Selecting invalid instruments to improve Mendelian randomization with two-sample summary data
Author(s)
Patel, Ashish
Ditraglia, Francis J
Zuber, Verena
Burgess, Stephen
Type
Journal Article
Abstract
Mendelian randomization (MR) is a widely-used method to estimate the causal relationship between a risk factor and disease. A fundamental part of any MR analysis is to choose appropriate genetic variants as instrumental variables. Genome-wide association studies often reveal that hundreds of genetic variants may be robustly associated with a risk factor, but in some situations investigators may have greater confidence in the instrument validity of only a smaller subset of variants. Nevertheless, the use of additional instruments may be optimal from the perspective of mean squared error, even if they are slightly invalid; a small bias in estimation may be a price worth paying for a larger reduction in variance. For this purpose we consider a method for “focused” instrument selection whereby genetic variants are selected to minimise the estimated asymptotic mean squared error of causal effect estimates. In a setting of many weak and locally invalid instruments, we propose a novel strategy to construct confidence intervals for postselection focused estimators that guards against the worst case loss in asymptotic coverage. In empirical applications to: (i) validate lipid drug targets and (ii) investigate vitamin D effects on a wide range of outcomes, our findings suggest that the optimal selection of instruments does not involve only a small number of biologically-justified instruments but also many potentially invalid instruments.
Date Issued
2024-06-01
Date Acceptance
2024-04-01
Citation
Annals of Applied Statistics, 2024, 18 (2), pp.1729-1749
ISSN
1932-6157
Publisher
Institute of Mathematical Statistics
Start Page
1729
End Page
1749
Journal / Book Title
Annals of Applied Statistics
Volume
18
Issue
2
Copyright Statement
© 2024 Institute of Mathematical Statistics.
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/38737575
PII: 23-aoas1856
Subjects
focused information criterion
INFERENCE
Mathematics
Mendelian randomization
Physical Sciences
postselection inference
Science & Technology
Statistics & Probability
Publication Status
Published
Coverage Spatial
United States
Date Publish Online
2024-04-05