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Mendelian randomization: genetic anchors for causal inference in epidemiological studies

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TLDR
Developments of MR, including two-sample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review.
Abstract
Observational epidemiological studies are prone to confounding, reverse causation and various biases and have generated findings that have proved to be unreliable indicators of the causal effects of modifiable exposures on disease outcomes. Mendelian randomization (MR) is a method that utilizes genetic variants that are robustly associated with such modifiable exposures to generate more reliable evidence regarding which interventions should produce health benefits. The approach is being widely applied, and various ways to strengthen inference given the known potential limitations of MR are now available. Developments of MR, including two-sample MR, bidirectional MR, network MR, two-step MR, factorial MR and multiphenotype MR, are outlined in this review. The integration of genetic information into population-based epidemiological studies presents translational opportunities, which capitalize on the investment in genomic discovery research.

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Journal ArticleDOI

Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

TL;DR: An adaption of Egger regression can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations, and provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.
Journal ArticleDOI

Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator.

TL;DR: A novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate is presented, which is consistent even when up to 50% of the information comes from invalid instrumental variables.
Journal ArticleDOI

The MR-Base platform supports systematic causal inference across the human phenome

TL;DR: MR-Base is a platform that integrates a curated database of complete GWAS results (no restrictions according to statistical significance) with an application programming interface, web app and R packages that automate 2SMR, and includes several sensitivity analyses for assessing the impact of horizontal pleiotropy and other violations of assumptions.
Journal ArticleDOI

An Expanded View of Complex Traits: From Polygenic to Omnigenic

TL;DR: It is proposed that gene regulatory networks are sufficiently interconnected such that all genes expressed in disease-relevant cells are liable to affect the functions of core disease-related genes and that most heritability can be explained by effects on genes outside core pathways.
References
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Journal ArticleDOI

Common polygenic variation contributes to risk of schizophrenia and bipolar disorder

Shaun Purcell, +81 more
- 06 Aug 2009 - 
TL;DR: The extent to which common genetic variation underlies the risk of schizophrenia is shown, using two analytic approaches, and the major histocompatibility complex is implicate, which is shown to involve thousands of common alleles of very small effect.
Journal ArticleDOI

A common variant in the FTO gene is associated with body mass index and predisposes to childhood and adult obesity

TL;DR: A genome-wide search for type 2 diabetes–susceptibility genes identified a common variant in the FTO (fat mass and obesity associated) gene that predisposes to diabetes through an effect on body mass index (BMI).
Journal ArticleDOI

‘Mendelian randomization’: can genetic epidemiology contribute to understanding environmental determinants of disease?

TL;DR: Mendelian randomization provides new opportunities to test causality and demonstrates how investment in the human genome project may contribute to understanding and preventing the adverse effects on human health of modifiable exposures.
Journal ArticleDOI

Discovery and refinement of loci associated with lipid levels

Cristen J. Willer, +319 more
- 06 Oct 2013 - 
TL;DR: It is found that loci associated with blood lipid levels are often associated with cardiovascular and metabolic traits, including coronary artery disease, type 2 diabetes, blood pressure, waist-hip ratio and body mass index.
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