 1.38) per unit increase in the log odds of genetic liability to pre-eclampsia/eclampsia and gestational hypertension, respectively. Furthermore, genetic liability to HDPs was associated with higher levels of systolic and diastolic blood pressure and younger age at hypertension diagnosis. Sensitivity analyses revealed no statistically significant differences when comparing the findings with those of nulligravidae and men. CONCLUSIONS: Genetic liability to HDPs is associated with higher CVD risk, lower blood pressure levels and earlier hypertension diagnosis. Our study suggests similar findings in ever pregnant women, nulligravidae and men, implying biological mechanisms relating to HDPs are causally related to CVD risk.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.019 | 0.033 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".