A Mendelian randomization study of the effects of blood lipids on breast cancer risk
Bibliographic record
Abstract
Observational studies have reported inconsistent associations between circulating lipids and breast cancer risk. Using results from >400,000 participants in two-sample Mendelian randomization, we show that genetically raised LDL-cholesterol is associated with higher risk of breast cancer (odds ratio, OR, per standard deviation, 1.09, 95% confidence interval, 1.02-1.18, P = 0.020) and estrogen receptor (ER)-positive breast cancer (OR 1.14 [1.05-1.24] P = 0.004). Genetically raised HDL-cholesterol is associated with higher risk of ER-positive breast cancer (OR 1.13 [1.01-1.26] P = 0.037). HDL-cholesterol-raising variants in the gene encoding the target of CETP inhibitors are associated with higher risk of breast cancer (OR 1.07 [1.03-1.11] P = 0.001) and ER-positive breast cancer (OR 1.08 [1.03-1.13] P = 0.001). LDL-cholesterol-lowering variants mimicking PCSK9 inhibitors are associated (P = 0.014) with lower breast cancer risk. We find no effects related to the statin and ezetimibe target genes. The possible risk-promoting effects of raised LDL-cholesterol and CETP-mediated raised HDL-cholesterol have implications for breast cancer prevention and clinical trials.
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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 | 0.055 | 0.120 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".