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Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases
High-dimensional omics datasets provide valuable resources to determine the causal role of molecular traits in mediating the path from genotype to phenotype. Making use of molecular quantitative trait loci (QTL) and genome-wide association study (GWAS) summary statistics, we propose a multivariable...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9729239/ https://www.ncbi.nlm.nih.gov/pubmed/36477627 http://dx.doi.org/10.1038/s41467-022-35196-3 |
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author | Sadler, Marie C. Auwerx, Chiara Lepik, Kaido Porcu, Eleonora Kutalik, Zoltán |
author_facet | Sadler, Marie C. Auwerx, Chiara Lepik, Kaido Porcu, Eleonora Kutalik, Zoltán |
author_sort | Sadler, Marie C. |
collection | PubMed |
description | High-dimensional omics datasets provide valuable resources to determine the causal role of molecular traits in mediating the path from genotype to phenotype. Making use of molecular quantitative trait loci (QTL) and genome-wide association study (GWAS) summary statistics, we propose a multivariable Mendelian randomization (MVMR) framework to quantify the proportion of the impact of the DNA methylome (DNAm) on complex traits that is propagated through the assayed transcriptome. Evaluating 50 complex traits, we find that on average at least 28.3% (95% CI: [26.9%–29.8%]) of DNAm-to-trait effects are mediated through (typically multiple) transcripts in the cis-region. Several regulatory mechanisms are hypothesized, including methylation of the promoter probe cg10385390 (chr1:8’022’505) increasing the risk for inflammatory bowel disease by reducing PARK7 expression. The proposed integrative framework can be extended to other omics layers to identify causal molecular chains, providing a powerful tool to map and interpret GWAS signals. |
format | Online Article Text |
id | pubmed-9729239 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-97292392022-12-09 Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases Sadler, Marie C. Auwerx, Chiara Lepik, Kaido Porcu, Eleonora Kutalik, Zoltán Nat Commun Article High-dimensional omics datasets provide valuable resources to determine the causal role of molecular traits in mediating the path from genotype to phenotype. Making use of molecular quantitative trait loci (QTL) and genome-wide association study (GWAS) summary statistics, we propose a multivariable Mendelian randomization (MVMR) framework to quantify the proportion of the impact of the DNA methylome (DNAm) on complex traits that is propagated through the assayed transcriptome. Evaluating 50 complex traits, we find that on average at least 28.3% (95% CI: [26.9%–29.8%]) of DNAm-to-trait effects are mediated through (typically multiple) transcripts in the cis-region. Several regulatory mechanisms are hypothesized, including methylation of the promoter probe cg10385390 (chr1:8’022’505) increasing the risk for inflammatory bowel disease by reducing PARK7 expression. The proposed integrative framework can be extended to other omics layers to identify causal molecular chains, providing a powerful tool to map and interpret GWAS signals. Nature Publishing Group UK 2022-12-07 /pmc/articles/PMC9729239/ /pubmed/36477627 http://dx.doi.org/10.1038/s41467-022-35196-3 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/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/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Sadler, Marie C. Auwerx, Chiara Lepik, Kaido Porcu, Eleonora Kutalik, Zoltán Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases |
title | Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases |
title_full | Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases |
title_fullStr | Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases |
title_full_unstemmed | Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases |
title_short | Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases |
title_sort | quantifying the role of transcript levels in mediating dna methylation effects on complex traits and diseases |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9729239/ https://www.ncbi.nlm.nih.gov/pubmed/36477627 http://dx.doi.org/10.1038/s41467-022-35196-3 |
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