Composite trait Mendelian randomization reveals distinct metabolic and lifestyle consequences of differences in body shape.
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ABSTRACT:
SUBMITTER: Sulc J
PROVIDER: S-EPMC8438050 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Obesity has been reported to be related to memory impairment and decline in cognitive function, possibly further leading to the development of Alzheimer's disease (AD). However, observational studies revealed both negative and positive associations between body shape (BS) and AD, thereby making it difficult to confirm causality due to residual confounds and reverse causation. Thus, using genome-wide association study summary data, two-sample Mendelian randomization (MR) analyses were applied to identify whether there exists a causal association between BS and AD. BS was measured using anthropometric traits (ATs) in this study, including body mass index (BMI), waist-to-hip ratio (WHR), waist-to-hip ratio adjusted by body mass index (WHRadjBMI), and waist circumference (WC). The associations of single nucleotide polymorphisms (SNP) with each AT and AD were obtained separately from aggregated data from the Genetic Investigation of Anthropometric Traits (GIANT) consortium and International Genomics of Alzheimer's Project (IGAP) summary data (17,008 cases with AD and 37,154 controls). An inverse-variance weighted method was applied to obtain the overall causal estimate for multiple instrumental SNPs. The odds ratio (OR) [95% confidence interval (CI)] for AD risk per 1-SD difference in BMI was 1.04 (0.88, 1.23), in WHR was 1.01 (0.77, 1.33), in WHRadjBMI was 1.12 (0.89, 1.41), and in WC was 1.02 (0.82, 1.27). Furthermore, simulation analyses of survivor bias indicated the overall causal effect of BMI on risk of AD was not biased. In conclusion, the evidence from MR analyses showed no casual effect of BS on AD risk, which is inconsistent with the results from previous observational studies. The biological mechanism underlying the findings warrants further study.
| S-EPMC6795688 | biostudies-literature
Project description:BackgroundBody size (BS) is one of the risk factors for the development of many clinical diseases, but the relationship between BS and glaucoma is controversial. Herein, we try to use Mendelian randomization (MR) method to study BS causal association with glaucoma risk from the genetic level.MethodsThe Body Size was determined through anthropometric traits (ATs), such as body mass index (BMI), waist-to-hip ratio adjusted by body mass index (WHRadjBMI), waist-to-hip ratio (WHR), and waist circumference (WC). Association of single nucleotide polymorphisms (SNPs) with each AT and glaucoma were determined individually from the aggregated data of the Genetic Investigation of Anthropometric Traits (GIANT) consortium and the FinnGen study summary data (8,591 cases with glaucoma and 210,201 controls). To explore the role of BS and glaucoma, a two-sample MR analysis was performed on genome-wide association study (GWAS) data. Besides, three MR methods [inverse variance weighted (IVW), Weighted median, and MR-Egger regression] were used to get the whole causal estimate for multiple instrumental SNPs.ResultsBMI (OR = 1.20; 95% CI = 1.02-1.41; P = 0.03) and WC (OR = 1.32; 95% CI =1.04-1.69; P = 0.03) were associated with a risk of glaucoma. Besides, genetically predicted WHRadjBMI (OR = 1.10; 95% CI = 0.88-1.35; P = 0.43) and WHR (OR = 1.22; 95% CI = 0.93-1,572; P = 0.14) were not associated with glaucoma. No heterogeneity and directional pleiotropy were detected.ConclusionThe data of this study revealed that increased BMI and WC are potential risk factors for glaucoma, and WHRadjBMI and WHR are not associated with the occurrence of glaucoma.
| S-EPMC9538570 | biostudies-literature
Project description:Observational studies have found associations between urinary sodium (UNa) with obesity, body shape and composition; but the findings may be biased by residual confounding. The objective of this two-sample Mendelian randomization (MR) study was to analyze their causal associations in both sex-combined and sex-specific models. Genome-wide association studies of UNa, body mass index (BMI), BMI-adjusted waist-to-hip ratio (WHR), body fat (BF) percentage and estimated glomerular filtration rate (eGFR) were identified. We initially extracted fifty SNPs associated with UNa at significance level of 5?×?10-8, but further removed those SNPs with potential horizontal pleiotropy. Univariable and multivariable MR with adjustment for eGFR were performed. Inverse-variance weighted MR was performed as the primary analysis, with MR-Egger methods as sensitivity analysis. The potential bidirectional association between BMI and UNa was investigated. All exposure and outcomes were continuous, and the effect measure was regression coefficients (beta) and their 95% confidence intervals (95% CI). The total sample size was up to 322 154. UNa was causally associated with increased BMI in both men [eGFR-adjusted beta 0.443 (0.163-0.724)] and women [0.594 (0.333-0.855)]. UNa caused BF percentage increase in men [0.622 (0.268-0.976)] and women [0.334 (0.007-0.662)]. UNa significantly elevated BMI-adjusted WHR in men [0.321 (0.094-0.548)], but not in women [0.170 (- 0.052 to 0.391)]. Additionally, we found that BMI causally increased UNa [0.043 (0.023-0.063)]. UNa increased BMI and BF percentage. Salt intake affects male body shape by increasing BMI-adjusted WHR, but showed no effects on female body shape. The bidirectional association between BMI and UNa suggested that salt reduction measures and weight reduction measures should be implemented simultaneously to break the vicious cycle and gain more health benefits.
| S-EPMC7562909 | biostudies-literature
Project description:A transcriptome-wide association study (TWAS) integrates data from genome-wide association studies and gene expression mapping studies for investigating the gene regulatory mechanisms underlying diseases. Existing TWAS methods are primarily univariate in nature, focusing on analyzing one outcome trait at a time. However, many complex traits are correlated with each other and share a common genetic basis. Consequently, analyzing multiple traits jointly through multivariate analysis can potentially improve the power of TWASs. Here, we develop a method, moPMR-Egger (multiple outcome probabilistic Mendelian randomization with Egger assumption), for analyzing multiple outcome traits in TWAS applications. moPMR-Egger examines one gene at a time, relies on its cis-SNPs that are in potential linkage disequilibrium with each other to serve as instrumental variables, and tests its causal effects on multiple traits jointly. A key feature of moPMR-Egger is its ability to test and control for potential horizontal pleiotropic effects from instruments, thus maximizing power while minimizing false associations for TWASs. In simulations, moPMR-Egger provides calibrated type I error control for both causal effects testing and horizontal pleiotropic effects testing and is more powerful than existing univariate TWAS approaches in detecting causal associations. We apply moPMR-Egger to analyze 11 traits from 5 trait categories in the UK Biobank. In the analysis, moPMR-Egger identified 13.15% more gene associations than univariate approaches across trait categories and revealed distinct regulatory mechanisms underlying systolic and diastolic blood pressures.
| S-EPMC7895847 | biostudies-literature
Project description:Background and purposeAssessing whether modifiable risk factors are causally associated with stroke risk is important in planning public health measures, but determining causality can be difficult in epidemiological data. We evaluated whether modifiable lifestyle factors including educational attainment, smoking, and body mass index are causal risk factors for ischemic stroke and its subtypes and hemorrhagic stroke.MethodsWe performed 2-sample and multivariable Mendelian randomization to assess the causal effect of 12 lifestyle factors on risk of stroke and whether these effects are independent.ResultsGenetically predicted years of education was inversely associated with ischemic, large artery, and small vessel stroke, and intracerebral hemorrhage. Genetically predicted smoking, body mass index, and waist-hip ratio were associated with ischemic and large artery stroke. The effects of education, body mass index, and smoking on ischemic stroke were independent.ConclusionsOur findings support the hypothesis that reduced education and increased smoking and obesity increase risk of ischemic, large artery, and small vessel stroke, suggesting that lifestyle modifications addressing these risk factors will reduce stroke risk.
| S-EPMC7903981 | biostudies-literature
Project description:AimsIncreases in fat-free mass and fat mass have been associated with higher risk of atrial fibrillation (AF) in observational studies. It is not known whether these associations reflect independent causal processes. Our aim was to evaluate independent causal roles of fat-free mass and fat mass on AF.Methods and resultsWe conducted a large observational study to estimate the associations between fat-free mass and fat mass on incident AF in the UK Biobank (N = 487 404, N events = 10 365). Genome-wide association analysis was performed to obtain genetic instruments for Mendelian randomization (MR). We evaluated the causal effects of fat-free mass and fat mass on AF with two-sample method by using genetic associations from AFGen consortium as outcome. Finally, we evaluated independent causal effects of fat-free mass and fat mass with multivariate MR. Both fat-free mass and fat mass had observational associations with incident AF [hazard ratio (HR) = 1.77, 95% confidence interval (CI) 1.72-1.83; HR = 1.40, 95% CI 1.37-1.43 per standard deviation increase in fat-free and fat mass, respectively]. The causal effects using the inverse-variance weighted method were 1.55 (95% CI 1.38-1.75) for fat-free mass and 1.30 (95% CI 1.17-1.45) for fat mass. Weighted median, Egger regression, and penalized methods showed similar estimates. The multivariate MR analysis suggested that the causal effects of fat-free and fat mass were independent of each other (causal risk ratios: 1.37, 95% CI 1.06-1.75; 1.28, 95% CI 1.03-1.58).ConclusionGenetically programmed increases in fat-free mass and fat mass independently cause an increased risk of AF.
| S-EPMC6475522 | biostudies-literature
Project description:The risk factors for nonalcoholic fatty liver disease (NAFLD) have not been clearly identified. We conducted a Mendelian randomization (MR) study to explore this. Independent genetic variants strongly associated with 5 lifestyle and 9 metabolic factors were selected as instrumental variables from corresponding genome-wide association studies (GWASs). Summary-level data for NAFLD were obtained from a GWAS meta-analysis of 8434 cases and 770,180 non-cases (discovery dataset) and another GWAS meta-analysis of 1483 cases and 17,781 non-cases (replication dataset). Univariable and multivariable MR analyses were performed. There were associations with NAFLD for lifetime smoking index (odds ratio (OR) 1.59, 95% confidence interval (CI) 1.31-1.93 per SD-increase), body mass index (BMI, OR 1.33, 95% CI 1.23-1.43 per SD-increase), waist circumference (OR 1.82; 95% CI 1.48-2.24 per SD-increase), type 2 diabetes (OR 1.21, 95% CI 1.15-1.27 per unit increase in log-transformed odds), systolic blood pressure (OR 1.17; 95% CI 1.07-1.26 per 10 mmHg increase), high-density lipoprotein cholesterol (OR 0.84, 95% CI 0.77-0.90 per SD-increase), and triglycerides (OR 1.23, 95% CI 1.15-1.33 per SD-increase). The associations for type 2 diabetes, systolic blood pressure, triglycerides, but not for high-density lipoprotein cholesterol remained strong after adjusting for genetically-predicted BMI. Genetic liability to type 2 diabetes mediated 51.4% (95% CI 13.4-89.3%) of the BMI-effects on NAFLD risk. There were suggestive inverse associations of genetically-predicted alcohol, coffee, and caffeine consumption, and vigorous physical activity with NAFLD risk. This study identified several lifestyle and metabolic factors that may be causally implicated in NAFLD.
| S-EPMC9329390 | biostudies-literature
Project description:Obesity is a highly prevalent risk factor for cardiometabolic diseases. Observational studies suggest that obesity is associated with psychiatric traits, but causal inference from such studies has several limitations. We used two-sample Mendelian randomization methods (inverse variance weighting, weighted median and MR-Egger regression) to evaluate the association of body mass index (BMI) with three psychiatric traits using data from the Genetic Investigation of Anthropometric Traits and Psychiatric Genomics consortia. Causal odds ratio estimates per 1-standard deviation increment in BMI ranged from 0.88 (95% CI: 0.62; 1.25) to 1.23 (95% CI: 0.65; 2.31) for bipolar disorder; 0.93 (0.78; 1.11) to 1.41 (0.87; 2.27) for schizophrenia; and 1.15 (95% CI: 0.92; 1.44) to 1.40 (95% CI: 1.03; 1.90) for major depressive disorder. Analyses removing potentially influential SNPs suggested that the effect estimates for depression might be underestimated. Our findings do not support the notion that higher BMI increases risk of bipolar disorder and schizophrenia. Although the point estimates for depression were consistent in all sensitivity analyses, the overall statistical evidence was weak. However, the fact that SNP-depression associations were estimated in relatively small samples reduced power to detect causal effects. This should be re-addressed when SNP-depression associations from larger studies become available.
| S-EPMC5013405 | biostudies-literature
Project description:BackgroundTestosterone is an essential sex hormone that plays a vital role in the overall health and development of males. It is well known that obesity decreases testosterone levels, but it is difficult to determine the causal relationship between body composition and testosterone.MethodsTo investigate potential causal associations between body composition and testosterone levels by a first time application of Mendelian randomization methods. Exposure variables in men included body composition (fat mass, fat-free mass, and body mass index). In addition to whole body fat and fat-free mass, we examined fat and fat-free mass for each body part (e.g., trunk, left arm, right arm, left leg and right leg) as exposures. Instrumental variables were defined using genome-wide association study data from the UK Biobank. Outcome variables in men included testosterone levels (total testosterone [TT], bioavailable testosterone [BT], and sex hormone-binding globulin [SHBG]). A one-sample Mendelian randomization analysis of inverse-variance weighted and weighted median was performed.ResultsThe number of genetic instruments for the 13 exposure traits related to body composition ranged from 156 to 540. Genetically predicted whole body fat mass was negatively associated with TT (β=-0.24, P=5.2×10-33), BT (β=-0.18, P=5.8×10-20) and SHBG (β=-0.06, P=8.0×10-9). Genetically predicted whole body fat-free mass was negatively associated with BT (β=-0.04, P=2.1×10-4), but not with TT and SHBG, after multiple testing corrections. When comparing the causal effect on testosterone levels, there was a consistent trend that the effect of fat mass was more potent than that of fat-free mass. There were no differences between body parts.ConclusionThese results show that reducing fat mass may increase testosterone levels.
| S-EPMC10711270 | biostudies-literature
Project description:The goal of the study was to identify genes whose aberrant expression can contribute to diabetic retinopathy. We determined differential response in gene expression to high glucose in lymphoblastoid cell lines derived from matched type 1 diabetic individuals with and without retinopathy. Those genes exhibiting the largest difference in glucose response between diabetic subjects with and without retinopathy were assessed for association to diabetic retinopathy utilizing genotype data from a meta-genome-wide association study. All genetic variants associated with gene expression (expression QTLs; eQTLs) of the glucose response genes were tested for association with diabetic retinopathy. We detected an enrichment of the glucose response gene eQTLs among small association p-values for diabetic retinopathy. Among these, we identified FLCN as a susceptibility gene for diabetic retinopathy. Expression of FLCN in response to glucose is greater in individuals with diabetic retinopathy compared to diabetic individuals without retinopathy. Three large, independent cohorts of diabetic individuals revealed an enhanced association of FLCN eQTL to diabetic retinopathy. Mendelian randomization confirmed a direct positive effect of increased FLCN expression on retinopathy in diabetic individuals. Together, our studies integrating genetic association and gene expression implicate FLCN as a disease gene in diabetic retinopathy.
2020-03-10 | GSE146615 | GEO