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Exercise training prevents age-related decline in muscle function. Targeting epigenetic aging is a promising actionable mechanism and late- life exercise mitigates epi -genetic aging in rodent muscle. Whether exercise training can decelerate, or reverse epigenetic aging in humans is unknown. Here, we performed a powerful meta- analysis of the methylome and transcriptome of an unprecedented number of human skeletal muscle samples (n= 3176). We show that: (1) individuals with higher baseline aero -bic fitness have younger epigenetic and transcriptomic profiles, (2) exercise training leads to significant shifts of epigenetic and transcriptomic patterns toward a younger profile, and (3) muscle disuse “ages” the transcriptome. Higher fitness levels were associated with attenuated differential methylation and transcription during aging. Furthermore, both epigenetic and transcriptomic profiles shifted toward a younger state after exercise training interventions, while the transcriptome shifted toward an older state after forced muscle disuse. We demonstrate that exercise training targets many of the age- related transcripts and DNA methylation loci to maintain younger methylome and transcriptome profiles, specifically in genes related to muscle struc-ture, metabolism, and mitochondrial function. Our comprehensive analysis will inform future studies aiming to identify the best combination of therapeutics and exercise regimes to optimize longevity.

Background Anthropometric measures show high heritability, and genetic correlations have been found between obesity-related traits. However, we lack a comprehensive analysis of the genetic background of human body morphology using detailed anthropometric measures. Methods Height, weight, 7 skinfold thicknesses, 7 body circumferences and 4 body diameters (skeletal breaths) were measured in 214 pairs of twin children aged 3–18 years (87 monozygotic pairs) in the Autonomous Region of Madeira, Portugal. Factor analysis (Varimax rotation) was used to analyze the underlying structure of body physique. Genetic twin modeling was used to estimate genetic and environmental contributions to the variation and co-variation of the anthropometric traits. Results Together, two factors explained 80% of the variation of all 22 anthropometric traits in boys and 73% in girls. Obesity measures (body mass index, skinfold thickness measures, as well as waist and hip circumferences) and limb circumferences loaded most strongly on the first factor, whereas height and body diameters loaded especially on the second factor. These factors as well as all anthropometric measures showed high heritability (80% or more for most of the traits), whereas the rest of the variation was explained by environmental factors not shared by co-twins. Obesity measures showed high genetic correlations (0.75–0.98). Height showed the highest genetic correlations with body diameter measures (0.58–0.76). Correlations between environmental factors not shared by co-twins were weaker than the genetic correlations but still substantial. The correlation patterns were roughly similar in boys and girls. Conclusions Our results show high genetic correlations underlying the human body physique, suggesting that there are sets of genes widely affecting anthropometric traits. Better knowledge of these genetic variants can help to understand the development of obesity and other features of the human physique.

Background: Heritability explains 45-82% of muscle mass and strength variation, yet polygenic models for muscle phenotypes in older women are scarce. Therefore, the objective of the present study was to (1) assess if total genotype predisposition score (GPSTOTAL) for a set of polymorphisms differed between older women with low and high muscle mass, and (2) utilise a data-driven GPS (GPSDD) to predict the variance in muscle size and strength-related phenotypes. Methods: In three-hundred 60- to 91-year-old Caucasian women (70.7 ± 5.7 years), skeletal muscle mass, biceps brachii thickness, vastus lateralis anatomical cross-sectional area (VLACSA), hand grip strength (HGS), and elbow flexion (MVCEF) and knee extension (MVCKE) maximum voluntary contraction were measured. Participants were classified as having low muscle mass if the skeletal muscle index (SMI) < 6.76 kg/m2 or relative skeletal muscle mass (%SMMr) < 22.1%. Genotyping was completed for 24 single-nucleotide polymorphisms (SNPs). GPSTOTAL was calculated from 23 SNPs and compared between the low and high muscle mass groups. A GPSDD was performed to identify the association of SNPs with other skeletal muscle phenotypes. Results: There was no significant difference in GPSTOTAL between low and high muscle mass groups, irrespective of classification based on SMI or %SMMr. The GPSDD model, using 23 selected SNPs, revealed that 13 SNPs were associated with at least one skeletal muscle phenotype: HIF1A rs11549465 was associated with four phenotypes and, in descending number of phenotype associations, ACE rs4341 with three; PTK2 rs7460 and CNTFR rs2070802 with two; and MTHFR rs17421511, ACVR1B rs10783485, CNTF rs1800169, MTHFR rs1801131, MTHFR rs1537516, TRHR rs7832552, MSTN rs1805086, COL1A1 rs1800012, and FTO rs9939609 with one phenotype. The GPSDD with age included as a predictor variable explained 1.7% variance of biceps brachii thickness, 12.5% of VLACSA, 19.0% of HGS, 8.2% of MVCEF, and 9.6% of MVCKE. Conc

Objectives To analyze the influence of genetic and environmental factors on the variation in somatotype, physical fitness, and their mutual associations. Methods Twins from 214 pairs (87 monozygotic) of the Autonomous Region of Madeira, Portugal, from 3 to 18 years of age (51% girls) were assessed in anthropometry and physical fitness tests. We estimated endomorphy, mesomorphy, and ectomorphy based on anthropometric measures and physical fitness using the Eurofit test battery. Two age categories were analyzed: children (3-11 years) and adolescents (12-18 years). Genetic and environmental variations were estimated using quantitative genetic twin modeling. Results No genetic sex differences were found, thus boys and girls were pooled in all genetic analyses. Heritability estimates were high for somatotype (a(2)= 0.80-0.93), physical fitness traits (a(2)= 0.67-0.83), and largely similar in children and adolescents. Positive correlations were found for ectomorphy with motor ability and cardiorespiratory endurance as well as for endomorphy and mesomorphy with muscular strength (r= 0.25-0.37). In contrast, negative associations were found for ectomorphy with muscular strength, as well as for endomorphy and mesomorphy with motor ability and cardiorespiratory endurance (-0.46 to -0.26). Twin modeling indicated that these associations were explained mostly by genetic factors in common to the two associated traits (84% or more). Conclusions Associations between somatotype and physical fitness tests are mainly explained by common genetic background in children and adolescents. Therefore, interventions in youth should consider that a child's performance in physical fitness tests partly reflects their inherited physique.

Background: Knowledge of age-related DNA methylation changes in skeletal muscle is limited, yet this tissue is severely affected by ageing in humans. Methods: We conducted a large-scale epigenome-wide association study meta-analysis of age in human skeletal muscle from 10 studies (total n = 908 muscle methylomes from men and women aged 18–89 years old). We explored the genomic context of age-related DNA methylation changes in chromatin states, CpG islands, and transcription factor binding sites and performed gene set enrichment analysis. We then integrated the DNA methylation data with known transcriptomic and proteomic age-related changes in skeletal muscle. Finally, we updated our recently developed muscle epigenetic clock (https://bioconductor.org/packages/release/bioc/html/MEAT.html). Results: We identified 6710 differentially methylated regions at a stringent false discovery rate <0.005, spanning 6367 unique genes, many of which related to skeletal muscle structure and development. We found a strong increase in DNA methylation at Polycomb target genes and bivalent chromatin domains and a concomitant decrease in DNA methylation at enhancers. Most differentially methylated genes were not altered at the mRNA or protein level, but they were nonetheless strongly enriched for genes showing age-related differential mRNA and protein expression. After adding a substantial number of samples from five datasets (+371), the updated version of the muscle clock (MEAT 2.0, total n = 1053 samples) performed similarly to the original version of the muscle clock (median of 4.4 vs. 4.6 years in age prediction error), suggesting that the original version of the muscle clock was very accurate. Conclusions: We provide here the most comprehensive picture of DNA methylation ageing in human skeletal muscle and reveal widespread alterations of genes involved in skeletal muscle structure, development, and differentiation. We have made our results available as an open-access, user-frien

There is a scarcity of studies that have investigated the role of multiple single nucleotide polymorphisms (SNPs) on a range of muscle phenotypes in an elderly population. The present study investigated the possible association of 24 SNPs with skeletal muscle phenotypes in 307 elderly Caucasian women (aged 60–91 years, 66.3 ± 11.3 kg). Skeletal muscle phenotypes included biceps brachii thickness, vastus lateralis cross-sectional areas, maximal hand grip strength, isometric knee extension and elbow flexion torque. Genotyping for 24 SNPs, chosen on their skeletal muscle structural or functional links, was conducted on DNA extracted from blood or saliva. Of the 24 SNPs, 10 were associated with at least one skeletal muscle phenotype. HIF1A rs11549465 was associated with three skeletal muscle phenotypes and PTK2 rs7460 and ACVR1B rs10783485 were each associated with two phenotypes. PTK2 rs7843014, COL1A1 rs1800012, CNTF rs1800169, NOS3 rs1799983, MSTN rs1805086, TRHR rs7832552 and FTO rs9939609 were each associated with one. Elderly women possessing favourable genotypes were 3.6–13.2% stronger and had 4.6–14.7% larger muscle than those with less favourable genotypes. These associations, together with future work involving a broader range of SNPs, may help identify individuals at particular risk of an age-associated loss of independence.

Background: Inter-individual variance in skeletal muscle is closely related to genetic architecture and epigenetic regulation. Studies have examined genetic and epigenetic relationships with characteristics of ageing muscle separately, while no study has combined both genetic and epigenetic profiles in ageing muscle research. The aim of this study was to evaluate the association between combined genetic and methylation scores and skeletal muscle in older women. Methods: 48 older Caucasian women (aged 65–79 yr) were included in this study. Biceps brachii thickness and vastus lateralis anatomical cross-sectional area (ACSAVL) were measured by ultrasonography. Maximum isometric elbow flexion (MVCEF) and knee extension (MVCKE) torques were measured by a customized dynamometer. The muscle-driven genetic predisposition score (GPSSNP) was calculated based on seven muscle-related single nucleotide polymorphisms (SNPs). DNA methylation levels of whole blood samples were analysed using Infinium MethylationEPIC BeadChip arrays. The DNA methylation score was calculated as a weighted sum of methylation levels of sarcopenia-driven CpG sites (MSSAR) or an overall gene-wise methylation score (MSSNP, the mean methylation level of CpG sites located in muscle-related genes). Linear regression models were built to study genetic and epigenetic associations with muscle size and strength. Three models were built with both genetic and methylation scores: (1) MSSAR + GPSSNP, (2) MSSNP + GPSSNP, (3) gene-wise combined scores which were calculated as the ratio of the SNP score to the mean methylation level of promoters in the corresponding gene. Additional models with only a genetic or methylation score were also built. All models were adjusted for age and BMI. Results: MSSAR was negatively associated with ACSAVL, MVCEF and MVCKE, and explained 10.1%, 35.5% and 40.1% of the variance, respectively. MSSAR explained more variance in these muscular phenotypes than GPSSNP, MSSNP and models includi

The authors regret to have indicated an incorrect reference to the study of Psilander et al. (2019). The statement in our introduction (and discussion) about the loss of myonuclei during inactivity/detraining periods was not observed in the study by Psilander et al. (2019), however it was reported in a secondary analysis in a selected subset of the individuals with a hypertrophic response to the training intervention, published by Murach et al. (2019). The statements referring to this interpretation should therefore only refer to the subanalysis paper by Murach et al. (2019) and not to the original work of Psilander et al. (2019). [...]

INTRODUCTION: Ageing is associated with an attenuated hypertrophic response to resistance training and periods of training interruptions. Hence, elderly would benefit from the 'muscle memory' effects of resistance training on muscle strength and mass during detraining and retraining. As the underlying mechanisms are not yet clear, this study investigated the role of myonuclei during training, detraining and retraining by using PCM1 labelling in muscle cross-sections of six older men. METHODS: Knee extension strength and power were measured in 30 older men and 10 controls before and after 12 weeks resistance training and after detraining and retraining of similar length. In a subset, muscle biopsies from the vastus lateralis were taken for analysis of fibre size, fibre type distribution, Pax7+ satellite cell number and myonuclear domain size. RESULTS: Resistance training increased knee extension strength and power parameters (+10 to +36%, p < .001) and decreased the frequency of type IIax fibres by half (from 20 to 10%, p = .034). Detraining resulted in a modest loss of strength and power (-5 to -15%, p ≤ .004) and a trend towards a fibre-type specific decrease in type II fibre cross-sectional area (-17%, p = .087), type II satellite cell number (-30%, p = .054) and type II myonuclear number (-12%, p = .084). Less than eight weeks of retraining were needed to reach the post-training level of one-repetition maximum strength. Twelve weeks of retraining were associated with type II fibre hypertrophy (+29%, p = .050), which also promoted an increase in the number of satellite cells (+72%, p = .036) and myonuclei (+13%, p = .048) in type II fibres. Changes in the type II fibre cross-sectional area were positively correlated with changes in the myonuclear number (Pearson's r between 0.40 and 0.73), resulting in a stable myonuclear domain. CONCLUSION: Gained strength and power and fibre type changes were partially preserved following 12 weeks of detraining, allowing for a f