scholarly journals Searching for the causal effects of BMI in over 300 000 individuals, using Mendelian randomization

2017 ◽  
Author(s):  
Louise A C Millard ◽  
Neil M Davies ◽  
Kate Tilling ◽  
Tom R Gaunt ◽  
George Davey Smith
Keyword(s):  
Body Mass Index ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Causal Effects ◽  
P Value ◽  
Protective Effects ◽  
Independent Subset ◽  
Uk Biobank ◽  
False Discovery ◽  
Causal Risk Factor

ABSTRACTMendelian randomization (MR) has been used to estimate the causal effect of body mass index (BMI) on particular traits thought to be affected by BMI. However, BMI may also be a modifiable, causal risk factor for outcomes where there is no prior reason to suggest that a causal effect exists. We perform a MR phenome-wide association study (MR-pheWAS) to search for the causal effects of BMI in UK Biobank (n=334 968), using the PHESANT open-source phenome scan tool. Of the 20 461 tests performed, our MR-pheWAS identified 519 associations below a stringent P value threshold corresponding to a 5% estimated false discovery rate, including many previously identified causal effects. We also identified several novel effects, including protective effects of higher BMI on a set of psychosocial traits, identified initially in our preliminary MR-pheWAS and replicated in an independent subset of UK Biobank. Such associations need replicating in an independent sample.

scholarly journals Body mass index and mortality in UK Biobank: revised estimates using Mendelian randomization

2018 ◽  
Author(s):  
Kaitlin H Wade ◽  
David Carslake ◽  
Naveed Sattar ◽  
George Davey Smith ◽  
Nicholas J Timpson
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Genotypic Variation ◽  
Lung Cancer Mortality ◽  
Causal Role ◽  
Uk Biobank ◽  
All Cause Mortality

AbstractObjectiveObtain estimates of the causal relationship between different levels of body mass index (BMI) and mortality.MethodsMendelian randomization (MR) was conducted using genotypic variation reliably associated with BMI to test the causal effect of increasing BMI on all-cause and cause-specific mortality in participants of White British ancestry in UK Biobank.ResultsMR analyses supported existing evidence for a causal association between higher levels of BMI and greater risk of all-cause mortality (hazard ratio (HR) per 1kg/m2: 1.02; 95% CI: 0.97,1.06) and mortality from cardiovascular diseases (HR: 1.12; 95% CI: 1.02, 1.23), specifically coronary heart disease (HR: 1.19; 95% CI: 1.05, 1.35) and those other than stroke/aortic aneurysm (HR: 1.13; 95% CI: 0.93, 1.38), stomach cancer (HR: 1.30; 95% CI: 0.91, 1.86) and oesophageal cancer (HR: 1.08; 95% CI: 0.84, 1.38), and with decreased risk of lung cancer mortality (HR: 0.97; 95% CI: 0.84, 1.11). Sex-stratified analyses supported a causal role of higher BMI in increasing the risk of mortality from bladder cancer in males and other causes in females, but in decreasing the risk of respiratory disease mortality in males. The characteristic J-shaped observational association between BMI and mortality was visible with MR analyses but with a smaller value of BMI at which mortality risk was lowest and apparently flatter over a larger range of BMI.ConclusionResults support a causal role of higher BMI in increasing the risk of all-cause mortality and mortality from other causes. However, studies with greater numbers of deaths are needed to confirm the current findings.

scholarly journals An examination of multivariable Mendelian randomization in the single sample and two-sample summary data settings

2018 ◽  
Author(s):  
Eleanor Sanderson ◽  
George Davey Smith ◽  
Frank Windmeijer ◽  
Jack Bowden
Keyword(s):  
Mendelian Randomization ◽  
Causal Effect ◽  
Causal Effects ◽  
Single Sample ◽  
Mendelian Randomisation ◽  
Uk Biobank ◽  
Level Data ◽  
Wide Range ◽  
Using Data ◽  
Summary Data

AbstractBackgroundMendelian Randomisation (MR) is a powerful tool in epidemiology which can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilising genetic variants that are instrumental variables (IVs) for the exposure. This has been extended to Multivariable MR (MVMR) to estimate the effect of two or more exposures on an outcome.Methods/ResultsWe use simulations and theory to clarify the interpretation of estimated effects in a MVMR analysis under a range of underlying scenarios, where a secondary exposure acts variously as a confounder, a mediator, a pleiotropic pathway and a collider. We then describe how instrument strength and validity can be assessed for an MVMR analysis in the single sample setting, and develop tests to assess these assumptions in the popular two-sample summary data setting. We illustrate our methods using data from UK biobank to estimate the effect of education and cognitive ability on body mass index.ConclusionMVMR analysis consistently estimates the effect of an exposure, or exposures, of interest and provides a powerful tool for determining causal effects in a wide range of scenarios with either individual or summary level data.

scholarly journals Searching for the causal effects of body mass index in over 300 000 participants in UK Biobank, using Mendelian randomization

PLoS Genetics ◽  
2019 ◽  
Vol 15 (2) ◽  
pp. e1007951 ◽  
Author(s):  
Louise A. C. Millard ◽  
Neil M. Davies ◽  
Kate Tilling ◽  
Tom R. Gaunt ◽  
George Davey Smith
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Mendelian Randomization ◽  
Causal Effects ◽  
Uk Biobank

scholarly journals Causality of Abdominal Obesity on Cognition: a Trans-ethnic Mendelian Randomization study

2021 ◽  
Author(s):  
Shi-Heng Wang ◽  
Mei-Hsin Su ◽  
Chia-Yen Chen ◽  
Yen-Feng Lin ◽  
Yen-Chen Anne Feng ◽  
...  
Keyword(s):  
Cognitive Aging ◽  
Observational Studies ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
European Ancestry ◽  
P Value ◽  
Abdominal Adiposity ◽  
Uk Biobank ◽  
Reverse Causality ◽  
Summary Data

Obesity has been associated with cognition in observational studies; however, whether its effect is confounding, reverse causality, or causal remains inconclusive. Using two-sample Mendelian randomization (MR) analyses, we investigated the causality of overall obesity, measured by BMI, and abdominal adiposity, measured by waist-hip ratio adjusted for BMI (WHRadjBMI), on cognition. Using summary data from the GIANT consortium, COGENT consortium, and UK Biobank of European ancestry, there was no causal effect of BMI on cognition performance (beta[95% CI]=-0.04[-0.12,0.04], p-value=0.35); however, a 1-SD increase in WHRadjBMI was associated with 0.07 standardized decrease in cognition performance (beta[95% CI]=-0.07[-0.12,-0.02], p=0.006). Using raw data from the Taiwan Biobank of Asian ancestry, there was no causal effect of BMI on cognitive aging (beta[95% CI]=0.00[-0.09,0.09], p-value=0.95); however, a 1-SD increase in WHRadjBMI was associated with a 0.17 standardized decrease in cognitive aging (beta[95% CI]=-0.17[-0.30,-0.03], p=0.02). This trans-ethnic MR study reveals that abdominal adiposity impairs cognition.

scholarly journals An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings

2018 ◽  
Vol 48 (3) ◽  
pp. 713-727 ◽  
Author(s):  
Eleanor Sanderson ◽  
George Davey Smith ◽  
Frank Windmeijer ◽  
Jack Bowden
Keyword(s):  
Genetic Variants ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Causal Effects ◽  
Single Sample ◽  
Uk Biobank ◽  
Level Data ◽  
Wide Range ◽  
Using Data ◽  
Summary Data

Abstract Background Mendelian randomization (MR) is a powerful tool in epidemiology that can be used to estimate the causal effect of an exposure on an outcome in the presence of unobserved confounding, by utilizing genetic variants that are instrumental variables (IVs) for the exposure. This has been extended to multivariable MR (MVMR) to estimate the effect of two or more exposures on an outcome. Methods and results We use simulations and theory to clarify the interpretation of estimated effects in a MVMR analysis under a range of underlying scenarios, where a secondary exposure acts variously as a confounder, a mediator, a pleiotropic pathway and a collider. We then describe how instrument strength and validity can be assessed for an MVMR analysis in the single-sample setting, and develop tests to assess these assumptions in the popular two-sample summary data setting. We illustrate our methods using data from UK Biobank to estimate the effect of education and cognitive ability on body mass index. Conclusion MVMR analysis consistently estimates the direct causal effect of an exposure, or exposures, of interest and provides a powerful tool for determining causal effects in a wide range of scenarios with either individual- or summary-level data.

scholarly journals Causal effect of renal function on venous thromboembolism: a two-sample Mendelian randomization investigation

2021 ◽  
Author(s):  
Shuai Yuan ◽  
Maria Bruzelius ◽  
Susanna C. Larsson
Keyword(s):  
Renal Function ◽  
Venous Thromboembolism ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Increased Risk ◽  
Mr Study

AbstractWhether renal function is causally associated with venous thromboembolism (VTE) is not yet fully elucidated. We conducted a two-sample Mendelian randomization (MR) study to determine the causal effect of renal function, measured as estimated glomerular filtration rate (eGFR), on VTE. Single-nucleotide polymorphisms associated with eGFR were selected as instrumental variables at the genome-wide significance level (p < 5 × 10−8) from a meta-analysis of 122 genome-wide association studies including up to 1,046,070 individuals. Summary-level data for VTE were obtained from the FinnGen consortium (6913 VTE cases and 169,986 non-cases) and UK Biobank study (4620 VTE cases and 356,574 non-cases). MR estimates were calculated using the random-effects inverse-variance weighted method and combined using fixed-effects meta-analysis. Genetically predicted decreased eGFR was significantly associated with an increased risk of VTE in both FinnGen and UK Biobank. For one-unit decrease in log-transformed eGFR, the odds ratios of VTE were 2.93 (95% confidence interval (CI) 1.25, 6.84) and 4.46 (95% CI 1.59, 12.5) when using data from FinnGen and UK Biobank, respectively. The combined odds ratio was 3.47 (95% CI 1.80, 6.68). Results were consistent in all sensitivity analyses and no horizontal pleiotropy was detected. This MR-study supported a casual role of impaired renal function in VTE.

Psychological factors as the risk factor of mouth ulcers: A two-sample Mendelian randomization study

2021 ◽  
pp. 135910532199969
Author(s):  
Yueqi Shi ◽  
Shaoyi Wang ◽  
Shunying Yu ◽  
Guan Ning Lin ◽  
Weichen Song
Keyword(s):  
Multiple Testing ◽  
Mendelian Randomization ◽  
Oral Care ◽  
Genetic Correlations ◽  
Well Being ◽  
Causal Effects ◽  
Mental Condition ◽  
Summary Statistics ◽  
Protective Effects ◽  
Psychological Traits

To examine whether psychological traits (PT) had causal effects on Mouth Ulcers (MU), we applied two-sample Mendelian randomization (MR) to genetics association summary statistics of eleven PT and MU. After the adjustment of outlier variants, genetic correlations and multiple testing, well-being (WB) spectrum PT like life satisfactory (odds ratio [OR] = 0.638 per one standard deviation increment of PT score) had protective effects on MU. Reverse WB traits like neuroticism (OR = 1.60) increased the risk of MU. The lack of well-being characteristics may increase the risk of MU, which highlighted the value of preventive oral care for people who have a reverse mental condition.

scholarly journals Causal Effects of Body Mass Index on Cardiometabolic Traits and Events: A Mendelian Randomization Analysis

2014 ◽  
Vol 94 (2) ◽  
pp. 312 ◽  
Author(s):  
Michael V. Holmes ◽  
Leslie A. Lange ◽  
Tom Palmer ◽  
Matthew B. Lanktree ◽  
Kari E. North ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Mendelian Randomization ◽  
Causal Effects ◽  
Mendelian Randomization Analysis ◽  
Randomization Analysis ◽  
Cardiometabolic Traits

scholarly journals Causal Effect Between Total Cholesterol and HDL Cholesterol as Risk Factors for Chronic Kidney Disease: A Mendelian Randomization Study

2020 ◽  
Author(s):  
Liu Miao ◽  
Yan Min ◽  
Chuan-Meng Zhu ◽  
Jian-Hong Chen ◽  
Bin Qi ◽  
...  
Keyword(s):  
Total Cholesterol ◽  
Serum Lipid ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Hdl Cholesterol ◽  
Causal Effects ◽  
Lipid Levels ◽  
Serum Lipid Levels ◽  
Genome Wide ◽  
Mr Study

Abstract Background/Aims: While observational studies show an association between serum lipid levels and cardiovascular disease (CVD), intervention studies that examine the preventive effects of serum lipid levels on the development of CKD are lacking. Methods: To estimate the role of serum lipid levels in the etiology of CKD, we conducted a two-sample Mendelian randomization (MR) study on serum lipid levels. Single nucleotide polymorphisms (SNPs), which were significantly associated genome-wide with plasma serum lipid levels from the GLGC and CKDGen consortium genome-wide association study (GWAS), including total cholesterol (TC, n = 187365), triglyceride (TG, n = 177861), HDL cholesterol (HDL-C, n = 187167), LDL cholesterol (LDL-C, n = 173082), apolipoprotein A1 (ApoA1, n = 20687), apolipoprotein B (ApoB, n = 20690) and CKD (n = 117165), were used as instrumental variables. None of the lipid-related SNPs was associated with CKD (all P > 0.05). Results: MR analysis genetically predicted the causal effect between TC/HDL-C and CKD. The odds ratio (OR) and 95% confidence interval (CI) of TC within CKD was 0.756 (0.579 to 0.933) (P = 0.002), and HDL-C was 0.85 (0.687 to 1.012) (P = 0.049). No causal effects between TG, LDL-C- ApoA1, ApoB and CKD were observed. Sensitivity analyses confirmed that TC and HDL-C were significantly associated with CKD. Conclusions: The findings from this MR study indicate causal effects between TC, HDL-C and CKD. Decreased TC and elevated HDL-C may reduce the incidence of CKD but need to be further confirmed by using a genetic and environmental approach.

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