scholarly journals Causal relationships between body mass index, smoking and lung cancer: Univariable and multivariable Mendelian randomization

2020 ◽  
Vol 148 (5) ◽  
pp. 1077-1086 ◽  
Author(s):  
Wen Zhou ◽  
Geoffrey Liu ◽  
Rayjean J. Hung ◽  
Philip C. Haycock ◽  
Melinda C. Aldrich ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Body Mass Index ◽  
Body Mass ◽  
Mendelian Randomization ◽  
Causal Relationships

scholarly journals The causal relevance of body mass index in different histological types of lung cancer: A Mendelian randomization study

2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Robert Carreras-Torres ◽  
Philip C. Haycock ◽  
Caroline L. Relton ◽  
Richard M. Martin ◽  
George Davey Smith ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Body Mass Index ◽  
Body Mass ◽  
Mendelian Randomization ◽  
Causal Relevance ◽  
Histological Types

scholarly journals MR-LDP: a two-sample Mendelian randomization for GWAS summary statistics accounting for linkage disequilibrium and horizontal pleiotropy

2019 ◽  
Author(s):  
Qing Cheng ◽  
Yi Yang ◽  
Xingjie Shi ◽  
Kar-Fu Yeung ◽  
Can Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Body Mass Index ◽  
Linkage Disequilibrium ◽  
Body Mass ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Alternative Methods ◽  
Summary Statistics ◽  
Causal Relationships ◽  
Disease Outcomes

AbstractThe proliferation of genome-wide association studies (GWAS) has prompted the use of two-sample Mendelian randomization (MR) with genetic variants as instrumental variables (IV) for drawing reliable causal relationships between health risk factors and disease outcomes. However, the unique features of GWAS demand that MR methods account for both linkage disequilibrium (LD) and ubiquitously existing horizontal pleiotropy among complex traits, which is the phenomenon wherein a variant affects the outcome through mechanisms other than exclusively through the exposure. Therefore, statistical methods that fail to consider LD and horizontal pleiotropy can lead to biased estimates and false-positive causal relationships. To overcome these limitations, we propose a probabilistic model for MR analysis to identify the casual effects between risk factors and disease outcomes using GWAS summary statistics in the presence of LD and to properly account for horizontal pleiotropy among genetic variants (MR-LDP). MR-LDP utilizes a computationally efficient parameter-expanded variational Bayes expectation-maximization (PX-VBEM) algorithm to estimate the parameter of interest and further calibrates the evidence lower bound (ELBO) for a likelihood ratio test. We then conducted comprehensive simulation studies to demonstrate the advantages of MR-LDP over the existing methods in terms of both type-I error control and point estimates. Moreover, we used two real exposure-outcome pairs (CAD-CAD and Height-Height; CAD for coronary artery disease) to validate the results from MR-LDP compared with alternative methods, showing that our method is more efficient in using all instrumental variants in LD. By further applying MR-LDP to lipid traits and body mass index (BMI) as risk factors for complex diseases, we identified multiple pairs of significant causal relationships, including a protective effect of high-density lipoprotein cholesterol (HDL-C) on peripheral vascular disease (PVD), and a positive causal effect of body mass index (BMI) on hemorrhoids.

Abstract #829: Effect of Body Mass Index (BMI) and Lipids on Non-Small Cell Lung Cancer (NSCLC) Survival

2016 ◽  
Vol 22 ◽  
pp. 176
Author(s):  
Genevieve Streb ◽  
Narjust Duma ◽  
Natasha Piracha ◽  
Sejal Kothadia ◽  
Komal Patel ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Body Mass Index ◽  
Small Cell Lung Cancer ◽  
Body Mass ◽  
Cell Lung Cancer ◽  
Small Cell ◽  
Small Cell Lung

scholarly journals Height and Body Mass Index as Modifiers of Breast Cancer Risk in BRCA1/2 Mutation Carriers: A Mendelian Randomization Study

2018 ◽  
Vol 111 (4) ◽  
pp. 350-364 ◽  
Author(s):  
Frank Qian ◽  
Shengfeng Wang ◽  
Jonathan Mitchell ◽  
Lesley McGuffog ◽  
Daniel Barrowdale ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Body Mass Index ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Body Mass ◽  
Mendelian Randomization ◽  
Mutation Carriers

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 The effect of body mass index on smoking behaviour and nicotine metabolism: a Mendelian randomization study

2018 ◽  
Author(s):  
Amy E. Taylor ◽  
Rebecca C. Richmond ◽  
Teemu Palviainen ◽  
Anu Loukola ◽  
Jaakko Kaprio ◽  
...  
Keyword(s):  
Body Mass Index ◽  
Dna Methylation ◽  
Body Mass ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Smoking Initiation ◽  
Smoking Behaviour ◽  
Bidirectional Association ◽  
Metabolite Ratio ◽  
Nicotine Metabolite Ratio

AbstractBackgroundGiven clear evidence that smoking lowers weight, it is possible that individuals with higher body mass index (BMI) smoke in order to lose or maintain their weight.Methods and FindingsWe undertook Mendelian randomization analyses using 97 genetic variants associated with BMI. We performed two sample Mendelian randomization analyses of the effects of BMI on smoking behaviour in UK Biobank (N=335,921) and the Tobacco and Genetics consortium genomewide association study (GWAS) (N≤74,035) respectively, and two sample Mendelian randomization analyses of the effects of BMI on cotinine levels (N≤4,548) and nicotine metabolite ratio (N≤1,518) in published GWAS, and smoking-related DNA methylation in the Avon Longitudinal Study of Parents and Children (N≤846).In inverse variance weighted Mendelian randomization analysis, there was evidence that higher BMI was causally associated with smoking initiation (OR for ever vs never smoking per one SD increase in BMI: 1.19, 95% CI: 1.11 to 1.27) and smoking heaviness (1.45 additional cigarettes smoked per day per SD increase in BMI, 95% CI: 1.03 to 1.86), but little evidence for a causal effect with smoking cessation. Results were broadly similar using pleiotropy robust methods (MR-Egger, median and weighted mode regression). These results were supported by evidence for a causal effect of BMI on DNA methylation at the aryl-hydrocarbon receptor repressor (AHRR) locus. There was no strong evidence that BMI was causally associated with cotinine, but suggestive evidence for a causal negative association with the nicotine metabolite ratio.ConclusionsThere is a causal bidirectional association between BMI and smoking, but the relationship is likely to be complex due to opposing effects on behaviour and metabolism. It may be useful to consider BMI and smoking together when designing prevention strategies to minimise the effects of these risk factors on health outcomes.

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