Sarcopenia is generally an age-related condition in older people that impacts adverse health consequences in terms of quality of life, morbidity and mortality. With the increasing interest of clinical and research interest in sarcopenia internationally, the epidemiological evidence reveals sarcopenia risk begins in early adulthood, influenced by gene, lifestyle and a range of chronic conditions across life course.

The purpose of this study was to systematically summarize the risk factors for sarcopenia across the life course, and to identity the high-risk population.

Searches were performed in PubMed, Web of Science, Scopus, Embase, MEDLINE, and SPORTDiscus databases from inception to July 2024. Longitudinal studies assessing the risk factors for sarcopenia in community setting were included in the analysis. Fixed- and random-effect models were used to pool effect size. Based on the results of meta-analysis, we developed a risk predictive model for sarcopenia.

Fifty-three studies were included in our systematic review. Risk factors associating with sarcopenia were grouped into eight domains: sociodemographic, anthropometric, health behaviors, health condition, biomarkers, early life factors, psychosocial and living environment factors. Fifteen risk factors derived from the twenty-three included studies were eligible for meta-analysis, and ten variables were identified as statistically significant. A risk predictive model was developed for secondary sarcopenia in community setting.

This study provides a fully understanding of sarcopenia across the life-course. Our risk predictive model could facilitate the early identification and prevention of secondary sarcopenia in community setting.

The systematic review and meta-analysis have been registered in PROSPERO(CRD42024536346).

Sarcopenia is recognized as an age-related muscle disease, but there has been no comprehensive analysis of what is different between normal aging and sarcopenia, with an awareness of the worldwide research to date. Therefore, in this study, we used text mining of PubMed articles on sarcopenia and focused our bioinformatics analysis on the items that have been identified.

This study compared gene-level changes in sarcopenia and normal aging to identify sarcopenia-specific gene changes using high-throughput sequencing data. In particular, text mining analysis was used to identify pathways and mechanisms of interest in sarcopenia research, and focus more on these mechanisms.

We identified the pathways common to sarcopenia and normal aging. Interleukin-7 pathways were associated with both conditions. Although changes in phagosome-related pathways were suggested as sarcopenia-specific, no significant changes in phagosome formation, lysosome-related and mitophagy-related gene groups were identified. However, genes in the nicotinamide adenine dinucleotide phosphate oxidase catalytic subunit family were shown to be possibly altered, suggesting the involvement of oxidative stress regulatory pathways.

A comprehensive bioinformatics analysis, complemented by the text mining of the extant literature, suggested that sarcopenia might not be characterized by a failure of autophagy as a whole, but rather, by a disruption of oxidative stress regulation, particularly nicotinamide adenine dinucleotide phosphate oxidase catalytic subunit-related pathways at a subsequent stage of autophagy after phagosome-lysosome fusion. Geriatr Gerontol Int 2025; ••: ••-••.

Adipogenesis is intricately linked to the onset and progression of muscle aging; however, the relevant biomarkers remain unclear. This study sought to identify key genes associated with adipogenesis in the context of muscle aging. Firstly, gene expression profiles from biopsies of the vastus lateralis muscle in both young and elderly population were retrieved from the GEO database. After intersecting with the results of differential gene analysis, weighted gene co-expression network analysis, and sets of adipogenesis-related genes, 29 adipogenesis-related differential expressed genes (ARDEGs) were selected. Connectivity Map (cMAP) analysis identified tamsulosin, fraxidin, and alaproclate as key target compounds. In further, using three machine learning algorithms and the friends analysis, four hub ARDEGs, ESRRA, RXRG, GADD45A, and CEBPB were identified and verified in vivo aged mice muscles. Immune infiltration analysis showed a strong link between several immune cells and hub ARDEGs. In all, these findings suggested that ESRRA, RXRG, GADD45A, and CEBPB could serve as adipogenesis related biomarkers in muscle aging.

Traditional transcriptomic studies often overlook the complex heterogeneity of skeletal muscle, as they typically isolate RNA from mixed muscle fibre and cell populations, resulting in an averaged transcriptomic profile that obscures fibre type-specific differences. This study assessed the potential of the recently developed Xenium platform for high-resolution spatial transcriptomic analysis of human skeletal muscle histological sections. Human vastus lateralis muscle samples from two individuals were analysed using the Xenium platform and Human Multi-Tissue and Cancer Panel targeting 377 genes complemented by staining of successive sections for Myosin Heavy Chain isoforms to differentiate between type 1 and type 2 muscle fibres. Manual segmentation of muscle fibres allowed accurate comparisons of transcript densities across fibre types and subcellular regions, overcoming limitations in the platform's automated segmentation. The analysis revealed higher transcript density in type 1 fibres, particularly in nuclear and perinuclear areas, and identified 191 out of 377 genes with differential expression between muscle fibres and perimysium. Genes such as PROX1, S100A1, LGR5, ACTA2, and LPL exhibited higher expression in type 1 fibres, whereas PEBP4, CAVIN1, GATM, and PVALB in type 2 fibres. We demonstrated that the Xenium platform is capable of high-resolution spatial in situ transcriptomic analysis of skeletal muscle histological sections. This study demonstrates that, with manual segmentation, the Xenium platform effectively performs fibre type-specific transcriptomic analysis, providing new insights into skeletal muscle biology.

Physical activity is essential for maintaining muscle mitochondrial function and aerobic capacity. The molecular mechanisms underlying such protective effects are incompletely understood, in part because it is difficult to separate the effects of disease status and physical activity. We explored the association of human skeletal muscle transcriptomic with four measures of energetics and mitochondria oxidative capacity in healthy individuals.

Using RNA sequencing of vastus lateralis muscle biopsies from 82 GESTALT participants (52 males, aged 22-89 years), we explored gene and splicing variant expression profiles associated with self-reported physical activity, peak oxygen consumption (VO2 peak), muscle oxidative capacity (kPCr) and mitochondrial respiration (Mit-O2 flux). The effect of aging on gene expression was examined in participants with low and high VO2 peak.

The four measures of energetics were negative correlated with age and generally intercorrelated. We identified protein-coding genes associated with four energetic measures adjusting for age, muscle fiber-ratio, sex and batch effect. Mitochondrial pathways were overrepresented across all energetic variables, albeit with little overlap at the gene level. Alternative spliced transcript isoforms associated with energetics were primarily enriched for cytoplasmic ribonucleoprotein granules. The splicing pathway was up-regulated with aging in low but not in high fitness participants, and transcript isoforms detected in the low fitness group pertain to processes such as cell cycle regulation, RNA/protein localization, nuclear transport and catabolism.

A consistent mitochondrial signature emerged across all energetic measures. Alternative splicing was enhanced in older, low fitness participants supporting the energy-splicing axis hypothesis. The identified splicing variants were enriched in pathways involving the accumulation of ribonucleoproteins in cytoplasmic granules, whose function remains unclear. Further research is needed to understand the function of these proteoforms in promoting adaptation to low energy availability.

Age-related muscle wasting, sarcopenia is an extensive loss of muscle mass and strength with age and a major cause of disability and accidents in the elderly. Mechanisms purported to be involved in muscle ageing and sarcopenia are numerous but poorly understood, necessitating deeper study. Hence, we employed high-throughput RNA sequencing to survey the global changes in protein-coding gene expression occurring in skeletal muscle with age. Caloric restriction (CR) is a known prophylactic intervention against sarcopenia. Therefore, total RNA was isolated from the muscle tissue of both rats fed ad libitum and CR rats. RNA-seq data were subjected to Gene Ontology, pathway, co-expression, and interaction network analyses. This revealed the functional pathways most activated by both ageing and CR, as well as the key "hub" proteins involved in their activation.RNA-seq revealed 442 protein-coding genes to be upregulated and 377 to be downregulated in aged muscle, compared to young muscle. Upregulated genes were commonly involved in protein folding and immune responses; meanwhile, downregulated genes were often related to developmental biology. CR was found to suppress 69.7% and rescue 57.8% of the genes found to be upregulated and downregulated in aged muscle, respectively. In addition, CR uniquely upregulated 291 and downregulated 304 protein-coding genes. Hub genes implicated in both ageing and CR included Gc, Plg, Irf7, Ifit3, Usp18, Rsad2, Blm and RT1-A2, whilst those exclusively implicated in CR responses included Alb, Apoa1, Ambp, F2, Apoh, Orm1, Mx1, Oasl2 and Rtp4. Hub genes involved in ageing but unaffected by CR included Fgg, Fga, Fgb and Serpinc1. In conclusion, this comprehensive RNA sequencing study highlights gene expression patterns, hub genes and signalling pathways most affected by ageing in skeletal muscle. This data may provide the initial evidence for several targets for potential future therapeutic interventions against sarcopenia.

Exercise is a potent stimulus for combatting skeletal muscle ageing. To study the effects of exercise on muscle in a preclinical setting, we developed a combined endurance-resistance training stimulus for mice called progressive weighted wheel running (PoWeR). PoWeR improves molecular, biochemical, cellular and functional characteristics of skeletal muscle and promotes aspects of partial epigenetic reprogramming when performed late in life (22-24 months of age). In this investigation, we leveraged pan-mammalian DNA methylome arrays and tandem mass-spectrometry proteomics in skeletal muscle to provide detailed information on late-life PoWeR adaptations in female mice relative to age-matched sedentary controls (n = 7-10 per group). Differential CpG methylation at conserved promoter sites was related to transcriptional regulation genes as well as Nr4a3, Hes1 and Hox genes after PoWeR. Using a holistic method of -omics integration called binding and expression target analysis (BETA), methylome changes were associated with upregulated proteins related to global and mitochondrial translation after PoWeR (P = 0.03). Specifically, BETA implicated methylation control of ribosomal, mitoribosomal, and mitochondrial complex I protein abundance after training. DNA methylation may also influence LACTB, MIB1 and UBR4 protein induction with exercise - all are mechanistically linked to muscle health. Computational cistrome analysis predicted several transcription factors including MYC as regulators of the exercise trained methylome-proteome landscape, corroborating prior late-life PoWeR transcriptome data. Correlating the proteome to muscle mass and fatigue resistance revealed positive relationships with VPS13A and NPL levels, respectively. Our findings expose differential epigenetic and proteomic adaptations associated with translational regulation after PoWeR that could influence skeletal muscle mass and function in aged mice. KEY POINTS: Late-life combined endurance-resistance exercise training from 22-24 months of age in mice is shown to improve molecular, biochemical, cellular and in vivo functional characteristics of skeletal muscle and promote aspects of partial epigenetic reprogramming and epigenetic age mitigation. Integration of DNA CpG 36k methylation arrays using conserved sites (which also contain methylation ageing clock sites) with exploratory proteomics in skeletal muscle extends our prior work and reveals coordinated and widespread regulation of ribosomal, translation initiation, mitochondrial ribosomal (mitoribosomal) and complex I proteins after combined voluntary exercise training in a sizeable cohort of female mice (n = 7-10 per group and analysis). Multi-omics integration predicted epigenetic regulation of serine β-lactamase-like protein (LACTB - linked to tumour resistance in muscle), mind bomb 1 (MIB1 - linked to satellite cell and type 2 fibre maintenance) and ubiquitin protein ligase E3 component N-recognin 4 (UBR4 - linked to muscle protein quality control) after training. Computational cistrome analysis identified MYC as a regulator of the late-life training proteome, in agreement with prior transcriptional analyses. Vacuolar protein sorting 13 homolog A (VPS13A) was positively correlated to muscle mass, and the glycoprotein/glycolipid associated sialylation enzyme N-acetylneuraminate pyruvate lyase (NPL) was associated to in vivo muscle fatigue resistance.

DNA methylation is an important epigenetic mechanism that helps define and maintain cellular functions. It is influenced by many factors, including environmental exposures, genotype, cell type, sex, and aging. Since age is the primary risk factor for developing neurodegenerative diseases, it is important to determine if aging-related DNA methylation is retained when cells are reprogrammed to an induced Pluripotent Stem Cell (iPSC) state. Here, we selected peripheral blood mononuclear cells (PBMCs; n = 99) from a cohort of diverse and healthy individuals enrolled in the Genetic and Epigenetic Signatures of Translational Aging Laboratory Testing (GESTALT) study to convert to iPSCs. After reprogramming we evaluated the resulting iPSCs for DNA methylation signatures to determine if they reflect the confounding factors of age and environmental factors. We used genome-wide DNA methylation arrays in both cell types to show that the epigenetic clock is largely reset to an early methylation age after conversion of PBMCs to iPSCs. We further examined the epigenetic age of each cell type using an Epigenome-wide Association Study (EWAS). Finally, we identified a set of methylation Quantitative Trait Loci (methQTL) in each cell type. Our results show that age-related DNA methylation is largely reset in iPSCs, and each cell type has a unique set of methylation sites that are genetically influenced.

Introduced in 2010, the subdiscipline of gerontologic biostatistics was conceptualized to address the specific challenges of analyzing data from clinical research studies involving older adults. Since then, the evolving technological landscape has led to a proliferation of advancements in biostatistics and other data sciences that have significantly influenced the practice of gerontologic research, including studies beyond the clinic. Data science is the field at the intersection of statistics and computer science, and although the term "data science" was not widely used in 2010, the field has quickly made palpable effects on gerontologic research. In this Review in Depth, we describe multiple advancements of biostatistics and data science that have been particularly impactful. Moreover, we propose the subdiscipline of "gerontologic biostatistics and data science," which subsumes gerontologic biostatistics into a more encompassing practice. Prominent gerontologic biostatistics and data science advancements that we discuss herein include cutting-edge methods in experimental design and causal inference, adaptations of machine learning, the rigorous quantification of deep phenotypic measurement, and analysis of high-dimensional -omics data. We additionally describe the need for integration of information from multiple studies and propose strategies to foster reproducibility, replicability, and open science. Lastly, we provide information on software resources for gerontologic biostatistics and data science practitioners to apply these approaches to their own work and propose areas where further advancement is needed. The methodological topics reviewed here aim to enhance data-rich research on aging and foster the next generation of gerontologic researchers.

Alternative splicing (AS) is a fundamental mechanism contributing to proteome diversity, yet its comprehensive landscape and regulatory dynamics during skeletal muscle development remain largely unexplored. Here, the temporal AS profiles are investigated during myogenesis in five vertebrates, conducting comprehensive profiling across 27 developmental stages in skeletal muscle and encompassing ten tissues in adult pigs. The analysis reveals a pervasive and evolutionarily conserved pattern of alternative exon usage throughout myogenic differentiation, with hundreds of skipped exons (SEs) showing developmental regulation, particularly within skeletal muscle. Notably, this study identifies a muscle-specific SE (exon 15) within the Fxr1 gene, whose AS generates two dynamically expressed isoforms with distinct functions: the isoform without exon 15 (Fxr1E15 -) regulates myoblasts proliferation, while the isoform incorporating exon 15 (Fxr1E15+) promotes myogenic differentiation and fusion. Transcriptome analysis suggests that specifically knocking-down Fxr1E15+ isoform in myoblasts modulates differentiation by influencing gene expression and splicing of specific targets. The increased inclusion of exon 15 during differentiation is mediated by the binding of Rbm24 to the intron. Furthermore, in vivo experiments indicate that the Fxr1E15+ isoform facilitates muscle regeneration. Collectively, these findings provide a comprehensive resource for AS studies in skeletal muscle development, underscoring the diverse functions and regulatory mechanisms governing distinct Fxr1 isoforms in myogenesis.

Sarcopenia is a progressive muscle wasting disorder that severely impacts the quality of life of elderly individuals. Although the natural aging process primarily causes sarcopenia, it can develop in response to other conditions. Because muscle function is influenced by numerous changes that occur with age, the etiology of sarcopenia remains unclear. However, recent characterizations of the aging muscle transcriptional landscape, signaling pathway disruptions, fiber and extracellular matrix compositions, systemic metabolomic and inflammatory responses, mitochondrial function, and neurological inputs offer insights and hope for future treatments. This review will discuss age-related changes in healthy muscle and our current understanding of how this can deteriorate into sarcopenia. As our elderly population continues to grow, we must understand sarcopenia and find treatments that allow individuals to maintain independence and dignity throughout an extended lifespan.

A majority of human genes produce non-protein-coding RNA (ncRNA), and some have roles in development and disease. Neither ncRNA nor human skeletal muscle is ideally studied using short-read sequencing, so we used a customised RNA pipeline and network modelling to study cell-type specific ncRNA responses during muscle growth at scale. We completed five human resistance-training studies (n=144 subjects), identifying 61% who successfully accrued muscle-mass. We produced 288 transcriptome-wide profiles and found 110 ncRNAs linked to muscle growth in vivo, while a transcriptome-driven network model demonstrated interactions via a number of discrete functional pathways and single-cell types. This analysis included established hypertrophy-related ncRNAs, including CYTOR - which was leukocyte-associated (FDR = 4.9 ×10-7). Novel hypertrophy-linked ncRNAs included PPP1CB-DT (myofibril assembly genes, FDR = 8.15 × 10-8), and EEF1A1P24 and TMSB4XP8 (vascular remodelling and angiogenesis genes, FDR = 2.77 × 10-5). We also discovered that hypertrophy lncRNA MYREM shows a specific myonuclear expression pattern in vivo. Our multi-layered analyses established that single-cell-associated ncRNA are identifiable from bulk muscle transcriptomic data and that hypertrophy-linked ncRNA genes mediate their association with muscle growth via multiple cell types and a set of interacting pathways.

To gain a deeper understanding of skeletal muscle function in younger age and aging in elderly, identification of molecular signatures regulating these functions under physiological conditions is needed. Although molecular studies of healthy muscle have been conducted on adults and older subjects, there is a lack of research on infant muscle in terms of combined morphological, transcriptomic and proteomic profiles. To address this gap of knowledge, we performed RNA sequencing (RNA-seq), tandem mass spectrometry (LC-MS/MS), morphometric analysis and assays for mitochondrial maintenance in skeletal muscle biopsies from both, infants aged 4-28 months and adults aged 19-65 years. We identified differently expressed genes (DEGs) and differentially expressed proteins (DEPs) in adults compared to infants. The down-regulated genes in adults were associated with functional terms primarily related to sarcomeres, cellular maintenance, and metabolic, immunological and developmental processes. Thus, our study indicates age-related differences in the molecular signatures and associated functions of healthy skeletal muscle. Moreover, the findings assert that processes previously associated solely with aging are indeed part of development and healthy aging. Hence, combined findings of this study also indicate that age-dependent controls are crucial in muscle disease studies, as otherwise the comparative results may not be reliable.

This study employed a comprehensive single-cell analysis approach to explore the role of cell apoptosis-related genes in muscle aging.

The single-cell RNA sequencing data from the GSE143704 dataset were used to identify distinct cell clusters and assess gene expression patterns related to apoptosis activation. The "limma" package was used to identify hub genes, after which we performed Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis to identify relevant pathways. Additionally, Gene Set Enrichment Analysis(GSEA) and Gene Set Variation Analysis (GSVA) were used to uncover relevant biological pathways. The Receiver Operating Characteristic Curve (ROC) was used to evaluate the diagnostic value of the hub genes. Single-sample Gene Set Enrichment Analysis (ssGSEA) was used to analyze the immune cell infiltration levels.

Single-cell sequencing data from muscle aging patients allowed the identification of various cell types, including epithelial cells, adipocytes, and tissue-resident macrophages. By conducting a differential expression analysis that intersected active and nonactive apoptosis, as well as comparing elderly and young samples, a total of 22 hub genes were identified (p < 0.05). The 22 hub genes have discriminative ability as potential biomarkers for diagnosing muscle aging. The enrichment analysis indicated that these genes were closely associated with diverse pathways, including "response to UV-B" and "extracellular matrix organization" (p < 0.05). Furthermore, GSEA and GSVA indicated that multiple pathways emerged-for example, the "complement and coagulation cascades", "proteasome", "insulin signaling pathway", and "MAPK signaling pathway". Additionally, the analysis of immune cell infiltration revealed positive correlations between most of the hub genes and immune cells.

Our study identified 22 apoptosis-related genes involved in muscle aging and indicated their potential diagnostic value. These findings offer a novel perspective on the pathogenesis of muscle aging and present potential targets for therapeutic interventions.

Sarcopenia is an age-related muscle disease that increases the risk of falls, disabilities, and death. It is associated with increased muscle protein degradation driven by molecular signalling pathways including Akt and FOXO1. This study aims to identify genes, gene interactions, and molecular pathways and processes associated with muscle aging and exercise in older adults that remained undiscovered until now leveraging on an artificial intelligence approach called artificial neural network inference (ANNi).

Four datasets reporting the profile of muscle transcriptome obtained by RNA-seq of young (21-43 years) and older adults (63-79 years) were selected and retrieved from the Gene Expression Omnibus (GEO) data repository. Two datasets contained the transcriptome profiles associated to muscle aging and two the transcriptome linked to resistant exercise in older adults, the latter before and after 6 months of exercise training. Each dataset was individually analysed by ANNi based on a swarm neural network approach integrated into a deep learning model (Intelligent Omics). This allowed us to identify top 200 genes influencing (drivers) or being influenced (targets) by aging or exercise and the strongest interactions between such genes. Downstream gene ontology (GO) analysis of these 200 genes was performed using Metacore (Clarivate™) and the open-source software, Metascape. To confirm the differential expression of the genes showing the strongest interactions, real-time quantitative PCR (RT-qPCR) was employed on human muscle biopsies obtained from eight young (25 ± 4 years) and eight older men (78 ± 7.6 years), partaking in a 6-month resistance exercise training programme.

CHAD, ZDBF2, USP54, and JAK2 were identified as the genes with the strongest interactions predicting aging, while SCFD1, KDM5D, EIF4A2, and NIPAL3 were the main interacting genes associated with long-term exercise in older adults. RT-qPCR confirmed significant upregulation of USP54 (P = 0.005), CHAD (P = 0.03), and ZDBF2 (P = 0.008) in the aging muscle, while exercise-related genes were not differentially expressed (EIF4A2 P = 0.99, NIPAL3 P = 0.94, SCFD1 P = 0.94, and KDM5D P = 0.64). GO analysis related to skeletal muscle aging suggests enrichment of pathways linked to bone development (adj P-value 0.006), immune response (adj P-value <0.001), and apoptosis (adj P-value 0.01). In older exercising adults, these were ECM remodelling (adj P-value <0.001), protein folding (adj P-value <0.001), and proteolysis (adj P-value <0.001).

Using ANNi and RT-qPCR, we identified three strongly interacting genes predicting muscle aging, ZDBF2, USP54, and CHAD. These findings can help to inform the design of nonpharmacological and pharmacological interventions that prevent or mitigate sarcopenia.

A majority of human genes produce non-protein-coding RNA (ncRNA), and some have roles in development and disease. Neither ncRNA nor human skeletal muscle is ideally studied using short-read sequencing, so we used a customized RNA pipeline and network modelling to study cell-type specific ncRNA responses during muscle growth at scale. We completed five human resistance-training studies (n = 144 subjects), identifying 61% who successfully accrued muscle-mass. We produced 288 transcriptome-wide profiles and found 110 ncRNAs linked to muscle growth in vivo, while a transcriptome-driven network model demonstrated interactions via a number of discrete functional pathways and single-cell types. This analysis included established hypertrophy-related ncRNAs, including CYTOR-which was leukocyte-associated (false discovery rate [FDR] = 4.9 × 10-7). Novel hypertrophy-linked ncRNAs included PPP1CB-DT (myofibril assembly genes, FDR = 8.15 × 10-8), and EEF1A1P24 and TMSB4XP8 (vascular remodelling and angiogenesis genes, FDR = 2.77 × 10-5). We also discovered that hypertrophy lncRNA MYREM shows a specific myonuclear expression pattern in vivo. Our multi-layered analyses established that single-cell-associated ncRNA are identifiable from bulk muscle transcriptomic data and that hypertrophy-linked ncRNA genes mediate their association with muscle growth via multiple cell types and a set of interacting pathways.

Marginal vitamin B6 (B6) deficiency is common in various segments worldwide. In a super-aged society, sarcopenia is a major concern and has gained significant research attention focused on healthy aging. To date, the primary interventions for sarcopenia have been physical exercise therapy. Recent evidence suggests that inadequate B6 status is associated with an increased risk of sarcopenia and mortality among older adults. Our previous study showed that B6 supplementation to a marginal B6-deficient diet up-regulated the expression of various exercise-induced genes in the skeletal muscle of rodents. Notably, a supplemental B6-to-B6-deficient diet stimulates satellite cell-mediated myogenesis in rodents, mirroring the effects of physical exercise. These findings suggest the potential role of B6 as an exercise-mimetic nutrient in skeletal muscle. To test this hypothesis, we reviewed relevant literature and compared the roles of B6 and exercise in muscles. Here, we provide several pieces of evidence supporting this hypothesis and discuss the potential mechanisms behind the similarities between the effects of B6 and exercise on muscle. This research, for the first time, provides insight into the exercise-mimetic roles of B6 in skeletal muscle.

(1) Background: Osteoarthritis (OA) is a heterogeneous disorder, and subgroup classification of OA remains elusive. The aim of our study was to identify endotypes of hip OA and investigate the altered pathways in the different endotypes. (2) Methods: Metabolomic profiling and genome-wide genotyping were performed on fasting blood. Transcriptomic profiling was performed on RNA extracted from cartilage samples. Machine learning methods were used to identify endotypes of hip OA. Pathway analysis was used to identify the altered pathways between hip endotypes and controls. GWAS was performed on each of the identified metabolites. Transcriptomic data was used to examine the expression levels of identified genes in cartilage. (3) Results: 180 hip OA patients and 120 OA-free controls were classified into three clusters based on metabolomic data. The combination of arginine, ornithine, and the average value of 7 lysophosphatidylcholines had an area under the curve (AUC) of 0.97 (95% CI: 0.96-0.99) to discriminate hip OA from controls, and the combination of γ-aminobutyric acid, spermine, aconitic acid, and succinic acid had an AUC of 0.96 (95% CI: 0.94-0.99) to distinguish two hip OA endotypes. GWAS identified 236 SNPs to be associated with identified metabolites at GWAS significance level. Pro-inflammatory cytokine levels were significantly different between two endotypes (all p < 0.05). (4) Conclusions: Hip OA could be classified into two distinct molecular endotypes. The primary differences between the two endotypes involve changes in pro-inflammatory factors and energy metabolism.

The sirtuin-1 (SIRT1) gene contains multiple exons that usually undergo alternative splicing. The exclusion of one or more exons causes domain loss in the alternatively spliced isoforms and may change their functions. However, it is not completely established to what extent the loss of a non-catalytic domain could affect its regulatory function. Using muscle cells and SIRT1-knockout cells, we examined the function of the constitutively spliced isoform (SIRT1-v1) versus the alternatively spliced isoforms SIRT1-v2 and SIRT1-v3 that had lost part of the N-terminal region. Our data indicate that partial loss of the N-terminal domains in SIRT1-v2 and SIRT1-v3 attenuated their function. The full-length SIRT1-v1 significantly increased the oxidative phosphorylation and ATP production rate. Furthermore, SIRT1-v1 specifically upregulated the mitochondrial respiratory complex I without affecting the activity of complexes II, III, and IV. Additionally, domain loss affected the regulation of site-specific lysine acetylation in the histone H4 protein, the gene expression of respiratory complex I subunits, and the metabolic balance of oxidative phosphorylation versus glycolysis. Since alternatively spliced isoforms tend to increase with advancing age, the impact of SIRT1 isoforms on mitochondrial respiratory complexes warrants further investigation.

Calorie restriction (CR) and treatment with rapamycin (RM), an inhibitor of the mTORC1 growth-promoting signaling pathway, are known to slow aging and promote health from worms to humans. At the transcriptome and proteome levels, long-term CR and RM treatments have partially overlapping effects, while their impact on protein phosphorylation within cellular signaling pathways have not been compared. Here we measured the phosphoproteomes of soleus, tibialis anterior, triceps brachii and gastrocnemius muscles from adult (10 months) and 30-month-old (aged) mice receiving either a control, a calorie restricted or an RM containing diet from 15 months of age. We reproducibly detected and extensively analyzed a total of 6960 phosphosites, 1415 of which are not represented in standard repositories. We reveal the effect of these interventions on known mTORC1 pathway substrates, with CR displaying greater between-muscle variation than RM. Overall, CR and RM have largely consistent, but quantitatively distinct long-term effects on the phosphoproteome, mitigating age-related changes to different degrees. Our data expands the catalog of protein phosphorylation sites in the mouse, providing important information regarding their tissue-specificity, and revealing the impact of long-term nutrient-sensing pathway inhibition on mouse skeletal muscle.

Sex is a crucial biological variable, and influence of biological sex on the change of gene expression in ageing skeletal muscle has not yet been fully revealed. In this study, the mRNA expression profiles were obtained from the Gene Expression Omnibus database. Key genes were identified by differential expression analysis and weighted gene co-expression network analysis. The gene set enrichment analysis software and Molecular Signatures Database were used for functional and enrichment analysis. A protein-protein interaction network was constructed using STRING and visualized in Cytoscape. The results were compared between female and male subgroups. Differentially expressed genes and enriched pathways in different sex subgroups shared only limited similarities. The pathways enriched in the female subgroup were more similar to the pathways enriched in the older groups without taking sex difference into consideration. The pathways enriched in the female subgroup were more similar to the pathways enriched in the older groups without taking sex difference into consideration. The muscle myosin filament pathways were downregulated in the both aged female and male samples whereas transforming growth factor beta pathway and extracellular matrix-related pathways were upregulated. With muscle ageing, the metabolism-related pathways, protein synthesis and degradation pathways, results of predicted immune cell infiltration, and gene cluster associated with slow-type myofibers drastically different between the female and male subgroups. This finding may indicate that changes in muscle type with ageing may differ between the sexes in vastus lateralis muscle.

Despite their biological importance, the role of stem cells in human aging remains to be elucidated. In this work, we applied a machine learning methodology to GTEx transcriptome data and assigned stemness scores to 17,382 healthy samples from 30 human tissues aged between 20 and 79 years. We found that ~60% of the studied tissues exhibit a significant negative correlation between the subject's age and stemness score. The only significant exception was the uterus, where we observed an increased stemness with age. Moreover, we observed that stemness is positively correlated with cell proliferation and negatively correlated with cellular senescence. Finally, we also observed a trend that hematopoietic stem cells derived from older individuals might have higher stemness scores. In conclusion, we assigned stemness scores to human samples and show evidence of a pan-tissue loss of stemness during human aging, which adds weight to the idea that stem cell deterioration may contribute to human aging.

Exome sequencing is becoming a first-tier clinical diagnostic test for Mendelian diseases, drastically reducing the time and cost of diagnostic odyssey and improving the diagnosis rate. Despite its success, exome sequencing faces practical challenges in assessing the pathogenicity of numerous intronic and synonymous variants, leaving a significant proportion of patients undiagnosed. In this study, a whole-blood transcriptome database was constructed that showed the expression profile of 2981 Online Mendelian Inheritance in Man disease genes in blood samples. Meanwhile, a workflow integrating exome sequencing, blood transcriptome sequencing, and in silico prediction tools to identify and validate splicing-altering intronic or synonymous variants was proposed. Following this pipeline, seven synonymous variants in eight patients were discovered. Of these, the functional evidence of c.981G>A (PIGN), c.1161A>G (ALPL), c.858G>A (ATP6AP2), and c.1011G>T (MTHFR) have not been reported previously. RNA sequencing validation confirmed that these variants induced aberrant splicing, expanding the disease-causing variant spectrum of these genes. Overall, this study shows the feasibility of combining multi-omics data to identify splicing-altering variants, especially the power of RNA sequencing. It also reveals that synonymous variants, which often are overlooked in standard diagnostic approaches, comprise an important portion of unresolved genetic diseases.

Amyotrophic lateral sclerosis is a fatal multisystemic neurodegenerative disease with motor neurons being a primary target. Although progressive weakness is a hallmark feature of amyotrophic lateral sclerosis, there is considerable heterogeneity, including clinical presentation, progression, and the underlying triggers for disease initiation. Based on longitudinal studies with families harboring amyotrophic lateral sclerosis-associated gene mutations, it has become apparent that overt disease is preceded by a prodromal phase, possibly in years, where compensatory mechanisms delay symptom onset. Since 85-90% of amyotrophic lateral sclerosis is sporadic, there is a strong need for identifying biomarkers that can detect this prodromal phase as motor neurons have limited capacity for regeneration. Current Food and Drug Administration-approved therapies work by slowing the degenerative process and are most effective early in the disease. Skeletal muscle, including the neuromuscular junction, manifests abnormalities at the earliest stages of the disease, before motor neuron loss, making it a promising source for identifying biomarkers of the prodromal phase. The accessibility of muscle through biopsy provides a lens into the distal motor system at earlier stages and in real time. The advent of "omics" technology has led to the identification of numerous dysregulated molecules in amyotrophic lateral sclerosis muscle, ranging from coding and non-coding RNAs to proteins and metabolites. This technology has opened the door for identifying biomarkers of disease activity and providing insight into disease mechanisms. A major challenge is correlating the myriad of dysregulated molecules with clinical or histological progression and understanding their relevance to presymptomatic phases of disease. There are two major goals of this review. The first is to summarize some of the biomarkers identified in human amyotrophic lateral sclerosis muscle that have a clinicopathological correlation with disease activity, evidence of a similar dysregulation in the SOD1G93A mouse during presymptomatic stages, and evidence of progressive change during disease progression. The second goal is to review the molecular pathways these biomarkers reflect and their potential role in mitigating or promoting disease progression, and as such, their potential as therapeutic targets in amyotrophic lateral sclerosis.

Common mitochondrial DNA (mtDNA) deletions are large structural variants in the mitochondrial genome that accumulate in metabolically active tissues with age and have been investigated in various diseases. We applied the Splice-Break2 pipeline (designed for high-throughput quantification of mtDNA deletions) to human RNA-Seq datasets and describe the methodological considerations for evaluating common deletions in bulk, single-cell, and spatial transcriptomics datasets. A robust evaluation of 1570 samples from 14 RNA-Seq studies showed: (i) the abundance of some common deletions detected in PCR-amplified mtDNA correlates with levels observed in RNA-Seq data; (ii) RNA-Seq library preparation method has a strong effect on deletion detection; (iii) deletions had a significant, positive correlation with age in brain and muscle; (iv) deletions were enriched in cortical grey matter, specifically in layers 3 and 5; and (v) brain regions with dopaminergic neurons (i.e., substantia nigra, ventral tegmental area, and caudate nucleus) had remarkable enrichment of common mtDNA deletions.

Identification of genes whose expression increases or decreases with age is central to understanding the mechanisms behind aging. Recent scRNA-seq studies have shown that changes in single-cell expression profiles with aging are complex and diverse. In this study, we introduce a novel workflow to detect changes in the distribution of arbitrary monotonic age-related changes in single-cell expression profiles. Since single-cell gene expression profiles can be analyzed as probability distributions, our approach uses information theory to quantify the differences between distributions and employs distance matrices for association analysis. We tested this technique on simulated data and confirmed that potential parameter changes could be detected in a set of probability distributions. Application of the technique to a public scRNA-seq dataset demonstrated its potential utility as a straightforward screening method for identifying aging-related cellular features.

We investigated fast and slow muscle fiber transcriptome exercise dynamics among three groups of men: lifelong exercisers (LLE, n = 8, 74 ± 1 yr), old healthy nonexercisers (OH, n = 9, 75 ± 1 yr), and young exercisers (YE, n = 8, 25 ± 1 yr). On average, LLE had exercised ∼4 day·wk-1 for ∼8 h·wk-1 over 53 ± 2 years. Muscle biopsies were obtained pre- and 4 h postresistance exercise (3 × 10 knee extensions at 70% 1-RM). Fast and slow fiber size and function were assessed preexercise with fast and slow RNA-seq profiles examined pre- and postexercise. LLE fast fiber size was similar to OH, which was ∼30% smaller than YE (P < 0.05) with contractile function variables among groups, resulting in lower power in LLE (P < 0.05). LLE slow fibers were ∼30% larger and more powerful compared with YE and OH (P < 0.05). At the transcriptome level, fast fibers were more responsive to resistance exercise compared with slow fibers among all three cohorts (P < 0.05). Exercise induced a comprehensive biological response in fast fibers (P < 0.05) including transcription, signaling, skeletal muscle cell differentiation, and metabolism with vast differences among the groups. Fast fibers from YE exhibited a growth and metabolic signature, with LLE being primarily metabolic, and OH showing a strong stress-related response. In slow fibers, only LLE exhibited a biological response to exercise (P < 0.05), which was related to ketone and lipid metabolism. The divergent exercise transcriptome signatures provide novel insight into the molecular regulation in fast and slow fibers with age and exercise and suggest that the ∼5% weekly exercise time commitment of the lifelong exercisers provided a powerful investment for fast and slow muscle fiber metabolic health at the molecular level.NEW & NOTEWORTHY This study provides the first insights into fast and slow muscle fiber transcriptome dynamics with lifelong endurance exercise. The fast fibers were more responsive to exercise with divergent transcriptome signatures among young exercisers (growth and metabolic), lifelong exercisers (metabolic), and old healthy nonexercisers (stress). Only lifelong exercisers had a biological response in slow fibers (metabolic). These data provide novel insights into fast and slow muscle fiber health at the molecular level with age and exercise.

Androgen receptor (AR) content has been implicated in the differential response between high and low responders following resistance exercise training (RET). However, the influence of AR expression on acute skeletal muscle damage and whether it may influence the adaptive response to RET in females is poorly understood. Thus, the purpose of this exploratory examination was to 1) investigate changes in AR content during skeletal muscle repair and 2) characterize AR-mediated sex-based differences following RET. A skeletal muscle biopsy from the vastus lateralis was obtained from 26 healthy young men (n = 13) and women (n = 13) at baseline and following 300 eccentric kicks. Subsequently, participants performed 10 weeks of full-body RET and a final muscle biopsy was collected. In the untrained state, AR mRNA expression was associated with paired box protein-7 (PAX7) mRNA in males. For the first time in human skeletal muscle, we quantified AR content in the myofiber and localized to the nucleus where AR has been shown to trigger cellular outcomes related to growth. Upon eccentric damage, nuclear-associated AR (nAR) content increased (p < .05) in males and not females. Males with the greatest increase in cross-sectional area (CSA) post-RET had more (p < .05) nAR content than females with the greatest gain CSA. Collectively, skeletal muscle damage and RET increased AR protein, and both gene and hypertrophy measures revealed sex differences in relation to AR. These findings suggest that AR content but more importantly, nuclear localization, is a factor that differentiates RET-induced hypertrophy between males and females.

Ageing is a complex biological process associated with increased morbidity and mortality. Nine classic, interdependent hallmarks of ageing have been proposed involving genetic and biochemical pathways that collectively influence ageing trajectories and susceptibility to pathology in humans. Ageing skeletal muscle undergoes profound morphological and physiological changes associated with loss of strength, mass, and function, a condition known as sarcopenia. The aetiology of sarcopenia is complex and whilst research in this area is growing rapidly, there is a relative paucity of human studies, particularly in older women. Here, we evaluate how the nine classic hallmarks of ageing: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication contribute to skeletal muscle ageing and the pathophysiology of sarcopenia. We also highlight five novel hallmarks of particular significance to skeletal muscle ageing: inflammation, neural dysfunction, extracellular matrix dysfunction, reduced vascular perfusion, and ionic dyshomeostasis, and discuss how the classic and novel hallmarks are interconnected. Their clinical relevance and translational potential are also considered.

The Study of Muscle, Mobility and Aging (SOMMA) aims to understand the biological basis of many facets of human aging, with a focus on mobility decline, by creating a unique platform of data, tissues, and images.

The multidisciplinary SOMMA team includes 2 clinical centers (University of Pittsburgh and Wake Forest University), a biorepository (Translational Research Institute at Advent Health), and the San Francisco Coordinating Center (California Pacific Medical Center Research Institute). Enrollees were age ≥70 years, able to walk ≥0.6 m/s (4 m); able to complete 400 m walk, free of life-threatening disease, and had no contraindications to magnetic resonance or tissue collection. Participants are followed with 6-month phone contacts and annual in-person exams. At baseline, SOMMA collected biospecimens (muscle and adipose tissue, blood, urine, fecal samples); a variety of questionnaires; physical and cognitive assessments; whole-body imaging (magnetic resonance and computed tomography); accelerometry; and cardiopulmonary exercise testing. Primary outcomes include change in walking speed, change in fitness, and objective mobility disability (able to walk 400 m in 15 minutes and change in 400 m speed). Incident events, including hospitalizations, cancer diagnoses, fractures, and mortality are collected and centrally adjudicated by study physicians.

SOMMA exceeded its goals by enrolling 879 participants, despite being slowed by the COVID-19 pandemic: 59.2% women; mean age 76.3 ± 5.0 years (range 70-94); mean walking speed 1.04 ± 0.20 m/s; 15.8% identify as other than Non-Hispanic White. Over 97% had data for key measurements.

SOMMA will provide the foundation for discoveries in the biology of human aging and mobility.

Modern breeding strategies have resulted in significant differences in muscle mass between indigenous chicken and specialized broiler. However, the molecular regulatory mechanisms that underlie these differences remain elusive. The aim of this study was to identify key genes and regulatory mechanisms underlying differences in breast muscle development between indigenous chicken and specialized broiler.

Two time-series RNA-sequencing profiles of breast muscles were generated from commercial Arbor Acres (AA) broiler (fast-growing) and Chinese indigenous Lushi blue-shelled-egg (LS) chicken (slow-growing) at embryonic days 10, 14, and 18, and post-hatching day 1 and weeks 1, 3, and 5. Principal component analysis of the transcriptome profiles showed that the top four principal components accounted for more than 80% of the total variance in each breed. The developmental axes between the AA and LS chicken overlapped at the embryonic stages but gradually separated at the adult stages. Integrative investigation of differentially-expressed transcripts contained in the top four principal components identified 44 genes that formed a molecular network associated with differences in breast muscle mass between the two breeds. In addition, alternative splicing analysis revealed that genes with multiple isoforms always had one dominant transcript that exhibited a significantly higher expression level than the others. Among the 44 genes, the TNFRSF6B gene, a mediator of signal transduction pathways and cell proliferation, harbored two alternative splicing isoforms, TNFRSF6B-X1 and TNFRSF6B-X2. TNFRSF6B-X1 was the dominant isoform in both breeds before the age of one week. A switching event of the dominant isoform occurred at one week of age, resulting in TNFRSF6B-X2 being the dominant isoform in AA broiler, whereas TNFRSF6B-X1 remained the dominant isoform in LS chicken. Gain-of-function assays demonstrated that both isoforms promoted the proliferation of chicken primary myoblasts, but only TNFRSF6B-X2 augmented the differentiation and intracellular protein content of chicken primary myoblasts.

For the first time, we identified several key genes and dominant isoforms that may be responsible for differences in muscle mass between slow-growing indigenous chicken and fast-growing commercial broiler. These findings provide new insights into the regulatory mechanisms underlying breast muscle development in chicken.

Rhabdomyosarcoma accounts for roughly 1% of adult sarcomas, with pleomorphic rhabdomyosarcoma (PRMS) as the most common subtype. Survival outcomes remain poor for patients with PRMS, and little is known about the molecular drivers of this disease. To better characterize PRMS, we performed a broad array of genomic and immunostaining analyses on 25 patient samples. In terms of gene expression and methylation, PRMS clustered more closely with other complex karyotype sarcomas than with pediatric alveolar and embryonal rhabdomyosarcoma. Immune infiltrate levels in PRMS were among the highest observed in multiple sarcoma types and contrasted with low levels in other rhabdomyosarcoma subtypes. Lower immune infiltrate was associated with complete loss of both TP53 and RB1. This comprehensive characterization of the genetic, epigenetic, and immune landscape of PRMS provides a roadmap for improved prognostications and therapeutic exploration.