Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits

Yang Wu; Jian Zeng; Futao Zhang; Zhihong Zhu; Ting Qi; Zhili Zheng; Lloyd-Jones Luke R; Riccardo Marioni; Nicolas G. Martin; Grant W Montgomery; Ian J Deary; Peter Visscher; Allan F. Mcrae; Jian Yang

doi:10.1038/s41467-018-03371-0

Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits

Yang Wu, Jian Zeng, Futao Zhang, Zhihong Zhu, Ting Qi, Zhili Zheng, Lloyd-Jones Luke R, Riccardo Marioni, Nicolas G. Martin, Grant W Montgomery, Ian J Deary, Peter Visscher, Allan F. Mcrae, Jian Yang

Research output: Contribution to journal › Article › peer-review

Abstract / Description of output

The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7,858 DNAm sites and 2,733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm.

Original language	English
Article number	918
Pages (from-to)	1-14
Number of pages	14
Journal	Nature Communications
Volume	9
Early online date	2 Mar 2018
DOIs	https://doi.org/10.1038/s41467-018-03371-0
Publication status	E-pub ahead of print - 2 Mar 2018

Keywords / Materials (for Non-textual outputs)

data integration
epigenomics
genetics

Access to Document

10.1038/s41467-018-03371-0Licence: Creative Commons: Attribution (CC-BY)

WuEtalNC2018IntegrativeAnalysisOfOmicsFinal published version, 5.08 MBLicence: Creative Commons: Attribution (CC-BY)

Brain imaging and cognitive ageing in the Lothian Birth Cohort 1936: III
Wardlaw, J., Bastin, M. & Deary, I.
MRC
1/05/15 → 30/04/19
Project: Research
Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2.
Maclullich, A.
1/09/13 → 31/08/19
Project: Research
Brain White mater imaging and cognitive ageing in the Lothian Birth Cohort of 1936:II
Deary, I., Bastin, M., Penke, L., Starr, J. & Wardlaw, J.
MRC
8/06/11 → 7/03/15
Project: Research

Cite this

Wu, Y., Zeng, J., Zhang, F., Zhu, Z., Qi, T., Zheng, Z., Luke R, L.-J., Marioni, R., Martin, N. G., Montgomery, G. W., Deary, I. J., Visscher, P., Mcrae, A. F., & Yang, J. (2018). Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits. Nature Communications, 9, 1-14. Article 918. Advance online publication. https://doi.org/10.1038/s41467-018-03371-0

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title = "Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits",

abstract = "The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7,858 DNAm sites and 2,733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm. ",

keywords = "data integration, epigenomics, genetics",

author = "Yang Wu and Jian Zeng and Futao Zhang and Zhihong Zhu and Ting Qi and Zhili Zheng and {Luke R}, Lloyd-Jones and Riccardo Marioni and Martin, {Nicolas G.} and Montgomery, {Grant W} and Deary, {Ian J} and Peter Visscher and Mcrae, {Allan F.} and Jian Yang",

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doi = "10.1038/s41467-018-03371-0",

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AU - Wu, Yang

AU - Zeng, Jian

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AU - Zheng, Zhili

AU - Luke R, Lloyd-Jones

AU - Marioni, Riccardo

AU - Martin, Nicolas G.

AU - Montgomery, Grant W

AU - Deary, Ian J

AU - Visscher, Peter

AU - Mcrae, Allan F.

AU - Yang, Jian

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N2 - The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7,858 DNAm sites and 2,733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm.

AB - The identification of genes and regulatory elements underlying the associations discovered by GWAS is essential to understanding the aetiology of complex traits (including diseases). Here, we demonstrate an analytical paradigm of prioritizing genes and regulatory elements at GWAS loci for follow-up functional studies. We perform an integrative analysis that uses summary-level SNP data from multi-omics studies to detect DNA methylation (DNAm) sites associated with gene expression and phenotype through shared genetic effects (i.e., pleiotropy). We identify pleiotropic associations between 7,858 DNAm sites and 2,733 genes. These DNAm sites are enriched in enhancers and promoters, and >40% of them are mapped to distal genes. Further pleiotropic association analyses, which link both the methylome and transcriptome to 12 complex traits, identify 149 DNAm sites and 66 genes, indicating a plausible mechanism whereby the effect of a genetic variant on phenotype is mediated by genetic regulation of transcription through DNAm.

KW - data integration

KW - epigenomics

KW - genetics

U2 - 10.1038/s41467-018-03371-0

DO - 10.1038/s41467-018-03371-0

M3 - Article

SN - 2041-1723

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JO - Nature Communications

JF - Nature Communications

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ER -

Integrative analysis of omics summary data reveals putative mechanisms underlying complex traits

Abstract / Description of output

Keywords / Materials (for Non-textual outputs)

Access to Document

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Projects

Brain imaging and cognitive ageing in the Lothian Birth Cohort 1936: III

Centre for Cognitive Ageing and Cognitive Epidemiology Phase 2.

Brain White mater imaging and cognitive ageing in the Lothian Birth Cohort of 1936:II

Cite this