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

Millard, Louise A C; Davies, Neil M; Tilling, Kate; Gaunt, Tom R.; Smith, George Davey

doi:10.1371/journal.pgen.1007951

Cited by 78 publications

(87 citation statements)

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“…Obesity traits were causally related to higher risk of T2D, in keeping with previous studies (6)(7)(8)(9)(10)(11)19,64). We could not detect a sex difference in risk of T2D from higher WHR or WHRadjBMI.…”

Section: Diabetessupporting

confidence: 89%

“…All obesity traits increased risk of CAD in both sexes, with no difference detected in the magnitude of effect between women and men. The associations with risk of CAD in men and women combined are consistent with previous studies (4,(6)(7)(8)10,11,15,17). While observational studies have indicated that waist-related traits may be more strongly associated with cardiovascular disease in women than men, they have not been conclusive (15,17,76).…”

Section: Cardiovascular Diseasesupporting

confidence: 84%

“…Previous studies have found causal relationships between higher BMI and WHR adjusted for BMI (WHRadjBMI) and type 2 diabetes (T2D) and coronary artery disease (CAD), using a limited number of previously known obesity-associated SNPs (6)(7)(8)(9)(10)(11). However, sex-specific relationships are largely unexplored as is the the role that obesity traits play in the leading causes of death beyond these cardiometabolic diseases.…”

Section: Introductionmentioning

confidence: 99%

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Causal relevance of obesity on the leading causes of death in women and men: A Mendelian randomization study

Censin

Bovijn

Ferreira³

et al. 2019

Preprint

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Obesity traits are causally implicated with risk of cardiometabolic diseases. It remains unclear whether there are similar causal effects of obesity traits on other non-communicable diseases. Also, it is largely unexplored whether there are any sex-specific differences in the causal effects of obesity traits on cardiometabolic diseases and other leading causes of death.We constructed sex-specific genetic risk scores (GRS) for three obesity traits; body mass index (BMI), waist-hip ratio (WHR), and WHR adjusted for BMI, including 565, 324, and 337 genetic variants, respectively. These GRSs were then used as instrumental variables to assess associations between the obesity traits and leading causes of mortality in the UK Biobank using Mendelian randomization. We also investigated associations with potential mediators, including smoking, glycemic and blood pressure traits. Sex-differences were subsequently assessed by Cochran's Q-test (Phet).A Mendelian randomization analysis of 228,466 women and 195,041 men showed that obesity causes coronary artery disease, stroke (particularly ischemic), chronic obstructive pulmonary disease, lung cancer, type 2 and 1 diabetes mellitus, non-alcoholic fatty liver disease, chronic liver disease, and acute and chronic renal failure. Higher BMI led to higher risk of type 2 diabetes in women than in men (Phet=1.4×10 -5 ). Waist-hip-ratio led to a higher risk of chronic obstructive pulmonary disease (Phet=3.7×10 -6 ) and higher risk of chronic renal failure (Phet=1.0×10 -4 ) in men than women.Obesity traits have an etiological role in the majority of the leading global causes of death. Sex differences exist in the effects of obesity traits on risk of type 2 diabetes, chronic obstructive pulmonary disease, and renal failure, which may have downstream implications for public health. 4 Author summaryObesity is increasing globally and has been linked to major causes of death, such as diabetes and heart disease. Still, the causal effects of obesity on other leading causes of death is relatively unexplored. It is also unclear if any such effects differ between men and women.Mendelian randomization is a method that explores causal relationships between traits using genetic data. Using Mendelian randomization, we investigated the effects of obesity traits on leading causes of death and assessed if any such effects differ between men and women.

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Section: Diabetessupporting

confidence: 89%

Section: Cardiovascular Diseasesupporting

confidence: 84%

Section: Introductionmentioning

confidence: 99%

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Causal relevance of obesity on the leading causes of death in women and men: A Mendelian randomization study

Censin

Bovijn

Ferreira³

et al. 2019

Preprint

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“…Milliard et 595 al. perform a large PheWAS study to examine phenotypic associations with BMI that focus on the 596 nervousness phenotypes: the study identified known associations such as diabetes and hypertension 597 (Millard et al 2019). 598…”

Section: Phewas Of Healthy Nevada Bmi and Obesity 592mentioning

confidence: 99%

A Comprehensive Genome-wide and Phenome-wide Examination of BMI and Obesity in a Northern Nevadan Cohort

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Lombardi

et al. 2019

Preprint

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21The aggregation of Election Health Records (EHR) and personalized genetics leads to powerful 22 discoveries relevant to population health. Here we perform genome-wide association studies (GWAS) 23 and accompanying phenome-wide association studies (PheWAS) to validate phenotype-genotype 24 associations of BMI, and to a greater extent, severe Class 2 obesity, using comprehensive diagnostic 25 and clinical data from the EHR database of our cohort. Three GWASs of 500,000 variants on the 26 Illumina platform of 6,645 Healthy Nevada participants identified several published and novel variants 27 that affect BMI and obesity. Each GWAS was followed with two independent PheWASs to examine 28 associations between extensive phenotypes (incidence of diagnoses, condition, or disease), significant 29 SNPs, BMI, and incidence of extreme obesity. The first GWAS excludes DM2-diagnosed individuals 30 and focuses on associations with BMI exclusively. The second GWAS examines the interplay between 31 Type 2 Diabetes (DM2) and BMI. The intersection of significant variants of these two studies is 32 surprising. The third complementary case-control GWAS, with cases defined as extremely obese (Class 33 2 or 3 obesity), identifies strong associations with extreme obesity, including established variants in the 34 FTO and NEGR1 genes, as well as loci not yet linked to obesity. The PheWASs validate published 35 associations between BMI and extreme obesity and incidence of specific diagnoses and conditions, yet 36 also highlight novel links. This study emphasizes the importance of our extensive longitudinal EHR 37 database to validate known associations and identify putative novel links with BMI and obesity. 38 39 2014; Qureshi et al. 2017; Huđek et al. 2018; Gonzalez-Herrera et al. 2018), none, to the best of our 63 knowledge, have included comprehensive GWASs on the quantitative BMI metric and on extreme 64 obesity case-control simultaneously, as well as investigated phenotypic associations with BMI, obesity, 65 and significant loci identified by the GWAS. 66 67 Our study begins with the Healthy Nevada Project (HNP), a project centered around a Northern Nevada 68 cohort formed in 2016 and 2017 by Renown Health and the Desert Research Institute in Reno, NV to 69 4investigate factors that may contribute to health outcomes in Northern Nevada. Its first phase provided 70 10,000 individuals in Northern Nevada with genotyping using the 23andMe platform at no cost. 71Renown Health is the only tertiary care health system in the area, and 75% of these 10,000 individuals 72 are cross-referenced in its extensive electronic health records (EHR) database. The Renown EHR 73 database contains 86,610 BMI measurements for these 10,000 individuals over twelve years, along 74 with comprehensive disease diagnoses, (e.g. diabetes or eating disorders) and other general conditions 75 such as pregnancy, allowing for precise individual phenotypic classifications and thereby leading to 76 more robust and meaningful phenotype-genotype associations. 77 78The focus ...

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“…Mendelian randomization is an approach to assess whether a risk factor has a causal effect on an outcome based on observational data [1,2]. Mendelian randomization can exploit summarized data on genetic associations obtained from genome-wide association studies to link modifiable risk factors to disease outcomes [3,4]. However, the validity of findings from a Mendelian randomization investigation is not guaranteed.…”

Section: Introductionmentioning

confidence: 99%

A robust and efficient method for Mendelian randomization with hundreds of genetic variants: unravelling mechanisms linking HDL-cholesterol and coronary heart disease

Burgess

Allara

Staley

et al. 2019

Preprint

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Mendelian randomization (MR) investigations with large numbers of genetic variants are becoming increasingly common. However, the reliability of findings from a MR investigation is dependent on the validity of the genetic variants as instrumental variables. We developed a method to identify groups of genetic variants with similar causal effect estimates, which may represent distinct mechanisms by which the risk factor influences the outcome. Our contamination mixture method is a robust and efficient method for valid MR in the presence of invalid IVs. Compared to other robust methods, our method had the lowest mean squared error across a range of realistic scenarios. The method is fast and efficient, and can perform analysis with hundreds of variants in a fraction of a second. In a MR analysis for highdensity lipoprotein (HDL) cholesterol and coronary heart disease (CHD) risk, the method identified 11 variants associated with increased HDL-cholesterol, decreased triglyceride levels, and decreased CHD risk that had the same directions of associations with platelet distribution width and other blood cell traits, suggesting a shared mechanism linking lipids and CHD risk relating to platelet aggregation.

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

Cited by 78 publications

References 78 publications

Causal relevance of obesity on the leading causes of death in women and men: A Mendelian randomization study

Causal relevance of obesity on the leading causes of death in women and men: A Mendelian randomization study

A Comprehensive Genome-wide and Phenome-wide Examination of BMI and Obesity in a Northern Nevadan Cohort

A robust and efficient method for Mendelian randomization with hundreds of genetic variants: unravelling mechanisms linking HDL-cholesterol and coronary heart disease

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