Integrating Family-Based and Mendelian Randomization Designs

Liang-Dar Hwang, Neil M Davies, Nicole M Warrington, David M Evans

Research output: Contribution to journalArticle (Academic Journal)

Abstract

Most Mendelian randomization (MR) studies published in the literature to date have involved analyses of unrelated, putatively independent sets of individuals. However, estimates obtained from these sorts of studies are subject to a range of biases including dynastic effects, assortative mating, residual population stratification, and horizontal pleiotropy. The inclusion of related individuals in MR studies can help control for and, in some cases, estimate the effect of these biases on causal parameters. In this review, we discuss these biases, how they can affect MR studies, and describe three sorts of family-based study designs that can be used to control for them. We conclude that including family information from related individuals is not only possible given the world's existing twin, birth, and large-scale population-based cohorts, but likely to reap rich rewards in understanding the etiology of complex traits and diseases in the near future.

Original languageEnglish
JournalCold Spring Harbor perspectives in medicine
Early online date2 Mar 2020
DOIs
Publication statusE-pub ahead of print - 2 Mar 2020

Bibliographical note

The acceptance date for this record is provisional and based upon the month of publication for the article.

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