Taller height and risk of coronary heart disease and cancer: A within-sibship Mendelian randomization study
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Evaluation Summary:
The authors examined the role of height in cancer, coronary heart disease and cardiovascular disease risk factors, using four different designs. They found that height increases risk of cancer and decreases risk of coronary heart disease, while the associations for the cardiovascular disease risk factors were largely null. This will be mainly of interest to epidemiologists.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)
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Abstract
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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Evaluation Summary:
The authors examined the role of height in cancer, coronary heart disease and cardiovascular disease risk factors, using four different designs. They found that height increases risk of cancer and decreases risk of coronary heart disease, while the associations for the cardiovascular disease risk factors were largely null. This will be mainly of interest to epidemiologists.
(This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)
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Reviewer #1 (Public Review):
This study is examining the role of height in cancer, coronary heart disease and cardiovascular disease risk factors, using four different designs, i.e., an innovative Mendelian randomization design comparing siblings, a population based Mendelian randomization study and purely observational studies in siblings and the population. All the methods gave the same interpretation for cancer and coronary heart disease, i.e., that height increases risk of cancer and decreases risk of coronary heart disease, while the associations for the cardiovascular disease risk factors were largely null.
The study does an excellent job of providing estimates likely free from confounding, particularly by using the Mendelian randomization sibling design.
The other major source of bias in studies of cause and effect is selection …
Reviewer #1 (Public Review):
This study is examining the role of height in cancer, coronary heart disease and cardiovascular disease risk factors, using four different designs, i.e., an innovative Mendelian randomization design comparing siblings, a population based Mendelian randomization study and purely observational studies in siblings and the population. All the methods gave the same interpretation for cancer and coronary heart disease, i.e., that height increases risk of cancer and decreases risk of coronary heart disease, while the associations for the cardiovascular disease risk factors were largely null.
The study does an excellent job of providing estimates likely free from confounding, particularly by using the Mendelian randomization sibling design.
The other major source of bias in studies of cause and effect is selection (or collider) bias. The study also needs to consider possible selection bias from inevitably only selecting survivors to recruitment of their height (measured or genetically endowed), the disease of interest and any competing risk of the disease of interest. Whether, the sibling design, by requiring at least two siblings to survive to recruitment, is more open to selection bias than a population-based design could also be considered.
The study provides an interesting comparison of four different methods. Height increasing cancer risk is plausible because of the potential mechanism given, i.e., IGF1, the consistency with well accepted biological theories from evolutionary biology, and that cancer deaths tend to occur at younger ages than cardiovascular disease deaths. The results for coronary artery disease are possible, but could be overstated Greater consideration should be also be given to as to how "an individual-level causal effect" observed largely in Europeans generalizes.
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Reviewer #2 (Public Review):
The paper by Howe et al investigates observational and genetic associations between taller height and cardiovascular disease (protective) as well as cancer (risk). They use within-sibship analyses to additionally control for familiar factors to confirm earlier findings. The strength of the study is the Mendelian Randomization models and family study designs used in two cohorts. However, they have limited power to explore more of the data, e.g., mediation, multivariate MR, to increase novelty. Hence, the impression is that they could have made some more analyses, and also presented the study with equal weights on observational/MR findings. Regardless, the conclusions from the results are fair.
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