Literature DB >> 32361724

Association of Epigenetic Age and p16INK4a With Markers of T-Cell Composition in a Healthy Cohort.

Christin E Burd1,2, Juan Peng3, Bryon F Laskowski4, Jennifer L Hollyfield4, Suohui Zhang2, Paolo Fadda2, Lianbo Yu3, Rebecca R Andridge5, Janice K Kiecolt-Glaser4.   

Abstract

How the measurement of aging biomarkers in peripheral blood T-lymphocytes (PBTLs) is influenced by cell composition is unclear. Here, we collected peripheral blood and isolated CD3+ PBTLs from 117 healthy couples between the ages of 21 and 72. Each sample was profiled for Horvath epigenetic clock (DNAm), p16INK4a expression, cytomegalovirus (CMV) seropositivity and 74 mRNA markers of PBTL subtype, differentiation, immune checkpoints, and cytokine production. Correlations between individual aging biomarkers (DNAm or p16INK4a) and PBTL mRNAs were corrected for chronological age, sex, and couple. DNAm measurements correlated with CMV seropositivity as well as PBTL mRNAs indicative of effector function (CD8A, EOMES, TBX21, GZMB), poor proliferative capacity (KLRG1, CD57), differentiation (CD45RO, CD45RA), and immune checkpoints (PDCD1, TIGIT, LAG3, CD160, CD244). In contrast, only three PBTL mRNAs, CD28, CD244, and p14ARF, showed a significant association with p16INK4a. p16INK4a expression also showed a weaker association with immunosenescent PBTL subsets than DNAm in flow cytometry analyses. These data suggest that PBTL composition has a greater influence on DNAm than p16INK4a and link accelerated epigenetic aging to immunosenescent phenotypes.
© The Author(s) 2020. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Entities:  

Keywords:  Aging biomarker; CMV; Horvath clock; Senescence; T cell

Mesh:

Substances:

Year:  2020        PMID: 32361724      PMCID: PMC7662168          DOI: 10.1093/gerona/glaa108

Source DB:  PubMed          Journal:  J Gerontol A Biol Sci Med Sci        ISSN: 1079-5006            Impact factor:   6.053


  18 in total

1.  CD28 expression in T cell aging and human longevity.

Authors:  N Boucher; T Dufeu-Duchesne; E Vicaut; D Farge; R B Effros; F Schächter
Journal:  Exp Gerontol       Date:  1998-05       Impact factor: 4.032

2.  Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries.

Authors:  Hude Quan; Bing Li; Chantal M Couris; Kiyohide Fushimi; Patrick Graham; Phil Hider; Jean-Marie Januel; Vijaya Sundararajan
Journal:  Am J Epidemiol       Date:  2011-02-17       Impact factor: 4.897

Review 3.  Cell-type deconvolution in epigenome-wide association studies: a review and recommendations.

Authors:  Andrew E Teschendorff; Shijie C Zheng
Journal:  Epigenomics       Date:  2017-03-14       Impact factor: 4.778

Review 4.  DNA methylation-based biomarkers and the epigenetic clock theory of ageing.

Authors:  Steve Horvath; Kenneth Raj
Journal:  Nat Rev Genet       Date:  2018-06       Impact factor: 53.242

5.  Expression of p16(INK4a) in peripheral blood T-cells is a biomarker of human aging.

Authors:  Yan Liu; Hanna K Sanoff; Hyunsoon Cho; Christin E Burd; Chad Torrice; Joseph G Ibrahim; Nancy E Thomas; Norman E Sharpless
Journal:  Aging Cell       Date:  2009-05-22       Impact factor: 9.304

Review 6.  An electronic application for rapidly calculating Charlson comorbidity score.

Authors:  William H Hall; Ramanathan Ramachandran; Samir Narayan; Ashesh B Jani; Srinivasan Vijayakumar
Journal:  BMC Cancer       Date:  2004-12-20       Impact factor: 4.430

7.  Charting a dynamic DNA methylation landscape of the human genome.

Authors:  Michael J Ziller; Hongcang Gu; Fabian Müller; Julie Donaghey; Linus T-Y Tsai; Oliver Kohlbacher; Philip L De Jager; Evan D Rosen; David A Bennett; Bradley E Bernstein; Andreas Gnirke; Alexander Meissner
Journal:  Nature       Date:  2013-08-07       Impact factor: 49.962

8.  Inhibitory Receptor Expression Depends More Dominantly on Differentiation and Activation than "Exhaustion" of Human CD8 T Cells.

Authors:  Amandine Legat; Daniel E Speiser; Hanspeter Pircher; Dietmar Zehn; Silvia A Fuertes Marraco
Journal:  Front Immunol       Date:  2013-12-19       Impact factor: 7.561

9.  Chemotherapy and Stem Cell Transplantation Increase p16INK4a Expression, a Biomarker of T-cell Aging.

Authors:  William A Wood; Janakiraman Krishnamurthy; Natalia Mitin; Chad Torrice; Joel S Parker; Anna C Snavely; Thomas C Shea; Jonathan S Serody; Norman E Sharpless
Journal:  EBioMedicine       Date:  2016-08-21       Impact factor: 8.143

10.  Hallmarks of human "immunosenescence": adaptation or dysregulation?

Authors:  Graham Pawelec
Journal:  Immun Ageing       Date:  2012-07-25       Impact factor: 6.400

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  1 in total

1.  Impact of age-related T cell dynamics on the identification of biomarkers predictive of immunotherapy discontinuation: a prospective cohort study.

Authors:  Jason E Galloway; Andrea M Holderbaum; Namrata Arya; Suohui Zhang; Michael S Bodnar; Ruthann Norman; William E Carson; Lianbo Yu; Kari L Kendra; Christin E Burd
Journal:  Aging Cancer       Date:  2020-09-17
  1 in total

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