Health-related quality of life and DNA methylation-based aging biomarkers among survivors of childhood cancer

Author:

Plonski Noel-Marie1,Pan Yue2,Chen Cheng13,Dong Qian1,Zhang Xijun1,Song Nan4,Shelton Kyla1,Easton John5ORCID,Mulder Heather5,Zhang Jinghui5ORCID,Neale Geoffrey6ORCID,Walker Emily6,Wang Hui3,Webster Rachel7,Brinkman Tara7,Krull Kevin R7,Armstrong Gregory T1,Ness Kirsten K1,Hudson Melissa M18ORCID,Li Qian2,Huang I-Chan1ORCID,Wang Zhaoming15ORCID

Affiliation:

1. Department of Epidemiology and Cancer Control, St Jude Children’s Research Hospital , Memphis, TN, USA

2. Department of Biostatistics, St Jude Children’s Research Hospital , Memphis, TN, USA

3. State Key Laboratory of Oncogenes and Related Genes, Center for Single-Cell Omics, School of Public Health, Shanghai Jiao Tong University School of Medicine , Shanghai, China

4. College of Pharmacy, Chungbuk National University , Cheongju, Korea

5. Department of Computational Biology, St Jude Children’s Research Hospital , Memphis, TN, USA

6. Hartwell Center, St Jude Children’s Research Hospital , Memphis, TN, USA

7. Department of Psychology, St Jude Children’s Research Hospital , Memphis, TN, USA

8. Department of Oncology, St Jude Children’s Research Hospital , Memphis, TN, USA

Abstract

Abstract Background Childhood cancer survivors are at high risk for morbidity and mortality and poor patient-reported outcomes, typically health-related quality of life (HRQOL). However, associations between DNA methylation–based aging biomarkers and HRQOL have not been evaluated. Methods DNA methylation was generated with Infinium EPIC BeadChip on blood-derived DNA (median for age at blood draw = 34.5 years, range = 18.5-66.6 years), and HRQOL was assessed with age at survey (mean = 32.3 years, range = 18.4-64.5 years) from 2206 survivors in the St Jude Lifetime Cohort. DNA methylation–based aging biomarkers, including epigenetic age using multiple clocks (eg, GrimAge) and others (eg, DNAmB2M: beta-2-microglobulin; DNAmADM: adrenomedullin), were derived from the DNAm Age Calculator (https://dnamage.genetics.ucla.edu). HRQOL was assessed using the Medical Outcomes Study 36-Item Short-Form Health Survey to capture 8 domains and physical and mental component summaries. General linear models evaluated associations between HRQOL and epigenetic age acceleration (EAA; eg, EAA_GrimAge) or other age-adjusted DNA methylation–based biomarkers (eg, ageadj_DNAmB2M) after adjusting for age at blood draw, sex, cancer treatments, and DNA methylation–based surrogate for smoking pack-years. All P values were 2-sided. Results Worse HRQOL was associated with greater EAA_GrimAge (physical component summaries: β = -0.18 years, 95% confidence interval [CI] = -0.251 to -0.11 years; P = 1.85 × 10−5; and 4 individual HRQOL domains), followed by ageadj_DNAmB2M (physical component summaries: β = -0.08 years, 95% CI = -0.124 to -0.037 years; P = .003; and 3 individual HRQOL domains) and ageadj_DNAmADM (physical component summaries: β = -0.082 years, 95% CI = -0.125 to -0.039 years; P = .002; and 2 HRQOL domains). EAA_Hannum (Hannum clock) was not associated with any HRQOL. Conclusions Overall and domain-specific measures of HRQOL are associated with DNA methylation measures of biological aging. Future longitudinal studies should test biological aging as a potential mechanism underlying the association between poor HRQOL and increased risk of clinically assessed adverse health outcomes.

Funder

V Foundation

American Lebanese Syrian Associated Charities to St Jude Children’s Research Hospital

National Institutes of Health

St Jude Children’s Research Hospital

Publisher

Oxford University Press (OUP)

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