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Age-related variations in the methylome associated with gene expression in human monocytes and T cells

Author

Listed:
  • Lindsay M. Reynolds

    (Wake Forest School of Medicine
    Wake Forest School of Medicine)

  • Jackson R. Taylor

    (Wake Forest School of Medicine
    J. Paul Sticht Center on Aging, Wake Forest School of Medicine)

  • Jingzhong Ding

    (Wake Forest School of Medicine
    J. Paul Sticht Center on Aging, Wake Forest School of Medicine
    Wake Forest School of Medicine)

  • Kurt Lohman

    (Wake Forest School of Medicine
    Wake Forest School of Medicine)

  • Craig Johnson

    (University of Washington)

  • David Siscovick

    (University of Washington
    University of Washington
    Cardiovascular Health Research Unit, University of Washington)

  • Gregory Burke

    (Wake Forest School of Medicine)

  • Wendy Post

    (Johns Hopkins University)

  • Steven Shea

    (Columbia University Medical Center
    Columbia University Medical Center)

  • David R. Jacobs Jr.

    (School of Public Health, University of Minnesota)

  • Hendrik Stunnenberg

    (Nijmegen Centre for Molecular Life Sciences (NCMLS))

  • Stephen B. Kritchevsky

    (Wake Forest School of Medicine
    J. Paul Sticht Center on Aging, Wake Forest School of Medicine
    Wake Forest School of Medicine)

  • Ina Hoeschele

    (Virginia Bioinformatics Institute, Virginia Tech)

  • Charles E. McCall

    (J. Paul Sticht Center on Aging, Wake Forest School of Medicine
    Wake Forest School of Medicine
    Department of Molecular Medicine
    Translational Science Institute, Wake Forest School of Medicine)

  • David M. Herrington

    (Wake Forest School of Medicine)

  • Russell P. Tracy

    (University of Vermont)

  • Yongmei Liu

    (Wake Forest School of Medicine
    Wake Forest School of Medicine
    J. Paul Sticht Center on Aging, Wake Forest School of Medicine)

Abstract

Age-related variations in DNA methylation have been reported; however, the functional relevance of these differentially methylated sites (age-dMS) are unclear. Here we report potentially functional age-dMS, defined as age- and cis-gene expression-associated methylation sites (age-eMS), identified by integrating genome-wide CpG methylation and gene expression profiles collected ex vivo from circulating T cells (227 CD4+ samples) and monocytes (1,264 CD14+ samples, age range: 55–94 years). None of the age-eMS detected in 227 T-cell samples are detectable in 1,264 monocyte samples, in contrast to the majority of age-dMS detected in T cells that replicated in monocytes. Age-eMS tend to be hypomethylated with older age, located in predicted enhancers and preferentially linked to expression of antigen processing and presentation genes. These results identify and characterize potentially functional age-related methylation in human T cells and monocytes, and provide novel insights into the role age-dMS may have in the aging process.

Suggested Citation

  • Lindsay M. Reynolds & Jackson R. Taylor & Jingzhong Ding & Kurt Lohman & Craig Johnson & David Siscovick & Gregory Burke & Wendy Post & Steven Shea & David R. Jacobs Jr. & Hendrik Stunnenberg & Stephe, 2014. "Age-related variations in the methylome associated with gene expression in human monocytes and T cells," Nature Communications, Nature, vol. 5(1), pages 1-8, December.
    • Handle: RePEc:nat:natcom:v:5:y:2014:i:1:d:10.1038_ncomms6366
    DOI: 10.1038/ncomms6366
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    Cited by:

    1. Zhaohui Qin & Ben Li & Karen N. Conneely & Hao Wu & Ming Hu & Deepak Ayyala & Yongseok Park & Victor X. Jin & Fangyuan Zhang & Han Zhang & Li Li & Shili Lin, 2016. "Statistical Challenges in Analyzing Methylation and Long-Range Chromosomal Interaction Data," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 8(2), pages 284-309, October.
    2. Mahdi Moqri & Kejun Ying & Jesse R. Poganik & Chiara Herzog & Qingwen Chen & Mehrnoosh Emamifar & Alexander Tyshkovskiy & Alec Eames & Jure Mur & Dmitrii Glubokov & Benyamin Matei-Dediu & Ludger Goemi, 2026. "Integrative epigenetics and transcriptomics identify aging genes in human blood," Nature Communications, Nature, vol. 17(1), pages 1-13, December.
    3. Tianyu Zhu & Huige Tong & Zhaozhen Du & Stephan Beck & Andrew E. Teschendorff, 2024. "An improved epigenetic counter to track mitotic age in normal and precancerous tissues," Nature Communications, Nature, vol. 15(1), pages 1-19, December.
    4. Tiago C. Silva & Juan I. Young & Lanyu Zhang & Lissette Gomez & Michael A. Schmidt & Achintya Varma & X. Steven Chen & Eden R. Martin & Lily Wang, 2022. "Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer’s disease," Nature Communications, Nature, vol. 13(1), pages 1-16, December.

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