Dataset Information

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways.

ABSTRACT:

Background

Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation.

Methods

We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particular where some of the effect of an exposure on the outcome may operate through an intermediate variable (a mediator). If instrumental variables for the exposure and mediator are available, direct and indirect effects of the exposure on the outcome can be estimated, for example using either a regression-based method or structural equation models. The direction of effect between the exposure and a possible mediator can also be assessed. Methods are illustrated in an applied example considering causal relationships between body mass index, C-reactive protein and uric acid.

Results

These estimators are consistent in the presence of unmeasured confounding if, in addition to the instrumental variable assumptions, the effects of both the exposure on the mediator and the mediator on the outcome are homogeneous across individuals and linear without interactions. Nevertheless, a simulation study demonstrates that even considerable heterogeneity in these effects does not lead to bias in the estimates.

Conclusions

These methods can be used to estimate direct and indirect causal effects in a mediation setting, and have potential for the investigation of more complex networks between multiple interrelated exposures and disease outcomes.

SUBMITTER: Burgess S

PROVIDER: S-EPMC4469795 | biostudies-literature | 2015 Apr

REPOSITORIES: biostudies-literature

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Publications

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways.

Burgess Stephen S Daniel Rhian M RM Butterworth Adam S AS Thompson Simon G SG

International journal of epidemiology 20140822 2

<h4>Background</h4>Mendelian randomization uses genetic variants, assumed to be instrumental variables for a particular exposure, to estimate the causal effect of that exposure on an outcome. If the instrumental variable criteria are satisfied, the resulting estimator is consistent even in the presence of unmeasured confounding and reverse causation.<h4>Methods</h4>We extend the Mendelian randomization paradigm to investigate more complex networks of relationships between variables, in particula ...[more]

PMID: 25150977

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Project description:Background and objectivesFatigue has been associated with adverse effects on recovery from ischemic stroke based on previous observational research. The purpose of our study was to explore the potential causal association of fatigue with poor functional outcome after ischemic stroke by employing Mendelian randomization (MR).MethodsA set of instrumental variables, comprising 36 single-nucleotide polymorphisms (SNPs) that are only related to fatigue, were derived from a genome-wide association study (GWAS) that included 449,019 general individuals. The functional outcomes after ischemic stroke were derived from a GWAS (Genetics of Ischemic Stroke Functional Outcome Network) involving 6,021 survivors. Two-sample MR methods were used to assess the causal effect, including inverse variance weighted, MR-Egger, weighted median, simple mode, and weighted mode. In bidirectional MR analysis, the reverse causal association was analyzed using the Wald ratio method. The mediation effects of lipid metabolites were analyzed using two-step MR analysis.ResultsGenetic liability to fatigue was causally associated with the poor functional outcome (modified Rankin Scale ≥3 at 3 months) after ischemic stroke (OR = 4.20, 95%CI [1.11-15.99], p < 0.05). However, genetic predicted poor functional outcome after ischemic stroke was not associated with fatigue (OR = 1.00, 95%CI [0.99-1.02], p > 0.05). The results of the two-step MR showed that cholesteryl esters to total lipids ratio in large very low-density lipoprotein (VLDL) (ME = -0.13, p < 0.05); concentration of very large VLDL particles (ME = -0.13, p < 0.05); free cholesterol in large VLDL (ME = -0.13, p < 0.05); free cholesterol to total lipids ratio in very large VLDL (ME = -0.22, p < 0.05); phospholipids in large VLDL (ME = -0.15, p < 0.05); phospholipids in very large VLDL (ME = -0.13, p < 0.05); phospholipids to total lipids ratio in large high-density lipoprotein (HDL) (ME = -0.17, p < 0.05); total lipids in very large VLDL (ME = -0.14, p < 0.05); triglycerides in small VLDL (ME = -0.11, p < 0.05); and triglycerides to total lipids ratio in large HDL (ME = -0.10, p < 0.05) assumed a pivotal role in mediating the association between fatigue and poor functional outcome after ischemic stroke.ConclusionOur study provides evidence supporting the causal association between fatigue and the poor functional outcome after ischemic stroke, which emphasizes the importance of implementing interventions aimed at addressing fatigue. This could offer a therapeutic target to improve recovery after ischemic stroke and warrant exploration in a clinical context. One potential mechanism by which fatigue affects functional outcomes after ischemic stroke is through the action of lipid metabolites.

Dataset Information

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways.

Background

Methods

Results

Conclusions

Publications

Network Mendelian randomization: using genetic variants as instrumental variables to investigate mediation in causal pathways.

Similar Datasets

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