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

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 were included, whose age span covered adulthood (23-69 years). Whole blood and m. vastus lateralis samples were collected, and DNA methylation 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 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 further insight into muscle tissue-specific ageing and the underlying biological pathways.

Methylation status of VTRNA2-1/nc886 is stable across human populations, monozygotic twin pairs and in majority of somatic tissues

“…FTC (the Finnish Twin Cohort) study includes three longitudinal cohorts (70,71) - the Older Twin cohort (71), FinnTwin16 (FT16) (72), and FinnTwin12 (FT12) (73). In this study, we included two subsets of FT16 and FT12 cohorts - a smaller subset of individuals for whom DNA methylation data was available from muscle, adipose tissue and blood (60) and a larger subset with methylation data only available from blood (54). For 49 MZ twin pairs, the information on whether they were dichorionic and diamniotic (DCDA, 22 pairs), monochorionic and diamniotic (MCDA, 9 pairs), or monochorionic and monoamniotic (MCMD, 18 pairs) was available.…”

“…The original ERMA cohort includes 47- to 55-year-old women living in the city of Jyväskylä or neighbouring municipalities in Finland. For this study, a subset of 47 individuals with both whole blood and muscle tissue samples available were included (60).…”

“…Datasets GSE61454, GSE71678, GSE134379, and GSE157896 were downloaded as raw idat-files, extracted with minfi package function read.metharray.exp and quantile normalized with default settings (80). For DILGOM (44), FTC (54,60), ERMA (60), KORA (11,45), LURIC (46), SATSA (47) and YFS (11), the processing of DNA methylation data has been described in detail in previous publications referenced here. For all datasets, information on sample material, Illumina array type (Illumina Infinium MethylationEPIC or Methylation450K BeadChip), and the used processing methods are provided in Supplementary Table 1.…”

Methylation status of VTRNA2-1 / nc886 is stable across populations, monozygotic twin pairs and in majority of tissues

“…The FTC study includes three longitudinal cohorts [71,72]: the Older Twin cohort [72], FinnTwin16 (FT16) [73] and FinnTwin12 (FT12) [74]. In this study, two subsets of FTC samples were included: a smaller subset of individuals from FT12 and FT16 for whom DNA methylation data was available from muscle, adipose tissue and blood [61] and a larger subset including individuals from the Older, FT16 and FT12 cohorts with methylation data only available from blood [54]. For 49 MZ twin pairs, the information on whether they were dichorionic and diamniotic (DCDA, 22 pairs), monochorionic and diamniotic (MCDA, 9 pairs) or monochorionic and monoamniotic (MCMA, 18 pairs) was available.…”

“…The cohort includes 47-to 55-year-old females from city of Jyväskylä or neighboring municipalities in Finland. For this study, a subset of 47 individuals were included from whom whole blood and muscle tissue samples were available [61].…”