Commentary: Tobacco consumption and body weight: Mendelian randomization across a range of exposure.
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ABSTRACT:
SUBMITTER: Dudbridge F
PROVIDER: S-EPMC5841830 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background: Alcohol consumption and smoking, 2 major risk factors for cardiovascular disease (CVD), often occur together. The objective of this study is to use a wide range of CVD risk factors and outcomes to evaluate potential total and direct causal roles of alcohol and tobacco use on CVD risk factors and events.Methods and findings: Using large publicly available genome-wide association studies (GWASs) (results from more than 1.2 million combined study participants) of predominantly European ancestry, we conducted 2-sample single-variable Mendelian randomization (SVMR) and multivariable Mendelian randomization (MVMR) to simultaneously assess the independent impact of alcohol consumption and smoking on a wide range of CVD risk factors and outcomes. Multiple sensitivity analyses, including complementary Mendelian randomization (MR) methods, and secondary alcohol consumption and smoking datasets were used. SVMR showed genetic predisposition for alcohol consumption to be associated with CVD risk factors, including high-density lipoprotein cholesterol (HDL-C) (beta 0.40, 95% confidence interval (CI), 0.04-0.47, P value = 1.72 × 10-28), triglycerides (TRG) (beta -0.23, 95% CI, -0.30, -0.15, P value = 4.69 × 10-10), automated systolic blood pressure (BP) measurement (beta 0.11, 95% CI, 0.03-0.18, P value = 4.72 × 10-3), and automated diastolic BP measurement (beta 0.09, 95% CI, 0.03-0.16, P value = 5.24 × 10-3). Conversely, genetically predicted smoking was associated with increased TRG (beta 0.097, 95% CI, 0.014-0.027, P value = 6.59 × 10-12). Alcohol consumption was also associated with increased myocardial infarction (MI) and coronary heart disease (CHD) risks (MI odds ratio (OR) = 1.24, 95% CI, 1.03-1.50, P value = 0.02; CHD OR = 1.21, 95% CI, 1.01-1.45, P value = 0.04); however, its impact was attenuated in MVMR adjusting for smoking. Conversely, alcohol maintained an association with coronary atherosclerosis (OR 1.02, 95% CI, 1.01-1.03, P value = 5.56 × 10-4). In comparison, after adjusting for alcohol consumption, smoking retained its association with several CVD outcomes including MI (OR = 1.84, 95% CI, 1.43, 2.37, P value = 2.0 × 10-6), CHD (OR = 1.64, 95% CI, 1.28-2.09, P value = 8.07 × 10-5), heart failure (HF) (OR = 1.61, 95% CI, 1.32-1.95, P value = 1.9 × 10-6), and large artery atherosclerosis (OR = 2.4, 95% CI, 1.41-4.07, P value = 0.003). Notably, using the FinnGen cohort data, we were able to replicate the association between smoking and several CVD outcomes including MI (OR = 1.77, 95% CI, 1.10-2.84, P value = 0.02), HF (OR = 1.67, 95% CI, 1.14-2.46, P value = 0.008), and peripheral artery disease (PAD) (OR = 2.35, 95% CI, 1.38-4.01, P value = 0.002). The main limitations of this study include possible bias from unmeasured confounders, inability of summary-level MR to investigate a potentially nonlinear relationship between alcohol consumption and CVD risk, and the generalizability of the UK Biobank (UKB) to other populations.Conclusions: Evaluating the widest range of CVD risk factors and outcomes of any alcohol consumption or smoking MR study to date, we failed to find a cardioprotective impact of genetically predicted alcohol consumption on CVD outcomes. However, alcohol was associated with and increased HDL-C, decreased TRG, and increased BP, which may indicate pathways through impact CVD risk, warranting further study. We found smoking to be a risk factor for many CVDs even after adjusting for alcohol. While future studies incorporating alcohol consumption patterns are necessary, our data suggest causal inference between alcohol, smoking, and CVD risk, further supporting that lifestyle modifications might be able to reduce overall CVD risk.
| S-EPMC7717538 | biostudies-literature
Project description:Background: Adenosine triphosphate-citrate lyase (ACLY) inhibition has proven clinically efficacious for low-density lipoprotein cholesterol (LDL-c) lowering and cardiovascular disease (CVD) risk reduction. Clinical and genetic evidence suggests that some LDL-c lowering strategies, such as 3-hydroxy-3-methylglutaryl-coenzyme A reductase (HMGCR) inhibition with statin therapy increase body weight and the risk of developing type 2 diabetes mellitus (T2DM). However, whether ACLY inhibition affects metabolic risk factors is currently unknown. We aimed to investigate the effects of ACLY inhibition on glycaemic and anthropometric traits using Mendelian randomization (MR). Methods: As genetic instruments for ACLY inhibition, we selected weakly correlated single-nucleotide polymorphisms at the ACLY gene associated with lower ACLY gene expression in the eQTLGen study (N = 31,684) and lower LDL-c levels in the Global Lipid Genetic Consortium study (N = 1.65 million). Two-sample Mendelian randomization was employed to investigate the effects of ACLY inhibition on T2DM risk, and glycaemic and anthropometric traits using summary data from large consortia, with sample sizes ranging from 151,013 to 806,834 individuals. Findings for genetically predicted ACLY inhibition were compared to those obtained for genetically predicted HMGCR inhibition using the same instrument selection strategy and outcome data. Results: Primary MR analyses showed that genetically predicted ACLY inhibition was associated with lower waist-to-hip ratio (β per 1 standard deviation lower LDL-c: -1.17; 95% confidence interval (CI): -1.61 to -0.73; p < 0.001) but not with risk of T2DM (odds ratio (OR) per standard deviation lower LDL-c: 0.74, 95% CI = 0.25 to 2.19, p = 0.59). In contrast, genetically predicted HMGCR inhibition was associated with higher waist-to-hip ratio (β = 0.15; 95%CI = 0.04 to 0.26; p = 0.008) and T2DM risk (OR = 1.73, 95% CI = 1.27 to 2.36, p < 0.001). The MR analyses considering secondary outcomes showed that genetically predicted ACLY inhibition was associated with a lower waist-to-hip ratio adjusted for body mass index (BMI) (β = -1.41; 95%CI = -1.81 to -1.02; p < 0.001). In contrast, genetically predicted HMGCR inhibition was associated with higher HbA1c (β = 0.19; 95%CI = 0.23 to 0.49; p < 0.001) and BMI (β = 0.36; 95%CI = 0.23 to 0.49; p < 0.001). Conclusions: Human genetic evidence supports the metabolically favourable effects of ACLY inhibition on body weight distribution, in contrast to HMGCR inhibition. These findings should be used to guide and prioritize ongoing clinical development efforts.
| S-EPMC11353272 | biostudies-literature
Project description:ObjectiveThe relationship between tobacco smoke exposure (TSE) and depression is controversial. This study combined observational research and Mendelian randomization (MR) to explore the relationship of depression with both smoking status and cotinine levels.MethodWe collected relevant data from the National Health and Nutrition Examination Survey (NHANES) database from 2005 to 2018, and used weighted multifactorial logistic regression modelling to assess the correlation between TSE and depression, and assessed the causal relationship of depression with both smoking status and cotinine levels by MR.ResultCurrent smokers had the highest risk of depression (OR 1.94; P < 0.01); there was a positive trend for correlation between daily smoking and depression (OR 1.66; P for trend < 0.01). Serum ketamine levels above 3.00 ng/ml had a higher risk of depression (OR 2.13; P < 0.001). MR results showed that current smoking (OR = 4.66; P < 0.001) and previous smoking (OR 2.09; P < 0.01) were risk factors for the onset of depression, and that there was no causal association between cotinine levels and depression.ConclusionSmoking is significantly associated with depression and plays a potential causal role in the development of depression. Cotinine was significantly associated with depression, however MR results showed no causal relationship between cotinine and depression.
| S-EPMC11221044 | biostudies-literature
Project description: Not available
| S-EPMC4190520 | biostudies-literature
Project description:Habitual coffee and caffeine consumption has been reported to be associated with numerous health outcomes. This perspective focuses on Mendelian Randomization (MR) approaches for determining whether such associations are causal. Genetic instruments for coffee and caffeine consumption are described, along with key concepts of MR and particular challenges when applying this approach to studies of coffee and caffeine. To date, at least fifteen MR studies have investigated the causal role of coffee or caffeine use on risk of type 2 diabetes, cardiovascular disease, Alzheimer's disease, Parkinson's disease, gout, osteoarthritis, cancers, sleep disturbances and other substance use. Most studies provide no consistent support for a causal role of coffee or caffeine on these health outcomes. Common study limitations include low statistical power, potential pleiotropy, and risk of collider bias. As a result, in many cases a causal role cannot confidently be ruled out. Conceptual challenges also arise from the different aspects of coffee and caffeine use captured by current genetic instruments. Nevertheless, with continued genome-wide searches for coffee and caffeine related loci along with advanced statistical methods and MR designs, MR promises to be a valuable approach to understanding the causal impact that coffee and caffeine have in human health.
| S-EPMC6213346 | biostudies-literature
Project description:BackgroundCoffee is one of the most consumed beverages in the world, coffee consumption has been growing in the United States over the past 20 years. Periodontitis is defined by the pathologic loss of the periodontal ligament and destruction of the connective tissue attachment and alveolar bone loss and is related to different systemic diseases and conditions. However, the causality has remained unclarified, thus we regarded discovering the causal relationship between coffee consumption and the liability to periodontitis as the objective of the study.MethodsCoffee consumption was subdivided into binary coffee consumption and continuous coffee consumption to refine the study design. Genetic instruments were stretched from the MRC-IEU's (MRC Integrative Epidemiology Unit) output from the GWAS pipeline using phesant-derived variables based on the UK Biobank, the Gene-Lifestyle Interactions in Dental Endpoints (GLIDE) project, and the joint meta-analysis of a recent GWAS. The IVW (Inverse Variance Weighted) was regarded as the primary method to estimate the causality, a scatter plot revealed the intuitive result, and tests for stability were also carried out.ResultsAn effect of continuous coffee consumption on the risk of periodontitis was found, with per SD of coffee consumed increases, the risk of periodontitis rises by 1.04% (Odds Ratio of IVW is 1.0104), while the effect of binary coffee consumption on periodontitis did not meet the requirement of indicating a strong causal association, neither were the reverse causality analyses.ConclusionsThe study indicated the causality of continuous coffee consumption to the risk of periodontitis with a relatively small scale of effect estimate and no strong evidence for an effect of binary coffee-consuming behavior on periodontitis. There was also no intensive evidence suggesting reverse causality.
| S-EPMC10492363 | biostudies-literature
Project description: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 (? = 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 (? = 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.
| S-EPMC5837824 | biostudies-literature
Project description:Background: Observational evidence has shown that smoking, alcohol consumption, type 2 diabetes, and body mass index (BMI) are risk factors for peptic ulcer disease (PUD), including gastric ulcer (GU) and duodenal ulcer (DU). However, the observed associations may be confounding factors. Herein, we use Mendelian randomization (MR) to examine causal associations such as smoking, alcohol, type 2 diabetes, BMI, and risks of PUD. Methods: We used 8,17,41,325,82, 231, and 616 identified genetic variants as proxies for age of smoking initiation (AgeSmk), smoking cessation (SmkCes, current/former), number of cigarettes smoked per day (CigDay), smoking status (SmkIni, ever/never), alcohol consumption, type 2 diabetes, and BMI to obtain unconfounded effect estimates on the GU and DU levels among 452,264 participants from the Gene ATLAS. The causal relationship was estimated by using inverse-variance weighted (IVW) as the main method. Sensitivity analysis includes Cochran's Q test, the MR-Egger test, MR pleiotropy residual sum and outlier (MR-PRESSO), and MR-robust adjusted profile score (MR-RAPS). In addition, secondary MR analysis was conducted within summary data using genetic risk scores (GRSs) as instrumental variables (IVs). Results: In our two-sample MR analyses, genetic predisposition to smoking (SmkInit) and BMI were associated with an increased risk of GU. The beta values were 0.0035 (95% CI, 0.0021, 0.0049, p = 1.56E-06) for smoking (SmkInit) and 0.0021 (95% CI, 0.0009, 0.0033, p = 0.0008) for BMI. Genetic predisposition to smoking (SmkInit) and higher genetically predicted BMI were associated with an increased risk of DU. The beta values of DU were 0.0029 (95% CI, 0.0017, 0.0041, p = 2.43E-06) for smoking (SmkInit) and 0.0018 (95% CI, 0.0007, 0.0029, p = 0.001) for BMI. No other causal association between smoking (AgeSmk, CigDay, and SmkCes), alcohol consumption, type 2 diabetes, and GU or DU was observed. Consistent results were obtained in sensitivity analyses. Furthermore, the GRS approach showed similar results in the several MR methods. Conclusion: These findings do not support a causal role of AgeSmk, CigDay, SmkCes, alcohol consumption, and type 2 diabetes in the development of GU and DU. However, it is confirmed that SmkInit and BMI have a causal part in the development of GU and DU.
| S-EPMC9852705 | biostudies-literature
Project description:To use Mendelian randomization to assess whether alcohol intake was causally associated with cognitive function.Mendelian randomization using a genetic variant related to alcohol intake (ADH1B rs1229984) was used to obtain unbiased estimates of the association between alcohol intake and cognitive performance.Europe.More than 34?000 adults.Any versus no alcohol intake and units of intake in the previous week was measured by questionnaire. Cognitive function was assessed in terms of immediate and delayed word recall, verbal fluency and processing speed.Having consumed any versus no alcohol was associated with higher scores by 0.17 standard deviations (SD) [95% confidence interval (CI)?=?0.15, 0.20] for immediate recall, 0.17 SD (95% CI?=?0.14, 0.19) for delayed recall, 0.17 SD (95% CI?=?0.14, 0.19) for verbal fluency and 0.12 SD (95% CI?=?0.09, 0.15) for processing speed. The minor allele of rs1229984 was associated with reduced odds of consuming any alcohol (odds ratio?=?0.87; 95% CI?=?0.80, 0.95; P?=?0.001; R(2) ?=?0.1%; F-statistic?=?47). In Mendelian randomization analysis, the minor allele was not associated with any cognitive test score, and instrumental variable analysis suggested no causal association between alcohol consumption and cognition: -0.74 SD (95% CI?=?-1.88, 0.41) for immediate recall, -1.09 SD (95% CI?=?-2.38, 0.21) for delayed recall, -0.63 SD (95% CI?=?-1.78, 0.53) for verbal fluency and -0.16 SD (95% CI?=?-1.29, 0.97) for processing speed.The Mendelian randomization analysis did not provide strong evidence of a causal association between alcohol consumption and cognitive ability.
| S-EPMC4309480 | biostudies-literature
Project description:BackgroundThe causal role of alcohol consumption for cardiovascular disease remains unclear. We used Mendelian randomization (MR) to predict the effect of alcohol consumption on 8 cardiovascular diseases.MethodsUp to 94 single-nucleotide polymorphisms were used as instrumental variables for alcohol consumption. Genetic association estimates for cardiovascular diseases were obtained from large-scale consortia and UK Biobank. Analyses were conducted using the inverse variance-weighted, weighted median, MR-PRESSO, MR-Egger, and multivariable MR methods.ResultsGenetically predicted alcohol consumption was consistently associated with stroke and peripheral artery disease across the different analyses. The odds ratios (ORs) per 1-SD increase of log-transformed alcoholic drinks per week were 1.27 ([95% CI, 1.12-1.45] P=2.87×10-4) for stroke and 3.05 ([95% CI, 1.92-4.85] P=2.30×10-6) for peripheral artery disease in the inverse variance-weighted analysis. There was some evidence for positive associations of genetically predicted alcohol consumption with coronary artery disease (OR, 1.16 [95% CI, 1.00-1.36]; P=0.052), atrial fibrillation (OR, 1.17 [95% CI, 1.00-1.37]; P=0.050), and abdominal aortic aneurysm (OR, 2.60 [95% CI, 1.15-5.89]; P=0.022) in the inverse variance-weighted analysis. These associations were somewhat attenuated in multivariable MR analysis adjusted for smoking initiation. There was no evidence of associations of genetically predicted alcohol consumption with heart failure (OR, 1.00 [95% CI, 0.68-1.47]; P=0.996), venous thromboembolism (OR, 1.04 [95% CI, 0.77-1.39]; P=0.810), and aortic valve stenosis (OR, 1.03 [95% CI, 0.56-1.90]; P=0.926).ConclusionsThis study provides evidence of a causal relationship between higher alcohol consumption and increased risk of stroke and peripheral artery disease. The causal role of alcohol consumption for other cardiovascular diseases requires further research.
| S-EPMC7299220 | biostudies-literature