The influence of biological sex in human skeletal muscle transcriptome during ageing

Biogerontology - Trang 1-18 - 2023
Xiaoyu Huang1, Mao Chen1, Ya Xiao1, Fangyi Zhu1, Liying Chen1, Xiaoyu Tian1, Li Hong1,2
1Department of Gynecology and Obstetrics, Renmin Hospital of Wuhan University, Wuhan, China
2Pelvic Floor Research Centre of Hubei Province, Renmin Hospital of Wuhan University, Wuhan, China

Tóm tắt

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.

Tài liệu tham khảo

Bader GD, Hogue CW (2003) An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinform 4:2 Badrov MB, Keir DA, Notarius CF, O’Donnell E, Millar PJ, Kimmerly DS, Shoemaker JK, Floras JS (2022) Influence of sex and age on the relationship between aerobic fitness and muscle sympathetic nerve activity in healthy adults. Am J Physiol Heart Circ Physiol 323(5):H934–H940 Baldwin KM, Haddad F (2001) Effects of different activity and inactivity paradigms on myosin heavy chain gene expression in striated muscle. J Appl Physiol (1985) 90(1):345–357 Blaauw B, Schiaffino S, Reggiani C (2013) Mechanisms modulating skeletal muscle phenotype. Compr Physiol 3(4):1645–1687 Boca SM, Leek JT (2018) A direct approach to estimating false discovery rates conditional on covariates. PeerJ 6:e6035 Bodine SC, Baehr LM (2014) Skeletal muscle atrophy and the E3 ubiquitin ligases MuRF1 and MAFbx/atrogin-1. Am J Physiol Endocrinol Metab 307(6):E469-484 Boyer JG, Prasad V, Song T, Lee D, Fu X, Grimes KM, Sargent MA, Sadayappan S, Molkentin JD (2019) ERK1/2 signaling induces skeletal muscle slow fiber-type switching and reduces muscular dystrophy disease severity. JCI Insight 5(10):e127356 El Assar M, Alvarez-Bustos A, Sosa P, Angulo J, Rodriguez-Manas L (2022) Effect of physical activity/exercise on oxidative stress and inflammation in muscle and vascular aging. Int J Mol Sci 23(15):8713 Chakraborty S, Datta S, Datta S (2012) Surrogate variable analysis using partial least squares (SVA-PLS) in gene expression studies. Bioinformatics 28(6):799–806 Cheng TH, Shih NL, Chen CH, Lin H, Liu JC, Chao HH, Liou JY, Chen YL, Tsai HW, Chen YS et al (2005) Role of mitogen-activated protein kinase pathway in reactive oxygen species-mediated endothelin-1-induced beta-myosin heavy chain gene expression and cardiomyocyte hypertrophy. J Biomed Sci 12(1):123–133 Chin CH, Chen SH, Wu HH, Ho CW, Ko MT, Lin CY (2014) cytoHubba: identifying hub objects and sub-networks from complex interactome. BMC Syst Biol 8(Suppl 4):S11 Cruz-Jentoft AJ, Bahat G, Bauer J, Boirie Y, Bruyere O, Cederholm T, Cooper C, Landi F, Rolland Y, Sayer AA et al (2019) Sarcopenia: revised european consensus on definition and diagnosis. Age Ageing 48(4):601 Daugaard JR, Nielsen JN, Kristiansen S, Andersen JL, Hargreaves M, Richter EA (2000) Fiber type-specific expression of GLUT4 in human skeletal muscle: influence of exercise training. Diabetes 49(7):1092–1095 Dennison EM, Sayer AA, Cooper C (2017) Epidemiology of sarcopenia and insight into possible therapeutic targets. Nat Rev Rheumatol 13(6):340–347 Dos Santos M, Backer S, Saintpierre B, Izac B, Andrieu M, Letourneur F, Relaix F, Sotiropoulos A, Maire P (2020) Single-nucleus RNA-seq and FISH identify coordinated transcriptional activity in mammalian myofibers. Nat Commun 11(1):5102 Dos Santos M, Backer S, Aurade F, Wong MM, Wurmser M, Pierre R, Langa F, Do Cruzeiro M, Schmitt A, Concordet JP et al (2022) A fast myosin super enhancer dictates muscle fiber phenotype through competitive interactions with myosin genes. Nat Commun 13(1):1039 Du J, Yuan Z, Ma Z, Song J, Xie X, Chen Y (2014) KEGG-PATH: Kyoto encyclopedia of genes and genomes-based pathway analysis using a path analysis model. Mol Biosyst 10(9):2441–2447 Englund DA, Sakamoto AE, Fritsche CM, Heeren AA, Zhang X, Kotajarvi BR, Lecy DR, Yousefzadeh MJ, Schafer MJ, White TA et al (2021) Exercise reduces circulating biomarkers of cellular senescence in humans. Aging Cell 20(7):e13415 Gaulton N, Wakelin G, Young LV, Wotherspoon S, Kamal M, Parise G, Nederveen JP, Holwerda A, Verdijk LB, van Loon LJC et al (2022) Twist2-expressing cells reside in human skeletal muscle and are responsive to aging and resistance exercise training. FASEB J 36(12):e22642 Gene Ontology C (2021) The gene ontology resource: enriching a GOld mine. Nucleic Acids Res 49(D1):D325–D334 Gillespie M, Jassal B, Stephan R, Milacic M, Rothfels K, Senff-Ribeiro A, Griss J, Sevilla C, Matthews L, Gong C et al (2022) The reactome pathway knowledgebase 2022. Nucleic Acids Res 50(D1):D687–D692 Han H, Cho JW, Lee S, Yun A, Kim H, Bae D, Yang S, Kim CY, Lee M, Kim E et al (2018) TRRUST v2: an expanded reference database of human and mouse transcriptional regulatory interactions. Nucleic Acids Res 46(D1):D380–D386 Hung YL, Sato A, Takino Y, Ishigami A, Machida S (2022) Influence of oestrogen on satellite cells and myonuclear domain size in skeletal muscles following resistance exercise. J Cachexia Sarcopenia Muscle 13(5):2525–2536 Hwang J, Park S (2022) Sex differences of sarcopenia in an elderly asian population: the prevalence and risk factors. Int J Environ Res Public Health 19(19):11980 Landi F, Liperoti R, Fusco D, Mastropaolo S, Quattrociocchi D, Proia A, Russo A, Bernabei R, Onder G (2012) Prevalence and risk factors of sarcopenia among nursing home older residents. J Gerontol A Biol Sci Med Sci 67(1):48–55 Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinform 9:559 Lee WJ, Liu LK, Peng LN, Lin MH, Chen LK, Group IR (2013) Comparisons of sarcopenia defined by IWGS and EWGSOP criteria among older people: results from the I-Lan longitudinal aging study. J Am Med Dir Assoc 14(7):521–527 Lee LA, Barrick SK, Meller A, Walklate J, Lotthammer JM, Tay JW, Stump WT, Bowman G, Geeves MA, Greenberg MJ et al (2023) Functional divergence of the sarcomeric myosin, MYH7b, supports species-specific biological roles. J Biol Chem 299(1):102657 Liberzon A, Birger C, Thorvaldsdottir H, Ghandi M, Mesirov JP, Tamayo P (2015) The molecular signatures database (MSigDB) hallmark gene set collection. Cell Syst 1(6):417–425 Lindholm ME, Huss M, Solnestam BW, Kjellqvist S, Lundeberg J, Sundberg CJ (2014) The human skeletal muscle transcriptome: sex differences, alternative splicing, and tissue homogeneity assessed with RNA sequencing. FASEB J 28(10):4571–4581 Love MI, Huber W, Anders S (2014) Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2. Genome Biol 15(12):550 Mahdy MAA (2019) Skeletal muscle fibrosis: an overview. Cell Tissue Res 375(3):575–588 Marzetti E, Calvani R, Tosato M, Cesari M, Di Bari M, Cherubini A, Collamati A, D’Angelo E, Pahor M, Bernabei R et al (2017) Sarcopenia: an overview. Aging Clin Exp Res 29(1):11–17 Melouane A, Ghanemi A, Aube S, Yoshioka M, St-Amand J (2018) Differential gene expression analysis in ageing muscle and drug discovery perspectives. Ageing Res Rev 41:53–63 Mi H, Muruganujan A, Ebert D, Huang X, Thomas PD (2019) PANTHER version 14: more genomes, a new PANTHER GO-slim and improvements in enrichment analysis tools. Nucleic Acids Res 47(D1):D419–D426 Murach KA, Dimet-Wiley AL, Wen Y, Brightwell CR, Latham CM, Dungan CM, Fry CS, Watowich SJ (2022) Late-life exercise mitigates skeletal muscle epigenetic aging. Aging Cell 21(1):e13527 Newman AM, Liu CL, Green MR, Gentles AJ, Feng W, Xu Y, Hoang CD, Diehn M, Alizadeh AA (2015) Robust enumeration of cell subsets from tissue expression profiles. Nat Methods 12(5):453–457 Patel HP, Syddall HE, Jameson K, Robinson S, Denison H, Roberts HC, Edwards M, Dennison E, Cooper C, Aihie Sayer A (2013) Prevalence of sarcopenia in community-dwelling older people in the UK using the european working group on sarcopenia in older people (EWGSOP) definition: findings from the Hertfordshire Cohort Study (HCS). Age Ageing 42(3):378–384 Peterson SJ, Braunschweig CA (2016) Prevalence of sarcopenia and associated outcomes in the clinical setting. Nutr Clin Pract 31(1):40–48 Phung LA, Karvinen SM, Colson BA, Thomas DD, Lowe DA (2018) Age affects myosin relaxation states in skeletal muscle fibers of female but not male mice. PLoS One 13(9):e0199062 Raue U, Trappe TA, Estrem ST, Qian HR, Helvering LM, Smith RC, Trappe S (2012) Transcriptome signature of resistance exercise adaptations: mixed muscle and fiber type specific profiles in young and old adults. J Appl Physiol (1985) 112(10):1625–1636 Reidy PT, Lindsay CC, McKenzie AI, Fry CS, Supiano MA, Marcus RL, LaStayo PC, Drummond MJ (2018) Aging-related effects of bed rest followed by eccentric exercise rehabilitation on skeletal muscle macrophages and insulin sensitivity. Exp Gerontol 107:37–49 Roth RJ, Le AM, Zhang L, Kahn M, Samuel VT, Shulman GI, Bennett AM (2009) MAPK phosphatase-1 facilitates the loss of oxidative myofibers associated with obesity in mice. J Clin Invest 119(12):3817–3829 Sayer AA, Cruz-Jentoft A (2022) Sarcopenia definition, diagnosis and treatment: consensus is growing. Age Ageing 51(10):afac220 Schiaffino S, Dyar KA, Ciciliot S, Blaauw B, Sandri M (2013) Mechanisms regulating skeletal muscle growth and atrophy. FEBS J 280(17):4294–4314 Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504 Sillanpaa E, Heikkinen A, Kankaanpaa A, Paavilainen A, Kujala UM, Tammelin TH, Kovanen V, Sipila S, Pietilainen KH, Kaprio J et al (2021) Blood and skeletal muscle ageing determined by epigenetic clocks and their associations with physical activity and functioning. Clin Epigenetics 13(1):110 Sorensen JR, Kaluhiokalani JP, Hafen PS, Deyhle MR, Parcell AC, Hyldahl RD (2019) An altered response in macrophage phenotype following damage in aged human skeletal muscle: implications for skeletal muscle repair. FASEB J 33(9):10353–10368 Stelzer G, Rosen N, Plaschkes I, Zimmerman S, Twik M, Fishilevich S, Stein TI, Nudel R, Lieder I, Mazor Y et al (2016) The GeneCards suite: from gene data mining to disease genome sequence analyses. Curr Protoc Bioinform 54:1 30 31-31 30 33 Subramanian A, Tamayo P, Mootha VK, Mukherjee S, Ebert BL, Gillette MA, Paulovich A, Pomeroy SL, Golub TR, Lander ES et al (2005) Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102(43):15545–15550 Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, Doncheva NT, Legeay M, Fang T, Bork P et al (2021) The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res 49(D1):D605–D612 Torrens-Mas M, Navas-Enamorado C, Wahl D, Sanchez-Polo A, Picca A, Oliver J, Roca P, Gonzalez-Freire M (2022) Sex specific differences in response to calorie restriction in skeletal muscle of young rats. Nutrients 14(21):4535 Trott DW, Islam MT, Buckley DJ, Donato AJ, Dutson T, Sorensen ES, Cai J, Gogulamudi VR, Phuong TTT, Lesniewski LA (2021) T lymphocyte depletion ameliorates age-related metabolic impairments in mice. Geroscience 43(3):1331–1347 Tumasian RA, Harish A, Kundu G, Yang JH, Ubaida-Mohien C, Gonzalez-Freire M, Kaileh M, Zukley LM, Chia CW, Lyashkov A et al (2021) Skeletal muscle transcriptome in healthy aging. Nat Commun 12(1):2014 Ubaida-Mohien C, Lyashkov A, Gonzalez-Freire M, Tharakan R, Shardell M, Moaddel R, Semba RD, Chia CW, Gorospe M, Sen R et al: Discovery proteomics in aging human skeletal muscle finds change in spliceosome, immunity, proteostasis and mitochondria. Elife 2019, 8. https://doi.org/10.7554/eLife.49874 Verdijk LB, Snijders T, Drost M, Delhaas T, Kadi F, van Loon LJ (2014) Satellite cells in human skeletal muscle; from birth to old age. Age (Dordr) 36(2):545–547 Wang Y, Wehling-Henricks M, Samengo G, Tidball JG (2015) Increases of M2a macrophages and fibrosis in aging muscle are influenced by bone marrow aging and negatively regulated by muscle-derived nitric oxide. Aging Cell 14(4):678–688 Yoshimoto Y, Ikemoto-Uezumi M, Hitachi K, Fukada SI, Uezumi A (2020) Methods for accurate assessment of myofiber maturity during skeletal muscle regeneration. Front Cell Dev Biol 8:267 Yu G, Wang LG, Han Y, He QY (2012) clusterProfiler: an R package for comparing biological themes among gene clusters. OMICS 16(5):284–287 Zahn JM, Sonu R, Vogel H, Crane E, Mazan-Mamczarz K, Rabkin R, Davis RW, Becker KG, Owen AB, Kim SK (2006) Transcriptional profiling of aging in human muscle reveals a common aging signature. PLoS Genet 2(7):e115 Zhao Y, Chen C, Pan J, Lam SM, Shui G, Yang S, Wu T, Yang N, Tao C, Zhao J et al (2023) Adipocyte Rnf20 ablation increases the fast-twitch fibers of skeletal muscle via lysophosphatidylcholine 16:0. Cell Mol Life Sci 80(9):243 Zhou Y, Zhou B, Pache L, Chang M, Khodabakhshi AH, Tanaseichuk O, Benner C, Chanda SK (2019) Metascape provides a biologist-oriented resource for the analysis of systems-level datasets. Nat Commun 10(1):1523