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Activity Number:
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248
- Recent Advances in Genetic Association and Gene-Environment Interaction Studies
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Type:
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Contributed
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Date/Time:
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Tuesday, August 9, 2022 : 8:30 AM to 10:20 AM
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Sponsor:
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Section on Statistics in Genomics and Genetics
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Abstract #322652
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Title:
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A Random Effect Model Based Method of Moments Estimation of Causal Effect in Mendelian Randomization Studies
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Author(s):
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Wenhao Cao* and Saonli Basu
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Companies:
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Division of Biostatistics, University of Minnesota and Division of Biostatistics, University of Minnesota
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Keywords:
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genetic variants;
invalid instruments;
Mendelian Randomization;
small sample size;
MR-IVW;
MR-Egger
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Abstract:
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Recent advances in genotyping technology have delivered a wealth of genetic data, which is rapidly advancing our understanding of the underlying genetic architecture of complex diseases. Mendelian Randomization leverages such genetic data to estimate the causal effect of a exposure factor on an outcome from observational studies. In this paper, we utilize genetic correlations to summarize information on a large set of gene variants associated with the exposure factor. Our approach provides an alternative to estimate causal effects using Mendelian Randomization in presence of many weak and invalid instruments, and small sample size. We use a Method-of Moments estimator to estimate the causal effect and demonstrate through simulation that our approach provides a robust alternative of the existing MR methods. In particular, through theoretical derivations, we show that our approach is conceptually similar to a weighted average of the widely used inverse-variance weighting and Egger regression methods. We illustrate through simulation and real data analysis the robustness of our approach under the violation of MR assumptions and compare the performance with several existing methods.
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Authors who are presenting talks have a * after their name.
