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Mendelian randomization: methods for using genetic variants in causal estimation

By: Burgess, Stephen.
Contributor(s): Thompson, Simon G.
Material type: materialTypeLabelBookSeries: Chapman and Hall/CRC interdisciplinary statistics series. Publisher: Boca Raton CRC Press 2015Description: xiv, 210 p.ISBN: 9781466573178.Subject(s): Medical genetics - Statistical methods | Mendelian randomization analysis - methods | Genetic Variation | Statistics as topic - methods | Medical genetics - Statistical methodsDDC classification: 616.042015195 Summary: Mendelian Randomization: Methods for Using Genetic Variants in Causal Estimation provides thorough coverage of the methods and practical elements of Mendelian randomization analysis. It brings together diverse aspects of Mendelian randomization spanning epidemiology, statistics, genetics, and econometrics. Although the book mainly focuses on epidemiology, much of the material can be applied to other areas of research. Through several examples, the first part of the book shows how to perform simple applied Mendelian randomization analyses and interpret their results. The second part addresses specific methodological issues, such as weak instruments, multiple instruments, power calculations, and meta-analysis, relevant to practical applications of Mendelian randomization. In this part, the authors draw on data from the C-reactive protein Coronary heart disease Genetics Collaboration (CCGC) to illustrate the analyses. They present the mathematics in an easy-to-understand way by using nontechnical language and reinforcing key points at the end of each chapter. The last part of the book examines the potential of Mendelian randomization in the future, exploring both methodological and applied developments. This book gives statisticians, epidemiologists, and geneticists the foundation to understand issues concerning the use of genetic variants as instrumental variables. It will get them up to speed in undertaking and interpreting Mendelian randomization analyses. Chapter summaries, paper summaries, web-based applications, and software code for implementing the statistical techniques are available on a supplementary website. (https://www.crcpress.com/Mendelian-Randomization-Methods-for-Using-Genetic-Variants-in-Causal-Estimation/Burgess-Thompson/9781466573178)
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Table of Contents:


I USING GENETIC VARIANTS AS INSTRUMENTAL VARIABLES TO ASSESS CAUSAL RELATIONSHIPS


1. Introduction and motivation
Shortcomings of classical epidemiology
The rise of genetic epidemiology
Motivating example: The inflammation hypothesis
Other examples of Mendelian randomization
Overview of book
Summary

2. What is Mendelian randomization?
What is Mendelian randomization?
Why use Mendelian randomization?
A brief overview of genetics
Summary

3. Assumptions for causal inference
Observational and causal relationships
Finding a valid instrumental variable
Testing for a causal relationship
Estimating a causal effect
Summary

4. Methods for instrumental variable analysis
Ratio of coefficients method
Two-stage methods
Likelihood-based methods
Semi-parametric methods
Efficiency and validity of instruments
Computer implementation
Summary

5. Examples of Mendelian randomization analysis
Fibrinogen and coronary heart disease
Adiposity and blood pressure
Lipoprotein(a) and myocardial infarction
High-density lipoprotein cholesterol and myocardial infarction
Discussion

6. Generalizability of estimates from Mendelian randomization
Internal and external validity
Comparison of estimates
Discussion
Summary


II STATISTICAL ISSUES IN INSTRUMENTAL VARIABLE ANALYSIS AND MENDELIAN RANDOMIZATION


7. Weak instruments and finite-sample bias
Introduction
Demonstrating the bias of IV estimates
Explaining the bias of IV estimates
Properties of IV estimates with weak instruments
Bias of IV estimates with different choices of IV
Minimizing the bias of IV estimates
Discussion
Key points from chapter

8. Multiple instruments and power
Introduction
Allele scores
Power of IV estimates
Multiple variants and missing data
Discussion
Key points from chapter

9. Multiple studies and evidence synthesis
Introduction
Assessing the causal relationship
Study-level meta-analysis
Summary-level meta-analysis
Individual-level meta-analysis
Example: C-reactive protein and fibrinogen
Binary outcomes
Discussion
Key points from chapter

10. Example: The CRP CHD Genetics Collaboration
Overview of the dataset
Single study: Cardiovascular Health Study
Meta-analysis of all studies
Discussion
Key points from chapter


III PROSPECTS FOR MENDELIAN RANDOMIZATION


11. Future directions
Methodological developments
Applied developments
Conclusion

Bibliography

Index


Mendelian Randomization: Methods for Using Genetic Variants in Causal Estimation provides thorough coverage of the methods and practical elements of Mendelian randomization analysis. It brings together diverse aspects of Mendelian randomization spanning epidemiology, statistics, genetics, and econometrics. Although the book mainly focuses on epidemiology, much of the material can be applied to other areas of research.

Through several examples, the first part of the book shows how to perform simple applied Mendelian randomization analyses and interpret their results. The second part addresses specific methodological issues, such as weak instruments, multiple instruments, power calculations, and meta-analysis, relevant to practical applications of Mendelian randomization. In this part, the authors draw on data from the C-reactive protein Coronary heart disease Genetics Collaboration (CCGC) to illustrate the analyses. They present the mathematics in an easy-to-understand way by using nontechnical language and reinforcing key points at the end of each chapter. The last part of the book examines the potential of Mendelian randomization in the future, exploring both methodological and applied developments.

This book gives statisticians, epidemiologists, and geneticists the foundation to understand issues concerning the use of genetic variants as instrumental variables. It will get them up to speed in undertaking and interpreting Mendelian randomization analyses. Chapter summaries, paper summaries, web-based applications, and software code for implementing the statistical techniques are available on a supplementary website.


(https://www.crcpress.com/Mendelian-Randomization-Methods-for-Using-Genetic-Variants-in-Causal-Estimation/Burgess-Thompson/9781466573178)

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