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McCartney, D.L.* ; Min, J.L.* ; Richmond, R.C.* ; Lu, A.T.* ; Sobczyk, M.K.* ; Davies, G.* ; Broer, L.* ; Guo, X.* ; Jeong, A.* ; Jung, J.* ; Kasela, S.* ; Katrinli, S.* ; Kuo, P.L.* ; Matias-Garcia, P.R. ; Mishra, P.P.* ; Nygaard, M.* ; Palviainen, T.* ; Patki, A.* ; Raffield, L.M.* ; Ratliff, S.M.* ; Richardson, T.G.* ; Robinson, O.* ; Soerensen, M.* ; Sun, D.* ; Tsai, P.C.* ; van der Zee, M.D.* ; Walker, R.M.* ; Wang, X.* ; Wang, Y.* ; Xia, R.* ; Xu, Z.* ; Yao, J.* ; Zhao, W.* ; Correa, A.* ; Boerwinkle, E.* ; Dugué, P.A.* ; Durda, P.* ; Elliott, H.R.* ; Gieger, C. ; de Geus, E.J.C.* ; Harris, S.E.* ; Hemani, G.* ; Imboden, M.* ; Kähönen, M.* ; Kardia, S.L.R.* ; Kresovich, J.K.* ; Li, S.* ; Lunetta, K.L.* ; Mangino, M.* ; Mason, D.* ; McIntosh, A.M.* ; Mengel-From, J.* ; Moore, A.Z.* ; Murabito, J.M.* ; Ollikainen, M.* ; Pankow, J.S.* ; Pedersen, N.L.* ; Peters, A. ; Polidoro, S.* ; Porteous, D.J.* ; Raitakari, O.* ; Rich, S.S.* ; Sandler, D.P.* ; Sillanpää, E.* ; Smith, A.K.* ; Southey, M.C.* ; Strauch, K. ; Tiwari, H.* ; Tanaka, T.* ; Tillin, T.* ; Uitterlinden, A.G.* ; Van Den Berg, D.J.* ; van Dongen, J.* ; Wilson, J.G.* ; Wright, J.* ; Yet, I.* ; Arnett, D.* ; Bandinelli, S.* ; Bell, J.T.* ; Binder, A.M.* ; Boomsma, D.I.* ; Chen, W.* ; Christensen, K.* ; Conneely, K.N.* ; Elliott, P.* ; Ferrucci, L.* ; Fornage, M.* ; Hägg, S.* ; Hayward, C.* ; Irvin, M.R.* ; Kaprio, J.* ; Lawlor, D.A.* ; Lehtimäki, T.* ; Lohoff, F.W.* ; Milani, L.* ; Milne, R.L.* ; Probst-Hensch, N.* ; Reiner, A.P.* ; Ritz, B.* ; Rotter, J.I.* ; Smith, J.A.* ; Taylor, J.A.* ; van Meurs, J.B.J.* ; Vineis, P.* ; Waldenberger, M. ; Deary, I.J.* ; Relton, C.L.* ; Horvath, S.* ; Marioni, R.E.*

Genome-wide association studies identify 137 genetic loci for DNA methylation biomarkers of aging.

Genome Biol. 22:194 (2021)
Publ. Version/Full Text Research data DOI
Open Access Gold
Creative Commons Lizenzvertrag
BACKGROUND: Biological aging estimators derived from DNA methylation data are heritable and correlate with morbidity and mortality. Consequently, identification of genetic and environmental contributors to the variation in these measures in populations has become a major goal in the field. RESULTS: Leveraging DNA methylation and SNP data from more than 40,000 individuals, we identify 137 genome-wide significant loci, of which 113 are novel, from genome-wide association study (GWAS) meta-analyses of four epigenetic clocks and epigenetic surrogate markers for granulocyte proportions and plasminogen activator inhibitor 1 levels, respectively. We find evidence for shared genetic loci associated with the Horvath clock and expression of transcripts encoding genes linked to lipid metabolism and immune function. Notably, these loci are independent of those reported to regulate DNA methylation levels at constituent clock CpGs. A polygenic score for GrimAge acceleration showed strong associations with adiposity-related traits, educational attainment, parental longevity, and C-reactive protein levels. CONCLUSION: This study illuminates the genetic architecture underlying epigenetic aging and its shared genetic contributions with lifestyle factors and longevity.
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Publication type Article: Journal article
Document type Scientific Article
Keywords Dna Methylation ; Epigenetic Clock ; Gwas; Mendelian Randomization; Susceptibility Loci; Age; Metaanalysis; Gwas; Enrichment; Regression; Insights; Provides; Blood
ISSN (print) / ISBN 1474-760X
e-ISSN 1465-6906
Journal Genome Biology
Quellenangaben Volume: 22, Issue: 1, Pages: , Article Number: 194 Supplement: ,
Publisher BioMed Central
Publishing Place Campus, 4 Crinan St, London N1 9xw, England
Reviewing status Peer reviewed
Grants Medical Research Council
Cancer Research UK
Alzheimer's Research UK
NIH HHS