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. 2021 Jun 29;22(1):194.
doi: 10.1186/s13059-021-02398-9.

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

Daniel L McCartney #  1 Josine L Min #  2   3 Rebecca C Richmond #  2   3 Ake T Lu #  4 Maria K Sobczyk #  2   3 Gail Davies #  5 Linda Broer #  6 Xiuqing Guo #  7 Ayoung Jeong #  8   9 Jeesun Jung #  10 Silva Kasela #  11 Seyma Katrinli #  12 Pei-Lun Kuo #  13 Pamela R Matias-Garcia #  14   15   16 Pashupati P Mishra #  17 Marianne Nygaard #  18   19 Teemu Palviainen #  20 Amit Patki #  21 Laura M Raffield #  22 Scott M Ratliff #  23 Tom G Richardson #  2   3 Oliver Robinson #  24 Mette Soerensen #  18   19   25 Dianjianyi Sun #  26 Pei-Chien Tsai #  27   28   29 Matthijs D van der Zee #  30   31 Rosie M Walker #  1 Xiaochuan Wang #  32 Yunzhang Wang #  33 Rui Xia #  34 Zongli Xu #  35 Jie Yao #  7 Wei Zhao #  23 Adolfo Correa  36 Eric Boerwinkle  37 Pierre-Antoine Dugué  32   38   39 Peter Durda  40 Hannah R Elliott  2   3 Christian Gieger  14   15 Genetics of DNA Methylation ConsortiumEco J C de Geus  30   31 Sarah E Harris  5 Gibran Hemani  2   3 Medea Imboden  8   9 Mika Kähönen  41 Sharon L R Kardia  23 Jacob K Kresovich  35 Shengxu Li  42 Kathryn L Lunetta  43 Massimo Mangino  27   44 Dan Mason  45 Andrew M McIntosh  46 Jonas Mengel-From  18   19 Ann Zenobia Moore  13 Joanne M Murabito  47 NHLBI Trans-Omics for Precision Medicine (TOPMed) ConsortiumMiina Ollikainen  20 James S Pankow  48 Nancy L Pedersen  33 Annette Peters  15   49 Silvia Polidoro  24 David J Porteous  1 Olli Raitakari  50   51   52 Stephen S Rich  53 Dale P Sandler  35 Elina Sillanpää  20   54 Alicia K Smith  12   55 Melissa C Southey  32   38   39 Konstantin Strauch  56   57   58 Hemant Tiwari  21 Toshiko Tanaka  13 Therese Tillin  59 Andre G Uitterlinden  6   60 David J Van Den Berg  61 Jenny van Dongen  30   31 James G Wilson  62   63 John Wright  45 Idil Yet  27   64 Donna Arnett  65 Stefania Bandinelli  66 Jordana T Bell  27 Alexandra M Binder  67   68 Dorret I Boomsma  30   31 Wei Chen  69 Kaare Christensen  18   19   25 Karen N Conneely  70 Paul Elliott  24 Luigi Ferrucci  13 Myriam Fornage  34 Sara Hägg  33 Caroline Hayward  71 Marguerite Irvin  72 Jaakko Kaprio  20   73 Deborah A Lawlor  2   3   74 Terho Lehtimäki  17 Falk W Lohoff  10 Lili Milani  11 Roger L Milne  32   38   39 Nicole Probst-Hensch  8   9 Alex P Reiner  75 Beate Ritz  67 Jerome I Rotter  7 Jennifer A Smith  23 Jack A Taylor  35 Joyce B J van Meurs  6   60 Paolo Vineis  24 Melanie Waldenberger  14   15   49 Ian J Deary  5 Caroline L Relton  2   3 Steve Horvath #  76   77 Riccardo E Marioni #  78
Affiliations

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

Daniel L McCartney et al. Genome Biol. .

Abstract

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.

Keywords: DNA methylation; Epigenetic clock; GWAS.

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Conflict of interest statement

The authors declare that they have no competing interests.

Figures

Fig. 1
Fig. 1
Genetic correlations and standard errors for the epigenetic biomarkers. IEAA (intrinsic epigenetic age acceleration)
Fig. 2
Fig. 2
Significant genetic correlations between GrimAge acceleration (A) and PhenoAge acceleration (B) and a selection of GWAS traits. *This variable was originally coded with a high score representing lower health rating. We have multiplied the genetic correlation by − 1 for interpretability
Fig. 3
Fig. 3
A Polygenic predictions for the six epigenetic biomarkers in LBC1921, LBC1936, SABRE, Born in Bradford, ARIES, FHS, and the Young Finns Study. IEAA (intrinsic epigenetic age acceleration), PAI1 (plasminogen activator inhibitor-1). B Associations between GrimAge polygenic risk score (P < 1) and UK Biobank GWAS traits
Fig. 4
Fig. 4
Causal effects of UK Biobank GWAS traits on GrimAge acceleration. Effects correspond to increase/decrease in GrimAge acceleration per SD increase in waist circumference, hip circumference, and BMI; or per log odds increase for university/college education and current smoker status

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