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Support Interval for Two-Sample Summary Data-Based Mendelian Randomization

The summary-data-based Mendelian randomization (SMR) method is gaining popularity in estimating the causal effect of an exposure on an outcome. In practice, the instrument SNP is often selected from the genome-wide association study (GWAS) on the exposure but no correction is made for such selection...

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Autor principal: Wang, Kai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9859138/
https://www.ncbi.nlm.nih.gov/pubmed/36672952
http://dx.doi.org/10.3390/genes14010211
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author Wang, Kai
author_facet Wang, Kai
author_sort Wang, Kai
collection PubMed
description The summary-data-based Mendelian randomization (SMR) method is gaining popularity in estimating the causal effect of an exposure on an outcome. In practice, the instrument SNP is often selected from the genome-wide association study (GWAS) on the exposure but no correction is made for such selection in downstream analysis, leading to a biased estimate of the effect size and invalid inference. We address this issue by using the likelihood derived from the sampling distribution of the estimated SNP effects in the exposure GWAS and the outcome GWAS. This likelihood takes into account how the instrument SNPs are selected. Since the effective sample size is 1, the asymptotic theory does not apply. We use a support for a profile likelihood as an interval estimate of the causal effect. Simulation studies indicate that this support has robust coverage while the confidence interval implied by the SMR method has lower-than-nominal coverage. Furthermore, the variance of the two-stage least squares estimate of the causal effect is shown to be the same as the variance used for SMR for one-sample data when there is no selection.
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spelling pubmed-98591382023-01-21 Support Interval for Two-Sample Summary Data-Based Mendelian Randomization Wang, Kai Genes (Basel) Article The summary-data-based Mendelian randomization (SMR) method is gaining popularity in estimating the causal effect of an exposure on an outcome. In practice, the instrument SNP is often selected from the genome-wide association study (GWAS) on the exposure but no correction is made for such selection in downstream analysis, leading to a biased estimate of the effect size and invalid inference. We address this issue by using the likelihood derived from the sampling distribution of the estimated SNP effects in the exposure GWAS and the outcome GWAS. This likelihood takes into account how the instrument SNPs are selected. Since the effective sample size is 1, the asymptotic theory does not apply. We use a support for a profile likelihood as an interval estimate of the causal effect. Simulation studies indicate that this support has robust coverage while the confidence interval implied by the SMR method has lower-than-nominal coverage. Furthermore, the variance of the two-stage least squares estimate of the causal effect is shown to be the same as the variance used for SMR for one-sample data when there is no selection. MDPI 2023-01-13 /pmc/articles/PMC9859138/ /pubmed/36672952 http://dx.doi.org/10.3390/genes14010211 Text en © 2023 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Kai
Support Interval for Two-Sample Summary Data-Based Mendelian Randomization
title Support Interval for Two-Sample Summary Data-Based Mendelian Randomization
title_full Support Interval for Two-Sample Summary Data-Based Mendelian Randomization
title_fullStr Support Interval for Two-Sample Summary Data-Based Mendelian Randomization
title_full_unstemmed Support Interval for Two-Sample Summary Data-Based Mendelian Randomization
title_short Support Interval for Two-Sample Summary Data-Based Mendelian Randomization
title_sort support interval for two-sample summary data-based mendelian randomization
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9859138/
https://www.ncbi.nlm.nih.gov/pubmed/36672952
http://dx.doi.org/10.3390/genes14010211
work_keys_str_mv AT wangkai supportintervalfortwosamplesummarydatabasedmendelianrandomization