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Mendelian Randomization With Refined Instrumental Variables From Genetic Score Improves Accuracy and Reduces Bias

Mendelian randomization (MR) can estimate the causal effect for a risk factor on a complex disease using genetic variants as instrument variables (IVs). A variety of generalized MR methods have been proposed to integrate results arising from multiple IVs in order to increase power. One of the method...

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Autores principales: Lin, Lijuan, Zhang, Ruyang, Huang, Hui, Zhu, Ying, Li, Yi, Dong, Xuesi, Shen, Sipeng, Wei, Liangmin, Chen, Xin, Christiani, David C., Wei, Yongyue, Chen, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044958/
https://www.ncbi.nlm.nih.gov/pubmed/33868364
http://dx.doi.org/10.3389/fgene.2021.618829
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author Lin, Lijuan
Zhang, Ruyang
Huang, Hui
Zhu, Ying
Li, Yi
Dong, Xuesi
Shen, Sipeng
Wei, Liangmin
Chen, Xin
Christiani, David C.
Wei, Yongyue
Chen, Feng
author_facet Lin, Lijuan
Zhang, Ruyang
Huang, Hui
Zhu, Ying
Li, Yi
Dong, Xuesi
Shen, Sipeng
Wei, Liangmin
Chen, Xin
Christiani, David C.
Wei, Yongyue
Chen, Feng
author_sort Lin, Lijuan
collection PubMed
description Mendelian randomization (MR) can estimate the causal effect for a risk factor on a complex disease using genetic variants as instrument variables (IVs). A variety of generalized MR methods have been proposed to integrate results arising from multiple IVs in order to increase power. One of the methods constructs the genetic score (GS) by a linear combination of the multiple IVs using the multiple regression model, which was applied in medical researches broadly. However, GS-based MR requires individual-level data, which greatly limit its application in clinical research. We propose an alternative method called Mendelian Randomization with Refined Instrumental Variable from Genetic Score (MR-RIVER) to construct a genetic IV by integrating multiple genetic variants based on summarized results, rather than individual data. Compared with inverse-variance weighted (IVW) and generalized summary-data-based Mendelian randomization (GSMR), MR-RIVER maintained the type I error, while possessing more statistical power than the competing methods. MR-RIVER also presented smaller biases and mean squared errors, compared to the IVW and GSMR. We further applied the proposed method to estimate the effects of blood metabolites on educational attainment, by integrating results from several publicly available resources. MR-RIVER provided robust results under different LD prune criteria and identified three metabolites associated with years of schooling and additional 15 metabolites with indirect mediation effects through butyrylcarnitine. MR-RIVER, which extends score-based MR to summarized results in lieu of individual data and incorporates multiple correlated IVs, provided a more accurate and powerful means for the discovery of novel risk factors.
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spelling pubmed-80449582021-04-15 Mendelian Randomization With Refined Instrumental Variables From Genetic Score Improves Accuracy and Reduces Bias Lin, Lijuan Zhang, Ruyang Huang, Hui Zhu, Ying Li, Yi Dong, Xuesi Shen, Sipeng Wei, Liangmin Chen, Xin Christiani, David C. Wei, Yongyue Chen, Feng Front Genet Genetics Mendelian randomization (MR) can estimate the causal effect for a risk factor on a complex disease using genetic variants as instrument variables (IVs). A variety of generalized MR methods have been proposed to integrate results arising from multiple IVs in order to increase power. One of the methods constructs the genetic score (GS) by a linear combination of the multiple IVs using the multiple regression model, which was applied in medical researches broadly. However, GS-based MR requires individual-level data, which greatly limit its application in clinical research. We propose an alternative method called Mendelian Randomization with Refined Instrumental Variable from Genetic Score (MR-RIVER) to construct a genetic IV by integrating multiple genetic variants based on summarized results, rather than individual data. Compared with inverse-variance weighted (IVW) and generalized summary-data-based Mendelian randomization (GSMR), MR-RIVER maintained the type I error, while possessing more statistical power than the competing methods. MR-RIVER also presented smaller biases and mean squared errors, compared to the IVW and GSMR. We further applied the proposed method to estimate the effects of blood metabolites on educational attainment, by integrating results from several publicly available resources. MR-RIVER provided robust results under different LD prune criteria and identified three metabolites associated with years of schooling and additional 15 metabolites with indirect mediation effects through butyrylcarnitine. MR-RIVER, which extends score-based MR to summarized results in lieu of individual data and incorporates multiple correlated IVs, provided a more accurate and powerful means for the discovery of novel risk factors. Frontiers Media S.A. 2021-03-17 /pmc/articles/PMC8044958/ /pubmed/33868364 http://dx.doi.org/10.3389/fgene.2021.618829 Text en Copyright © 2021 Lin, Zhang, Huang, Zhu, Li, Dong, Shen, Wei, Chen, Christiani, Wei and Chen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Lin, Lijuan
Zhang, Ruyang
Huang, Hui
Zhu, Ying
Li, Yi
Dong, Xuesi
Shen, Sipeng
Wei, Liangmin
Chen, Xin
Christiani, David C.
Wei, Yongyue
Chen, Feng
Mendelian Randomization With Refined Instrumental Variables From Genetic Score Improves Accuracy and Reduces Bias
title Mendelian Randomization With Refined Instrumental Variables From Genetic Score Improves Accuracy and Reduces Bias
title_full Mendelian Randomization With Refined Instrumental Variables From Genetic Score Improves Accuracy and Reduces Bias
title_fullStr Mendelian Randomization With Refined Instrumental Variables From Genetic Score Improves Accuracy and Reduces Bias
title_full_unstemmed Mendelian Randomization With Refined Instrumental Variables From Genetic Score Improves Accuracy and Reduces Bias
title_short Mendelian Randomization With Refined Instrumental Variables From Genetic Score Improves Accuracy and Reduces Bias
title_sort mendelian randomization with refined instrumental variables from genetic score improves accuracy and reduces bias
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044958/
https://www.ncbi.nlm.nih.gov/pubmed/33868364
http://dx.doi.org/10.3389/fgene.2021.618829
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