Effect of selection bias on two sample summary data based Mendelian randomization

Abstract Mendelian randomization (MR) is becoming more and more popular for inferring causal relationship between an exposure and a trait. Typically, instrument SNPs are selected from an exposure GWAS based on their summary statistics and the same summary statistics on the selected SNPs are used for...

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Autores principales:	Kai Wang, Shizhong Han
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0d6b81de6c9f42d9a9fde154769608a2
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spelling	oai:doaj.org-article:0d6b81de6c9f42d9a9fde154769608a22021-12-02T18:15:33ZEffect of selection bias on two sample summary data based Mendelian randomization10.1038/s41598-021-87219-62045-2322https://doaj.org/article/0d6b81de6c9f42d9a9fde154769608a22021-04-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-87219-6https://doaj.org/toc/2045-2322Abstract Mendelian randomization (MR) is becoming more and more popular for inferring causal relationship between an exposure and a trait. Typically, instrument SNPs are selected from an exposure GWAS based on their summary statistics and the same summary statistics on the selected SNPs are used for subsequent analyses. However, this practice suffers from selection bias and can invalidate MR methods, as showcased via two popular methods: the summary data-based MR (SMR) method and the two-sample MR Steiger method. The SMR method is conservative while the MR Steiger method can be either conservative or liberal. A simple and yet more powerful alternative to SMR is proposed.Kai WangShizhong HanNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-8 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Kai Wang Shizhong Han Effect of selection bias on two sample summary data based Mendelian randomization
description	Abstract Mendelian randomization (MR) is becoming more and more popular for inferring causal relationship between an exposure and a trait. Typically, instrument SNPs are selected from an exposure GWAS based on their summary statistics and the same summary statistics on the selected SNPs are used for subsequent analyses. However, this practice suffers from selection bias and can invalidate MR methods, as showcased via two popular methods: the summary data-based MR (SMR) method and the two-sample MR Steiger method. The SMR method is conservative while the MR Steiger method can be either conservative or liberal. A simple and yet more powerful alternative to SMR is proposed.
format	article
author	Kai Wang Shizhong Han
author_facet	Kai Wang Shizhong Han
author_sort	Kai Wang
title	Effect of selection bias on two sample summary data based Mendelian randomization
title_short	Effect of selection bias on two sample summary data based Mendelian randomization
title_full	Effect of selection bias on two sample summary data based Mendelian randomization
title_fullStr	Effect of selection bias on two sample summary data based Mendelian randomization
title_full_unstemmed	Effect of selection bias on two sample summary data based Mendelian randomization
title_sort	effect of selection bias on two sample summary data based mendelian randomization
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/0d6b81de6c9f42d9a9fde154769608a2
work_keys_str_mv	AT kaiwang effectofselectionbiasontwosamplesummarydatabasedmendelianrandomization AT shizhonghan effectofselectionbiasontwosamplesummarydatabasedmendelianrandomization
_version_	1718378375749304320

Effect of selection bias on two sample summary data based Mendelian randomization

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