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Frailty Is Associated with the Epigenetic Clock but Not With Breitling et al. Clinical Epigenetics (2016) 8:21 DOI 10.1186/s13148-016-0186-5 RESEARCH Open Access Frailty is associated with the epigenetic clock but not with telomere length in a German cohort Lutz Philipp Breitling1*, Kai-Uwe Saum1, Laura Perna1, Ben Schöttker1,3, Bernd Holleczek2 and Hermann Brenner1,3 Abstract Background: The epigenetic clock, in particular epigenetic pre-aging quantified by the so-called DNA methylation age acceleration, has recently been suggested to closely correlate with a variety of disease phenotypes. There remains a dearth of data, however, on its association with telomere length and frailty, which can be considered major correlates of age on the genomic and clinical level, respectively. Results: In this cross-sectional observational study on altogether 1820 subjects from two subsets (n = 969 and n = 851; mean ± standard deviation age 62.1 ± 6.5 and 63.0 ± 6.7 years, respectively) of the ESTHER cohort study of the elderly general population in Germany, DNA methylation age was calculated based on a 353 loci predictor previously developed in a large meta-study, and the difference-based epigenetic age acceleration was calculated as predicted methylation age minus chronological age. No correlation of epigenetic age acceleration with telomere length was found in our study (p = 0.63). However, there was an association of DNA methylation age acceleration with a comprehensive frailty measure, such that the accumulated deficits significantly increased with increasing age acceleration. Quantitatively, about half an additional deficit was added per 6 years of methylation age acceleration (p = 0.0004). This association was independent from age, sex, and estimated leukocyte distribution, as well as from a variety of other confounding variables considered. Conclusions: The results of the present study suggest that epigenetic age acceleration is correlated with clinically relevant aging-related phenotypes through pathways unrelated to cellular senescence as assessed by telomere length. Innovative approaches like Mendelian randomization will be needed to elucidate whether epigenetic age acceleration indeed plays a causal role for the development of clinical phenotypes. Keywords: Telomere length, CpG methylation, Epigenetic age acceleration, Frailty index, Cross-sectional study, General population Background been found to be a substantially heritable trait in twin DNA methylation patterns are known to change with study datasets that furthermore shows plausible associ- chronological age, and multiple CpG sites with replicable ations with several phenotypes across studies and associations with age have been identified [1]. Based on tissues [2]. regression coefficients estimated from a large number of Frailty describes a clinical syndrome characterized by a datasets, an individual’s chronological age can be pre- depletion of physical and cognitive resilience and re- dicted from DNA methylation data with high accuracy serves, commonly associated with an accumulation of [2]. The difference between the thus predicted methyla- functional deficits [3, 4]. Frailty has received growing at- tion age (DNAm age) and the chronological age has tention in recent years, due to pronounced associations been termed “age acceleration” and, intriguingly, has with longevity and other aging-related phenotypes and the corresponding perception that frailty measures * Correspondence: [email protected] reflect an individual’s clinically relevant biological age 1German Cancer Research Center (DKFZ), Division of Clinical Epidemiology and Aging Research, 69120 Heidelberg, Germany [4, 5]. Stable intra-individual differences in biological Full list of author information is available at the end of the article © 2016 Breitling et al. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Breitling et al. Clinical Epigenetics (2016) 8:21 Page 2 of 8 aging and accruing frailty exist [6], and DNA methyla- In light of inconclusive previous findings on associations tion patterns might play a role in this phenomenon [7]. of TL with frailty [12], interaction analyses were con- Telomere length (TL) has been suggested to reflect an ducted to evaluate whether DNAm age alters the associ- individual’s biological age at the genomic DNA level, ation of TL with frailty. and associations of measures of TL with various aging- and frailty-related phenotypes, such as sarcopenia [8] Results and bone loss [9], have been reported. Whereas epigen- Description of study population and main variables etic age acceleration has been shown to be associated Major characteristics of the study populations are shown with various cancer phenotypes [2], its correlation with in Table 1. The two ESTHER subsets analyzed in the TL apparently has not been investigated to date, and present work—dataset 1 consisting of 1000 consecutively seemingly only one study has addressed age acceleration recruited participants of the ESTHER cohort and dataset and frailty [10]. In a rare study analyzing both TL and 2 originating from a case-cohort design (see “Methods” DNAm age, the development of symptoms of post- section for details)—resembled one another closely, al- traumatic stress syndrome was associated with both var- though some of the slight differences between these two iables—in plausibly opposite, yet altogether unexpected very large subsets were statistically significant. The mean directions—but their mutual correlation apparently was age was 62.1 and 63.0 years, respectively. Methylation not investigated [11]. age and difference-based epigenetic age acceleration ap- A better understanding of the interplay of epigenetic peared somewhat higher in dataset 2, in which relative and genomic correlates of age as determinants of clinical telomere length also tended to be lower. There was no frailty could help to elucidate novel pathways to healthy difference with respect to the frailty index. Current aging and longevity. In the present study, the correlation smoking was prevalent in one fifth of participants in of epigenetic age acceleration with TL and frailty was in- both datasets, and harmful alcohol consumption was re- vestigated in two large subsets of a general population ported by less than 10 % of participants. Histograms of sample of community-dwelling older adults in Germany. the main analysis variables are shown in Additional file Table 1 Description of two subsets of the ESTHER study, an epidemiological study of the elderly general population in Germany Characteristic Dataset 1 Dataset 2 pa Total n 969 851 Age in years μ (SD) 62.1 (6.5) 63.0 (6.7) 0.0078 Methylation age in years μ (SD) 61.7 (7.1) 64.6 (7.7) <0.0001 Age acceleration in yearsb μ (SD) −0.5 (5.0) 1.6 (5.3) <0.0001 Relative telomere length μ (SD) 1.22 (0.31) 1.03 (0.27) <0.0001 Frailty index (in %) μ (SD) 25.0 (14.7) 25.5 (15.1) 0.41 Sex Females n (%) 484 (50.0) 464 (54.5) 0.051 Males n (%) 485 (50.1) 387 (45.5) Smoking behaviorc Never n (%) 455 (48.0) 371 (45.0) 0.38 Former n (%) 320 (33.7) 284 (34.5) Current n (%) 174 (18.3) 169 (20.5) Alcohol consumptionc None n (%) 300 (33.6) 260 (33.7) 0.76 <20 g/d (women), <40 g/d (men) n (%) 524 (58.6) 458 (59.4) 20+ g/d (women), 40+ g/d (men) n (%) 70 (7.8) 53 (6.9) History of cancerc Self-report negative n (%) 882 (93.2) 742 (90.5) 0.034 Self-report positive n (%) 64 (6.8) 78 (9.5) Dataset 1, consecutively recruited subsample of the source study. Dataset 2, sampled in the context of a case-cohort study. For details, see text a Chi-square test for categorical variables, t test for continuous variables b Difference-based age acceleration, i.e., methylation age—chronological age c Missing values (dataset 1, dataset 2) in smoking (20, 27), alcohol consumption (75, 80), and history of cancer (23, 31) Breitling et al. Clinical Epigenetics (2016) 8:21 Page 3 of 8 1: Figure S1 and suggested some skewness of frailty only, acceleration and frailty index (FI) in both datasets, with whereas DNAm age acceleration and relative telomere statistically significant results in the fully adjusted length closely followed a normal distribution. models in both individual datasets and the combined analysis. After adjustment for age, sex, and leukocyte Age acceleration and telomere length distribution, FI increased by about 0.25 % points per When exploring the sex-adjusted associations of chrono- year of epigenetic age acceleration. logical age and methylation age with relative telomere To improve the interpretability of this result, we aimed length in regression models of our combined dataset, to derive a more tangible presentation of the estimated the associations of both variables with relative telomere association. Since the FI used increases by about 2.9 % length were clearly significant (p < 0.0001; details not points per deficit, a 0.25 % points increase per year of shown). The corresponding F values were 46.8 for epigenetic age acceleration translates into one additional chronological age and 32.9 for DNA methylation age, deficit per 2.9/0.25 = 11.6 years of acceleration. Rounding suggesting a possibly closer correlation with cellular sen- conservatively, we thus may state that our results sug- escence for the former variable. The results of regression gest one added deficit per 12 years of methylation age analyses of relative telomere length on difference-based acceleration, or half an added deficit per 6 years of methylation age acceleration are shown in Table 2.
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