Exercise is associated with younger methylome and transcriptome profiles in human skeletal muscle.

Exercise training prevents age-related decline in muscle function. Targeting epigenetic aging is a promising actionable mechanism and late-life exercise mitigates epigenetic 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 aerobic 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 structure, 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.

Muscle miRNAs are influenced by sex at baseline and in response to exercise.

BACKGROUND: Sex differences in microRNA (miRNA) expression profiles have been found across multiple tissues. Skeletal muscle is one of the most sex-biased tissues of the body. MiRNAs are necessary for development and have regulatory roles in determining skeletal muscle phenotype and have important roles in the response to exercise in muscle. Yet there is limited research into the role and regulation of miRNAs in the skeletal muscle at baseline and in response to exercise, a well-known modulator of miRNA expression. The aim of this study was to investigate the effect of sex on miRNA expression in the skeletal muscle at baseline and after an acute bout of high-intensity interval exercise. A total of 758 miRNAs were measured using Taqman®miRNA arrays in the skeletal muscle of 42 healthy participants from the Gene SMART study (23 males and 19 females of comparable fitness levels and aged 18-45 years), of which 308 were detected. MiRNAs that differed by sex at baseline and whose change in expression following high-intensity interval exercise differed between the sexes were identified using mixed linear models adjusted for BMI and Wpeak. We performed in silico analyses to identify the putative gene targets of the exercise-induced, sex-specific miRNAs and overrepresentation analyses to identify enriched biological pathways. We performed functional assays by overexpressing two sex-biased miRNAs in human primary muscle cells derived from male and female donors to understand their downstream effects on the transcriptome. RESULTS: At baseline, 148 miRNAs were differentially expressed in the skeletal muscle between the sexes. Interaction analysis identified 111 miRNAs whose response to an acute bout of high-intensity interval exercise differed between the sexes. Sex-biased miRNA gene targets were enriched for muscle-related processes including proliferation and differentiation of muscle cells and numerous metabolic pathways, suggesting that miRNAs participate in programming sex differences in skeletal muscle function. Overexpression of sex-biased miRNA-30a and miRNA-30c resulted in profound changes in gene expression profiles that were specific to the sex of the cell donor in human primary skeletal muscle cells. CONCLUSIONS: We uncovered sex differences in the expression levels of muscle miRNAs at baseline and in response to acute high-intensity interval exercise. These miRNAs target regulatory pathways essential to skeletal muscle development and metabolism. Our findings highlight that miRNAs play an important role in programming sex differences in the skeletal muscle phenotype.

Sex differences in muscle protein expression and DNA methylation in response to exercise training.

BACKGROUND: Exercise training elicits changes in muscle physiology, epigenomics, transcriptomics, and proteomics, with males and females exhibiting differing physiological responses to exercise training. However, the molecular mechanisms contributing to the differing adaptations between the sexes are poorly understood. METHODS: We performed a meta-analysis for sex differences in skeletal muscle DNA methylation following an endurance training intervention (Gene SMART cohort and E-MTAB-11282 cohort). We investigated for sex differences in the skeletal muscle proteome following an endurance training intervention (Gene SMART cohort). Lastly, we investigated whether the methylome and proteome are associated with baseline cardiorespiratory fitness (maximal oxygen consumption; VO2max) in a sex-specific manner. RESULTS: Here, we investigated for the first time, DNA methylome and proteome sex differences in response to exercise training in human skeletal muscle (n = 78; 50 males, 28 females). We identified 92 DNA methylation sites (CpGs) associated with exercise training; however, no CpGs changed in a sex-dependent manner. In contrast, we identified 189 proteins that are differentially expressed between the sexes following training, with 82 proteins differentially expressed between the sexes at baseline. Proteins showing the most robust sex-specific response to exercise include SIRT3, MRPL41, and MBP. Irrespective of sex, cardiorespiratory fitness was associated with robust methylome changes (19,257 CpGs) and no proteomic changes. We did not observe sex differences in the association between cardiorespiratory fitness and the DNA methylome. Integrative multi-omic analysis identified sex-specific mitochondrial metabolism pathways associated with exercise responses. Lastly, exercise training and cardiorespiratory fitness shifted the DNA methylomes to be more similar between the sexes. CONCLUSIONS: We identified sex differences in protein expression changes, but not DNA methylation changes, following an endurance exercise training intervention; whereas we identified no sex differences in the DNA methylome or proteome response to lifelong training. Given the delicate interaction between sex and training as well as the limitations of the current study, more studies are required to elucidate whether there is a sex-specific training effect on the DNA methylome. We found that genes involved in mitochondrial metabolism pathways are differentially modulated between the sexes following endurance exercise training. These results shed light on sex differences in molecular adaptations to exercise training in skeletal muscle.

Methylome and proteome integration in human skeletal muscle uncover group and individual responses to high-intensity interval training.

Exercise is a major beneficial contributor to muscle metabolism, and health benefits acquired by exercise are a result of molecular shifts occurring across multiple molecular layers (i.e., epigenome, transcriptome, and proteome). Identifying robust, across-molecular level targets associated with exercise response, at both group and individual levels, is paramount to develop health guidelines and targeted health interventions. Sixteen, apparently healthy, moderately trained (VO2 max = 51.0 ± 10.6 mL min-1 kg-1 ) males (age range = 18-45 years) from the Gene SMART (Skeletal Muscle Adaptive Responses to Training) study completed a longitudinal study composed of 12-week high-intensity interval training (HIIT) intervention. Vastus lateralis muscle biopsies were collected at baseline and after 4, 8, and 12 weeks of HIIT. DNA methylation (~850 CpG sites) and proteomic (~3000 proteins) analyses were conducted at all time points. Mixed models were applied to estimate group and individual changes, and methylome and proteome integration was conducted using a holistic multilevel approach with the mixOmics package. A total of 461 proteins significantly changed over time (at 4, 8, and 12 weeks), whilst methylome overall shifted with training only one differentially methylated position (DMP) was significant (adj.p-value < .05). K-means analysis revealed cumulative protein changes by clusters of proteins that presented similar changes over time. Individual responses to training were observed in 101 proteins. Seven proteins had large effect-sizes >0.5, among them are two novel exercise-related proteins, LYRM7 and EPN1. Integration analysis showed bidirectional relationships between the methylome and proteome. We showed a significant influence of HIIT on the epigenome and more so on the proteome in human muscle, and uncovered groups of proteins clustering according to similar patterns across the exercise intervention. Individual responses to exercise were observed in the proteome with novel mitochondrial and metabolic proteins consistently changed across individuals. Future work is required to elucidate the role of these proteins in response to exercise.

A meta-analysis of immune-cell fractions at high resolution reveals novel associations with common phenotypes and health outcomes.

BACKGROUND: Changes in cell-type composition of tissues are associated with a wide range of diseases and environmental risk factors and may be causally implicated in disease development and progression. However, these shifts in cell-type fractions are often of a low magnitude, or involve similar cell subtypes, making their reliable identification challenging. DNA methylation profiling in a tissue like blood is a promising approach to discover shifts in cell-type abundance, yet studies have only been performed at a relatively low cellular resolution and in isolation, limiting their power to detect shifts in tissue composition. METHODS: Here we derive a DNA methylation reference matrix for 12 immune-cell types in human blood and extensively validate it with flow-cytometric count data and in whole-genome bisulfite sequencing data of sorted cells. Using this reference matrix, we perform a directional Stouffer and fixed effects meta-analysis comprising 23,053 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes. In a separate cohort of 4386 blood samples, we assess associations between immune-cell fractions and health outcomes. RESULTS: Our meta-analysis reveals many associations of cell-type fractions with age, sex, smoking and obesity, many of which we validate with single-cell RNA sequencing. We discover that naïve and regulatory T-cell subsets are higher in women compared to men, while the reverse is true for monocyte, natural killer, basophil, and eosinophil fractions. Decreased natural killer counts associated with smoking, obesity, and stress levels, while an increased count correlates with exercise and sleep. Analysis of health outcomes revealed that increased naïve CD4 + T-cell and N-cell fractions associated with a reduced risk of all-cause mortality independently of all major epidemiological risk factors and baseline co-morbidity. A machine learning predictor built only with immune-cell fractions achieved a C-index value for all-cause mortality of 0.69 (95%CI 0.67-0.72), which increased to 0.83 (0.80-0.86) upon inclusion of epidemiological risk factors and baseline co-morbidity. CONCLUSIONS: This work contributes an extensively validated high-resolution DNAm reference matrix for blood, which is made freely available, and uses it to generate a comprehensive map of associations between immune-cell fractions and common phenotypes, including health outcomes.

Implementation of multiple statistical methods to estimate variability and individual response to training.

Multiple statistical methods have been proposed to estimate individual responses to exercise training; yet, the evaluation of these methods is lacking. We compared five of these methods including the following: the use of a control group, a control period, repeated testing during an intervention, a reliability trial and a repeated intervention. Apparently healthy males from the Gene SMART study completed a 4-week control period, 4 weeks of High-Intensity Interval Training (HIIT), >1 year of washout, and then subsequently repeated the same 4 weeks of HIIT, followed by an additional 8 weeks of HIIT. Aerobic fitness measurements were measured in duplicates at each time point. We found that the control group and control period were not intended to measure the degree to which individuals responded to training, but rather estimated whether individual responses to training can be detected with the current exercise protocol. After a repeated intervention, individual responses to 4 weeks of HIIT were not consistent, whereas repeated testing during the 12-week-long intervention was able to capture individual responses to HIIT. The reliability trial should not be used to study individual responses, rather should be used to classify participants as responders with a certain level of confidence. 12 weeks of HIIT with repeated testing during the intervention is sufficient and cost-effective to measure individual responses to exercise training since it allows for a confident estimate of an individual's true response. Our study has significant implications for how to improve the design of exercise studies to accurately estimate individual responses to exercise training interventions.HighlightsWhat are the findings? We implemented five statistical methods in a single study to estimate the magnitude of within-subject variability and quantify responses to exercise training at the individual level.The various proposed methods used to estimate individual responses to training provide different types of information and rely on different assumptions that are difficult to test.Within-subject variability is often large in magnitude, and as such, should be systematically evaluated and carefully considered in future studies to successfully estimate individual responses to training.How might it impact on clinical practice in the future?Within-subject variability in response to exercise training is a key factor that must be considered in order to obtain a reproducible measurement of individual responses to exercise training. This is akin to ensuring data are reproducible for each subject.Our findings provide guidelines for future exercise training studies to ensure results are reproducible within participants and to minimise wasting precious research resources.By implementing five suggested methods to estimate individual responses to training, we highlight their feasibility, strengths, weaknesses and costs, for researchers to make the best decision on how to accurately measure individual responses to exercise training.

Genetic variants within the COL5A1 gene are associated with ligament injuries in physically active populations from Australia, South Africa, and Japan.

Previous small-scale studies have shown an association between the COL5A1 gene and anterior cruciate ligament (ACL) injury risk. In this larger study, the genotype and allele frequency distributions of the COL5A1 rs12722 C/T and rs10628678 AGGG/deletion (AGGG/-) indel variants were compared between participants: (i) with ACL injury in independent and combined cohorts from South-Africa (SA) and Australia (AUS) vs controls (CON), and (ii) with any ligament (ALL) or only ACL injury in a Japanese (JPN) cohort vs CON. Samples were collected from SA (235 cases; 232 controls), AUS (362 cases; 80 controls) and JPN (500 cases; 1,403 controls). Genomic DNA was extracted and genotyped. Distributions were compared, and inferred haplotype analyses performed. No independent associations were noted for rs12722 or rs10628678 when the combined SA + AUS cohort was analysed. However, the C-deletion (rs12722-rs10628678) inferred haplotype was under-represented (p = 0.040, OR = 0.15, CI = 0.04-0.56), while the T-deletion inferred haplotype was over-represented in the female SA + AUS ACL participants versus controls (p < 0.001, OR = 4.74, CI = 1.66-13.55). Additionally, the rs12722 C/C genotype was under-represented in JPN CON vs ACL (p = 0.039, OR = 0.52, 0.27-1.00), while the rs10628678 -/- genotype was associated with increased risk of any ligament injuries (p = 0.035, OR = 1.31, CI = 1.02-1.68) in the JPN cohort. Collectively, these results highlight that a region within the COL5A1 3'-UTR is associated with ligament injury risk. This must be evaluated in larger cohorts and its functional relevance to the structure and capacity of ligaments and joint biomechanics be explored.Highlights The COL5A1 T-deletion inferred haplotype (rs12722-rs10628678) was associated with an increased risk of ACL rupture in the combined SA and AUS female participants.The COL5A1 C-deletion inferred haplotype (rs12722-rs10628678) was associated with a decreased risk of ACL rupture in the combined SA and AUS female participants.The COL5A1 rs12722 C/C and rs10628678 -/- genotypes were associated with increased risk of ACL rupture and of ligament injuries in JPN, respectively.A region within the COL5A1 3'-UTR is associated with risk of ligament injury, including ACL rupture, and therefore the functional significance of this region on ligament capacity and joint biomechanics requires further exploration.

Physiological and molecular sex differences in human skeletal muscle in response to exercise training.

Sex differences in exercise physiology, such as substrate metabolism and skeletal muscle fatigability, stem from inherent biological factors, including endogenous hormones and genetics. Studies investigating exercise physiology frequently include only males or do not take sex differences into consideration. Although there is still an underrepresentation of female participants in exercise research, existing studies have identified sex differences in physiological and molecular responses to exercise training. The observed sex differences in exercise physiology are underpinned by the sex chromosome complement, sex hormones and, on a molecular level, the epigenome and transcriptome. Future research in the field should aim to include both sexes, control for menstrual cycle factors, conduct large-scale and ethnically diverse studies, conduct meta-analyses to consolidate findings from various studies, leverage unique cohorts (such as post-menopausal, transgender, and those with sex chromosome abnormalities), as well as integrate tissue and cell-specific -omics data. This knowledge is essential for developing deeper insight into sex-specific physiological responses to exercise training, thus directing future exercise physiology studies and practical application.

Uncovering the effects of gender affirming hormone therapy on skeletal muscle and epigenetics: protocol for a prospective matched cohort study in transgender individuals (the GAME study).

INTRODUCTION: Gender affirming hormone therapy (GAHT) is increasingly used by transgender individuals and leads to shifts in sex hormone levels. Skeletal muscle is highly responsive to hormone activity, with limited data on the effects of GAHT on different human tissues. Here, we present the protocol for the GAME study (the effects of Gender Affirming hormone therapy on skeletal Muscle training and Epigenetics), which aims to uncover the effects of GAHT on skeletal muscle 'omic' profiles (methylomics, transcriptomics, proteomics, metabolomics) and markers of skeletal muscle health and fitness. METHODS AND ANALYSIS: This study is a prospective age-matched cohort study in transgender adults commencing GAHT (n=80) and age-matched individuals not commencing GAHT (n=80), conducted at Austin Health and Victoria University in Victoria, Australia. Assessments will take place prior to beginning GAHT and 6 and 12 months into therapies in adults commencing GAHT. Age-matched individuals will be assessed at the same time points. Assessments will be divided over three examination days, involving (1) aerobic fitness tests, (2) muscle strength assessments and (3) collection of blood and muscle samples, as well as body composition measurements. Standardised diets, fitness watches and questionnaires will be used to control for key confounders in analyses. Primary outcomes are changes in aerobic fitness and muscle strength, as well as changes in skeletal muscle DNA methylation and gene expression profiles. Secondary outcomes include changes in skeletal muscle characteristics, proteomics, body composition and blood markers. Linear mixed models will be used to assess changes in outcomes, while accounting for repeated measures within participants and adjusting for known confounders. ETHICS AND DISSEMINATION: The Austin Health Human Research Ethics Committee (HREC) and Victoria University HREC granted approval for this study (HREC/77146/Austin-2021). Findings from this project will be published in open-access, peer-reviewed journals and presented to scientific and public audiences. TRIAL REGISTRATION NUMBER: ACTRN12621001415897; Pre-results.

Low-Load Resistance Training to Volitional Failure Induces Muscle Hypertrophy Similar to Volume-Matched, Velocity Fatigue.

ABSTRACT: Terada, K, Kikuchi, N, Burt, D, Voisin, S, and Nakazato, K. Full title: Low-load resistance training to volitional failure induces muscle hypertrophy similar to volume-matched, velocity fatigue. J Strength Cond Res 36(6): 1576-1581, 2022-We investigated how resistance training (RT) to failure at low load affects acute responses and chronic muscle adaptations compared with low-load RT to velocity fatigue at equal work volume. Twenty-seven subjects performed 8 weeks of bench press twice weekly. Subjects were randomly assigned to one of 3 groups: low-load volitional failure (LVoF, n = 9), low-load velocity fatigue (LVeF, n = 8), and high-load (HL, n = 10). Resistance training comprised 3 sets to failure at 40% one repetition maximum (1RM) in the LVoF group, 3 sets to velocity fatigue (20% lifting velocity loss) at 40% 1RM in the LVeF group, and 3 sets of 8 repetitions at 80% 1RM in the HL group. We measured muscle strength, hypertrophy, endurance, and power at baseline and after the RT program. We also measured muscle swelling and blood lactate after each RT bout to investigate the acute response. There were no differences in total work volume between the LVoF and LVeF groups. Responses to RT were similar between LVoF and LVeF, whether looking at acute muscle swelling, increase in blood lactate, chronic hypertrophy, and strength gain. However, LVoF and LVeF RT triggered different responses to muscle function in comparison with HL training: LVoF and LVeF showed enhanced acute responses and greater chronic endurance gains, but lower chronic strength gains than HL. In conclusion, low-load RT to volitional failure induces muscle hypertrophy similar to volume-matched velocity fatigue.

Making sense of the ageing methylome.

Over time, the human DNA methylation landscape accrues substantial damage, which has been associated with a broad range of age-related diseases, including cardiovascular disease and cancer. Various age-related DNA methylation changes have been described, including at the level of individual CpGs, such as differential and variable methylation, and at the level of the whole methylome, including entropy and correlation networks. Here, we review these changes in the ageing methylome as well as the statistical tools that can be used to quantify them. We detail the evidence linking DNA methylation to ageing phenotypes and the longevity strategies aimed at altering both DNA methylation patterns and machinery to extend healthspan and lifespan. Lastly, we discuss theories on the mechanistic causes of epigenetic ageing.

Osteoglycin Across the Adult Lifespan.

CONTEXT: Osteoglycin (OGN) is a proteoglycan released from bone and muscle which has been associated with markers of metabolic health. However, it is not clear whether the levels of circulating OGN change throughout the adult lifespan or if they are associated with clinical metabolic markers or fitness. OBJECTIVE: We aimed to identify the levels of circulating OGN across the lifespan and to further explore the relationship between OGN and aerobic capacity as well as OGN's association with glucose and HOMA-IR. METHODS: 107 individuals (46 males and 61 females) aged 21-87 years were included in the study. Serum OGN levels, aerobic capacity (VO2peak), glucose, and homeostatic model assessment for insulin resistance (HOMA-IR) were assessed. T-tests were used to compare participant characteristics between sexes. Regression analyses were performed to assess the relationship between OGN and age, and OGN and fitness and metabolic markers. RESULTS: OGN displayed a nonlinear, weak "U-shaped" relationship with age across both sexes. Men had higher levels of OGN than women across the lifespan (ß = 0.23, P = .03). Age and sex explained 16% of the variance in OGN (adjusted R2 = 0.16; P < .001). Higher OGN was associated with higher VO2peak (ß = 0.02, P = .001); however, those aged <50 showed a stronger positive relationship than those aged >50. A higher OGN level was associated with a higher circulating glucose level (ß = 0.17, P < .01). No association was observed between OGN and HOMA-IR. CONCLUSION: OGN was characterized by a U-shaped curve across the lifespan which was similar between sexes. Those with a higher aerobic capacity or higher glucose concentration had higher OGN levels. Our data suggest an association between OGN and aerobic fitness and glucose regulation. Future studies should focus on exploring the potential of OGN as a biomarker for chronic disease.

Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism.

Nearly all human complex traits and diseases exhibit some degree of sex differences, with epigenetics being one of the main contributing factors. Various tissues display sex differences in DNA methylation; however, this has not yet been explored in skeletal muscle, despite skeletal muscle being among the tissues with the most transcriptomic sex differences. For the first time, we investigated the effect of sex on autosomal DNA methylation in human skeletal muscle across three independent cohorts (Gene SMART, FUSION, and GSE38291) using a meta-analysis approach, totalling 369 human muscle samples (222 males and 147 females), and integrated this with known sex-biased transcriptomics. We found 10,240 differentially methylated regions (DMRs) at FDR < 0.005, 94% of which were hypomethylated in males, and gene set enrichment analysis revealed that differentially methylated genes were involved in muscle contraction and substrate metabolism. We then investigated biological factors underlying DNA methylation sex differences and found that circulating hormones were not associated with differential methylation at sex-biased DNA methylation loci; however, these sex-specific loci were enriched for binding sites of hormone-related transcription factors (with top TFs including androgen (AR), estrogen (ESR1), and glucocorticoid (NR3C1) receptors). Fibre type proportions were associated with differential methylation across the genome, as well as across 16% of sex-biased DNA methylation loci (FDR < 0.005). Integration of DNA methylomic results with transcriptomic data from the GTEx database and the FUSION cohort revealed 326 autosomal genes that display sex differences at both the epigenome and transcriptome levels. Importantly, transcriptional sex-biased genes were overrepresented among epigenetic sex-biased genes (p value = 4.6e-13), suggesting differential DNA methylation and gene expression between male and female muscle are functionally linked. Finally, we validated expression of three genes with large effect sizes (FOXO3A, ALDH1A1, and GGT7) in the Gene SMART cohort with qPCR. GGT7, involved in antioxidant metabolism, displays male-biased expression as well as lower methylation in males across the three cohorts. In conclusion, we uncovered 8420 genes that exhibit DNA methylation differences between males and females in human skeletal muscle that may modulate mechanisms controlling muscle metabolism and health.

Meta-analysis of genome-wide DNA methylation and integrative omics of age in human skeletal muscle.

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-friendly, web-based tool called MetaMeth (https://sarah-voisin.shinyapps.io/MetaMeth/).

Individual physiological and mitochondrial responses during 12 weeks of intensified exercise.

AIM: Observed effects of exercise are highly variable between individuals, and subject-by-training interaction (i.e., individual response variability) is often not estimated. Here, we measured mitochondrial (citrate synthetase, cytochrome-c oxidase, succinate dehydrogenase, and mitochondrial copy-number), performance markers (Wpeak , lactate threshold [LT], and VO2peak ), and fiber type proportions/expression (type I, type IIa, and type IIx) in multiple time points during 12-week of high-intensity interval training (HIIT) to investigate effects of exercise at the individual level. METHODS: Sixteen young (age: 33.1 ± 9.0 years), healthy men (VO2peak 35-60 ml/min/kg and BMI: 26.4 ± 4.2) from the Gene SMART study completed 12-week of progressive HIIT. Performance markers and muscle biopsies were collected every 4 weeks. We used mixed-models and bivariate growth models to quantify individual response and to estimate correlations between variables. RESULTS: All performance markers exhibited significant (Wpeak 0.56 ± 0.33 p = 0.003, LT 0.37 ± 0.35 p = 0.007, VO2peak 3.81 ± 6.13 p = 0.02) increases overtime, with subject-by-training interaction being present (95% CI: Wpeak 0.09-0.24, LT 0.06-0.18, VO2peak 0.27-2.32). All other measurements did not exhibit significant changes. Fiber type IIa proportions at baseline was significantly associated with all physiological variables (p < 0.05), and citrate synthetase and cytochrome-c oxidase levels at baseline and overtime (i.e., intercept and slope) presented significant covariance (p < 0.05). Finally, low correlations between performance and mitochondrial markers were observed. CONCLUSION: We identified a significant subject-by-training interaction for the performance markers. While for all other measures within-subject variability was too large and interindividual differences in training efficacy could not be verified. Changes in measurements in response to exercise were not correlated, and such disconnection should be further investigated by future studies.

Mapping Robust Genetic Variants Associated with Exercise Responses.

This review summarised robust and consistent genetic variants associated with aerobic-related and resistance-related phenotypes. In total we highlight 12 SNPs and 7 SNPs that are robustly associated with variance in aerobic-related and resistance-related phenotypes respectively. To date, there is very little literature ascribed to understanding the interplay between genes and environmental factors and the development of physiological traits. We discuss future directions, including large-scale exercise studies to elucidate the functional relevance of the discovered genomic markers. This approach will allow more rigour and reproducible research in the field of exercise genomics.

meQTL and ncRNA functional analyses of 102 GWAS-SNPs associated with depression implicate HACE1 and SHANK2 genes.

BACKGROUND: Little is known about how genetics and epigenetics interplay in depression. Evidence suggests that genetic variants may change vulnerability to depression by modulating DNA methylation (DNAm) and non-coding RNA (ncRNA) levels. Therefore, the aim of the study was to investigate the effect of the genetic variation, previously identified in the largest genome-wide association study for depression, on proximal DNAm and ncRNA levels. RESULTS: We performed DNAm quantitative trait locus (meQTL) analysis in two independent cohorts (total n = 435 healthy individuals), testing associations between 102 single-nucleotide polymorphisms (SNPs) and DNAm levels in whole blood. We identified and replicated 64 SNP-CpG pairs (padj. < 0.05) with meQTL effect. Lower DNAm at cg02098413 located in the HACE1 promoter conferred by the risk allele (C allele) at rs1933802 was associated with higher risk for depression (praw = 0.014, DNAm = 2.3%). In 1202 CD14+ cells sorted from blood, DNAm at cg02088412 positively correlated with HACE1 mRNA expression. Investigation in postmortem brain tissue of adults diagnosed with major depressive disorder (MDD) indicated 1% higher DNAm at cg02098413 in neurons and lower HACE1 mRNA expression in CA1 hippocampus of MDD patients compared with healthy controls (p = 0.008 and 0.012, respectively). Expression QTL analysis in blood of 74 adolescent revealed that hsa-miR-3664-5p was associated with rs7117514 (SHANK2) (padj. = 0.015, mRNA difference = 5.2%). Gene ontology analysis of the miRNA target genes highlighted implication in neuronal processes. CONCLUSIONS: Collectively, our findings from a multi-tissue (blood and brain) and multi-layered (genetic, epigenetic, transcriptomic) approach suggest that genetic factors may influence depression by modulating DNAm and miRNA levels. Alterations at HACE1 and SHANK2 loci imply potential mechanisms, such as oxidative stress in the brain, underlying depression. Our results deepened the knowledge of molecular mechanisms in depression and suggest new epigenetic targets that should be further evaluated.

An epigenetic clock for human skeletal muscle.

BACKGROUND: Ageing is associated with DNA methylation changes in all human tissues, and epigenetic markers can estimate chronological age based on DNA methylation patterns across tissues. However, the construction of the original pan-tissue epigenetic clock did not include skeletal muscle samples and hence exhibited a strong deviation between DNA methylation and chronological age in this tissue. METHODS: To address this, we developed a more accurate, muscle-specific epigenetic clock based on the genome-wide DNA methylation data of 682 skeletal muscle samples from 12 independent datasets (18-89 years old, 22% women, 99% Caucasian), all generated with Illumina HumanMethylation (HM) arrays (HM27, HM450, or HMEPIC). We also took advantage of the large number of samples to conduct an epigenome-wide association study of age-associated DNA methylation patterns in skeletal muscle. RESULTS: The newly developed clock uses 200 cytosine-phosphate-guanine dinucleotides to estimate chronological age in skeletal muscle, 16 of which are in common with the 353 cytosine-phosphate-guanine dinucleotides of the pan-tissue clock. The muscle clock outperformed the pan-tissue clock, with a median error of only 4.6 years across datasets (vs. 13.1 years for the pan-tissue clock, P < 0.0001) and an average correlation of ρ = 0.62 between actual and predicted age across datasets (vs. ρ = 0.51 for the pan-tissue clock). Lastly, we identified 180 differentially methylated regions with age in skeletal muscle at a false discovery rate < 0.005. However, gene set enrichment analysis did not reveal any enrichment for gene ontologies. CONCLUSIONS: We have developed a muscle-specific epigenetic clock that predicts age with better accuracy than the pan-tissue clock. We implemented the muscle clock in an r package called Muscle Epigenetic Age Test available on Bioconductor to estimate epigenetic age in skeletal muscle samples. This clock may prove valuable in assessing the impact of environmental factors, such as exercise and diet, on muscle-specific biological ageing processes.

Mitochondrial respiration variability and simulations in human skeletal muscle: The Gene SMART study.

Mitochondrial respiration using the oxygraph-2k respirometer (Oroboros) is widely used to estimate mitochondrial capacity in human skeletal muscle. Here, we measured mitochondrial respiration variability, in a relatively large sample, and for the first time, using statistical simulations, we provide the sample size required to detect meaningful respiration changes following lifestyle intervention. Muscle biopsies were taken from healthy, young men from the Gene SMART cohort, at multiple time points. We utilized samples for each measurement with two technical repeats using two respirometer chambers (n = 160 pairs of same muscle after removal of low-quality samples). We measured the Technical Error of measurement (TEM ) and the coefficient of variation (CV) for each mitochondrial complex. There was a high correlation between measurements from the two chambers (R > 0.7 P < .001) for all complexes, but the TEM was large (7.9-27 pmol s-1  mg-1 ; complex dependent), and the CV was >15% for all complexes. We performed statistical simulations of a range of effect sizes at 80% power and found that 75 participants (with duplicate measurements) are required to detect a 6% change in mitochondrial respiration after an intervention, while for interventions with 11% effect size, ~24 participants are sufficient. The high variability in respiration suggests that the typical sample sizes in exercise studies may not be sufficient to capture exercise-induced changes.

Aerobic capacity and telomere length in human skeletal muscle and leukocytes across the lifespan.

A reduction in aerobic capacity and the shortening of telomeres are hallmarks of the ageing process. We examined whether a lower aerobic capacity is associated with shorter TL in skeletal muscle and/or leukocytes, across a wide age range of individuals. We also tested whether TL in human skeletal muscle (MTL) correlates with TL in leukocytes (LTL). Eighty-two recreationally active, healthy men from the Gene SMART cohort (31.4±8.2 years; body mass index (BMI)=25.3±3.3kg/m2), and 11 community dwelling older men (74.2±7.5years-old; BMI=28.7±2.8kg/m2) participated in the study. Leukocytes and skeletal muscle samples were collected at rest. Relative telomere length (T/S ratio) was measured by RT-PCR. Associations between TL, aerobic capacity (VO2 peak and peak power) and age were assessed with robust linear models. Older age was associated with shorter LTL (45% variance explained, P<0.001), but not MTL (P= 0.7). Aerobic capacity was not associated with MTL (P=0.5), nor LTL (P=0.3). MTL and LTL were correlated across the lifespan (rs=0.26, P=0.03). In healthy individuals, age explain most of the variability of LTL and this appears to be independent of individual aerobic capacity. Individuals with longer LTL also have a longer MTL, suggesting that there might be a shared molecular mechanism regulating telomere length.