scholarly journals Cannabis Use and the Risk of Cardiovascular Diseases: A Mendelian Randomization Study

2021 ◽  
Vol 8 ◽  
Author(s):  
Jianqiang Zhao ◽  
Heng Chen ◽  
Chengui Zhuo ◽  
Shudong Xia

Several observational studies have shown that cannabis use has negative effects on the cardiovascular system, but the causality of this relationship has not been confirmed. The aim of the current study was to estimate the effects of genetically determined cannabis use on risk of cardiovascular diseases. Ten single-nucleotide polymorphisms related to cannabis use were employed as instruments to estimate the association between genetically determined cannabis use and risk of cardiovascular diseases using a two-sample Mendelian randomization (MR) method. Summary statistics data on exposure and outcomes were obtained from different genome-wide association meta-analysis studies. The results of this MR analysis showed no causal effects of cannabis use on the risk of several common cardiovascular diseases, including coronary artery disease, myocardial infarction, stroke and ischemic stroke subtypes, atrial fibrillation (AF), and heart failure. Various sensitivity analyses yielded similar results, and no heterogeneity and directional pleiotropy were observed. After adjusting for tobacco use and body mass index, multivariable MR analysis suggested a causal effect of cannabis use on small vessel stroke (SVS) [odds ratio (OR) 1.17; 95% CI 1.02–1.35; p = 0.03] and AF (OR 1.06; 95% CI 1.01–1.10; p = 0.01), respectively. This two-sample MR study did not demonstrate a causal effect of genetic predisposition to cannabis use on several common cardiovascular outcomes. After adjusting for tobacco use and body mass index, the multivariable MR analysis suggested a detrimental effect of cannabis use on the risk of SVS and AF, respectively.

2020 ◽  
Vol 49 (4) ◽  
pp. 1236-1245 ◽  
Author(s):  
Jean Claude Dusingize ◽  
Catherine M Olsen ◽  
Jiyuan An ◽  
Nirmala Pandeya ◽  
Matthew H Law ◽  
...  

Abstract Background Height and body mass index (BMI) have both been positively associated with melanoma risk, although findings for BMI have been less consistent than height. It remains unclear, however, whether these associations reflect causality or are due to residual confounding by environmental and lifestyle risk factors. We re-evaluated these associations using a two-sample Mendelian randomization (MR) approach. Methods We identified single nucleotide polymorphisms (SNPs) for BMI and height from separate genome-wide association study (GWAS) meta-analyses. We obtained melanoma SNPs from the most recent melanoma GWAS meta-analysis comprising 12 874 cases and 23 203 controls. We used the inverse variance-weighted estimator to derive separate causal risk estimates across all SNP instruments for BMI and height. Results Based on the combined estimate derived from 730 SNPs for BMI, we found no evidence of an association between genetically predicted BMI and melanoma [odds ratio (OR) per one standard deviation (1 SD) (4.6 kg/m2) increase in BMI 1.00, 95% confidence interval (CI): 0.91–1.11]. In contrast, we observed a positive association between genetically-predicted height (derived from a pooled estimate of 3290 SNPs) and melanoma risk [OR 1.08, 95% CI: 1.02–1.13, per 1 SD (9.27 cm) increase in height]. Sensitivity analyses using two alternative MR methods yielded similar results. Conclusions These findings provide no evidence for a causal association between higher BMI and melanoma, but support the notion that height is causally associated with melanoma risk. Mechanisms through which height influences melanoma risk remain unclear, and it remains possible that the effect could be mediated through diverse pathways including growth factors and even socioeconomic status.


2018 ◽  
Vol 64 (1) ◽  
pp. 183-191 ◽  
Author(s):  
Tao Huang ◽  
Ming Ding ◽  
K M Bergholdt Helle ◽  
Tiange Wang ◽  
Yoriko Heianza ◽  
...  

Abstract BACKGROUND Associations between dairy intake and body mass index (BMI) have been inconsistently observed in epidemiological studies, and the causal relationship remains ill defined. METHODS We performed Mendelian randomization (MR) analysis using an established dairy intake-associated genetic polymorphism located upstream of the lactase gene (LCT-13910 C/T, rs4988235) as an instrumental variable (IV). Linear regression models were fitted to analyze associations between (a) dairy intake and BMI, (b) rs4988235 and dairy intake, and (c) rs4988235 and BMI in each study. The causal effect of dairy intake on BMI was quantified by IV estimators among 184802 participants from 25 studies. RESULTS Higher dairy intake was associated with higher BMI (β = 0.03 kg/m2 per serving/day; 95% CI, 0.00–0.06; P = 0.04), whereas the LCT genotype with 1 or 2 T allele was significantly associated with 0.20 (95% CI, 0.14–0.25) serving/day higher dairy intake (P = 3.15 × 10−12) and 0.12 (95% CI, 0.06–0.17) kg/m2 higher BMI (P = 2.11 × 10−5). MR analysis showed that the genetically determined higher dairy intake was significantly associated with higher BMI (β = 0.60 kg/m2 per serving/day; 95% CI, 0.27–0.92; P = 3.0 × 10−4). CONCLUSIONS The present study provides strong evidence to support a causal effect of higher dairy intake on increased BMI among adults.


2018 ◽  
Author(s):  
Amy E. Taylor ◽  
Rebecca C. Richmond ◽  
Teemu Palviainen ◽  
Anu Loukola ◽  
Jaakko Kaprio ◽  
...  

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.


2020 ◽  
Vol 40 (2) ◽  
pp. 156-169 ◽  
Author(s):  
Christoph F. Kurz ◽  
Michael Laxy

Causal effect estimates for the association of obesity with health care costs can be biased by reversed causation and omitted variables. In this study, we use genetic variants as instrumental variables to overcome these limitations, a method that is often called Mendelian randomization (MR). We describe the assumptions, available methods, and potential pitfalls of using genetic information and how to address them. We estimate the effect of body mass index (BMI) on total health care costs using data from a German observational study and from published large-scale data. In a meta-analysis of several MR approaches, we find that models using genetic instruments identify additional annual costs of €280 for a 1-unit increase in BMI. This is more than 3 times higher than estimates from linear regression without instrumental variables (€75). We found little evidence of a nonlinear relationship between BMI and health care costs. Our results suggest that the use of genetic instruments can be a powerful tool for estimating causal effects in health economic evaluation that might be superior to other types of instruments where there is a strong association with a modifiable risk factor.


2021 ◽  
Vol 12 ◽  
Author(s):  
Haoxin Peng ◽  
Xiangrong Wu ◽  
Yaokai Wen ◽  
Yiyuan Ao ◽  
Yutian Li ◽  
...  

Background:Leisure sedentary behaviors (LSB) are widespread, and observational studies have provided emerging evidence that LSB play a role in the development of lung cancer (LC). However, the causal inference between LSB and LC remains unknown.Methods: We utilized univariable (UVMR) and multivariable two-sample Mendelian randomization (MVMR) analysis to disentangle the effects of LSB on the risk of LC. MR analysis was conducted with genetic variants from genome-wide association studies of LSB (408,815 persons from UK Biobank), containing 152 single-nucleotide polymorphisms (SNPs) for television (TV) watching, 37 SNPs for computer use, and four SNPs for driving, and LC from the International Lung Cancer Consortium (11,348 cases and 15,861 controls). Multiple sensitivity analyses were further performed to verify the causality.Results: UVMR demonstrated that genetically predisposed 1.5-h increase in LSB spent on watching TV increased the odds of LC by 90% [odds ratio (OR), 1.90; 95% confidence interval (CI), 1.44–2.50; p < 0.001]. Similar trends were observed for squamous cell lung cancer (OR, 1.97; 95%CI, 1.31–2.94; p = 0.0010) and lung adenocarcinoma (OR, 1.64; 95%CI 1.12–2.39; p = 0.0110). The causal effects remained significant after adjusting for education (OR, 1.97; 95%CI, 1.44–2.68; p < 0.001) and body mass index (OR, 1.86; 95%CI, 1.36–2.54; p < 0.001) through MVMR approach. No association was found between prolonged LSB spent on computer use and driving and LC risk. Genetically predisposed prolonged LSB was additionally correlated with smoking (OR, 1.557; 95%CI, 1.287–1.884; p < 0.001) and alcohol consumption (OR, 1.010; 95%CI, 1.004–1.016; p = 0.0016). Consistency of results across complementary sensitivity MR methods further strengthened the causality.Conclusion: Robust evidence was demonstrated for an independent, causal effect of LSB spent on watching TV in increasing the risk of LC. Further work is necessary to investigate the potential mechanisms.


2018 ◽  
Author(s):  
Kaitlin H Wade ◽  
David Carslake ◽  
Naveed Sattar ◽  
George Davey Smith ◽  
Nicholas J Timpson

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.


2019 ◽  
Vol 77 (1) ◽  
pp. 48-55 ◽  
Author(s):  
Rahman Shiri ◽  
Kobra Falah-Hassani ◽  
Tea Lallukka

The aim of this study was to determine the associations of body mass index (BMI) with all-cause and cause-specific disability retirement. Literature searches were conducted in PubMed, Embase and Web of Science from their inception to May 2019. A total of 27 (25 prospective cohort and 2 nested case-control) studies consisting of 2 199 632 individuals qualified for a meta-analysis. Two reviewers independently assessed the methodological quality of the included studies. We used a random effects meta-analysis, assessed heterogeneity and publication bias, and performed sensitivity analyses. There were a large number of participants and the majority of studies were rated at low or moderate risk of bias. There was a J-shaped relationship between BMI and disability retirement. Underweight (hazard ratio (HR)/risk ratio (RR)=1.20, 95% CI 1.02 to 1.41), overweight (HR/RR=1.13, 95% CI 1.07 to 1.19) and obese individuals (HR/RR=1.52, 95% CI 1.36 to 1.71) were more commonly granted all-cause disability retirement than normal-weight individuals. Moreover, overweight increased the risk of disability retirement due to musculoskeletal disorders (HR/RR=1.26, 95% CI 1.15 to 1.39) and cardiovascular diseases (HR=1.73, 95% CI 1.24 to 2.41), and obesity increased the risk of disability retirement due to musculoskeletal disorders (HR/RR=1.66, 95% CI 1.42 to 1.94), mental disorders (HR=1.29, 95% CI 1.04 to 1.61) and cardiovascular diseases (HR=2.80, 95% CI 1.85 to 4.24). The association between excess body mass and all-cause disability retirement did not differ between men and women and was independent of selection bias, performance bias, confounding and adjustment for publication bias. Obesity markedly increases the risk of disability retirement due to musculoskeletal disorders, cardiovascular diseases and mental disorders. Since the prevalence of obesity is increasing globally, disease burden associated with excess body mass and disability retirement consequently are projected to increase. Reviewregistrationnumber: CRD42018103110.


Allergy ◽  
2017 ◽  
Vol 73 (1) ◽  
pp. 153-164 ◽  
Author(s):  
T. Skaaby ◽  
A. E. Taylor ◽  
B. H. Thuesen ◽  
R. K. Jacobsen ◽  
N. Friedrich ◽  
...  

2016 ◽  
Vol 23 (11) ◽  
pp. 1461-1468 ◽  
Author(s):  
Julia Devorak ◽  
Lauren E Mokry ◽  
John A Morris ◽  
Vincenzo Forgetta ◽  
George Davey Smith ◽  
...  

Background: Mendelian randomization (MR) studies have demonstrated strong support for an association between genetically increased body mass index and risk of multiple sclerosis (MS). The adipokine adiponectin may be a potential mechanism linking body mass to risk of MS. Objective: To evaluate whether genetically increased adiponectin levels influence risk of MS. Methods: Using genome-wide significant single nucleotide polymorphisms (SNPs) for adiponectin, we undertook an MR study to estimate the effect of adiponectin on MS. This method prevents bias due to reverse causation and minimizes bias due to confounding. Sensitivity analyses were performed to evaluate the assumptions of MR. Results: MR analyses did not support a role for genetically elevated adiponectin in risk of MS (odds ratio (OR) = 0.93 per unit increase in natural-log-transformed adiponectin, equivalent to a two-standard deviation increase in adiponectin on the absolute scale; 95% confidence interval (CI) = 0.66–1.33; p = 0.61). Further MR analysis suggested that genetic variation at the adiponectin gene, which influences adiponectin level, does not impact MS risk. Sensitivity analyses, including MR-Egger regression, suggested no bias due to pleiotropy. Conclusion: Lifelong genetically increased adiponectin levels in humans have no clear effect on risk of MS. Other biological factors driving the association between body mass and MS should be investigated.


Sign in / Sign up

Export Citation Format

Share Document