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Combining Human Genetics and Causal Inference to Understand Human Disease and Development


Book Series:  A Cold Spring Harbor Perspectives in Medicine Collection
Subject Area(s):  Human Biology and DiseaseGeneticsDiseases

Edited by George Davey Smith, University of Bristol; Rebecca Richmond, University of Bristol; John-Baptiste Pingault, University College London

Due February 2021 • 225 pages (approx.), illustrated, index
Hardcover • $135
ISBN  978-1-621823-81-0

  •     Description    
  •     Contents    

Description

Mendelian randomization and related techniques allow researchers to use knowledge about genetic factors that contribute to a disease to predict whether other risk factors, such as environmental exposure, play a part. This volume examines how these approaches allow researchers to make causal inferences about modifiable exposures and how this can benefit public health.

Contents

Preliminary
1. New Opportunities
George Davey Smith, Rebecca Richmond, and John-Baptiste Pingault
Concepts
2. The Meaning of “Cause” in Genetics
Kate E. Lynch
Family based study designs
3. Twins and Causal Inference: Leveraging Nature’s Experiment
Tom A. McAdams, Fruhling V. Rijsdijk, Helena M.S. Zavos, and Jean-Baptiste Pingault
4. Family-Based Designs that Disentangle Inherited Factors from Pre- and Post-Natal Environmental Exposures: In Vitro Fertilization, Discordant Sibling Pairs, Maternal Versus Paternal Comparisons and Adoption Designs
Anita Thapar and Frances Rice
Population-based genetic designs
5. Mendelian Randomization: Concepts and Scope
Rebecca C. Richmond and George Smith Davey
6. Polygenic Mendelian Randomization
Frank Dudbridge
7. Multivariable Mendelian Randomization and Mediation
Eleanor Sanderson
INTEGRATION OF METHODS AND DATA
8. Integrating Family-Based and Mendelian Randomization Designs
Liang-Dar Hwang, Neil M. Davies, Nicole M. Warrington, and David M. Evans
9. Causal Inference Methods to Integrate Omics and Complex Traits
Eleonora Porcu, Jennifer Sjaarda, Kaido Lepik, Cristian Carmeli, Liza Darrous, Jonathan Sulc, Ninon Mounier, and Zoltán Kutalik
10. Computational Tools for Causal Inference in Genetics
Tom G. Richardson, Jie Zheng, and Tom R. Gaunt
Genetics and causation in practice
11. Using Mendelian Randomization to Improve the Design of Randomized Trials
Brian A. Ference, Michael V. Holmes, and George Davey Smith
12. Triangulating Evidence Through the Inclusion of Genetically Informed Designs
Marcus R. Munafò, Julian P.T. Higgins, and George Davey Smith
Index