Taller height and risk of coronary heart disease and cancer: A within-sibship Mendelian randomization study
Bibliographic record
Abstract
Background: Taller people have a lower risk of coronary heart disease but a higher risk of many cancers. Mendelian randomization (MR) studies in unrelated individuals (population MR) have suggested that these relationships are potentially causal. However, population MR studies are sensitive to demography (population stratification, assortative mating) and familial (indirect genetic) effects. Methods: In this study, we performed within-sibship MR analyses using 78,988 siblings, a design robust against demography and indirect genetic effects of parents. For comparison, we also applied population MR and estimated associations with measured height. Results: Within-sibship MR estimated that 1 SD taller height lowers the odds of coronary heart disease by 14% (95% CI: 3-23%) but increases the odds of cancer by 18% (95% CI: 3-34%), highly consistent with population MR and height-disease association estimates. There was some evidence that taller height reduces systolic blood pressure and low-density lipoprotein cholesterol, which may mediate some of the protective effects of taller height on coronary heart disease risk. Conclusions: For the first time, we have demonstrated that the purported effects of height on adulthood disease risk are unlikely to be explained by demographic or familial factors, and so likely reflect an individual-level causal effect. Disentangling the mechanisms via which height affects disease risk may improve the understanding of the etiologies of atherosclerosis and carcinogenesis. Funding: This project was conducted by researchers at the MRC Integrative Epidemiology Unit (MC_UU_00011/1) and also supported by a Norwegian Research Council Grant number 295989.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".