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.

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

2020 ◽  
Vol 2 (2) ◽  
Author(s):  
Qing Cheng ◽  
Yi Yang ◽  
Xingjie Shi ◽  
Kar-Fu Yeung ◽  
Can Yang ◽  
...  
Keyword(s):  
Risk Factors ◽  
Linkage Disequilibrium ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Alternative Methods ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Causal Relationships ◽  
Disease Outcomes

Abstract The proliferation of genome-wide association studies (GWAS) has prompted the use of two-sample Mendelian randomization (MR) with genetic variants as instrumental variables (IVs) 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 proposed a probabilistic model for MR analysis in identifying the causal 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) and develop a computationally efficient algorithm to make the causal inference. We then conducted comprehensive simulation studies to demonstrate the advantages of MR-LDP over the existing methods. Moreover, we used two real exposure–outcome pairs 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 on peripheral vascular disease and a positive causal effect of BMI on hemorrhoids.

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

Maternal Hypertension Increases Risk of Preeclampsia and Low Fetal Birthweight: Genetic Evidence From a Mendelian Randomization Study

Hypertension ◽  
2022 ◽  
Author(s):  
Maddalena Ardissino ◽  
Eric A.W. Slob ◽  
Ophelia Millar ◽  
Rohin K. Reddy ◽  
Laura Lazzari ◽  
...  
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Body Mass Index ◽  
Cardiovascular Risk ◽  
Cardiovascular Risk Factors ◽  
Body Mass ◽  
Mendelian Randomization ◽  
European Ancestry ◽  
Increased Risk

Background: Maternal cardiovascular risk factors have been associated with adverse maternal and fetal outcomes. Given the difficulty in establishing causal relationships using epidemiological data, we applied Mendelian randomization to explore the role of cardiovascular risk factors on risk of developing preeclampsia or eclampsia, and low fetal birthweight. Methods: Uncorrelated single-nucleotide polymorphisms associated systolic blood pressure (SBP), body mass index, type 2 diabetes, LDL (low-density lipoprotein) with cholesterol, smoking, urinary albumin-to-creatinine ratio, and estimated glomerular filtration rate at genome-wide significance in studies of 298 957 to 1 201 909 European ancestry participants were selected as instrumental variables. A 2-sample Mendelian randomization study was performed with primary outcome of preeclampsia or eclampsia (PET). Risk factors associated with PET were further investigated for their association with low birthweight. Results: Higher genetically predicted SBP was associated increased risk of PET (odds ratio [OR] per 1-SD SBP increase 1.90 [95% CI=1.45–2.49]; P =3.23×10 −6 ) and reduced birthweight (OR=0.83 [95% CI=0.79–0.86]; P =3.96×10 −18 ), and this was not mediated by PET. Body mass index and type 2 diabetes were also associated with PET (respectively, OR per 1-SD body mass index increase =1.67 [95% CI=1.44–1.94]; P =7.45×10 −12 ; and OR per logOR increase type 2 diabetes =1.11 [95% CI=1.04–1.19]; P =1.19×10 −3 ), but not with reduced birthweight. Conclusions: Our results provide evidence for causal effects of SBP, body mass index, and type 2 diabetes on PET and identify that SBP is associated with reduced birthweight independently of PET. The results provide insight into the pathophysiological basis of PET and identify hypertension as a potentially modifiable risk factor amenable to therapeutic intervention.

scholarly journals Risk factors mediating the effect of body mass index and waist-to-hip ratio on cardiovascular outcomes: Mendelian randomization analysis

2021 ◽  
Author(s):  
Dipender Gill ◽  
Verena Zuber ◽  
Jesse Dawson ◽  
Jonathan Pearson-Stuttard ◽  
Alice R. Carter ◽  
...  
Keyword(s):  
Risk Factors ◽  
Blood Pressure ◽  
Cardiovascular Disease ◽  
Body Mass Index ◽  
Body Mass ◽  
Mendelian Randomization ◽  
European Ancestry ◽  
Standard Deviation Increase ◽  
Waist To Hip Ratio ◽  
Artery Disease

Abstract Background Higher body mass index (BMI) and waist-to-hip ratio (WHR) increase the risk of cardiovascular disease, but the extent to which this is mediated by blood pressure, diabetes, lipid traits, and smoking is not fully understood. Methods Using consortia and UK Biobank genetic association summary data from 140,595 to 898,130 participants predominantly of European ancestry, Mendelian randomization mediation analysis was performed to investigate the degree to which systolic blood pressure (SBP), diabetes, lipid traits, and smoking mediated an effect of BMI and WHR on the risk of coronary artery disease (CAD), peripheral artery disease (PAD) and stroke. Results The odds ratio of CAD per 1-standard deviation increase in genetically predicted BMI was 1.49 (95% CI 1.39 to 1.60). This attenuated to 1.34 (95% CI 1.24 to 1.45) after adjusting for genetically predicted SBP (proportion mediated 27%, 95% CI 3% to 50%), to 1.27 (95% CI 1.17 to 1.37) after adjusting for genetically predicted diabetes (41% mediated, 95% CI 18% to 63%), to 1.47 (95% CI 1.36 to 1.59) after adjusting for genetically predicted lipids (3% mediated, 95% −23% to 29%), and to 1.46 (95% CI 1.34 to 1.58) after adjusting for genetically predicted smoking (6% mediated, 95% CI −20% to 32%). Adjusting for all the mediators together, the estimate attenuated to 1.14 (95% CI 1.04 to 1.26; 66% mediated, 95% CI 42% to 91%). A similar pattern was observed when considering genetically predicted WHR as the exposure, and PAD or stroke as the outcome. Conclusions Measures to reduce obesity will lower the risk of cardiovascular disease primarily by impacting downstream metabolic risk factors, particularly diabetes and hypertension. Reduction of obesity prevalence alongside control and management of its mediators is likely to be most effective for minimizing the burden of obesity.

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

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.

scholarly journals Association of Cardiovascular Risk Factors and Lifestyle Behaviors With Hypertension

Hypertension ◽  
2020 ◽  
Vol 76 (6) ◽  
pp. 1971-1979
Author(s):  
Sabine van Oort ◽  
Joline W.J. Beulens ◽  
Adriana J. van Ballegooijen ◽  
Diederick E. Grobbee ◽  
Susanna C. Larsson
Keyword(s):  
Risk Factors ◽  
Type 2 Diabetes ◽  
Body Mass Index ◽  
Body Mass ◽  
Educational Level ◽  
Mendelian Randomization ◽  
Density Lipoprotein ◽  
Lifestyle Behaviors ◽  
Prevention Of Hypertension

Hypertension is a major risk factor for cardiovascular disease and mortality. To identify targets for the prevention of hypertension and its associated disease burden, we used the 2-sample Mendelian randomization method to investigate the causal associations of 18 cardiovascular risk factors and lifestyle behaviors with hypertension. From European-descent genome-wide association studies, we selected genetic variants ( P <5×10 −8 ) for type 2 diabetes, fasting glucose, lipids, body mass index, smoking, alcohol and coffee consumption, physical activity, sleep duration, insomnia, and educational level. We extracted the genetic associations with hypertension from 2 European cohorts: the FinnGen Study (15 870 cases and 74 345 controls) and UK Biobank (54 358 cases and 408 652 controls). The inverse-variance weighted method was used as main analysis method. Genetically predicted triglycerides (pooled odds ratio [OR] per 1 SD, 1.17 [1.10–1.25]), body mass index (OR per 1 SD, 1.42 [1.37–1.48]), alcohol dependence (OR, 1.10 [1.06–1.13]), and insomnia (OR, 1.17 [1.13–1.20]) were associated with a higher odds of hypertension. Higher genetically predicted high-density lipoprotein cholesterol (OR per 1 SD, 0.88 [0.83–0.94]) and educational level (OR per 1 SD, 0.56 [0.54–0.59]) were associated with a lower odds of hypertension. Suggestive evidence was obtained for type 2 diabetes, smoking initiation and alcohol consumption with a higher hypertension odds, and longer sleep duration with a lower hypertension odds. This Mendelian randomization study identified high-density lipoprotein cholesterol, triglycerides, body mass index, alcohol dependence, insomnia, and educational level as causal risk factors for hypertension. This implicates that these modifiable risk factors are important targets in the prevention of hypertension.

scholarly journals The impact of education inequality on rheumatoid arthritis risk is mediated by smoking and body mass index: mendelian randomization study

2021 ◽  
Author(s):  
Sizheng Steven Zhao ◽  
Michael V Holmes ◽  
Jie Zheng ◽  
Eleanor Sanderson ◽  
Alice R Carter
Keyword(s):  
Risk Factors ◽  
Body Mass Index ◽  
Educational Attainment ◽  
Body Mass ◽  
Mendelian Randomization ◽  
Total Effect ◽  
Smoking Exposure ◽  
Higher Educational ◽  
Higher Educational Attainment ◽  
The Impact

Objective. To estimate the causal relationship between educational attainment - as a proxy for socioeconomic inequality - and risk of RA and quantify the roles of cigarette smoking and body mass index (BMI) as potential mediators. Methods. Using the largest genome-wide association studies (GWAS), we performed a two-sample Mendelian randomization (MR) study of genetically predicted educational attainment (instrumented using 1265 variants from GWAS of 766,345 individuals) and RA (14,361 cases, 43,923 controls). We used two-step MR to quantify the proportion of education's effect on RA mediated by smoking exposure (as a composite index capturing duration, heaviness and cessation, using 124 variants from 462,690 individuals) and BMI (517 variants, 681,275 individuals), and multivariable MR to estimate proportion mediated by both factors combined. Results. Each standard deviation (SD) increase in educational attainment (4.2 years of schooling) was protective of RA (OR 0.37; 95%CI 0.31, 0.44). Higher educational attainment was also protective for smoking exposure (b= -0.25 SD; 95%CI -0.26, -0.23) and BMI (b= -0.27 SD (~1.3kg/m2); 95%CI -0.31, -0.24). Smoking mediated 24% (95%CI 13%, 35%) and BMI 17% (95%CI 11%, 23%) of the total effect of education on RA. Combined, the two risk factors explained 47% (95%CI 11%, 82%) of the total effect. Conclusion. Higher educational attainment has a protective effect on RA risk. Interventions to reduce smoking and excess adiposity at a population level may reduce this risk, but a large proportion of education's effect on RA remains unexplained. Further research into other risk factors that act as potentially modifiable mediators are required.

scholarly journals Elucidation of causal direction between asthma and obesity: a bi-directional Mendelian randomization study

2019 ◽  
Vol 48 (3) ◽  
pp. 899-907 ◽  
Author(s):  
Shujing Xu ◽  
Frank D Gilliland ◽  
David V Conti
Keyword(s):  
Body Mass Index ◽  
Body Mass ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
European Ancestry ◽  
Summary Statistics ◽  
Adult Body Mass ◽  
Causal Direction ◽  
Genome Wide ◽  
Adult Body

Abstract Background Observational associations between asthma and obesity are well established, but inferring causality is challenging. We leveraged publicly available summary statistics to ascertain the causal direction between asthma and obesity via Mendelian randomization in European-ancestry adults. Methods We performed two-sample bi-directional Mendelian randomization analysis using publicly available genome-wide association studies summary statistics. Single nucleotide polymorphisms associated with asthma and body mass index at genome-wide significance were combined using a fixed effect meta-analysis in each direction. An extensive sensitivity analysis was considered. Results There was evidence in support of increasing causal effect of body mass index on risk of asthma (odds ratio 1.18 per unit increase, 95% confidence interval (CI) (1.11, 1.25), P = 2 × 10−8. No significant causal effect of asthma on adult body mass index was observed [estimate −0.004, 95% CI (−0.018, 0.009), P = 0.553]. Conclusions Our results confirmed that in European-ancestry populations, adult body mass index is likely to be causally linked to the risk of asthma; yet the effect of asthma on body mass index is small, if present at all.

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