Evidence map›Paper›PMID 34001218›Full record

ArticleClinical epigenetics2021

Blood and skeletal muscle ageing determined by epigenetic clocks and their associations with physical activity and functioning.

Elina Sillanpää, Aino Heikkinen, Anna Kankaanpää, Aini Paavilainen, Urho M Kujala, Tuija H Tammelin, Vuokko Kovanen, Sarianna Sipilä, Kirsi H Pietiläinen, Jaakko Kaprio and 2 more

Open access · goldAbstract read
In one paragraph

Article in Clinical epigenetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
25citing papers in PubMed, 1 pooled it
2.5field-weighted citation impact, top 10% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

25 citing papers in PubMed, 1 synthesis or guideline pooled it, 41 citations in OpenAlex.

  1. Pooled it
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  15. Quantification of Epigenetic Aging in Public Health.Annual review of public health · 2025
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 1 country.

Elina SillanpääGerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland. elina.sillanpaa@jyu.fi.ORCID 0000-0001-6375-959X
Aino HeikkinenInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Anna KankaanpääGerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland.
Aini PaavilainenGerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland.
Urho M KujalaFaculty of Sport and Health Sciences, University of Jyväskylä, Jyväskylä, Finland.
Tuija H TammelinLIKES Research Centre for Physical Activity and Health, Jyväskylä, Finland.
Vuokko KovanenGerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland.
Sarianna SipiläGerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland.
Kirsi H PietiläinenObesity Research Unit, Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
Jaakko KaprioInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Miina OllikainenInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
Eija K LaakkonenGerontology Research Center, Faculty of Sport and Health Sciences, University of Jyväskylä, P.O. Box 35 (VIV), 40014, Jyväskylä, Finland.
University of Jyväskylä · FIUniversity of Helsinki · FILIKES – Foundation for Sport and Health Sciences · FI

Funding

A GENOME-WIDE METHYLATION STUDY ON ESSENTIAL HYPERTENSIONR01HL104125 · NHLBI · AUGUSTA UNIVERSITY · PI WANG, XIAOLING · 2011 to 2015
$2.9M
Academy of Finland 213506Academy of Finland 251316Academy of Finland 260001Academy of Finland 266286Academy of Finland 275323Academy of Finland 297908Academy of Finland 308248Academy of Finland 309504Academy of Finland 312073Academy of Finland 314181Academy of Finland 314383Academy of Finland 336823Acedemy of Finland Center of Excellence in Research on Mitochondria, Metabolism and Disease 272376EC MC ITN EPITRAINNHLBI NIH HHS R01 HL104125NIH HHS HL104125Novo Nordisk Fonden NNF10OC1013354Novo Nordisk Fonden NNF17OC0027232
6 · The paper itself

Abstract

The aim of this study was to investigate the correspondence of different biological ageing estimates (i.e. epigenetic age) in blood and muscle tissue and their associations with physical activity (PA), physical function and body composition. Two independent cohorts (N = 139 and N = 47) were included, whose age span covered adulthood (23-69 years). Whole blood and m. vastus lateralis samples were collected, and DNA methylation was analysed. Four different DNA methylation age (DNAmAge) estimates were calculated using genome-wide methylation data and publicly available online tools. A novel muscle-specific methylation age was estimated using the R-package 'MEAT'. PA was measured with questionnaires and accelerometers. Several tests were conducted to estimate cardiorespiratory fitness and muscle strength. Body composition was estimated by dual-energy X-ray absorptiometry. DNAmAge estimates from blood and muscle were highly correlated with chronological age, but different age acceleration estimates were weakly associated with each other. The monozygotic twin within-pair similarity of ageing pace was higher in blood (r = 0.617-0.824) than in muscle (r = 0.523-0.585). Associations of age acceleration estimates with PA, physical function and body composition were weak in both tissues and mostly explained by smoking and sex. The muscle-specific epigenetic clock MEAT was developed to predict chronological age, which may explain why it did not associate with functional phenotypes. The Horvath's clock and GrimAge were weakly associated with PA and related phenotypes, suggesting that higher PA would be linked to accelerated biological ageing in muscle. This may, however, be more reflective of the low capacity of epigenetic clock algorithms to measure functional muscle ageing than of actual age acceleration. Based on our results, the investigated epigenetic clocks have rather low value in estimating muscle ageing with respect to the physiological adaptations that typically occur due to ageing or PA. Thus, further development of methods is needed to gain insight into muscle tissue-specific ageing and the underlying biological pathways.

Indexed as

AdultAgedAgingCohort StudiesDNA MethylationEpigenesis, GeneticEpigenomicsExerciseFemaleHumansMaleMiddle AgedMuscle, SkeletalYoung AdultBiological ageingDNA methylationDual-energy X-ray absorptiometryMaximal oxygen consumptionMuscle massMuscle strengthTwin study

Identifiers

PMID34001218
PMCPMC8127311
OpenAlexW3163231593

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.