Association of Body Mass Index with DNA Methylation and Gene Expression in Blood Cells and Relations to Cardiometabolic Disease: A Mendelian Randomization Approach

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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Selection into shift work is influenced by educational attainment and body mass index: A Mendelian randomization study

10.1101/2020.03.10.20032698 ◽

2020 ◽

Author(s):

Iyas Daghlas ◽

Rebecca C. Richmond ◽

Jacqueline M. Lane ◽

Hassan S. Dashti ◽

Hanna M. Ollila ◽

...

Keyword(s):

Risk Factors ◽

Body Mass Index ◽

Educational Attainment ◽

Body Mass ◽

Shift Work ◽

Cardiometabolic Risk ◽

Mendelian Randomization ◽

Cardiometabolic Risk Factors ◽

Cardiometabolic Disease ◽

Sleep Timing

AbstractBackgroundShift work is associated with increased cardiometabolic disease risk, but whether this association is influenced by cardiometabolic risk factors driving selection into shift work is currently unclear. We addressed this question using Mendelian randomization (MR) in the UK Biobank.MethodsWe created genetic risk scores (GRS) associating with nine cardiometabolic risk factors (including education, body mass index [BMI], smoking, and alcohol consumption), and tested associations of each GRS with self-reported current frequency of shift work and night shift work amongst employed UKB participants of European ancestry (n=190,573). We used summary-level MR sensitivity analyses and multivariable MR to probe robustness of the identified effects, and tested whether effects were mediated through sleep timing preference.ResultsGenetically instrumented lower educational attainment and higher body mass index increased odds of reporting frequent shift work (odds ratio [OR] per 3.6 years [1-SD] decrease in educational attainment=2.40, 95% confidence interval [CI]=2.22-2.59, p=4.84 × 10−20; OR per 4.7kg/m2 [1-SD] increase in BMI=1.30, 95%CI=1.14-1.47, p=5.85 × 10−05). Results were unchanged in sensitivity analyses allowing for different assumptions regarding horizontal pleiotropy, and the effects of education and BMI were independent in multivariable MR. No causal effects were evident for the remaining factors, nor for any exposures on selection out of shift work. Sleep timing preference did not mediate any causal effects.ConclusionsEducational attainment and BMI may influence selection into shift work, which may have implications for epidemiologic associations of shift work with cardiometabolic disease.Key messagesAlthough it has been hypothesized that cardiometabolic risk factors and diseases may influence selection into shift work, little evidence for such an effect is currently available.Using Mendelian randomization, we assessed whether cardiometabolic risk factors and diseases influenced selection into or out of shift work in the UK Biobank.Our results were consistent with a causal effect of both higher BMI and lower educational attainment on selection into current shift work, with stronger effects seen for shift work that is more frequent and includes more night shifts.Using multivariable Mendelian randomization, we found that effects of higher BMI and lower education were independent. Sleep timing preference had a null effect on shift work selection and therefore did not mediate these effects.Selection through education and BMI may bias the relationship of shift work with cardiometabolic disease. Social mechanisms underlying these effects warrant further investigation.

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Integrative analysis of gene expression, DNA methylation, physiological traits, and genetic variation in human skeletal muscle

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.1814263116 ◽

2019 ◽

Vol 116 (22) ◽

pp. 10883-10888 ◽

Cited By ~ 18

Author(s):

D. Leland Taylor ◽

Anne U. Jackson ◽

Narisu Narisu ◽

Gibran Hemani ◽

Michael R. Erdos ◽

...

Keyword(s):

Gene Expression ◽

Skeletal Muscle ◽

Body Mass Index ◽

Dna Methylation ◽

Body Mass ◽

Muscle Fiber ◽

Quantitative Trait ◽

Human Skeletal Muscle ◽

Fiber Type ◽

Genetic Associations

We integrate comeasured gene expression and DNA methylation (DNAme) in 265 human skeletal muscle biopsies from the FUSION study with >7 million genetic variants and eight physiological traits: height, waist, weight, waist–hip ratio, body mass index, fasting serum insulin, fasting plasma glucose, and type 2 diabetes. We find hundreds of genes and DNAme sites associated with fasting insulin, waist, and body mass index, as well as thousands of DNAme sites associated with gene expression (eQTM). We find that controlling for heterogeneity in tissue/muscle fiber type reduces the number of physiological trait associations, and that long-range eQTMs (>1 Mb) are reduced when controlling for tissue/muscle fiber type or latent factors. We map genetic regulators (quantitative trait loci; QTLs) of expression (eQTLs) and DNAme (mQTLs). Using Mendelian randomization (MR) and mediation techniques, we leverage these genetic maps to predict 213 causal relationships between expression and DNAme, approximately two-thirds of which predict methylation to causally influence expression. We use MR to integrate FUSION mQTLs, FUSION eQTLs, and GTEx eQTLs for 48 tissues with genetic associations for 534 diseases and quantitative traits. We identify hundreds of genes and thousands of DNAme sites that may drive the reported disease/quantitative trait genetic associations. We identify 300 gene expression MR associations that are present in both FUSION and GTEx skeletal muscle and that show stronger evidence of MR association in skeletal muscle than other tissues, which may partially reflect differences in power across tissues. As one example, we find that increased RXRA muscle expression may decrease lean tissue mass.

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Resistin levels and its relation with body mass index and hydrogen peroxide production in blood cells from diabetic periodontal patients

10.26226/morressier.5ac3831d2afeeb00097a4004 ◽

2018 ◽

Author(s):

Isabel Baptista

Keyword(s):

Body Mass Index ◽

Hydrogen Peroxide ◽

Body Mass ◽

Blood Cells ◽

Hydrogen Peroxide Production

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

JNCI Journal of the National Cancer Institute ◽

10.1093/jnci/djy132 ◽

2018 ◽

Vol 111 (4) ◽

pp. 350-364 ◽

Cited By ~ 7

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

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

The American Journal of Human Genetics ◽

10.1016/j.ajhg.2014.01.012 ◽

2014 ◽

Vol 94 (2) ◽

pp. 312 ◽

Cited By ~ 1

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

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Assessing the robustness of sisVIVE in a Mendelian randomization study to estimate the causal effect of body mass index on income using multiple SNPs from understanding society

Statistics in Medicine ◽

10.1002/sim.8066 ◽

2018 ◽

Vol 38 (9) ◽

pp. 1529-1542 ◽

Cited By ~ 2

Author(s):

Yanchun Bao ◽

Paul S. Clarke ◽

Melissa Smart ◽

Meena Kumari

Keyword(s):

Body Mass Index ◽

Body Mass ◽

Mendelian Randomization ◽

Causal Effect ◽

Multiple Snps

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The Relationship between Body Mass Index, Obesity, and LINE-1 Methylation: A Cross-Sectional Study on Women from Southern Italy

Disease Markers ◽

10.1155/2021/9910878 ◽

2021 ◽

Vol 2021 ◽

pp. 1-7

Author(s):

Andrea Maugeri ◽

Martina Barchitta ◽

Roberta Magnano San Lio ◽

Giuliana Favara ◽

Claudia La Mastra ◽

...

Keyword(s):

Body Mass Index ◽

Dna Methylation ◽

Body Mass ◽

Methylation Level ◽

Molecular Mechanisms ◽

Smoking Status ◽

Cross Sectional Study ◽

Sectional Study ◽

Cross Sectional ◽

The Relationship

Uncovering the relationship between body mass index (BMI) and DNA methylation could be useful to understand molecular mechanisms underpinning the effects of obesity. Here, we presented a cross-sectional study, aiming to evaluate the association of BMI and obesity with long interspersed nuclear elements (LINE-1) methylation, among 488 women from Catania, Italy. LINE-1 methylation was assessed in leukocyte DNA by pyrosequencing. We found a negative association between BMI and LINE-1 methylation level in both the unadjusted and adjusted linear regression models. Accordingly, obese women exhibited lower LINE-1 methylation level than their normal weight counterpart. This association was confirmed after adjusting for the effect of age, educational level, employment status, marital status, parity, menopause, and smoking status. Our findings were in line with previous evidence and encouraged further research to investigate the potential role of DNA methylation markers in the management of obesity.

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