Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study

Pierre-Antoine Dugue; Julie K. Bassett; Ee Ming Wong; Jihoon E. Joo; Shuai Li; Chenglong Yu; Daniel F. Schmidt; Enes Makalic; Nicole Wong Doo; Daniel D Buchanan; Allison M. Hodge; Dallas Roland English; John Llewelyn Hopper; Graham Giles; Melissa Caroline Southey; Roger L. Milne

doi:10.1093/jncics/pkaa109

Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study

Pierre-Antoine Dugue, Julie K. Bassett, Ee Ming Wong, Jihoon E. Joo, Shuai Li, Chenglong Yu, Daniel F. Schmidt, Enes Makalic, Nicole Wong Doo, Daniel D Buchanan, Allison M. Hodge, Dallas Roland English, John Llewelyn Hopper, Graham Giles, Melissa Caroline Southey, Roger L. Milne

Research output: Contribution to journal › Article › Research › peer-review

28 Citations (Scopus)

Abstract

Background: We previously investigated the association between 5 "first-generation"measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length. Methods: We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity. Results: We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively). Conclusions: The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.

Original language	English
Article number	pkaa109
Number of pages	8
Journal	JNCI Cancer Spectrum
Volume	5
Issue number	1
DOIs	https://doi.org/10.1093/jncics/pkaa109
Publication status	Published - Feb 2021

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10.1093/jncics/pkaa109Licence: CC BY

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Dugue, P-A., Bassett, J. K., Wong, E. M., Joo, J. E., Li, S., Yu, C., Schmidt, D. F., Makalic, E., Wong Doo, N., Buchanan, D. D., Hodge, A. M., English, D. R., Hopper, J. L., Giles, G., Southey, M. C., & Milne, R. L. (2021). Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study. JNCI Cancer Spectrum, 5(1), [pkaa109]. https://doi.org/10.1093/jncics/pkaa109

@article{2b6027444c4b4b7eb209d1c1f8383844,

title = "Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study",

abstract = "Background: We previously investigated the association between 5 {"}first-generation{"}measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length. Methods: We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity. Results: We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively). Conclusions: The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer. ",

author = "Pierre-Antoine Dugue and Bassett, {Julie K.} and Wong, {Ee Ming} and Joo, {Jihoon E.} and Shuai Li and Chenglong Yu and Schmidt, {Daniel F.} and Enes Makalic and {Wong Doo}, Nicole and Buchanan, {Daniel D} and Hodge, {Allison M.} and English, {Dallas Roland} and Hopper, {John Llewelyn} and Graham Giles and Southey, {Melissa Caroline} and Milne, {Roger L.}",

note = "Publisher Copyright: {\textcopyright} 2020 The Author(s). Published by Oxford University Press.",

year = "2021",

month = feb,

doi = "10.1093/jncics/pkaa109",

language = "English",

volume = "5",

journal = "JNCI Cancer Spectrum",

issn = "2515-5091",

publisher = "Oxford University Press",

number = "1",

}

Dugue, P-A, Bassett, JK, Wong, EM, Joo, JE, Li, S, Yu, C , Schmidt, DF, Makalic, E, Wong Doo, N, Buchanan, DD, Hodge, AM, English, DR, Hopper, JL, Giles, G, Southey, MC & Milne, RL 2021, 'Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study', JNCI Cancer Spectrum, vol. 5, no. 1, pkaa109. https://doi.org/10.1093/jncics/pkaa109

TY - JOUR

T1 - Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer

T2 - A Prospective Study

AU - Dugue, Pierre-Antoine

AU - Bassett, Julie K.

AU - Wong, Ee Ming

AU - Joo, Jihoon E.

AU - Li, Shuai

AU - Yu, Chenglong

AU - Schmidt, Daniel F.

AU - Makalic, Enes

AU - Wong Doo, Nicole

AU - Buchanan, Daniel D

AU - Hodge, Allison M.

AU - English, Dallas Roland

AU - Hopper, John Llewelyn

AU - Giles, Graham

AU - Southey, Melissa Caroline

AU - Milne, Roger L.

PY - 2021/2

Y1 - 2021/2

N2 - Background: We previously investigated the association between 5 "first-generation"measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length. Methods: We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity. Results: We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively). Conclusions: The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.

AB - Background: We previously investigated the association between 5 "first-generation"measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length. Methods: We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity. Results: We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively). Conclusions: The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.

UR - http://www.scopus.com/inward/record.url?scp=85099025803&partnerID=8YFLogxK

U2 - 10.1093/jncics/pkaa109

DO - 10.1093/jncics/pkaa109

M3 - Article

C2 - 33442664

AN - SCOPUS:85099025803

VL - 5

JO - JNCI Cancer Spectrum

JF - JNCI Cancer Spectrum

SN - 2515-5091

IS - 1

M1 - pkaa109

ER -

Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study

Abstract

UN SDGs

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Other files and links

Increasing precision in epidemiological exposure assessment by integrating genetic and epigenetic data

Improving the lives of people at increased risk of cancer

Precision Public Health for major cancers - novel approaches to building the genetic, epigenetic and lifestyle knowledge base for assessing risk and prognosis

Cite this

Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study

Abstract

UN SDGs

Access to Document

Other files and links

Projects

Increasing precision in epidemiological exposure assessment by integrating genetic and epigenetic data

Improving the lives of people at increased risk of cancer

Precision Public Health for major cancers - novel approaches to building the genetic, epigenetic and lifestyle knowledge base for assessing risk and prognosis

Cite this