Biology subjects

Voisin, S.

Publications and source records attributed to Voisin, S..

11 recordsLinked to original sources

bioRxiv2026

Tissue-specific divergence in sex-biased DNA methylation across the lifespan

BackgroundAgeing is a sex-specific process characterised by a progressive decline in physiological integrity. DNA methylation represents a primary epigenetic hallmark of ageing, yet sex-specific patterns of epigenetic ageing within and across tissues remain poorly understood. This study aims to address these gaps through an integrated analysis of sex-moderated epigenetic ageing across eight human tissues. MethodsA total of 137 DNA methylation datasets comprising over 36,000 individuals aged 10-114 years were analysed using a meta-analytic workflow to identify age-associated differentially methylated positions (aDMPs) and regions (aDMRs), meta-regression to assess sex moderation, and pathway enrichment analyses to interpret functional relevance. FindingsIndividual tissues displayed distinct age-related methylation trajectories, but some DMP sites showed consistent hyper- or hypomethylation across tissues. Across tissues, we identified 68,630 aDMPs (10%) robustly associated with ageing. Age-associated changes at the regional level were less common, with only 80 robust age-associated aDMRs detected across tissues, representing 0.09% of analysed regions. Sex moderation was observed for only 16 aDMPs (0.002%), indicating that sex effects on age-associated DNA methylation are largely tissue-specific rather than shared across tissues. InterpretationOur findings indicate that age-associated DNA methylation changes predominantly occur at isolated CpG sites rather than extended genomic regions and are strongly dependent on tissue and genomic context. The minimal overlap of sex-moderated methylation signals across tissues suggests that age-related sex differences at the epigenetic level are more likely attributable to tissue- and cell-type-specific variation rather than to broadly conserved epigenetic mechanisms shared across tissues. FundingThis study was funded by an Australian Research Council (ARC) Discovery project (DP200101830). Severine Lamon was funded by an ARC Future Fellowship (FT210100278). Nir Eynon was funded by NHMRC Investigator Grant (APP1194159), and a Hevolution/AFAR New Investigator Award in Aging Biology and Geroscience Research. Mandhri D. Abeysooryia was supported by an Australian Government Research Training Program (RTP) Scholarship. Research in context Evidence before this studyDNA methylation is widely recognised as a central epigenetic hallmark of ageing. Previous research has demonstrated that some age-related methylation changes are conserved across tissues, forming the basis of pan-tissue epigenetic clocks. Most studies to date have primarily examined age effects in isolation. Although biological sex influences ageing trajectories and susceptibility to nearly all age-related diseases, sex-moderated epigenetic ageing has received limited investigation. Specifically, pan-tissue clocks, including GrimAge and PhenoAge, are "sex-aware" but were trained and validated in mixed-sex cohorts, limiting their capacity to disentangle tissue-specific sex effects. Consequently, it remains unclear whether sex-moderated epigenetic ageing signals are shared across tissues or are tissue-specific. Added value of this studyThis study provides a large-scale, comprehensive multi-tissue analysis of sex-moderated epigenetic ageing, integrating 137 DNA methylation datasets across eight human tissues and more than 36,000 male and female individuals spanning the lifespan. Our findings show that while age-associated methylation changes are widespread at the CpG level, sex-moderated effects are rare and largely tissue-specific, with minimal overlap across tissues. Implications of all the available evidenceTogether, the available evidence indicates that epigenetic ageing is predominantly driven by shared, conserved age-related methylation changes, whereas sex differences in epigenetic ageing are modest and context dependent. These sex-related effects are more likely to reflect tissue- and cell-type-specific variation rather than widespread, shared mechanisms. This underscores the need to develop sex-specific epigenetic clocks and to conduct longitudinal cohort and intervention studies to more precisely characterise sex-specific dynamics of epigenetic ageing across tissues.

genetics↗

bioRxiv2025

DNA Methylation Ageing Atlas Across 17 Human Tissues

Aging involves widespread epigenetic remodeling across tissues, yet the nature and consistency of these changes remain unclear. We conducted a meta-analysis of more than 15,000 human methylomes spanning 17 tissues, identifying both conserved and tissue-specific aging signatures. We examined linear changes via differentially methylated positions, variability shifts via variably methylated positions, and Shannon-entropy to capture methylation disorder. Network analysis revealed fragile co-methylation modules largely resistant to beneficial perturbation. Key disruptors, including PCDHGA1, MEST, HDAC4, and HOX genes, exacerbated aging signals across tissues. Notably, a resilient module enriched for NAD{square} salvage metabolism supports therapeutic targeting of NAD{square} in aging. PCDHGA1 emerged as a conserved cross-tissue driver, suggesting protocadherin-mediated adhesion plays a broader role in maintaining structural and signaling stability in multiple organ systems. Our open-access atlas provides a foundational resource for dissecting the molecular architecture of human aging and identifying testable targets for intervention, biomarkers, and translational epigenetic therapies.

bioinformatics↗

bioRxiv2023

A comprehensive map of the ageing blood methylome

During ageing, the human methylome exhibits both differential (i.e. change in mean) and variable (i.e. change in variance) shifts, along with a general rise in entropy. However, it remains unclear whether DNA methylation sites that increasingly diverge between people (i.e. variably methylated positions (VMPs)) are distinct from those undergoing changes in mean methylation levels (i.e. differentially methylated positions (DMPs)), which changes drive entropy, how they contribute to epigenetic age measured by epigenetic clocks, and whether cell type heterogeneity plays a role in these alterations. To address these questions, we conducted a comprehensive analysis using > 32,000 human blood methylomes from 56 datasets (age range = 6-101 years). Our findings revealed an unprecedented proportion of the blood methylome that is differentially methylated with age (48% DMPs; FDR< 0.005) and variably methylated with age (37% VMPs; FDR< 0.005), with many sites overlapping between the two groups (59% of DMPs are VMPs). We observed that bivalent and Polycomb regions become increasingly methylated and divergent between individuals, while quiescent regions lose methylation in a more homogeneous manner between individuals. Unexpectedly, both chronological and biological clocks, but not pace-of-aging clocks, show a strong enrichment for those CpGs that accrue both mean and variance changes during aging. Furthermore, we uncovered that it is the accumulation of DMPs shifting towards a methylation fraction of 50% that drive the increase in entropy, resulting in an overall smoothening of the epigenetic landscape. However, approximately a quarter of DMPs oppose this direction of change, exhibiting anti-entropic effects. While DMPs were mostly unaffected by changes in cell type composition, VMPs and entropy measurements showed moderate sensitivity to such alterations. This investigation represents the largest to date of genome-wide DNA methylation changes and ageing in a single tissue, offering valuable insights into primary molecular changes that hold meaning for chronological and biological ageing.

molecular biology↗

bioRxiv2023

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

AbstractO_ST_ABSBackgroundC_ST_ABSChanges in cell-type composition of complex tissues are associated with a wide range of diseases, 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 these shifts in tissue composition. MethodsHere 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 and Stouffers method, we perform a meta-analysis encompassing 25,629 blood samples from 22 different cohorts, to comprehensively map associations between the 12 immune-cell fractions and common phenotypes, including health outcomes. ResultsOur meta-analysis reveals many associations with age, sex, smoking and obesity, many of which we validate with single-cell RNA-sequencing. We discover that T-regulatory and naive T-cell subsets are higher in women compared to men, whilst the reverse is true for monocyte, natural killer, basophil and eosinophil fractions. In a large subset encompassing 5000 individuals we find associations with stress, exercise, sleep and health outcomes, revealing that naive T-cell and B-cell fractions are associated with a reduced risk of all-cause mortality independently of age, sex, race, smoking, obesity and alcohol consumption. We find that decreased natural killer cell counts are associated with smoking, obesity and stress levels, whilst an increased count correlates with exercise, sleep and a reduced risk of all-cause mortality. ConclusionsThis work derives and extensively validates a high resolution DNAm reference matrix for blood, and uses it to generate a comprehensive map of associations between immune cell fractions and common phenotypes, including health outcomes. AvailabilityThe 12 immune cell-type DNAm reference matrices for Illumina 850k and 450k beadarrays alongside tools for cell-type fraction estimation are freely available from our EpiDISH Bioconductor R-package http://www.bioconductor.org/packages/devel/bioc/html/EpiDISH.html

bioinformatics↗

bioRxiv2023

The influence of Sex on microRNA expression in Human Skeletal Muscle

IntroductionSex differences in microRNA (miRNA) expression profiles have been found across multiple tissues. Skeletal muscle is one of the top tissues that underpin sex-based differences, yet there is limited research into whether there are sex differences in miRNA expression in skeletal muscle. Further, there is limited literature investigating potential differences between males and females in skeletal muscle miRNA expression following exercise, a well-known modulator of miRNA expression. Therefore, the aim of this study was to investigate the effect of sex on miRNA expression in skeletal muscle at baseline and after an acute bout of exercise. MethodsMiRNAs were measured using Taqman(R)miRNA arrays in skeletal muscle of 42 healthy participants from the GeneSMART study (24 males and 20 females aged 18-45 yrs). Differentially expressed miRNAs were identified using mixed linear models adjusted for age. Experimentally validated miRNA gene targets enriched in skeletal muscle were identified in-silico. Over representation analysis was conducted to identify enriched pathways. TransmiR V.2 was used to identify transcription factor (TF)-miR regulatory networks using CHIP-derived data. We further profiled the effects of two sex-biased miRNAs overexpressed in human primary muscle cells lines derived from male and female donors to understand the transcriptome targeted by these miRNAs and investigate and potential sex-specific effects. ResultsA total of 80 miRNAs were differentially expressed in skeletal muscle between the sexes, with 61 miRNAs responding differently to the exercise between the sexes. Sex-biased miRNA gene targets were enriched for muscle-related processes including proliferation and differentiation of the muscle cells and numerous metabolic pathways, suggesting that miRNAs are playing a role in programming sex differences in skeletal muscle. Over-expression of sex-biased miRNAs miRNA-30a and miRNA-30c resulted in profound changes to gene expression profiles that were partly specific to the sex of the cell donor in human primary skeletal muscle cells. ConclusionWe found sex-differences in the expression profile of skeletal muscle miRNAs at baseline and in response to exercise. These miRNAs target regulatory pathways essential to skeletal muscle development and metabolism, suggesting that miRNAs play a profound but highly complex role in programming sex-differences in the skeletal muscle phenotype.

physiology↗

bioRxiv2022

Exercise rejuvenates the skeletal muscle methylome and transcriptome in humans

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 = 3,176). 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 towards 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 towards a younger state after exercise training interventions, while the transcriptome shifted towards 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.

molecular biology↗

bioRxiv2021

Genome-wide DNA methylation and transcriptome integration reveal distinct sex differences in skeletal muscle.

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, 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 8,420 genes that exhibit DNA methylation differences between males and females in human skeletal muscle that may modulate mechanisms controlling muscle metabolism and health. SignificanceThe importance of uncovering biological sex differences and their translation to physiology has become increasingly evident. Using a large-scale meta-analysis of three cohorts, we perform the first comparison of genome-wide skeletal muscle DNA methylation between males and females, and identify thousands of genes that display sex-differential methylation. We then explore intrinsic biological factors that may be underlying the DNA methylation sex differences, such as fibre type proportions and sex hormones. Leveraging the GTEx database, we identify hundreds of genes with both sex-differential expression and DNA methylation in skeletal muscle. We further confirm the sex-biased genes with gene expression data from two cohorts included in the methylation meta-analysis. Our study integrates genomewide sex-biased DNA methylation and expression in skeletal muscle, shedding light on distinct sex differences in skeletal muscle.

genomics↗

bioRxiv2020

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

Knowledge of age-related DNA methylation changes in skeletal muscle is limited, yet this tissue is severely affected by aging in humans. Using a large-scale epigenome-wide association study (EWAS) meta-analysis of age in human skeletal muscle from 10 studies (total n = 908 human muscle methylomes), we identified 9,986 differentially methylated regions at a stringent false discovery rate < 0.005, spanning 8,748 unique genes, many of which related to skeletal muscle structure and development. We then integrated the DNA methylation results with known transcriptomic and proteomic age-related changes in skeletal muscle, and found that even though most differentially methylated genes are not altered at the mRNA or protein level, they are nonetheless strongly enriched for genes showing age-related differential expression. We provide here the most comprehensive picture of DNA methylation aging in human skeletal muscle, and have made our results available as an open-access, user-friendly, web-based tool called MetaMeth (https://sarah-voisin.shinyapps.io/MetaMeth/).

genetics↗

bioRxiv2020

Identification of novel mitochondrial and mitochondrial related genetic loci associated with exercise response in the Gene SMART study

Mitochondria supply intracellular energy requirements during exercise. Specific mitochondrial haplogroups and mitochondrial genetic variants have been associated with athletic performance, and exercise responses. However, these associations were discovered using underpowered, candidate gene approaches, and consequently have not been replicated. Here, we used whole-mitochondrial genome sequencing, in conjunction with high-throughput genotyping arrays, to discover novel genetic variants associated with exercise responses in the Gene SMART (Skeletal Muscle Adaptive Response to Training) cohort (n=62 completed). We performed a Principal Component Analysis of cohort aerobic fitness measures to build composite traits and test for variants associated with exercise outcomes. None of the mitochondrial genetic variants but nine nuclear encoded variants in eight separate genes were found to be associated with exercise responses (FDR<0.05) (rs11061368: DIABLO, rs113400963: FAM185A, rs6062129 and rs6121949: MTG2, rs7231304: AFG3L2, rs2041840: NDUFAF7, rs7085433: TIMM23, rs1063271: SPTLC2, rs2275273: ALDH18A1). Additionally, we outline potential mechanisms by which these variants may be contributing to exercise phenotypes. Our data suggest novel nuclear-encoded SNPs and mitochondrial pathways associated with exercise response phenotypes. Future studies should focus on validating these variants across different cohorts and ethnicities. AUTHOR SUMMARYPrevious exercise genetic studies contain many flaws that impede the growth in knowledge surrounding change in exercise outcomes. In particular, exercise studies looking at mtDNA variants have looked at very small portions of the mitochondrial genome. Mitochondria are the power house of the cell and therefore understanding the mitochondrial genetics behind adaptations to training can help us fill knowledge gaps in current research. Here, we utilised a new mitochondrial genetic sequencing technique to examine all mitochondrial and mitochondrial related genetic variations. We have shown that there were no mitochondrial specific variants that influenced exercise training however there were 9 related variants that were significantly associated with exercise phenotypes. Additionally, we have shown that building composite traits increased the significance of our association testing and lead to novel findings. We will be able to understand why response to training is so varied and increase the effectiveness of exercise training on a host of metabolic disorders.

genetics↗

bioRxiv2019

DNA methylation across the genome in aged human skeletal muscle tissue and muscle stem cells: The role of HOX genes and physical activity

Skeletal muscle tissue demonstrates global hypermethylation with aging. However, methylome changes across the time-course of differentiation in aged human muscle derived stem cells, and larger coverage arrays in aged muscle tissue have not been undertaken. Using 850K DNA methylation arrays we compared the methylomes of young (27 {+/-} 4.4 years) and aged (83 {+/-} 4 years) human skeletal muscle and that of young/aged muscle stem cells over several time points of differentiation (0, 72 hours, 7, 10 days). Aged muscle tissue was hypermethylated compared with young tissue, enriched for; pathways-in-cancer (including; focal adhesion, MAPK signaling, PI3K-Akt-mTOR signaling, p53 signaling, Jak-STAT signaling, TGF-beta and notch signaling), rap1-signaling, axon-guidance and hippo-signalling. Aged muscle stem cells also demonstrated a hypermethylated profile in pathways; axon-guidance, adherens-junction and calcium-signaling, particularly at later timepoints of myotube formation, corresponding with reduced morphological differentiation and reductions in MyoD/Myogenin gene expression compared with young cells. While young cells showed little alteration in DNA methylation during differentiation, aged cells demonstrated extensive and significantly altered DNA methylation, particularly at 7 days of differentiation and most notably in the focal adhesion and PI3K-AKT signalling pathways. While the methylomes were vastly different between muscle tissue and isolated muscle stem cells, we identified a small number of CpG sites showing a hypermethylated state with age, in both muscle and tissue and stem cells (on genes KIF15, DYRK2, FHL2, MRPS33, ABCA17P). Most notably, differential methylation analysis of chromosomal regions identified three locations containing enrichment of 6-8 CpGs in the HOX family of genes altered with age. With HOXD10, HOXD9, HOXD8, HOXA3, HOXC9, HOXB1, HOXB3, HOXC-AS2 and HOXC10 all hypermethylated in aged tissue. In aged cells the same HOX genes (and additionally HOXC-AS3) displayed the most variable methylation at 7 days of differentiation versus young cells, with HOXD8, HOXC9, HOXB1 and HOXC-AS3 hypermethylated and HOXC10 and HOXC-AS2 hypomethylated. We also determined that there was an inverse relationship between DNA methylation and gene expression for HOXB1, HOXA3 and HOXC-AS3. Finally, increased physical activity in young adults was associated with oppositely regulating HOXB1 and HOXA3 methylation compared with age. Overall, we demonstrate that a considerable number of HOX genes are differentially epigenetically regulated in aged human skeletal muscle and muscle stem cells and increased physical activity may help prevent age-related epigenetic changes in these HOX genes.

physiology↗

bioRxiv2019

An epigenetic clock for skeletal muscle

BackgroundAgeing 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. MethodsTo 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 arrays (HM27, HM450 or HMEPIC). We also took advantage of the large number of samples to conduct an epigenome-wide association study (EWAS) of age-associated DNA methylation patterns in skeletal muscle. ResultsThe newly developed clock uses 200 CpGs to estimate chronological age in skeletal muscle, 16 of which are in common with the 353 CpGs 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 {rho} = 0.62 between actual and predicted age across datasets (vs {rho} = 0.51 for the pan-tissue clock). Lastly, we identified 180 differentially methylated regions (DMRs) 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. ConclusionsWe 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 MEAT 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.

bioinformatics↗