Sarah Voisin and Nir Eynon are Co-senior authorship.Abbreviations: ATP, adenosine triphosphate; CI, complex I, electron input through CI; CV, coefficient of variation; CI P , oxidative phosphorylation (OXPHOS) capacity (P) through CI; ETS, electron transport system; CI+CII, convergent electron input through CI and CII CI+CII E , capacity (E) through CI+CII; CI+CII P , complex II (CII) linked respiration; E, ETS capacity; ETS, measurement of electron transport system; FCCP, p-trifluoromethoxyphenylhydrazone; Gene SMART, genes and skeletal muscle adaptive response to training; Inv-RCR, inverse of respiratory control ratio (CIL/CI+II P ); L, leak respiration; LCR, leak control ratio (CIL/CI+II E ); OXPHOS, oxidative phosphorylation; P, oxphos capacity; PCR, phosphorylation control ratio (CI+II P / CI+II E ); ROX, residual oxygen consumption; SCR, substrate control ratio at constant P (CIP/CI+II P ); TCA, tricarboxylic acid; TE M , technical error of measurement. AbstractMitochondrial 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 (TE M ) 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 TE M 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. K E Y W O R D Sexercise, intervention, mitochondria, OXPHOS, oxygen consumption | 2979 JACQUES Et Al.
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.
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.
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/m 2), and 11 community dwelling older men (74.2±7.5yearsold; BMI=28.7±2.8kg/m 2) 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.
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