Telomere length and epigenetic clocks as markers of cellular aging: a comparative study
Abstract Telomere length (TL) and DNA methylation–based epigenetic clocks are markers of biological age, but the relationship between the two is not fully understood. Here, we used multivariable regression models to evaluate the relationships between leukocyte TL (LTL; measured by qPCR [n = 635] or flow FISH [n = 144]) and five epigenetic clocks (Hannum, DNAmAge pan-tissue, PhenoAge, SkinBlood, or GrimAge clocks), or their epigenetic age acceleration measures in healthy adults (age 19–61 years). LTL showed statistically significant negative correlations with all clocks (qPCR: r = − 0.26 to − 0.32; flow FISH: r = − 0.34 to − 0.49; p < 0.001 for all). Yet, models adjusted for age, sex, and race revealed significant associations between three of five clocks (PhenoAge, GrimAge, and Hannum clocks) and LTL by flow FISH (p < 0.01 for all) or qPCR (p < 0.001 for all). Significant associations between age acceleration measures for the same three clocks and qPCR or flow FISH TL were also found (p < 0.01 for all). Additionally, LTL (by qPCR or flow FISH) showed significant associations with extrinsic epigenetic age acceleration (EEAA: p < 0.0001 for both), but not intrinsic epigenetic age acceleration (IEAA; p > 0.05 for both). In conclusion, the relationships between LTL and epigenetic clocks were limited to clocks reflecting phenotypic age. The observed association between LTL and EEAA reflects the ability of both measures to detect immunosenescence. The observed modest correlations between LTL and epigenetic clocks highlight a possible benefit from incorporating both measures in understanding disease etiology and prognosis..
Medienart: |
E-Artikel |
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Erscheinungsjahr: |
2022 |
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Erschienen: |
2022 |
Enthalten in: |
Zur Gesamtaufnahme - volume:44 |
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Enthalten in: |
Age - 44(2022), 3 vom: 18. Mai, Seite 1861-1869 |
Sprache: |
Englisch |
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Beteiligte Personen: |
Pearce, Emily E. [VerfasserIn] |
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Links: |
Volltext [lizenzpflichtig] |
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Anmerkungen: |
© This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply 2022 |
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doi: |
10.1007/s11357-022-00586-4 |
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funding: |
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PPN (Katalog-ID): |
SPR047364564 |
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520 | |a Abstract Telomere length (TL) and DNA methylation–based epigenetic clocks are markers of biological age, but the relationship between the two is not fully understood. Here, we used multivariable regression models to evaluate the relationships between leukocyte TL (LTL; measured by qPCR [n = 635] or flow FISH [n = 144]) and five epigenetic clocks (Hannum, DNAmAge pan-tissue, PhenoAge, SkinBlood, or GrimAge clocks), or their epigenetic age acceleration measures in healthy adults (age 19–61 years). LTL showed statistically significant negative correlations with all clocks (qPCR: r = − 0.26 to − 0.32; flow FISH: r = − 0.34 to − 0.49; p < 0.001 for all). Yet, models adjusted for age, sex, and race revealed significant associations between three of five clocks (PhenoAge, GrimAge, and Hannum clocks) and LTL by flow FISH (p < 0.01 for all) or qPCR (p < 0.001 for all). Significant associations between age acceleration measures for the same three clocks and qPCR or flow FISH TL were also found (p < 0.01 for all). Additionally, LTL (by qPCR or flow FISH) showed significant associations with extrinsic epigenetic age acceleration (EEAA: p < 0.0001 for both), but not intrinsic epigenetic age acceleration (IEAA; p > 0.05 for both). In conclusion, the relationships between LTL and epigenetic clocks were limited to clocks reflecting phenotypic age. The observed association between LTL and EEAA reflects the ability of both measures to detect immunosenescence. The observed modest correlations between LTL and epigenetic clocks highlight a possible benefit from incorporating both measures in understanding disease etiology and prognosis. | ||
650 | 4 | |a Telomere length |7 (dpeaa)DE-He213 | |
650 | 4 | |a Methylation age |7 (dpeaa)DE-He213 | |
650 | 4 | |a Epigenetic clocks |7 (dpeaa)DE-He213 | |
700 | 1 | |a Alsaggaf, Rotana |4 aut | |
700 | 1 | |a Katta, Shilpa |4 aut | |
700 | 1 | |a Dagnall, Casey |4 aut | |
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700 | 1 | |a Hicks, Belynda D. |4 aut | |
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700 | 1 | |a Savage, Sharon A. |4 aut | |
700 | 1 | |a Horvath, Steve |4 aut | |
700 | 1 | |a Gadalla, Shahinaz M. |4 aut | |
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