학술논문
Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function
Document Type
Article
Author
Hawe, Johann S.; Wilson, Rory; Schmid, Katharina T.; Zhou, Li; Lakshmanan, Lakshmi Narayanan; Lehne, Benjamin C.; Kühnel, Brigitte; Scott, William R.; Wielscher, Matthias; Yew, Yik Weng; Baumbach, Clemens; Lee, Dominic P.; Marouli, Eirini; Bernard, Manon; Pfeiffer, Liliane; Matías-García, Pamela R.; Autio, Matias I.; Bourgeois, Stephane; Herder, Christian; Karhunen, Ville; Meitinger, Thomas; Prokisch, Holger; Rathmann, Wolfgang; Roden, Michael; Sebert, Sylvain; Shin, Jean; Strauch, Konstantin; Zhang, Weihua; Tan, Wilson L. W.; Hauck, Stefanie M.; Merl-Pham, Juliane; Grallert, Harald; Barbosa, Eudes G. V.; Illig, Thomas; Peters, Annette; Paus, Tomas; Pausova, Zdenka; Deloukas, Panos; Foo, Roger S. Y.; Jarvelin, Marjo-Riitta; Kooner, Jaspal S.; Loh, Marie; Heinig, Matthias; Gieger, Christian; Waldenberger, Melanie; Chambers, John C.
Source
Nature Genetics; 20240101, Issue: Preprints p1-12, 12p
Subject
Language
ISSN
10614036; 15461718
Abstract
We determined the relationships between DNA sequence variation and DNA methylation using blood samples from 3,799 Europeans and 3,195 South Asians. We identify 11,165,559 SNP–CpG associations (methylation quantitative trait loci (meQTL), P< 10−14), including 467,915 meQTL that operate in trans. The meQTL are enriched for functionally relevant characteristics, including shared chromatin state, High-throuhgput chromosome conformation interaction, and association with gene expression, metabolic variation and clinical traits. We use molecular interaction and colocalization analyses to identify multiple nuclear regulatory pathways linking meQTL loci to phenotypic variation, including UBASH3B(body mass index), NFKBIE(rheumatoid arthritis), MGA(blood pressure) and COMMD7(white cell counts). For rs6511961, chromatin immunoprecipitation followed by sequencing (ChIP–seq) validates zinc finger protein (ZNF)333 as the likely transacting effector protein. Finally, we used interaction analyses to identify population- and lineage-specific meQTL, including rs174548in FADS1, with the strongest effect in CD8+T cells, thus linking fatty acid metabolism with immune dysregulation and asthma. Our study advances understanding of the potential pathways linking genetic variation to human phenotype.