Literature DB >> 34980917

Genetic variation influencing DNA methylation provides insights into molecular mechanisms regulating genomic function.

Johann S Hawe1,2, Rory Wilson3,4, Katharina T Schmid1,2, Li Zhou5, Lakshmi Narayanan Lakshmanan5, Benjamin C Lehne6, Brigitte Kühnel3,4, William R Scott6, Matthias Wielscher6, Yik Weng Yew5, Clemens Baumbach3,4, Dominic P Lee7, Eirini Marouli8,9, Manon Bernard10,11, Liliane Pfeiffer3,4, Pamela R Matías-García3,4, Matias I Autio7,12, Stephane Bourgeois9, Christian Herder13,14,15, Ville Karhunen6,16, Thomas Meitinger17,18, Holger Prokisch18,19, Wolfgang Rathmann13,20, Michael Roden13,14,15, Sylvain Sebert16,21,22, Jean Shin10,11, Konstantin Strauch23,24,25, Weihua Zhang6,26, Wilson L W Tan7, Stefanie M Hauck27, Juliane Merl-Pham27, Harald Grallert3,4,28, Eudes G V Barbosa1, Thomas Illig29,30, Annette Peters3,4,31, Tomas Paus32, Zdenka Pausova10,11, Panos Deloukas8,9, Roger S Y Foo7,12, Marjo-Riitta Jarvelin6,16,21,33, Jaspal S Kooner34, Marie Loh35,36, Matthias Heinig37,38, Christian Gieger39,40, Melanie Waldenberger41,42,43, John C Chambers44,45.   

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 trans acting effector protein. Finally, we used interaction analyses to identify population- and lineage-specific meQTL, including rs174548 in 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.
© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.

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Year:  2022        PMID: 34980917     DOI: 10.1038/s41588-021-00969-x

Source DB:  PubMed          Journal:  Nat Genet        ISSN: 1061-4036            Impact factor:   38.330


  78 in total

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Authors:  Rudolf Jaenisch; Adrian Bird
Journal:  Nat Genet       Date:  2003-03       Impact factor: 38.330

2.  Perceptions of epigenetics.

Authors:  Adrian Bird
Journal:  Nature       Date:  2007-05-24       Impact factor: 49.962

Review 3.  Function and information content of DNA methylation.

Authors:  Dirk Schübeler
Journal:  Nature       Date:  2015-01-15       Impact factor: 49.962

Review 4.  Translational Perspective on Epigenetics in Cardiovascular Disease.

Authors:  Pim van der Harst; Leon J de Windt; John C Chambers
Journal:  J Am Coll Cardiol       Date:  2017-08-01       Impact factor: 24.094

Review 5.  Active turnover of DNA methylation during cell fate decisions.

Authors:  Aled Parry; Steffen Rulands; Wolf Reik
Journal:  Nat Rev Genet       Date:  2020-10-06       Impact factor: 53.242

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7.  DNA methylation age of blood predicts all-cause mortality in later life.

Authors:  Riccardo E Marioni; Sonia Shah; Allan F McRae; Brian H Chen; Elena Colicino; Sarah E Harris; Jude Gibson; Anjali K Henders; Paul Redmond; Simon R Cox; Alison Pattie; Janie Corley; Lee Murphy; Nicholas G Martin; Grant W Montgomery; Andrew P Feinberg; M Daniele Fallin; Michael L Multhaup; Andrew E Jaffe; Roby Joehanes; Joel Schwartz; Allan C Just; Kathryn L Lunetta; Joanne M Murabito; John M Starr; Steve Horvath; Andrea A Baccarelli; Daniel Levy; Peter M Visscher; Naomi R Wray; Ian J Deary
Journal:  Genome Biol       Date:  2015-01-30       Impact factor: 13.583

8.  Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity.

Authors:  Simone Wahl; Alexander Drong; Benjamin Lehne; Marie Loh; William R Scott; Sonja Kunze; Pei-Chien Tsai; Janina S Ried; Weihua Zhang; Youwen Yang; Sili Tan; Giovanni Fiorito; Lude Franke; Simonetta Guarrera; Silva Kasela; Jennifer Kriebel; Rebecca C Richmond; Marco Adamo; Uzma Afzal; Mika Ala-Korpela; Benedetta Albetti; Ole Ammerpohl; Jane F Apperley; Marian Beekman; Pier Alberto Bertazzi; S Lucas Black; Christine Blancher; Marc-Jan Bonder; Mario Brosch; Maren Carstensen-Kirberg; Anton J M de Craen; Simon de Lusignan; Abbas Dehghan; Mohamed Elkalaawy; Krista Fischer; Oscar H Franco; Tom R Gaunt; Jochen Hampe; Majid Hashemi; Aaron Isaacs; Andrew Jenkinson; Sujeet Jha; Norihiro Kato; Vittorio Krogh; Michael Laffan; Christa Meisinger; Thomas Meitinger; Zuan Yu Mok; Valeria Motta; Hong Kiat Ng; Zacharoula Nikolakopoulou; Georgios Nteliopoulos; Salvatore Panico; Natalia Pervjakova; Holger Prokisch; Wolfgang Rathmann; Michael Roden; Federica Rota; Michelle Ann Rozario; Johanna K Sandling; Clemens Schafmayer; Katharina Schramm; Reiner Siebert; P Eline Slagboom; Pasi Soininen; Lisette Stolk; Konstantin Strauch; E-Shyong Tai; Letizia Tarantini; Barbara Thorand; Ettje F Tigchelaar; Rosario Tumino; Andre G Uitterlinden; Cornelia van Duijn; Joyce B J van Meurs; Paolo Vineis; Ananda Rajitha Wickremasinghe; Cisca Wijmenga; Tsun-Po Yang; Wei Yuan; Alexandra Zhernakova; Rachel L Batterham; George Davey Smith; Panos Deloukas; Bastiaan T Heijmans; Christian Herder; Albert Hofman; Cecilia M Lindgren; Lili Milani; Pim van der Harst; Annette Peters; Thomas Illig; Caroline L Relton; Melanie Waldenberger; Marjo-Riitta Järvelin; Valentina Bollati; Richie Soong; Tim D Spector; James Scott; Mark I McCarthy; Paul Elliott; Jordana T Bell; Giuseppe Matullo; Christian Gieger; Jaspal S Kooner; Harald Grallert; John C Chambers
Journal:  Nature       Date:  2016-12-21       Impact factor: 49.962

9.  DNA methylation signatures in peripheral blood strongly predict all-cause mortality.

Authors:  Yan Zhang; Rory Wilson; Jonathan Heiss; Lutz P Breitling; Kai-Uwe Saum; Ben Schöttker; Bernd Holleczek; Melanie Waldenberger; Annette Peters; Hermann Brenner
Journal:  Nat Commun       Date:  2017-03-17       Impact factor: 14.919

10.  Epigenome-wide association of DNA methylation markers in peripheral blood from Indian Asians and Europeans with incident type 2 diabetes: a nested case-control study.

Authors:  John C Chambers; Marie Loh; Benjamin Lehne; Alexander Drong; Jennifer Kriebel; Valeria Motta; Marjo-Riitta Jarvelin; James Scott; Harald Grallert; Valentina Bollati; Paul Elliott; Mark I McCarthy; Jaspal S Kooner; Simone Wahl; Hannah R Elliott; Federica Rota; William R Scott; Weihua Zhang; Sian-Tsung Tan; Gianluca Campanella; Marc Chadeau-Hyam; Loic Yengo; Rebecca C Richmond; Martyna Adamowicz-Brice; Uzma Afzal; Kiymet Bozaoglu; Zuan Yu Mok; Hong Kiat Ng; François Pattou; Holger Prokisch; Michelle Ann Rozario; Letizia Tarantini; James Abbott; Mika Ala-Korpela; Benedetta Albetti; Ole Ammerpohl; Pier Alberto Bertazzi; Christine Blancher; Robert Caiazzo; John Danesh; Tom R Gaunt; Simon de Lusignan; Christian Gieger; Thomas Illig; Sujeet Jha; Simon Jones; Jeremy Jowett; Antti J Kangas; Anuradhani Kasturiratne; Norihiro Kato; Navaratnam Kotea; Sudhir Kowlessur; Janne Pitkäniemi; Prakash Punjabi; Danish Saleheen; Clemens Schafmayer; Pasi Soininen; E-Shyong Tai; Barbara Thorand; Jaakko Tuomilehto; Ananda Rajitha Wickremasinghe; Soterios A Kyrtopoulos; Timothy J Aitman; Christian Herder; Jochen Hampe; Stéphane Cauchi; Caroline L Relton; Philippe Froguel; Richie Soong; Paolo Vineis
Journal:  Lancet Diabetes Endocrinol       Date:  2015-06-18       Impact factor: 32.069

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2.  The immune factors driving DNA methylation variation in human blood.

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3.  Cell-type heterogeneity: Why we should adjust for it in epigenome and biomarker studies.

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4.  DNA methylation and aeroallergen sensitization: The chicken or the egg?

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5.  Conditional GWAS of non-CG transposon methylation in Arabidopsis thaliana reveals major polymorphisms in five genes.

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Journal:  PLoS Genet       Date:  2022-09-09       Impact factor: 6.020

6.  A Methylation Diagnostic Model Based on Random Forests and Neural Networks for Asthma Identification.

Authors:  Dong-Dong Li; Ting Chen; You-Liang Ling; YongAn Jiang; Qiu-Gen Li
Journal:  Comput Math Methods Med       Date:  2022-09-28       Impact factor: 2.809

Review 7.  Insights into Exosome in the Intervertebral Disc: Emerging Role for Disc Homeostasis and Normal Function.

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8.  Fatty acid metabolism-related genes in bronchoalveolar lavage fluid unveil prognostic and immune infiltration in idiopathic pulmonary fibrosis.

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