An epigenetic aging analysis of randomized metformin and weight loss interventions in overweight postmenopausal breast cancer survivors

Jamaji C Nwanaji-Enwerem, Felicia Fei-Lei Chung, Lars Van der Laan, Alexei Novoloaca, Cyrille Cuenin, Harriet Johansson, Bernardo Bonanni, Alan E Hubbard, Martyn T Smith, Sheri J Hartman, Andres Cardenas, Dorothy D Sears, Zdenko Herceg, Jamaji C Nwanaji-Enwerem, Felicia Fei-Lei Chung, Lars Van der Laan, Alexei Novoloaca, Cyrille Cuenin, Harriet Johansson, Bernardo Bonanni, Alan E Hubbard, Martyn T Smith, Sheri J Hartman, Andres Cardenas, Dorothy D Sears, Zdenko Herceg

Abstract

Metformin and weight loss relationships with epigenetic age measures-biological aging biomarkers-remain understudied. We performed a post-hoc analysis of a randomized controlled trial among overweight/obese breast cancer survivors (N = 192) assigned to metformin, placebo, weight loss with metformin, or weight loss with placebo interventions for 6 months. Epigenetic age was correlated with chronological age (r = 0.20-0.86; P < 0.005). However, no significant epigenetic aging associations were observed by intervention arms. Consistent with published reports in non-cancer patients, 6 months of metformin therapy may be inadequate to observe expected epigenetic age deceleration. Longer duration studies are needed to better characterize these relationships.Trial Registration: Registry Name: ClincialTrials.Gov.Registration Number: NCT01302379.Date of Registration: February 2011.URL: https://ichgcp.net/clinical-trials-registry/NCT01302379.

Keywords: Biomarkers; DNA methylation age; GrimAge; PhenoAge; RCT.

Conflict of interest statement

The authors declare that they have no competing interests.

© 2021. The Author(s).

Figures

Fig. 1
Fig. 1
Epigenetic Age and Chronological Age Pearson Correlations. Figure presents the baseline chronological age and epigenetic age correlation coefficients for the study sample (N = 192) for DNAmAge Hannum (A), DNAmAge Horvath (B), DNAmAge SkinBloodClock (C), DNAm PhenoAge (D), DNAm GrimAge (E), DNAm TL (F), EpiTOC (G), EpiTOC2 (H), and MiAge (I)

References

    1. Patterson RE, Marinac CR, Natarajan L, Hartman SJ, Cadmus-Bertram L, Flatt SW, et al. Recruitment strategies, design, and participant characteristics in a trial of weight-loss and metformin in breast cancer survivors. Contemp Clin Trials. 2016;47:64–71. doi: 10.1016/j.cct.2015.12.009.
    1. Hägg S, Jylhävä J. Should we invest in biological age predictors to treat colorectal cancer in older adults? Eur J Surg Oncol. 2020;46(3):316–320. doi: 10.1016/j.ejso.2019.11.003.
    1. Ambatipudi S, Horvath S, Perrier F, Cuenin C, Hernandez-Vargas H, Le Calvez-Kelm F, et al. DNA methylome analysis identifies accelerated epigenetic ageing associated with postmenopausal breast cancer susceptibility. Eur J Cancer. 2017;75:299–307. doi: 10.1016/j.ejca.2017.01.014.
    1. Patterson RE, Marinac CR, Sears DD, Kerr J, Hartman SJ, Cadmus-Bertram L, et al. The effects of metformin and weight loss on biomarkers associated with breast cancer outcomes. J Natl Cancer Inst. 2018;110(11):1239–1247. doi: 10.1093/jnci/djy040.
    1. Lu AT, Quach A, Wilson JG, Reiner AP, Aviv A, Raj K, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY) 2019;11(2):303–327. doi: 10.18632/aging.101684.
    1. Teschendorff AE. A comparison of epigenetic mitotic-like clocks for cancer risk prediction. Genome Med. 2020;12(1):56. doi: 10.1186/s13073-020-00752-3.
    1. Lu AT, Seeboth A, Tsai P-C, Sun D, Quach A, Reiner AP, et al. DNA methylation-based estimator of telomere length. Aging (Albany NY) 2019;11(16):5895–5923. doi: 10.18632/aging.102173.
    1. Pidsley R, Zotenko E, Peters TJ, Lawrence MG, Risbridger GP, Molloy P, et al. Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling. Genome Biol. 2016;17(1):208. doi: 10.1186/s13059-016-1066-1.
    1. Fahy GM, Brooke RT, Watson JP, Good Z, Vasanawala SS, Maecker H, et al. Reversal of epigenetic aging and immunosenescent trends in humans. Aging Cell. 2019;18(6):e13028. doi: 10.1111/acel.13028.
    1. Horvath S, Erhart W, Brosch M, Ammerpohl O, von Schönfels W, Ahrens M, et al. Obesity accelerates epigenetic aging of human liver. Proc Natl Acad Sci USA. 2014;111(43):15538–15543. doi: 10.1073/pnas.1412759111.
    1. Chapman IM. Obesity paradox during aging. Interdiscip Top Gerontol. 2010;37:20–36. doi: 10.1159/000319992.
    1. Miller SL, Wolfe RR. The danger of weight loss in the elderly. J Nutr Health Aging. 2008;12(7):487–491. doi: 10.1007/BF02982710.
    1. Baracos VE, Arribas L. Sarcopenic obesity: hidden muscle wasting and its impact for survival and complications of cancer therapy. Ann Oncol. 2018;29:ii1–9. doi: 10.1093/annonc/mdx810.
    1. Bhurchandi S, Kumar S, Agrawal S, Acharya S, Jain S, Talwar D, et al. Correlation of sarcopenia with modified frailty index as a predictor of outcome in critically Ill elderly patients: a cross-sectional study. Cureus. 2021;13(10):e19065.

Source: PubMed

Подписаться