The association between the body height and cardiovascular diseases: a retrospective analysis of 657,310 outpatients in Germany

Krieg, Sarah; Kostev, Karel; Luedde, Mark; Krieg, Andreas; Luedde, Tom; Roderburg, Christoph; Loosen, Sven H.

doi:10.1186/s40001-022-00881-y

Cited by 6 publications

(1 citation statement)

References 35 publications

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“…It is necessary to investigate the risk factors of CAD for prevention and treatment. Observational studies have identified that adiposity, height, and lipoprotein metabolism are associated with the risk of CAD (Emerging Risk Factors Collaboration, 2011;Krieg et al, 2022;Rader and Daugherty, 2008). To further disentangle the causal relationship between those potential risk factors and CAD, we applied MVMR-PRESS and other existing MR methods to their GWAS summary statistics.…”

Section: Coronary Artery Diseasementioning

confidence: 99%

A robust penalized-regression-based method for multivariable Mendelian randomization using GWAS summary statistics

Zhao,

Jiang,

Song

et al. 2023

Preprint

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Mendelian randomization (MR) is a statistical approach to inferring the causal relationships from genome-wide association studies (GWAS) by using genetic variants as instrumental variables (IVs). As IVs, the selected genetic variants should be solely associated with the exposure of interest, and have no associations with confounders and the studied outcome except through the exposure. Sometimes the selected genetic variants have effects on the outcome through other pathways, a phenomenon known as horizontal pleiotropy, which makes the selected variants violate IV assumptions. Two different approaches have been proposed to address this issue: one is to improve robustness to pleiotropic effects, and the other one is to generalize univariate exposure to multivariate cases so that we can incorporate possible pathways into MR analysis. Compared to pleiotropy-robust methods, multivariable Mendelian randomization (MVMR) can uncover the exposures having direct effects on the outcome. However, measuring all possible pathways from genetic variants to the outcome in MVMR analysis is difficult. Although MVMR methods with robustness to unmeasured pleiotropy have been proposed recently, they are statistically inefficient as a result of ignoring correlations among exposures and distributions of effect sizes. Given the limitations from both directions, we propose a novel method named MVMR-PRESS that can infer causal relationships between multivariate exposures and the outcome with robustness to horizontal pleiotropic effects from unconsidered pathways. MVMR-PRESS estimates causal effects by using a Penalized Regression on Summary Statistics from GWAS considering both correlations among exposures and distributions of effect sizes. One merit of MVMR-PRESS is that samples in GWAS of different exposures can have overlaps, which allows us to include GWAS summary statistics from the same cohort or consortium. Simulation experiments showed that our method achieved the smallest bias and highest power compared to existing pleiotropy-robust MR and MVMR methods while the type 1 error rate was well-controlled. Applying MVMR-PRESS to publicly available GWAS summary statistics demonstrated that body mass index (BMI), height (HT), and low-density lipoprotein cholesterol (LDL) have significant causal effects on coronary artery disease (CAD), and BMI and high-density lipoprotein cholesterol (HDL) were causally related to type 2 diabetes (T2D). On the contrary, the causal estimates of triglycerides (TG), HDL, and total cholesterol (TC) on CAD, and the estimates of HT, LDL, TG, and TC on T2D were non-significant. In addition, we found no evidence suggesting BMI, HT, and lipid levels have causal effects on inflammatory bowel disease (IBD) and schizophrenia (SCZ).

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Section: Coronary Artery Diseasementioning

confidence: 99%

A robust penalized-regression-based method for multivariable Mendelian randomization using GWAS summary statistics

Zhao,

Jiang,

Song

et al. 2023

Preprint

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Trend in physical growth among Chinese urban students: Results from five national successive cross‐sectional surveys within the past two decades

Zhang,

Li,

Taerken

2024

American J Hum Biol

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ObjectivesTo examine the orientation, magnitude, and pace of secular trends in body height, weight, and body mass index (BMI) among Chinese urban students aged 7–18 years from 2000 to 2019.MethodsData were extracted from Chinese urban students aged 7–18 years from the Chinese National Surveillance on Students' Constitution and Health in 2000, 2005, 2010, 2014, and 2019. The height, weight, and BMI of 548 419, 548 408, and 548 365 urban students aged 7–18 years, respectively, were tested. The mean differences across survey years were tested by one‐way analysis of variance (ANOVA). The pace of secular trends is expressed as the change every 5 years between every two adjacent survey years.ResultsHeight increments between 1.9 and 6.2 cm, weight increments between 2.7 and 8.6 kg, and BMI increments between 0.9 and 1.9 kg/m2 were observed in boys. For girls, height increments between 1.5 and 4.9 cm, weight increments between 2.2 and 6.0 kg, and BMI increments between 0.7 and 1.7 kg/m2 were observed. The pace of secular trends in height decreased in the last 5 years, and the secular trends in weight and BMI have accelerated in the last 9 years compared with the previous 10 years.ConclusionsAlthough the secular trend in height among Chinese urban students has slowed, it has not yet reached its genetic potential and continues to increase. The rapid increase in weight and BMI was a cause for concern. Our findings provide a basis for the future formulation of public health interventions in China.

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TEMR: Trans-ethnic mendelian randomization method using large-scale GWAS summary datasets

Hou,

Wu,

Yuan

et al. 2024

The American Journal of Human Genetics

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The association between the body height and cardiovascular diseases: a retrospective analysis of 657,310 outpatients in Germany

Cited by 6 publications

References 35 publications

A robust penalized-regression-based method for multivariable Mendelian randomization using GWAS summary statistics

A robust penalized-regression-based method for multivariable Mendelian randomization using GWAS summary statistics

Trend in physical growth among Chinese urban students: Results from five national successive cross‐sectional surveys within the past two decades

TEMR: Trans-ethnic mendelian randomization method using large-scale GWAS summary datasets

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