Polymorphisms in the Renin‐Angiotensin System and Migraine in Women
Bibliographic record
Abstract
BACKGROUND: Recent findings suggest an association between the renin-angiotensin system and migraine. However, genetic studies are scarce and controversial. OBJECTIVE: To investigate the association between the AGTR1 1166A > C and AGT Met235Thr polymorphisms with migraine and migraine aura status. METHODS: We performed an association study among 25,000 Caucasian US women, participating in the Women's Health Study, with information on the AGTR1 1166A > C and AGT Met235Thr polymorphisms. Migraine and migraine aura status were self-reported. We distinguished between any history of migraine, active migraine with aura, active migraine without aura, and prior migraine (history of migraine, but not in the year prior to baseline). We used logistic regression to investigate the genotype-migraine association. RESULTS: At baseline, 4577 (18.3%) women reported any history of migraine; 39.5% of the 3226 women with active migraine indicated aura. The polymorphisms were not associated with migraine or migraine-specific subgroups. We also did not find a significant interaction between the polymorphisms. CONCLUSIONS: Data from this large cohort of Caucasian women do not suggest an association of polymorphisms in the renin-angiotensin system with migraine or aura status. Future studies should focus on haplotype analyses and additional gene-gene as well as gene-environment interactions.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".