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

Arthritis, Rheumatoid / genetics Asia Blood Pressure / genetics Body Mass Index CD8-Positive T-Lymphocytes / metabolism CpG Islands DNA Methylation / genetics DNA Replication Europe Genetic Variation Genome-Wide Association Study Humans Leukocytes / metabolism Polymorphism, Single Nucleotide Quantitative Trait Loci

Journal

Nature genetics
ISSN: 1546-1718
Titre abrégé: Nat Genet
Pays: United States
ID NLM: 9216904

Informations de publication

Date de publication:
01 2022
Historique:
received: 22 08 2019
accepted: 18 10 2021
pubmed: 5 1 2022
medline: 24 2 2022
entrez: 4 1 2022
Statut: ppublish

Résumé

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

Identifiants

DOI: 10.1038/s41588-021-00969-x PMID: 34980917
pubmed: 34980917
doi: 10.1038/s41588-021-00969-x
pii: 10.1038/s41588-021-00969-x
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

18-29

Subventions

Organisme : Medical Research Council
ID : G1002319
Pays : United Kingdom
Organisme : British Heart Foundation
ID : SP/04/002
Pays : United Kingdom
Organisme : NIMH NIH HHS
ID : R01 MH063706
Pays : United States
Organisme : CIHR
Pays : Canada
Organisme : Wellcome Trust
ID : 081917/Z/07/Z
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/J004480/1
Pays : United Kingdom
Organisme : NHLBI NIH HHS
ID : R01 HL087679
Pays : United States
Organisme : Wellcome Trust
ID : 084723/Z/08/Z
Pays : United Kingdom
Organisme : NIMH NIH HHS
ID : RL1 MH083268
Pays : United States
Organisme : Medical Research Council
ID : G0601966
Pays : United Kingdom
Organisme : British Heart Foundation
ID : RG/14/5/30893
Pays : United Kingdom
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/S020845/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0500539
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_UP_1605/7
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0600705
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/L007150/1
Pays : United Kingdom
Organisme : Medical Research Council
ID : G0700931
Pays : United Kingdom

Investigateurs

Kourosh R Ahmadi (KR)
Chrysanthi Ainali (C)
Amy Barrett (A)
Veronique Bataille (V)
Jordana T Bell (JT)
Alfonso Buil (A)
Emmanouil T Dermitzakis (ET)
Antigone S Dimas (AS)
Richard Durbin (R)
Daniel Glass (D)
Elin Grundberg (E)
Neelam Hassanali (N)
Åsa K Hedman (ÅK)
Catherine Ingle (C)
David Knowles (D)
Maria Krestyaninova (M)
Cecilia M Lindgren (CM)
Christopher E Lowe (CE)
Mark I McCarthy (MI)
Eshwar Meduri (E)
Paola di Meglio (P)
Josine L Min (JL)
Stephen B Montgomery (SB)
Frank O Nestle (FO)
Alexandra C Nica (AC)
James Nisbet (J)
Stephen O'Rahilly (S)
Leopold Parts (L)
Simon Potter (S)
Johanna Sandling (J)
Magdalena Sekowska (M)
So-Youn Shin (SY)
Kerrin S Small (KS)
Nicole Soranzo (N)
Tim D Spector (TD)
Gabriela Surdulescu (G)
Mary E Travers (ME)
Loukia Tsaprouni (L)
Sophia Tsoka (S)
Alicja Wilk (A)
Tsun-Po Yang (TP)
Krina T Zondervan (KT)

Informations de copyright

© 2022. The Author(s), under exclusive licence to Springer Nature America, Inc.

Références

Bird, A. Perceptions of epigenetics. Nature 447, 396–398 (2007).
pubmed: 17522671 doi: 10.1038/nature05913
Schubeler, D. Function and information content of DNA methylation. Nature 517, 321–326 (2015).
pubmed: 25592537 doi: 10.1038/nature14192
Parry, A., Rulands, S. & Reik, W. Active turnover of DNA methylation during cell fate decisions. Nat. Rev. Genet. 22, 59–66 (2021).
pubmed: 33024290 doi: 10.1038/s41576-020-00287-8
Jaenisch, R. & Bird, A. Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat. Genet. 33, 245–254 (2003).
pubmed: 12610534 doi: 10.1038/ng1089
Chambers, J. C. et al. 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. Lancet Diabetes Endocrinol. 3, 526–534 (2015).
pubmed: 26095709 pmcid: 4724884 doi: 10.1016/S2213-8587(15)00127-8
Marioni, R. E. et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biol. 16, 25 (2015).
pubmed: 25633388 pmcid: 4350614 doi: 10.1186/s13059-015-0584-6
van der Harst, P., de Windt, L. J. & Chambers, J. C. Translational perspective on epigenetics in cardiovascular disease. J. Am. Coll. Cardiol. 70, 590–606 (2017).
pubmed: 28750703 pmcid: 5543329 doi: 10.1016/j.jacc.2017.05.067
Wahl, S. et al. Epigenome-wide association study of body mass index, and the adverse outcomes of adiposity. Nature 541, 81–86 (2017).
pubmed: 28002404 doi: 10.1038/nature20784
Zhang, Y. et al. DNA methylation signatures in peripheral blood strongly predict all-cause mortality. Nat. Commun. 8, 14617 (2017).
pubmed: 28303888 pmcid: 5357865 doi: 10.1038/ncomms14617
Sugiura, M. et al. Epigenetic modifications in prostate cancer. Int. J. Urol. 28, 140–149 (2020).
pubmed: 33111429 doi: 10.1111/iju.14406
Blokhin, I. O., Khorkova, O., Saveanu, R. V. & Wahlestedt, C. Molecular mechanisms of psychiatric diseases. Neurobiol. Dis. 146, 105136 (2020).
pubmed: 33080337 doi: 10.1016/j.nbd.2020.105136
Darwiche, N. Epigenetic mechanisms and the hallmarks of cancer: an intimate affair. Am. J. Cancer Res. 10, 1954–1978 (2020).
pubmed: 32774995 pmcid: 7407342
Bonder, M. J. et al. Genetic and epigenetic regulation of gene expression in fetal and adult human livers. BMC Genomics 15, 860 (2014).
pubmed: 25282492 pmcid: 4287518 doi: 10.1186/1471-2164-15-860
Bonder, M. J. et al. Disease variants alter transcription factor levels and methylation of their binding sites. Nat. Genet. 49, 131–138 (2017).
pubmed: 27918535 doi: 10.1038/ng.3721
Gibbs, J. R. et al. Abundant quantitative trait loci exist for DNA methylation and gene expression in human brain. PLoS Genet. 6, e1000952 (2010).
pubmed: 20485568 pmcid: 2869317 doi: 10.1371/journal.pgen.1000952
Grundberg, E. et al. Global analysis of DNA methylation variation in adipose tissue from twins reveals links to disease-associated variants in distal regulatory elements. Am. J. Hum. Genet. 93, 876–890 (2013).
pubmed: 24183450 pmcid: 3824131 doi: 10.1016/j.ajhg.2013.10.004
Gutierrez-Arcelus, M. et al. Passive and active DNA methylation and the interplay with genetic variation in gene regulation. eLife 2, e00523 (2013).
pubmed: 23755361 pmcid: 3673336 doi: 10.7554/eLife.00523
Lemire, M. et al. Long-range epigenetic regulation is conferred by genetic variation located at thousands of independent loci. Nat. Commun. 6, 6326 (2015).
pubmed: 25716334 doi: 10.1038/ncomms7326
Huan, T. et al. Genome-wide identification of DNA methylation QTLs in whole blood highlights pathways for cardiovascular disease. Nat. Commun. 10, 4267 (2019).
pubmed: 31537805 pmcid: 6753136 doi: 10.1038/s41467-019-12228-z
Hannon, E. et al. Leveraging DNA-methylation quantitative-trait loci to characterize the relationship between methylomic variation, gene expression, and complex traits. Am. J. Hum. Genet. 103, 654–665 (2018).
pubmed: 30401456 pmcid: 6217758 doi: 10.1016/j.ajhg.2018.09.007
Gaunt, T. R. et al. Systematic identification of genetic influences on methylation across the human life course. Genome Biol. 17, 61 (2016).
pubmed: 27036880 pmcid: 4818469 doi: 10.1186/s13059-016-0926-z
McRae, A. F. et al. Identification of 55,000 replicated DNA methylation QTL. Sci. Rep. 8, 17605 (2018).
pubmed: 30514905 pmcid: 6279736 doi: 10.1038/s41598-018-35871-w
Hop, P. J. et al. Genome-wide identification of genes regulating DNA methylation using genetic anchors for causal inference. Genome Biol. 21, 220 (2020).
pubmed: 32859263 pmcid: 7453518 doi: 10.1186/s13059-020-02114-z
Peterson, R. E. et al. Genome-wide association studies in ancestrally diverse populations: opportunities, methods, pitfalls, and recommendations. Cell 179, 589–603 (2019).
pubmed: 31607513 pmcid: 6939869 doi: 10.1016/j.cell.2019.08.051
Bell, C. G. et al. Obligatory and facilitative allelic variation in the DNA methylome within common disease-associated loci. Nat. Commun. 9, 8 (2018).
pubmed: 29295990 pmcid: 5750212 doi: 10.1038/s41467-017-01586-1
Zhu, Z. et al. Integration of summary data from GWAS and eQTL studies predicts complex trait gene targets. Nat. Genet. 48, 481–487 (2016).
pubmed: 27019110 doi: 10.1038/ng.3538
Brenner, C. et al. Myc represses transcription through recruitment of DNA methyltransferase corepressor. EMBO J. 24, 336–346 (2005).
pubmed: 15616584 doi: 10.1038/sj.emboj.7600509
Esteve, P. O., Chin, H. G. & Pradhan, S. Human maintenance DNA (cytosine-5)-methyltransferase and p53 modulate expression of p53-repressed promoters. Proc. Natl Acad. Sci. USA 102, 1000–1005 (2005).
pmcid: 544618 doi: 10.1073/pnas.0407729102
Shlyueva, D., Stampfel, G. & Stark, A. Transcriptional enhancers: from properties to genome-wide predictions. Nat. Rev. Genet. 15, 272–286 (2014).
pubmed: 24614317 doi: 10.1038/nrg3682
Visel, A., Rubin, E. M. & Pennacchio, L. A. Genomic views of distant-acting enhancers. Nature 461, 199–205 (2009).
pubmed: 19741700 pmcid: 2923221 doi: 10.1038/nature08451
Javierre, B. M. et al. Lineage-specific genome architecture links enhancers and non-coding disease variants to target gene promoters. Cell 167, 1369–1384 (2016).
pubmed: 27863249 pmcid: 5123897 doi: 10.1016/j.cell.2016.09.037
Rao, S. S. et al. A 3D map of the human genome at kilobase resolution reveals principles of chromatin looping. Cell 159, 1665–1680 (2014).
pubmed: 25497547 pmcid: 5635824 doi: 10.1016/j.cell.2014.11.021
Liu, Y., Toh, H., Sasaki, H., Zhang, X. & Cheng, X. An atomic model of Zfp57 recognition of CpG methylation within a specific DNA sequence. Genes Dev. 26, 2374–2379 (2012).
pubmed: 23059534 pmcid: 3489995 doi: 10.1101/gad.202200.112
Shi, H. et al. ZFP57 regulation of transposable elements and gene expression within and beyond imprinted domains. Epigenetics Chromatin 12, 49 (2019).
pubmed: 31399135 pmcid: 6688207 doi: 10.1186/s13072-019-0295-4
Yengo, L. et al. Meta-analysis of genome-wide association studies for height and body mass index in approximately 700000 individuals of European ancestry. Hum. Mol. Genet. 27, 3641–3649 (2018).
pubmed: 30124842 pmcid: 6488973 doi: 10.1093/hmg/ddy271
Lee, S. T. et al. Protein tyrosine phosphatase UBASH3B is overexpressed in triple-negative breast cancer and promotes invasion and metastasis. Proc. Natl Acad. Sci. USA 110, 11121–11126 (2013).
pubmed: 23784775 pmcid: 3704014 doi: 10.1073/pnas.1300873110
Pulit, S. L. et al. Meta-analysis of genome-wide association studies for body fat distribution in 694 649 individuals of European ancestry. Hum. Mol. Genet. 28, 166–174 (2019).
pubmed: 30239722 doi: 10.1093/hmg/ddy327
Kichaev, G. et al. Leveraging polygenic functional enrichment to improve GWAS power. Am. J. Hum. Genet. 104, 65–75 (2019).
pubmed: 30595370 doi: 10.1016/j.ajhg.2018.11.008
Zhu, Z. et al. Shared genetic and experimental links between obesity-related traits and asthma subtypes in UK Biobank. J. Allergy Clin. Immunol. 145, 537–549 (2020).
pubmed: 31669095 doi: 10.1016/j.jaci.2019.09.035
Richardson, T. G. et al. Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: a multivariable Mendelian randomisation analysis. PLoS Med. 17, e1003062 (2020).
pubmed: 32203549 pmcid: 7089422 doi: 10.1371/journal.pmed.1003062
Konieczna, J., Sanchez, J., Palou, M., Pico, C. & Palou, A. Blood cell transcriptomic-based early biomarkers of adverse programming effects of gestational calorie restriction and their reversibility by leptin supplementation. Sci. Rep. 5, 9088 (2015).
pubmed: 25766068 pmcid: 4357898 doi: 10.1038/srep09088
Mancuso, N. et al. Integrating gene expression with summary association statistics to identify genes associated with 30 complex traits. Am. J. Hum. Genet. 100, 473–487 (2017).
pubmed: 28238358 pmcid: 5339290 doi: 10.1016/j.ajhg.2017.01.031
Okada, Y. et al. Genetics of rheumatoid arthritis contributes to biology and drug discovery. Nature 506, 376–381 (2014).
pubmed: 24390342 doi: 10.1038/nature12873
Emery, P. et al. IL-6 receptor inhibition with tocilizumab improves treatment outcomes in patients with rheumatoid arthritis refractory to anti-tumour necrosis factor biologicals: results from a 24-week multicentre randomised placebo-controlled trial. Ann. Rheum. Dis. 67, 1516–1523 (2008).
pubmed: 18625622 doi: 10.1136/ard.2008.092932
Navarro-Millan, I., Singh, J. A. & Curtis, J. R. Systematic review of tocilizumab for rheumatoid arthritis: a new biologic agent targeting the interleukin-6 receptor. Clin. Ther. 34, 788–802 (2012).
pubmed: 22444783 pmcid: 3805022 doi: 10.1016/j.clinthera.2012.02.014
Wen, X., Pique-Regi, R. & Luca, F. Integrating molecular QTL data into genome-wide genetic association analysis: probabilistic assessment of enrichment and colocalization. PLoS Genet. 13, e1006646 (2017).
pubmed: 28278150 pmcid: 5363995 doi: 10.1371/journal.pgen.1006646
Burnichon, N. et al. MAX mutations cause hereditary and sporadic pheochromocytoma and paraganglioma. Clin. Cancer Res. 18, 2828–2837 (2012).
pubmed: 22452945 doi: 10.1158/1078-0432.CCR-12-0160
Li, H. et al. Novel treatment of hypertension by specifically targeting E2F for restoration of endothelial dihydrofolate reductase and eNOS function under oxidative stress. Hypertension 73, 179–189 (2019).
pubmed: 30571557 doi: 10.1161/HYPERTENSIONAHA.118.11643
Burstein, E. et al. COMMD proteins, a novel family of structural and functional homologs of MURR1. J. Biol. Chem. 280, 22222–22232 (2005).
pubmed: 15799966 doi: 10.1074/jbc.M501928200
Astle, W. J. et al. The allelic landscape of human blood cell trait variation and links to common complex disease. Cell 167, 1415–1429 (2016).
pubmed: 27863252 pmcid: 5300907 doi: 10.1016/j.cell.2016.10.042
Suhail, A. et al. DeSUMOylase SENP7-mediated epithelial signaling triggers intestinal inflammation via expansion of γδ T cells. Cell Rep. 29, 3522–3538 (2019).
pubmed: 31825833 doi: 10.1016/j.celrep.2019.11.028
Jing, Z., Liu, Y., Dong, M., Hu, S. & Huang, S. Identification of the DNA binding element of the human ZNF333 protein. J. Biochem. Mol. Biol. 37, 663–670 (2004).
pubmed: 15607024
Chen, M. H. et al. Trans-ethnic and ancestry-specific blood-cell genetics in 746,667 individuals from 5 global populations. Cell 182, 1198–1213 (2020).
pubmed: 32888493 pmcid: 7480402 doi: 10.1016/j.cell.2020.06.045
Nedelec, Y. et al. Genetic ancestry and natural selection drive population differences in immune responses to pathogens. Cell 167, 657–669 (2016).
pubmed: 27768889 doi: 10.1016/j.cell.2016.09.025
Joehanes, R. et al. Epigenetic signatures of cigarette smoking. Circ. Cardiovasc. Genet. 9, 436–447 (2016).
pubmed: 27651444 pmcid: 5267325 doi: 10.1161/CIRCGENETICS.116.001506
Singmann, P. et al. Characterization of whole-genome autosomal differences of DNA methylation between men and women. Epigenetics Chromatin 8, 43 (2015).
pubmed: 26500701 pmcid: 4615866 doi: 10.1186/s13072-015-0035-3
Zeilinger, S. et al. Tobacco smoking leads to extensive genome-wide changes in DNA methylation. PLoS ONE 8, e63812 (2013).
pubmed: 23691101 pmcid: 3656907 doi: 10.1371/journal.pone.0063812
Giri, A. K. et al. DNA methylation profiling reveals the presence of population-specific signatures correlating with phenotypic characteristics. Mol. Genet. Genomics 292, 655–662 (2017).
pubmed: 28271161 doi: 10.1007/s00438-017-1298-0
Breeze, C. E. et al. eFORGE: a tool for identifying cell type-specific signal in epigenomic data. Cell Rep. 17, 2137–2150 (2016).
pubmed: 27851974 pmcid: 5120369 doi: 10.1016/j.celrep.2016.10.059
Westra, H. J. et al. Cell specific eQTL analysis without sorting cells. PLoS Genet. 11, e1005223 (2015).
pubmed: 25955312 pmcid: 4425538 doi: 10.1371/journal.pgen.1005223
Guan, W. et al. Genome-wide association study of plasma N
pubmed: 24823311 pmcid: 4123862 doi: 10.1161/CIRCGENETICS.113.000208
Shin, S. Y. et al. An atlas of genetic influences on human blood metabolites. Nat. Genet. 46, 543–550 (2014).
pubmed: 24816252 pmcid: 4064254 doi: 10.1038/ng.2982
Kamat, M. A. et al. PhenoScanner V2: an expanded tool for searching human genotype–phenotype associations. Bioinformatics 35, 4851–4853 (2019).
pubmed: 31233103 pmcid: 6853652 doi: 10.1093/bioinformatics/btz469
Gelfand, E. W. & Dakhama, A. CD8
pubmed: 16522456 doi: 10.1016/j.jaci.2005.12.1340
Cho, S. H., Stanciu, L. A., Holgate, S. T. & Johnston, S. L. Increased interleukin-4, interleukin-5, and interferon-γ in airway CD4
pubmed: 15502111 doi: 10.1164/rccm.200310-1416OC
Zhou, X. & Stephens, M. Genome-wide efficient mixed-model analysis for association studies. Nat. Genet. 44, 821–824 (2012).
pubmed: 22706312 pmcid: 3386377 doi: 10.1038/ng.2310
Ernst, J. & Kellis, M. Discovery and characterization of chromatin states for systematic annotation of the human genome. Nat. Biotechnol. 28, 817–825 (2010).
pubmed: 20657582 pmcid: 2919626 doi: 10.1038/nbt.1662
Roadmap Epigenomics Consortium et al. Integrative analysis of 111 reference human epigenomes. Nature 518, 317–330 (2015).
doi: 10.1038/nature14248
Shabalin, A. A. Matrix eQTL: ultra fast eQTL analysis via large matrix operations. Bioinformatics 28, 1353–1358 (2012).
pubmed: 22492648 pmcid: 3348564 doi: 10.1093/bioinformatics/bts163
GTEx Consortium et al. Genetic effects on gene expression across human tissues. Nature 550, 204–213 (2017).
pmcid: 5776756 doi: 10.1038/nature24277
Kim, K. A. et al. Environmental risk factors and comorbidities of primary biliary cholangitis in Korea: a case–control study. Korean J. Intern. Med. 36, 313–321 (2020).
pubmed: 32204000 pmcid: 7969053 doi: 10.3904/kjim.2019.234
GTEx Consortium The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science 369, 1318–1330 (2020).
doi: 10.1126/science.aaz1776
Staley, J. R. et al. PhenoScanner: a database of human genotype–phenotype associations. Bioinformatics 32, 3207–3209 (2016).
pubmed: 27318201 pmcid: 5048068 doi: 10.1093/bioinformatics/btw373
Griffon, A. et al. Integrative analysis of public ChIP–seq experiments reveals a complex multi-cell regulatory landscape. Nucleic Acids Res. 43, e27 (2015).
pubmed: 25477382 doi: 10.1093/nar/gku1280
Franceschini, A. et al. STRING v9.1: protein–protein interaction networks, with increased coverage and integration. Nucleic Acids Res. 41, D808–D815 (2013).
Suthram, S., Beyer, A., Karp, R. M., Eldar, Y. & Ideker, T. eQED: an efficient method for interpreting eQTL associations using protein networks. Mol. Syst. Biol. 4, 162 (2008).
pubmed: 18319721 pmcid: 2290938 doi: 10.1038/msb.2008.4
Tu, Z., Wang, L., Arbeitman, M. N., Chen, T. & Sun, F. An integrative approach for causal gene identification and gene regulatory pathway inference. Bioinformatics 22, e489–96 (2006).
pubmed: 16873511 doi: 10.1093/bioinformatics/btl234
Haghverdi, L., Buettner, F. & Theis, F. J. Diffusion maps for high-dimensional single-cell analysis of differentiation data. Bioinformatics 31, 2989–2998 (2015).
pubmed: 26002886 doi: 10.1093/bioinformatics/btv325
Haghverdi, L., Buttner, M., Wolf, F. A., Buettner, F. & Theis, F. J. Diffusion pseudotime robustly reconstructs lineage branching. Nat. Methods 13, 845–848 (2016).
pubmed: 27571553 doi: 10.1038/nmeth.3971
Schramm, K. et al. Mapping the genetic architecture of gene regulation in whole blood. PLoS ONE 9, e93844 (2014).
pubmed: 24740359 pmcid: 3989189 doi: 10.1371/journal.pone.0093844
Benjamini, Y., Drai, D., Elmer, G., Kafkafi, N. & Golani, I. Controlling the false discovery rate in behavior genetics research. Behav. Brain Res. 125, 279–284 (2001).
pubmed: 11682119 doi: 10.1016/S0166-4328(01)00297-2
Buniello, A. et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Res. 47, D1005–D1012 (2019).
pubmed: 30445434 doi: 10.1093/nar/gky1120
Taylor-Weiner, A. et al. Scaling computational genomics to millions of individuals with GPUs. Genome Biol. 20, 228 (2019).
pubmed: 31675989 pmcid: 6823959 doi: 10.1186/s13059-019-1836-7
Hawe, J. S., Heinig, M. & Loh, M. Code for the analyses described in Hawe et al. Nature Genetics. Zenodo https://doi.org/10.5281/zenodo.5529828 (2021).

Auteurs

Johann S Hawe (JS)

Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, Neuherberg, Germany.
Department of Informatics, Technical University of Munich, Garching bei München, Germany.
ORCID: 0000-0003-3890-303X

Rory Wilson (R)

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.
ORCID: 0000-0001-6135-3764

Katharina T Schmid (KT)

Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, Neuherberg, Germany.
Department of Informatics, Technical University of Munich, Garching bei München, Germany.
ORCID: 0000-0001-7082-1099

Li Zhou (L)

Lee Kong Chian School of Medicine, Singapore, Singapore.

Lakshmi Narayanan Lakshmanan (LN)

Lee Kong Chian School of Medicine, Singapore, Singapore.
ORCID: 0000-0002-2892-1931

Benjamin C Lehne (BC)

Department of Epidemiology and Biostatistics, Imperial College London, London, UK.

Brigitte Kühnel (B)

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.

William R Scott (WR)

Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
ORCID: 0000-0001-5467-114X

Matthias Wielscher (M)

Department of Epidemiology and Biostatistics, Imperial College London, London, UK.

Yik Weng Yew (YW)

Lee Kong Chian School of Medicine, Singapore, Singapore.

Clemens Baumbach (C)

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.

Dominic P Lee (DP)

Genome Institute of Singapore, Singapore, Singapore.

Eirini Marouli (E)

Centre for Genomic Health, Queen Mary University of London, London, UK.
William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
ORCID: 0000-0001-6179-1609

Manon Bernard (M)

Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada.
The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.

Liliane Pfeiffer (L)

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.

Pamela R Matías-García (PR)

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.

Matias I Autio (MI)

Genome Institute of Singapore, Singapore, Singapore.
Cardiovascular Research Institute, National University Health Systems, National University of Singapore, Singapore, Singapore.
ORCID: 0000-0001-9579-9617

Stephane Bourgeois (S)

William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
ORCID: 0000-0001-9245-9510

Christian Herder (C)

German Center for Diabetes Research (DZD), partner site Düsseldorf, Düsseldorf, Germany.
Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany.
Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.

Ville Karhunen (V)

Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
ORCID: 0000-0001-6064-1588

Thomas Meitinger (T)

Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Institute of Human Genetics, Technical University Munich, Munich, Germany.

Holger Prokisch (H)

Institute of Human Genetics, Technical University Munich, Munich, Germany.
Institute of Neurogenomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
ORCID: 0000-0003-2379-6286

Wolfgang Rathmann (W)

German Center for Diabetes Research (DZD), partner site Düsseldorf, Düsseldorf, Germany.
Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University Düsseldorf, Düsseldorf, Germany.

Michael Roden (M)

German Center for Diabetes Research (DZD), partner site Düsseldorf, Düsseldorf, Germany.
Institute for Clinical Diabetology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich Heine University, Düsseldorf, Germany.
Division of Endocrinology and Diabetology, Medical Faculty, Heinrich Heine University, Düsseldorf, Germany.

Sylvain Sebert (S)

Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
Biocenter Oulu, University of Oulu, Oulu, Finland.
Department for Genomics of Common Diseases, School of Public Health, Imperial College London, London, UK.
ORCID: 0000-0001-6681-6983

Jean Shin (J)

Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada.
The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
ORCID: 0000-0001-7353-5178

Konstantin Strauch (K)

Chair of Genetic Epidemiology, IBE, Faculty of Medicine, LMU Munich, Munich, Germany.
Institute of Genetic Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Institute of Medical Biostatistics, Epidemiology and Informatics (IMBEI), University Medical Center, Johannes Gutenberg University, Mainz, Germany.

Weihua Zhang (W)

Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
Department of Cardiology, Ealing Hospital, London North West Healthcare NHS Trust, Southall, UK.
ORCID: 0000-0001-8279-3611

Wilson L W Tan (WLW)

Genome Institute of Singapore, Singapore, Singapore.

Stefanie M Hauck (SM)

Research Unit Protein Science, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany.
ORCID: 0000-0002-1630-6827

Juliane Merl-Pham (J)

Research Unit Protein Science, Helmholtz Zentrum München, German Research Centre for Environmental Health, Munich, Germany.
ORCID: 0000-0002-3422-4083

Harald Grallert (H)

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.
German Center for Diabetes Research (DZD), Munich-Neuherberg, Germany.

Eudes G V Barbosa (EGV)

Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, Neuherberg, Germany.

Thomas Illig (T)

Hannover Unified Biobank, Hannover Medical School, Hannover, Germany.
Institute for Human Genetics, Hannover Medical School, Hannover, Germany.

Annette Peters (A)

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany.
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany.
German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Hannover, Germany.
ORCID: 0000-0001-6645-0985

Tomas Paus (T)

Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, Canada.
ORCID: 0000-0003-1495-9338

Zdenka Pausova (Z)

Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, Ontario, Canada.
The Hospital for Sick Children, University of Toronto, Toronto, Ontario, Canada.
ORCID: 0000-0002-7784-1380

Panos Deloukas (P)

Centre for Genomic Health, Queen Mary University of London, London, UK.
William Harvey Research Institute, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
ORCID: 0000-0001-9251-070X

Roger S Y Foo (RSY)

Genome Institute of Singapore, Singapore, Singapore.
Cardiovascular Research Institute, National University Health Systems, National University of Singapore, Singapore, Singapore.
ORCID: 0000-0002-8079-4618

Marjo-Riitta Jarvelin (MR)

Department of Epidemiology and Biostatistics, Imperial College London, London, UK.
Center for Life Course Health Research, Faculty of Medicine, University of Oulu, Oulu, Finland.
Biocenter Oulu, University of Oulu, Oulu, Finland.
Unit of Primary Care, Oulu University Hospital, Oulu, Finland.
ORCID: 0000-0002-2149-0630

Jaspal S Kooner (JS)

National Heart and Lung Institute, Imperial College London, London, UK. j.kooner@ic.ac.uk.
ORCID: 0000-0003-2086-4837

Marie Loh (M)

Lee Kong Chian School of Medicine, Singapore, Singapore. marie.loh@ntu.edu.sg.
Department of Epidemiology and Biostatistics, Imperial College London, London, UK. marie.loh@ntu.edu.sg.
ORCID: 0000-0003-3626-8466

Matthias Heinig (M)

Institute of Computational Biology, Deutsches Forschungszentrum für Gesundheit und Umwelt, Helmholtz Zentrum München, Neuherberg, Germany. matthias.heinig@helmholtz-muenchen.de.
Department of Informatics, Technical University of Munich, Garching bei München, Germany. matthias.heinig@helmholtz-muenchen.de.
ORCID: 0000-0002-5612-1720

Christian Gieger (C)

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. christian.gieger@helmholtz-muenchen.de.
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany. christian.gieger@helmholtz-muenchen.de.
ORCID: 0000-0001-6986-9554

Melanie Waldenberger (M)

Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany. waldenberger@helmholtz-muenchen.de.
Research Unit Molecular Epidemiology, Helmholtz Zentrum München, German Research Centre for Environmental Health, Neuherberg, Germany. waldenberger@helmholtz-muenchen.de.
German Research Center for Cardiovascular Disease (DZHK), partner site Munich Heart Alliance, Hannover, Germany. waldenberger@helmholtz-muenchen.de.
ORCID: 0000-0003-0583-5093

John C Chambers (JC)

Lee Kong Chian School of Medicine, Singapore, Singapore. john.chambers@ic.ac.uk.
Department of Epidemiology and Biostatistics, Imperial College London, London, UK. john.chambers@ic.ac.uk.
ORCID: 0000-0003-0209-4541

Articles similaires

[Redispensing of expensive oral anticancer medicines: a practical application].

Lisanne N van Merendonk, Kübra Akgöl, Bastiaan Nuijen
1.00
Humans Antineoplastic Agents Administration, Oral Drug Costs Counterfeit Drugs

Smoking Cessation and Incident Cardiovascular Disease.

Jun Hwan Cho, Seung Yong Shin, Hoseob Kim et al.
1.00
Humans Male Smoking Cessation Cardiovascular Diseases Female

Evaluation of Low-Value Services Across Major Medicare Advantage Insurers and Traditional Medicare.

Ciara Duggan, Adam L Beckman, Ishani Ganguli et al.
1.00
Humans United States Aged Cross-Sectional Studies Medicare Part C

Effectiveness of Virtual Yoga for Chronic Low Back Pain: A Randomized Clinical Trial.

Hallie Tankha, Devyn Gaskins, Amanda Shallcross et al.
1.00
Humans Yoga Low Back Pain Female Male

Classifications MeSH

questionsmedicales.fr › Maladies du système immunitaire › Maladies auto-immunes › Polyarthrite rhumatoïde › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Régions géographiques › Asie › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Phénomènes physiologiques respiratoires et circulatoires › Phénomènes physiologiques cardiovasculaires › Hémodynamique › Pression sanguine › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Mesures épidémiologiques › Biométrie › Anthropométrie › Indice de masse corporelle › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Systèmes sanguin et immunitaire › Système immunitaire › Leucocytes › Agranulocytes › Lymphocytes › Lymphocytes T › Lymphocytes T CD8+ › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Génome › Composants de génome › Ilots CpG › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Phénomènes génétiques › Méthylation de l'ADN › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Phénomènes génétiques › Réplication de l'ADN › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Régions géographiques › Europe › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Phénomènes génétiques › Variation génétique › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Environnement et santé publique › Santé publique › Méthodes épidémiologiques › Épidémiologie moléculaire › Étude d'association pangénomique › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Systèmes sanguin et immunitaire › Système immunitaire › Leucocytes › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Phénomènes génétiques › Variation génétique › Polymorphisme génétique › Polymorphisme de nucléotide simple › Genetic variation influencing DNA methylation...
questionsmedicales.fr › Phénomènes génétiques › Structures génétiques › Génome › Composants de génome › Locus génétiques › Locus de caractère quantitatif › Genetic variation influencing DNA methylation...