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Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids
Inference of causality between gene expression and complex traits using Mendelian randomization (MR) is confounded by pleiotropy and linkage disequilibrium (LD) of gene-expression quantitative trait loci (eQTL). Here, we propose an MR method, MR-link, that accounts for unobserved pleiotropy and LD b...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530717/ https://www.ncbi.nlm.nih.gov/pubmed/33004804 http://dx.doi.org/10.1038/s41467-020-18716-x |
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author | van der Graaf, Adriaan Claringbould, Annique Rimbert, Antoine Westra, Harm-Jan Li, Yang Wijmenga, Cisca Sanna, Serena |
author_facet | van der Graaf, Adriaan Claringbould, Annique Rimbert, Antoine Westra, Harm-Jan Li, Yang Wijmenga, Cisca Sanna, Serena |
author_sort | van der Graaf, Adriaan |
collection | PubMed |
description | Inference of causality between gene expression and complex traits using Mendelian randomization (MR) is confounded by pleiotropy and linkage disequilibrium (LD) of gene-expression quantitative trait loci (eQTL). Here, we propose an MR method, MR-link, that accounts for unobserved pleiotropy and LD by leveraging information from individual-level data, even when only one eQTL variant is present. In simulations, MR-link shows false-positive rates close to expectation (median 0.05) and high power (up to 0.89), outperforming all other tested MR methods and coloc. Application of MR-link to low-density lipoprotein cholesterol (LDL-C) measurements in 12,449 individuals with expression and protein QTL summary statistics from blood and liver identifies 25 genes causally linked to LDL-C. These include the known SORT1 and ApoE genes as well as PVRL2, located in the APOE locus, for which a causal role in liver was not known. Our results showcase the strength of MR-link for transcriptome-wide causal inferences. |
format | Online Article Text |
id | pubmed-7530717 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75307172020-10-19 Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids van der Graaf, Adriaan Claringbould, Annique Rimbert, Antoine Westra, Harm-Jan Li, Yang Wijmenga, Cisca Sanna, Serena Nat Commun Article Inference of causality between gene expression and complex traits using Mendelian randomization (MR) is confounded by pleiotropy and linkage disequilibrium (LD) of gene-expression quantitative trait loci (eQTL). Here, we propose an MR method, MR-link, that accounts for unobserved pleiotropy and LD by leveraging information from individual-level data, even when only one eQTL variant is present. In simulations, MR-link shows false-positive rates close to expectation (median 0.05) and high power (up to 0.89), outperforming all other tested MR methods and coloc. Application of MR-link to low-density lipoprotein cholesterol (LDL-C) measurements in 12,449 individuals with expression and protein QTL summary statistics from blood and liver identifies 25 genes causally linked to LDL-C. These include the known SORT1 and ApoE genes as well as PVRL2, located in the APOE locus, for which a causal role in liver was not known. Our results showcase the strength of MR-link for transcriptome-wide causal inferences. Nature Publishing Group UK 2020-10-01 /pmc/articles/PMC7530717/ /pubmed/33004804 http://dx.doi.org/10.1038/s41467-020-18716-x Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article van der Graaf, Adriaan Claringbould, Annique Rimbert, Antoine Westra, Harm-Jan Li, Yang Wijmenga, Cisca Sanna, Serena Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids |
title | Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids |
title_full | Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids |
title_fullStr | Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids |
title_full_unstemmed | Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids |
title_short | Mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids |
title_sort | mendelian randomization while jointly modeling cis genetics identifies causal relationships between gene expression and lipids |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7530717/ https://www.ncbi.nlm.nih.gov/pubmed/33004804 http://dx.doi.org/10.1038/s41467-020-18716-x |
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