Modified aging of elite athletes revealed by analysis of epigenetic age markers

Spólnicka, Magdalena; Pośpiech, Ewelina; Adamczyk, Jakub Grzegorz; Freire-Aradas, Ana; Pepłońska, Beata; Zbieć-Piekarska, Renata; Makowska, Żanetta; Pięta, Anna; Lareu, Maria Victoria; Phillips, Christopher; Płoski, Rafał; Zekanowski, Cezary; Branicki, Wojciech

doi:10.18632/aging.101385

Cited by 21 publications

(29 citation statements)

References 40 publications

(53 reference statements)

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“…The development of single-locus age prediction models based on ELOVL2 promoter methylation was also particularly interesting as DNA methylation of this age-prediction biomarker, contrary to other DNA methylation-based age-prediction biomarkers, has proven to be correlated with age in most types of tissues 45 and could thereby potentially be used on different types of samples without requiring many changes. Our model could also potentially be used to study the modification of the epigenetic clock in individuals with different health conditions, as shown in numerous studies using high-throughput multi-locus age prediction models relying on epigenotyping microarray data 12 and low-throughput multi-locus age prediction models based on pyrosequencing 17,46 . Further evaluations of our single-locus age prediction models based on ELOVL2 promoter methylation should be performed on samples from different types of tissues as well as from individuals with different health conditions and/or diseases to define the applicability of these models to such samples.…”

Section: Discussionmentioning

confidence: 99%

“…In forensics, the ability to precisely determine the chronological age of samples from DNA methylation-based age prediction models could greatly help investigators to identify and find unknown individuals 13 . In other bio-medical applications, the estimated age from DNA methylation could give an estimation of the biological age 4 and could also be an indicator of different diseases, risks and health conditions when compared to the chronological age of individuals 14 – 17 .…”

Section: Introductionmentioning

confidence: 99%

“…6 These authors contributed equally: Imene Garali and Mourad Sahbatou. * email: alexandre.how-kit@fjd-ceph.org age from DNA methylation could give an estimation of the biological age 4 and could also be an indicator of different diseases, risks and health conditions when compared to the chronological age of individuals [14][15][16][17] .…”

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confidence: 99%

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Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter

Garali

Sahbatou

Daunay

et al. 2020

Sci Rep

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Several blood-based age prediction models have been developed using less than a dozen to more than a hundred DNA methylation biomarkers. Only one model (Z-P1) based on pyrosequencing has been developed using DNA methylation of a single locus located in the ELOVL2 promoter, which is considered as one of the best age-prediction biomarker. Although multi-locus models generally present better performances compared to the single-locus model, they require more DNA and present more inter-laboratory variations impacting the predictions. Here we developed 17,018 single-locus age prediction models based on DNA methylation of the ELOVL2 promoter from pooled data of four different studies (training set of 1,028 individuals aged from 0 and 91 years) using six different statistical approaches and testing every combination of the 7 CpGs, aiming to improve the prediction performances and reduce the effects of inter-laboratory variations. Compared to Z-P1 model, three statistical models with the optimal combinations of CpGs presented improved performances (MAD of 4.41–4.77 in the testing set of 385 individuals) and no age-dependent bias. In an independent testing set of 100 individuals (19–65 years), we showed that the prediction accuracy could be further improved by using different CpG combinations and increasing the number of technical replicates (MAD of 4.17).

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter

Garali

Sahbatou

Daunay

et al. 2020

Sci Rep

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“…CALB1 demonstrated robustly down-regulated expression across rhesus monkeys and humans (Loerch et al, 2008;Pabba et al, 2017). While KLF14 served as a master regulator of many genes and its altered methylation patterns were associated with the aging process (Spolnicka et al, 2018). But both of these two genes didn't demonstrate gender-specific patterns.…”

Section: Discussionmentioning

confidence: 97%

AgeGuess, a Methylomic Prediction Model for Human Ages

Gao

Liu

Song

et al. 2020

Front. Bioeng. Biotechnol.

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Aging was a biological process under regulations from both inherited genetic factors and various molecular modifications within cells during the lifespan. Multiple studies demonstrated that the chronological age may be accurately predicted using the methylomic data. This study proposed a three-step feature selection algorithm AgeGuess for the age regression problem. AgeGuess selected 107 methylomic features as the gender-independent age biomarkers and the Support Vector Regressor (SVR) model using these biomarkers achieved 2.0267 in the mean absolute deviation (MAD) compared with the real chronological ages. Another regression algorithm Ridge achieved a slightly better MAD 1.9859 using the same biomarkers. The gender-independent age prediction models may be further improved by establishing two gender-specific models. And it's interesting to observe that there were only two methylation biomarkers shared by the two gender-specific biomarker sets and these two biomarkers were within the two known age-associated biomarker genes CALB1 and KLF14.

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“…population-specific susceptibility to diseases, pharmacogenomics), but also in evolutionary studies and forensics (e.g. populations origin, relationships, identification) (1)(2)(3)(4)(5). The relation between the genome variation and population ancestry has been admittedly proven (6)(7)(8)(9).…”

Section: Introductionmentioning

confidence: 99%

Discrimination between human populations using a small number of differentially methylated CpG sites: A preliminary study using lymphoblastoid cell lines and peripheral blood samples of Caucasian and Chinese origin.

Daca-Roszak

Jaksik

Paczkowska

et al. 2020

Preprint

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Background Epigenetics is one of the factors shaping natural variability observed among human populations. A small proportion of heritable inter-population differences are observed in the context of both the genome-wide methylation level and the methylation status of individual CpG sites. It has been demonstrated that a limited number of carefully selected differentially methylated sites may allow discrimination between main human populations. However, most of the few published results have been performed exclusively on B-lymphocyte cell lines. Results The goal of our study was to identify a set of CpG sites sufficient to discriminate between Caucasian and Chinese populations based on the difference in the DNA methylation profile not only in cell lines but also in primary cell samples. The preliminary selection of CpG sites differentially methylated in these two populations (pop-diff-met CpGs) was based on the analysis of two groups of commercially available ethnically-specific B-lymphocyte cell lines, performed using Illumina Infinium Human Methylation 450 BeadChip Array. A subset of ten pop-diff-met CpGs characterized by the best differentiating criteria (|Mdiff|>1, q<0.05; lack of the confounding genomic features), and ten additional CpGs in their immediate vicinity, were further tested using pyrosequencing technology in both B-lymphocyte cell lines and in the primary samples of the peripheral blood representing two analyzed populations. To assess the population-discriminating potential of the selected set of CpGs (further referred to as “composite pop(CEU-CHB)-diff-met CpG marker”), three classification methods were applied. The predictive ability of the composite 8-site pop(CEU-CHB)-diff-met CpG marker was assessed using 10-fold cross-validation method on two independent sets of samples. Concussions Our results showed that less than 10 pop-diff-met CpG sites may distinguish Caucasian and Chinese populations; importantly, this small composite pop-diff-met CpG marker performs well in both lymphoblastoid cell lines and in non-homogenous blood samples.

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Modified aging of elite athletes revealed by analysis of epigenetic age markers

Cited by 21 publications

References 40 publications

Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter

Improvements and inter-laboratory implementation and optimization of blood-based single-locus age prediction models using DNA methylation of the ELOVL2 promoter

AgeGuess, a Methylomic Prediction Model for Human Ages

Discrimination between human populations using a small number of differentially methylated CpG sites: A preliminary study using lymphoblastoid cell lines and peripheral blood samples of Caucasian and Chinese origin.

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