ArticleBMC genomics2014
Proteomics of muscle chronological ageing in post-menopausal women.
Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers, 1 of them a synthesis that pooled it.
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Who cites it
48 citing papers in PubMed, 1 synthesis or guideline pooled it, 77 citations in OpenAlex.
- Gene Ontology (GO)-Driven Inference of Candidate Proteomic Markers Associated with Muscle Atrophy Conditions.Molecules (Basel, Switzerland) · 2022Pooled it
- Aging concomitantly reduces skeletal muscle proteome plasticity and hypertrophic responses to resistance training in male adults.Physiological reports · 2026Article
- Sarcopenia and Muscle Aging: Updated Insights into Molecular Mechanisms and Translational Therapeutics.Endocrinology and metabolism (Seoul, Korea) · 2026Review
- Leveraging mitochondrial stress to improve healthy aging.Sports medicine and health science · 2026Review
- Exercise attenuates stress-related signaling as sensed by higher phosphorylation of small heat shock proteins in skeletal muscle from older individuals.Journal of sport and health science · 2025Article
- A Comprehensive Multiomics Signature of Doxorubicin-Induced Cellular Senescence in the Postmenopausal Human Ovary.Aging cell · 2025Article
- Changing landscape of hematopoietic and mesenchymal cells and their interactions during aging and in age-related skeletal pathologies.Mechanisms of ageing and development · 2025Review
- The skeletal muscle proteomic determinants of neuromuscular function in young and older women following 8 weeks of resistance training.Experimental physiology · 2025Article
- Review
- Molecular composition of skeletal muscle in infants and adults: a comparative proteomic and transcriptomic study.Scientific reports · 2024Article
- Proteomic reference map for sarcopenia research: mass spectrometric identification of key muscle proteins of organelles, cellular signaling, bioenergetic metabolism and molecular chaperoning.European journal of translational myology · 2024Article
- Proteomic reference map for sarcopenia research: mass spectrometric identification of key muscle proteins located in the sarcomere, cytoskeleton and the extracellular matrix.European journal of translational myology · 2024Article
- Mass Spectrometry-Based Proteomic Technology and Its Application to Study Skeletal Muscle Cell Biology.Cells · 2023Review
- Article
- Sarcoplasmic Reticulum CaCells · 2023Review
- Fiber-Type Shifting in Sarcopenia of Old Age: Proteomic Profiling of the Contractile Apparatus of Skeletal Muscles.International journal of molecular sciences · 2023Review
- Aged gastrocnemius muscle of mice positively responds to a late onset adapted physical training.Frontiers in cell and developmental biology · 2023Article
- Exercised accelerated the production of muscle-derived kynurenic acid in skeletal muscle and alleviated the postmenopausal osteoporosis through the Gpr35/NFκB p65 pathway.Journal of orthopaedic translation · 2022Article
- A Single Bout of Ultra-Endurance Exercise Reveals Early Signs of Muscle Aging in Master Athletes.International journal of molecular sciences · 2022Article
- Unveiling genetic variants for age-related sarcopenia by conducting a genome-wide association study on Korean cohorts.Scientific reports · 2022Article
Corrections and comments
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Authors and funding
12 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMuscle ageing contributes to both loss of functional autonomy and increased morbidity. Muscle atrophy accelerates after 50 years of age, but the mechanisms involved are complex and likely result from the alteration of a variety of interrelated functions. In order to better understand the molecular mechanisms underlying muscle chronological ageing in human, we have undertaken a top-down differential proteomic approach to identify novel biomarkers after the fifth decade of age.
resultsMuscle samples were compared between adult (56 years) and old (78 years) post-menopausal women. In addition to total muscle extracts, low-ionic strength extracts were investigated to remove high abundance myofibrillar proteins and improve the detection of low abundance proteins. Two-dimensional gel electrophoreses with overlapping IPGs were used to improve the separation of muscle proteins. Overall, 1919 protein spots were matched between all individuals, 95 were differentially expressed and identified by mass spectrometry, and they corresponded to 67 different proteins. Our results suggested important modifications in cytosolic, mitochondrial and lipid energy metabolism, which may relate to dysfunctions in old muscle force generation. A fraction of the differentially expressed proteins were linked to the sarcomere and cytoskeleton (myosin light-chains, troponin T, ankyrin repeat domain-containing protein-2, vinculin, four and a half LIM domain protein-3), which may account for alterations in contractile properties. In line with muscle contraction, we also identified proteins related to calcium signal transduction (calsequestrin-1, sarcalumenin, myozenin-1, annexins). Muscle ageing was further characterized by the differential regulation of several proteins implicated in cytoprotection (catalase, peroxiredoxins), ion homeostasis (carbonic anhydrases, selenium-binding protein 1) and detoxification (aldo-keto reductases, aldehyde dehydrogenases). Notably, many of the differentially expressed proteins were central for proteostasis, including heat shock proteins and proteins involved in proteolysis (valosin-containing protein, proteasome subunit beta type-4, mitochondrial elongation factor-Tu).
conclusionsThis study describes the most extensive proteomic analysis of muscle ageing in humans, and identified 34 new potential biomarkers. None of them were previously recognized as differentially expressed in old muscles, and each may represent a novel starting point to elucidate the mechanisms of muscle chronological ageing in humans.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.