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DNA methylation age of blood predicts all-cause mortality in later life - PubMed

  • ️Thu Jan 01 2015

doi: 10.1186/s13059-015-0584-6.

Riccardo E Marioni  1   2   3 Allan F McRae  6   7 Brian H Chen  8   9 Elena Colicino  10 Sarah E Harris  11   12 Jude Gibson  13 Anjali K Henders  14 Paul Redmond  15 Simon R Cox  16   17 Alison Pattie  18 Janie Corley  19 Lee Murphy  20 Nicholas G Martin  21 Grant W Montgomery  22 Andrew P Feinberg  23   24 M Daniele Fallin  25   26 Michael L Multhaup  27 Andrew E Jaffe  28   29 Roby Joehanes  30   31   32 Joel Schwartz  33   34 Allan C Just  35 Kathryn L Lunetta  36   37 Joanne M Murabito  38   39 John M Starr  40   41 Steve Horvath  42   43 Andrea A Baccarelli  44   45 Daniel Levy  46   47 Peter M Visscher  48   49   50 Naomi R Wray  51 Ian J Deary  52   53

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DNA methylation age of blood predicts all-cause mortality in later life

Riccardo E Marioni et al. Genome Biol. 2015.

Abstract

Background: DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age.

Results: Here we test whether differences between people's chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43.

Conclusions: DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors.

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Figures

Figure 1
Figure 1

Plot of predicted methylation age against chronological age and plot of Hannum versus Horvath predicted methylation age. *To prevent the potential identification of individual participants, only FHS data points with chronological ages between 45 and 85, and NAS data points between ages 56 and 100 are displayed. r = Pearson correlation coefficient. FHS: Framingham Heart Study, LBC: Lothian Birth Cohort, NAS: Normative Aging Study.

Figure 2
Figure 2

Meta-analysis results of Δ age versus mortality. The basic adjusted models controlled for chronological age, sex (NAS had only male participants), and laboratory batch (FHS only). The fully adjusted models controlled for chronological age, sex, smoking, education, childhood IQ (LBC1921 and LBC1936 only), social class (LBC1921 and LBC1936 only), APOE (LBC1921, LBC1936, and NAS only), cardiovascular disease, high blood pressure, and diabetes. CI: confidence interval, FHS: Framingham Heart Study, HR: hazard ratio, LBC: Lothian Birth Cohort, NAS: Normative Aging Study, W: fixed effect weight.

Figure 3
Figure 3

Survival probability by quartiles of Δ age in LBC1921 adjusted for sex, and chronological age. LBC: Lothian Birth Cohort.

Figure 4
Figure 4

Heritability of methylation Δ age . (A) Intra-class correlation of Hannum and Horvath Δage across relationship class. (B) Heritability of Hannum and Horvath Δage in BSGS data. Both plots show estimates with standard errors. *Pseudo-independent pairs. r represents the degree of relatedness.

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