scholarly journals Debiased inverse-variance weighted estimator in two-sample summary-data Mendelian randomization

2021 ◽  
Vol 49 (4) ◽  
Author(s):  
Ting Ye ◽  
Jun Shao ◽  
Hyunseung Kang
Keyword(s):  
Mendelian Randomization ◽  
Weighted Estimator ◽  
Inverse Variance ◽  
Summary Data

scholarly journals Software application profile: mrrobust—a tool for performing two-sample summary Mendelian randomization analyses

2018 ◽  
Vol 48 (3) ◽  
pp. 684-690 ◽  
Author(s):  
Wes Spiller ◽  
Neil M Davies ◽  
Tom M Palmer
Keyword(s):  
Mendelian Randomization ◽  
Association Studies ◽  
Estimation Methods ◽  
Genome Wide Association Studies ◽  
Software Application ◽  
Genome Wide ◽  
Inverse Variance ◽  
Randomization Analysis ◽  
Summary Data ◽  
Weighted Estimation

Abstract Motivation In recent years, Mendelian randomization analysis using summary data from genome-wide association studies has become a popular approach for investigating causal relationships in epidemiology. The mrrobust Stata package implements several of the recently developed methods. Implementation mrrobust is freely available as a Stata package. General features The package includes inverse variance weighted estimation, as well as a range of median, modal and MR-Egger estimation methods. Using mrrobust, plots can be constructed visualizing each estimate either individually or simultaneously. The package also provides statistics such as IGX2, which are useful in assessing attenuation bias in causal estimates. Availability The software is freely available from GitHub [https://raw.github.com/remlapmot/mrrobust/master/].

scholarly journals Combining the strengths of inverse-variance weighting and Egger regression in Mendelian randomization using a mixture of regressions model

PLoS Genetics ◽  
2021 ◽  
Vol 17 (11) ◽  
pp. e1009922
Author(s):  
Zhaotong Lin ◽  
Yangqing Deng ◽  
Wei Pan
Keyword(s):  
Large Scale ◽  
Type I Error ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Type I ◽  
Perturbation Scheme ◽  
Analysis Model ◽  
Component Mixture ◽  
Inverse Variance ◽  
Summary Data

With the increasing availability of large-scale GWAS summary data on various traits, Mendelian randomization (MR) has become commonly used to infer causality between a pair of traits, an exposure and an outcome. It depends on using genetic variants, typically SNPs, as instrumental variables (IVs). The inverse-variance weighted (IVW) method (with a fixed-effect meta-analysis model) is most powerful when all IVs are valid; however, when horizontal pleiotropy is present, it may lead to biased inference. On the other hand, Egger regression is one of the most widely used methods robust to (uncorrelated) pleiotropy, but it suffers from loss of power. We propose a two-component mixture of regressions to combine and thus take advantage of both IVW and Egger regression; it is often both more efficient (i.e. higher powered) and more robust to pleiotropy (i.e. controlling type I error) than either IVW or Egger regression alone by accounting for both valid and invalid IVs respectively. We propose a model averaging approach and a novel data perturbation scheme to account for uncertainties in model/IV selection, leading to more robust statistical inference for finite samples. Through extensive simulations and applications to the GWAS summary data of 48 risk factor-disease pairs and 63 genetically uncorrelated trait pairs, we showcase that our proposed methods could often control type I error better while achieving much higher power than IVW and Egger regression (and sometimes than several other new/popular MR methods). We expect that our proposed methods will be a useful addition to the toolbox of Mendelian randomization for causal inference.

scholarly journals Software Application Profile: mrrobust - a tool for performing two-sample summary Mendelian randomization analyses

2017 ◽  
Author(s):  
Wesley Spiller ◽  
Neil M. Davies ◽  
Tom M. Palmer
Keyword(s):  
Mendelian Randomization ◽  
Association Studies ◽  
Estimation Methods ◽  
Genome Wide Association Studies ◽  
Software Application ◽  
Genome Wide ◽  
Inverse Variance ◽  
Randomization Analysis ◽  
Summary Data ◽  
Weighted Estimation

AbstractMotivationIn recent years Mendelian randomization analysis using summary data from genome-wide association studies has become a popular approach for investigating causal relationships in epidemiology. The mrrobust Stata package implements several of the recently developed methods.Implementationmrrobust is freely available as a Stata package.General FeaturesThe package includes inverse variance weighted estimation, as well as a range of median and MR-Egger estimation methods. Using mrrobust, plots can be constructed visualising each estimate either individually or simultaneously. The package also provides statistics such as which are useful in assessing attenuation bias in causal estimates.AvailabilityThe software is freely available from GitHub [https://raw.github.com/remlapmot/mrrobust/master/].

scholarly journals A Mendelian randomization analysis of the relationship between cardioembolic risk factors and ischemic stroke

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Danyang Tian ◽  
Linjing Zhang ◽  
Zhenhuang Zhuang ◽  
Tao Huang ◽  
Dongsheng Fan
Keyword(s):  
Risk Factors ◽  
Ischemic Stroke ◽  
Mendelian Randomization ◽  
P Wave ◽  
Cardioembolic Stroke ◽  
Large Artery ◽  
Weighted Analysis ◽  
Inverse Variance ◽  
Weighted Median ◽  
Genetically Determined

AbstractObservational studies have shown that several risk factors are associated with cardioembolic stroke. However, whether such associations reflect causality remains unknown. We aimed to determine whether established and provisional cardioembolic risk factors are causally associated with cardioembolic stroke. Genetic instruments for atrial fibrillation (AF), myocardial infarction (MI), electrocardiogram (ECG) indices and N-terminal pro-brain natriuretic peptide (NT-pro BNP) were obtained from large genetic consortiums. Summarized data of ischemic stroke and its subtypes were extracted from the MEGASTROKE consortium. Causal estimates were calculated by applying inverse-variance weighted analysis, weighted median analysis, simple median analysis and Mendelian randomization (MR)-Egger regression. Genetically predicted AF was significantly associated with higher odds of ischemic stroke (odds ratio (OR): 1.20, 95% confidence intervals (CI): 1.16–1.24, P = 6.53 × 10–30) and cardioembolic stroke (OR: 1.95, 95% CI: 1.85–2.06, P = 8.81 × 10–125). Suggestive associations were found between genetically determined resting heart rate and higher odds of ischemic stroke (OR: 1.01, 95% CI: 1.00–1.02, P = 0.005), large-artery atherosclerotic stroke (OR: 1.02, 95% CI: 1.00–1.04, P = 0.026) and cardioembolic stroke (OR: 1.02, 95% CI: 1.00–1.04, P = 0.028). There was no causal association of P‐wave terminal force in the precordial lead V1 (PTFVI), P-wave duration (PWD), NT-pro BNP or PR interval with ischemic stroke or any subtype.

The association of arterial stiffness index with cerebrovascular and cardiometabolic disease: A Mendelian randomization study

2022 ◽  
pp. 174749302110664
Author(s):  
Weishi Liu ◽  
Luyang Zhang ◽  
Yuan Gao ◽  
Kai Liu ◽  
Yanan Li ◽  
...  
Keyword(s):  
Arterial Stiffness ◽  
Mendelian Randomization ◽  
Causal Effects ◽  
Stiffness Index ◽  
Large Artery ◽  
Vessel Occlusion ◽  
Cardiometabolic Diseases ◽  
Suggestive Association ◽  
Inverse Variance ◽  
Arterial Stiffness Index

Background: Arterial stiffness index (ASI) is a potential risk factor for cerebrovascular and cardiometabolic diseases, but the causal links between them are inconclusive. The aim is to evaluate the causal effects of ASI on cerebrovascular and cardiometabolic diseases by Mendelian randomization (MR). Methods: Two-sample MR analysis was performed to infer causal links. Genetic variants significantly associated with ASI were extracted. The inverse variance weighted method was used for estimating the effects. Sensitivity analysis was performed to test heterogeneity or pleiotropy. Results: MR analysis indicated an effect of genetically predicted ASI on the risk of ischemic stroke (IS) of all causes (OR = 1.894, 95% CI 1.210–2.965, p = 0.005). No links were identified between genetically predicted ASI and other cerebrovascular or cardiometabolic diseases (all p > 0.05). Subgroup analysis of IS etiologies found a suggestive association between genetically predicted ASI and large artery atherosclerosis stroke (LAS) (OR = 3.726, 95% CI 1.230–11.286, p = 0.020). There were no effects of ASI on IS due to cardioembolism or small vessel occlusion. Conclusion: The current MR analysis suggested that genetically predicted ASI was associated with higher risk of IS of all causes. The results and the underlying pathways or mechanisms between ASI and IS needs further investigation.

Effect of metabolites levels on type 2 diabetes mellitus and glycemic traits: a Mendelian randomization study

2021 ◽  
Author(s):  
Yue Sun ◽  
Ya-Ke Lu ◽  
Hao-Yu Gao ◽  
Yu-Xiang Yan
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Significance Level ◽  
Inverse Variance ◽  
Meta Analyses

Abstract Objective To assess the causal associations of plasma levels of metabolites with type 2 diabetes mellitus (T2DM) and glycemic traits. Methods Two-sample mendelian randomization (MR) was conducted to assess the causal associations. Genetic variants strongly associated with metabolites at genome-wide significance level (P < 5 × 10 −8) were selected from public GWAS, and SNPs of Outcomes were obtained from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium for T2DM and from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) for the fasting glucose, insulin and HbA1c. The Wald ratio and inverse-variance weighted methods were used for analyses, and MR-Egger was used for sensitivity analysis. Results The β estimates per 1 SD increasement of arachidonic acid (AA) level was 0.16 (95% CI: 0.078, 0.242; P<0.001). Genetic predisposition to higher plasma AA levels were associated with higher FG levels (β 0.10 [95%CI: 0.064, 0.134], P<0.001), higher HbA1c levels (β 0.04 [95%CI: 0.027, 0.061]) and lower FI levels (β -0.025 [95%CI: -0.047, -0.002], P=0.033). Besides, 2-hydroxybutyric acid (2-HBA) might have positive causal effect on glycemic traits. Conclusions Our findings suggest that AA and 2-HBA may have the causal associations on T2DM and glycemic traits. It is beneficial for clarifying the pathogenesis of T2DM, which would be valuable for early identification and prevention for T2DM.

Daytime sleepiness, night sleep changes and ALS: a Mendelian randomization study

2020 ◽  
Author(s):  
Gan Zhang ◽  
Linjing Zhang ◽  
Tao Huang ◽  
Dongsheng Fan
Keyword(s):  
Sleep Duration ◽  
Daytime Sleepiness ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Sleep Efficiency ◽  
Genome Wide Association Studies ◽  
Night Sleep ◽  
Inverse Variance ◽  
Point Increase ◽  
Increased Risk

Abstract Background Observational studies have indicated that there is a high prevalence of daytime sleepiness and night sleep changes in amyotrophic lateral sclerosis (ALS). However, the actual relation between these symptoms and ALS remains unclear. We aimed to determine whether daytime sleepiness and night sleep changes have an effect on ALS. Methods We used 2-sample mendelian randomization to estimate the effects of daytime sleepiness, sleep efficiency, number of sleep episodes and sleep duration on ALS. Summary statistics we used was from resent and large genome-wide association studies on the traits we chosen (n = 85,670–452,071) and ALS (cases n = 20,806, controls n = 59,804). Inverse variance weighted method was used as the main method for assessing causality. Results A genetically predicted 1-point increase in the assessment of daytime sleepiness was significantly associated with an increased risk of ALS (inverse-variance-weighted (IVW) odds ratio = 2.70, 95% confidence interval (CI): 1.27–5.76; P = 0.010). ALS was not associated with a genetically predicted 1-SD increase in sleep efficiency (IVW 1.01, 0.64–1.58; P = 0.973), Number of sleep episodes (IVW 1.02, 0.80–1.30; P = 0.859) or sleep duration (IVW 1.00, 1.00–1.01; P = 0.250). Conclusions Our results provide novel evidence that daytime sleepiness causes an increase in the risk of ALS and indicate that daytime sleepiness may be inherent in preclinical and clinical ALS patients, rather than simply affected by potential influencing factors.

Circulating adiponectin levels and systemic lupus erythematosus: a two-sample Mendelian randomization study

Rheumatology ◽  
2020 ◽  
Author(s):  
Yi-Lin Dan ◽  
Peng Wang ◽  
Zhongle Cheng ◽  
Qian Wu ◽  
Xue-Rong Wang ◽  
...  
Keyword(s):  
Single Nucleotide Polymorphisms ◽  
Instrumental Variables ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Causal Effects ◽  
European Ancestry ◽  
Nucleotide Polymorphisms ◽  
Single Nucleotide ◽  
Inverse Variance ◽  
Weighted Median

Abstract Objectives Several studies have reported increased serum/plasma adiponectin levels in SLE patients. This study was performed to estimate the causal effects of circulating adiponectin levels on SLE. Methods We selected nine independent single-nucleotide polymorphisms that were associated with circulating adiponectin levels (P < 5 × 10−8) as instrumental variables from a published genome-wide association study (GWAS) meta-analysis. The corresponding effects between instrumental variables and outcome (SLE) were obtained from an SLE GWAS analysis, including 7219 cases with 15 991 controls of European ancestry. Two-sample Mendelian randomization (MR) analyses with inverse-variance weighted, MR-Egger regression, weighted median and weight mode methods were used to evaluate the causal effects. Results The results of inverse-variance weighted methods showed no significantly causal associations of genetically predicted circulating adiponectin levels and the risk for SLE, with an odds ratio (OR) of 1.38 (95% CI 0.91, 1.35; P = 0.130). MR-Egger [OR 1.62 (95% CI 0.85, 1.54), P = 0.195], weighted median [OR 1.37 (95% CI 0.82, 1.35), P = 0.235) and weighted mode methods [OR 1.39 (95% CI 0.86, 1.38), P = 0.219] also supported no significant associations of circulating adiponectin levels and the risk for SLE. Furthermore, MR analyses in using SLE-associated single-nucleotide polymorphisms as an instrumental variable showed no associations of genetically predicted risk of SLE with circulating adiponectin levels. Conclusion Our study did not find evidence for a causal relationship between circulating adiponectin levels and the risk of SLE or of a causal effect of SLE on circulating adiponectin levels.

scholarly journals Genetically Determined Levels of Serum Metabolites and Risk of Neuroticism: A Mendelian Randomization Study

2020 ◽  
Author(s):  
Li Qian ◽  
Yajuan Fan ◽  
Fengjie Gao ◽  
Binbin Zhao ◽  
Bin Yan ◽  
...  
Keyword(s):  
Uric Acid ◽  
Lower Risk ◽  
Genome Wide Association Study ◽  
Mendelian Randomization ◽  
Strong Predictor ◽  
Causal Effects ◽  
Sensitivity Analyses ◽  
Nucleotide Polymorphisms ◽  
Genetic Associations ◽  
Inverse Variance

Abstract Background Neuroticism is a strong predictor for a variety of social and behavioral outcomes, but the etiology is still unknown. Our study aims to provide a comprehensive investigation of causal effects of serum metabolome phenotypes on risk of neuroticism using Mendelian randomization (MR) approaches. Methods Genetic associations with 486 metabolic traits were utilized as exposures, and data from a large genome-wide association study of neuroticism were selected as outcome. For MR analysis, we used the standard inverse-variance weighted (IVW) method for primary MR analysis and 3 additional MR methods (MR-Egger, weighted median, and MR pleiotropy residual sum and outlier) for sensitivity analyses. Results Our study identified 31 metabolites that might have causal effects on neuroticism. Of the 31 metabolites, uric acid and paraxanthine showed robustly significant association with neuroticism in all MR methods. Using single nucleotide polymorphisms as instrumental variables, a 1-SD increase in uric acid was associated with approximately 30% lower risk of neuroticism (OR: 0.77; 95% CI: 0.62–0.95; PIVW = 0.0145), whereas a 1-SD increase in paraxanthine was associated with a 7% higher risk of neuroticism (OR: 1.07; 95% CI: 1.01–1.12; PIVW = .0145). Discussion Our study suggested an increased level of uric acid was associated with lower risk of neuroticism, whereas paraxanthine showed the contrary effect. Our study provided novel insight by combining metabolomics with genomics to help understand the pathogenesis of neuroticism.

scholarly journals Corrigendum to: An examination of multivariable Mendelian randomization in the single-sample and two-sample summary data settings

2020 ◽  
Vol 49 (3) ◽  
pp. 1057-1057
Author(s):  
Eleanor Sanderson ◽  
George Davey Smith ◽  
Frank Windmeijer ◽  
Jack Bowden
Keyword(s):  
Mendelian Randomization ◽  
Single Sample ◽  
Summary Data
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