Original Articles

Proteomic and bioinformatic profiling of the aging mouse heart-diaphragm system

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Received: 7 August 2026
Accepted: 26 August 2026
Published: 2 October 2026
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With advancing age, cardiac weakness and a progressive loss of skeletal muscle mass and contractile strength, is observed in most humans. Although considerable inter-individual differences exist in the degree of age-related muscle wasting, progressive cardiac impairment and sarcopenia play a key role during the natural aging process and form an integral part of the frailty syndrome. Here, we have used comparative bottom-up proteomic profiling to study age-related changes in an established murine model of sarcopenia. The simultaneous assessment of heart and diaphragm muscle aging using peptide mass spectrometry showed that senescence is associated with myofiber degeneration, considerable changes in metabolic processes and increased extracellular matrix deposition. A striking reduction in two mitochondrial enzymes, NAD(P) transhydrogenase and hydroxymethylglutaryl-CoA synthase, was identified by proteomics in the senescent heart and diaphragm muscle, respectively. Bioinformatic analyses revealed abundance changes in distinct protein families and potential alterations in protein-protein interaction patterns. The altered protein profile of the heart-diaphragm system, as determined by comparative discovery proteomics, can be helpful to establish an improved biomarker signature for diagnostic, prognostic and therapeutic monitoring of muscle aging.

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1. Sieck GC, Fogarty MJ. Diaphragm muscle: a pump that can not fail. Physiol Rev 2025;105:2589–2656. DOI: https://doi.org/10.1152/physrev.00043.2024

2. Anderson RH, Razavi R, Taylor AM. Cardiac anatomy revisited. J Anat 2004;205:159–77. DOI: https://doi.org/10.1111/j.0021-8782.2004.00330.x

3. Kelley RC, Ferreira LF. Diaphragm abnormalities in heart failure and aging: mechanisms and integration of cardiovascular and respiratory pathophysiology. Heart Fail Rev 2017;22:191–207. DOI: https://doi.org/10.1007/s10741-016-9549-4

4. Salah HM, Goldberg LR, Molinger J, et al. Diaphragmatic function in cardiovascular disease: JACC review topic of the week. J Am Coll Cardiol 2022;80:1647–59. DOI: https://doi.org/10.1016/j.jacc.2022.08.760

5. Castro C, Delwarde C, Shi Y, Roh J. Geroscience in heart failure: the search for therapeutic targets in the shared pathobiology of human aging and heart failure. J Cardiovasc Aging 2025;5:10.20517/jca.2024.15. DOI: https://doi.org/10.20517/jca.2024.15

6. Sayer AA, Cooper R, Arai H, et al. Sarcopenia. Nat Rev Dis Primers 2024;10:68. DOI: https://doi.org/10.1038/s41572-024-00550-w

7. Picca A, Coelho-Junior HJ, Calvani R, et al. Biomarkers shared by frailty and sarcopenia in older adults: A systematic review and meta-analysis. Ageing Res Rev 2022;73:101530. DOI: https://doi.org/10.1016/j.arr.2021.101530

8. Cruz-Jentoft AJ, Sayer AA. Sarcopenia. Lancet 2019;393:2636–46. DOI: https://doi.org/10.1016/S0140-6736(19)31138-9

9. Petermann-Rocha F, Balntzi V, Gray SR, et al. Global prevalence of sarcopenia and severe sarcopenia: a systematic review and meta-analysis. J Cachexia Sarcopenia Muscle 2022;13:86–99. DOI: https://doi.org/10.1002/jcsm.12783

10. Maccarone MC, Caregnato A, Regazzo G, et al. Effects of the Full-Body in-Bed Gym program on quality of life, pain and risk of sarcopenia in elderly sedentary individuals: preliminary positive results of a Padua prospective observational study. Eur J Transl Myol 2023;33:11780. DOI: https://doi.org/10.4081/ejtm.2023.11780

11. Hassani M, Renzini A, Nguyen L, Coletti D. Changes in physical performance with aging in master athletes and in the general population: an update. Eur J Transl Myol 2026;36:14884. DOI: https://doi.org/10.4081/ejtm.2026.14884

12. Coletti C, Acosta GF, Keslacy S, Coletti D. Exercise-mediated reinnervation of skeletal muscle in elderly people: An update. Eur J Transl Myol 2022;32:10416. DOI: https://doi.org/10.4081/ejtm.2022.10416

13. Bordoni B, Zanier E. Anatomic connections of the diaphragm: influence of respiration on the body system. J Multidiscip Healthc 2013;6:281–91. DOI: https://doi.org/10.2147/JMDH.S45443

14. Kocjan J, Adamek M, Gzik-Zroska B, et al. Network of breathing. Multifunctional role of the diaphragm: a review. Adv Respir Med 2017;85:224–232. DOI: https://doi.org/10.5603/ARM.2017.0037

15. Bordoni B, Morabito B, Escher AR. Diaphragm's role as a systems-connector muscle: a narrative review. Cureus 2025;17:e94679. DOI: https://doi.org/10.7759/cureus.94679

16. Argentieri MA, Xiao S, Bennett D, et al. Proteomic aging clock predicts mortality and risk of common age-related diseases in diverse populations. Nat Med 2024;30:2450–60. DOI: https://doi.org/10.1038/s41591-024-03164-7

17. Dowling P, Gargan S, Swandulla D, Ohlendieck K. Fiber-type shifting in sarcopenia of old age: proteomic profiling of the contractile apparatus of skeletal muscles. Int J Mol Sci 2023;24:2415. DOI: https://doi.org/10.3390/ijms24032415

18. Kedlian VR, Wang Y, Liu T, et al. Human skeletal muscle aging atlas. Nat Aging 2024;4:727–744. DOI: https://doi.org/10.1038/s43587-024-00613-3

19. Basilicata MG, Malavolta M, Marcozzi S, et al. Electron microscopy and multi-omics reveal mitochondrial dysfunction and structural remodeling in the hearts of elderly mice. Aging Cell 2025;24:e70286. DOI: https://doi.org/10.1111/acel.70286

20. Shavlakadze T, Xiong K, Mishra S, et al. Age-related gene expression signatures from limb skeletal muscles and the diaphragm in mice and rats reveal common and species-specific changes. Skelet Muscle 2023;13:11. DOI: https://doi.org/10.1186/s13395-023-00321-3

21. Ersoy U, Kanakis I, Alameddine M, et al. Lifelong dietary protein restriction accelerates skeletal muscle loss and reduces muscle fibre size by impairing proteostasis and mitochondrial homeostasis. Redox Biol 2024;69:102980. DOI: https://doi.org/10.1016/j.redox.2023.102980

22. Soffe Z, Radley-Crabb HG, McMahon C, et al. Effects of loaded voluntary wheel exercise on performance and muscle hypertrophy in young and old male C57Bl/6J mice. Scand J Med Sci Sports 2016;26:172–88. DOI: https://doi.org/10.1111/sms.12416

23. Dowling P, Gargan S, Zweyer M, et al. Proteomic reference map for sarcopenia research: mass spectrometric identification of key muscle proteins located in the sarcomere, cytoskeleton and the extracellular matrix. Eur J Transl Myol 2024;34:12564. DOI: https://doi.org/10.4081/ejtm.2024.12564

24. Gargan S, Dowling P, Zweyer M, et al. Proteomic identification of markers of membrane repair, regeneration and fibrosis in the aged and dystrophic diaphragm. Life (Basel) 2022;12:1679. DOI: https://doi.org/10.3390/life12111679

25. Murphy S, Zweyer M, Henry M, et al. Proteomic analysis of the sarcolemma-enriched fraction from dystrophic mdx-4cv skeletal muscle. J Proteomics 2019;191:212–27. DOI: https://doi.org/10.1016/j.jprot.2018.01.015

26. Dowling P, Gargan S, Zweyer M, et al. Protocol for the bottom-up proteomic analysis of mouse spleen. STAR Protoc 2020;1:100196. DOI: https://doi.org/10.1016/j.xpro.2020.100196

27. Dowling P, Gargan S, Zweyer M, et al. Proteomic reference map for sarcopenia research: mass spectrometric identification of key muscle proteins of organelles, cellular signaling, bioenergetic metabolism and molecular chaperoning. Eur J Transl Myol 2024;34:12565. DOI: https://doi.org/10.4081/ejtm.2024.12565

28. Gargan S, Ohlendieck K. Sample preparation and protein determination for 2D-DIGE proteomics. Methods Mol Biol 2023;2596:325–37. DOI: https://doi.org/10.1007/978-1-0716-2831-7_22

29. Murphy S, Zweyer M, Swandulla D, Ohlendieck K. Bioinformatic analysis of the subproteomic profile of cardiomyopathic tissue. Methods Mol Biol 2023;2596:377–95. DOI: https://doi.org/10.1007/978-1-0716-2831-7_26

30. Ge SX, Jung D, Yao R. ShinyGO: a graphical gene-set enrichment tool for animals and plants. Bioinformatics 2020;36:2628-9. DOI: https://doi.org/10.1093/bioinformatics/btz931

31. Kanehisa M, Furumichi M, Sato Y, et al. KEGG for taxonomy-based analysis of pathways and genomes. Nucleic Acids Res 2023;51:D587–92. DOI: https://doi.org/10.1093/nar/gkac963

32. Thomas PD, Ebert D, Muruganujan A, et al. PANTHER: Making genome-scale phylogenetics accessible to all. Protein Sci 2022;3:8–22. DOI: https://doi.org/10.1002/pro.4218

33. Szklarczyk D, Kirsch R, Koutrouli M, et al. The STRING database in 2023: protein-protein association networks and functional enrichment analyses for any sequenced genome of interest. Nucleic Acids Res 2023;51:D638–46. DOI: https://doi.org/10.1093/nar/gkac1000

34. Francisco A, Figueira TR, Castilho RF. Mitochondrial NAD(P)+ transhydrogenase: from molecular features to physiology and disease. Antioxid Redox Signal 2022;36:864–84. DOI: https://doi.org/10.1089/ars.2021.0111

35. Navarro CDC, Francisco A, Costa EFD, et al. Aging-dependent mitochondrial bioenergetic impairment in the skeletal muscle of NNT-deficient mice. Exp Gerontol 2024;193:112465. DOI: https://doi.org/10.1016/j.exger.2024.112465

36. Rosa FLL, de Souza IIA, Monnerat G, et al. Aging triggers mitochondrial dysfunction in mice. Int J Mol Sci 2023;24:10591. DOI: https://doi.org/10.3390/ijms241310591

37. Chen MS, Lee RT, Garbern JC. Senescence mechanisms and targets in the heart. Cardiovasc Res 2022;118:1173-87. DOI: https://doi.org/10.1093/cvr/cvab161

38. Zheng P, Yan W, Ding Y, et al. Cardiovascular ageing: hallmarks, signaling pathways, diseases and therapeutic targets. Signal Transduct Target Ther 2026;11:142. DOI: https://doi.org/10.1038/s41392-026-02630-7

39. Song Y, Spurlock B, Liu J, Qian L. Cardiac aging in the multi-omics era: high-throughput sequencing insights. Cells 2024;13:1683. DOI: https://doi.org/10.3390/cells13201683

40. Grünert SC, Baumgartner MR, Bouchereau J, et al. Mitochondrial 3-hydroxy-3-methylglutaryl-coenzyme A synthase deficiency: From metabolism to clinical implications. Genet Med 2025;27:101484. DOI: https://doi.org/10.1016/j.gim.2025.101484

41. Wang Y, Ping LF, Bai FY, et al. Hmgcs2 is the hub gene in diabetic cardiomyopathy and is negatively regulated by Hmgcs2, promoting high glucose-induced cardiomyocyte injury. Immun Inflamm Dis 2024;12:e1191. DOI: https://doi.org/10.1002/iid3.1191

42. Herranz N, Gil J. Mechanisms and functions of cellular senescence. J Clin Invest 2018;128:1238–46. DOI: https://doi.org/10.1172/JCI95148

43. Hernandez-Segura A, Nehme J, Demaria M. Hallmarks of cellular senescence. Trends Cell Biol 2018;28:436–453. DOI: https://doi.org/10.1016/j.tcb.2018.02.001

44. López-Otín C, Blasco MA, Partridge L, et al. Hallmarks of aging: an expanding universe. Cell 2023;186:243–78. DOI: https://doi.org/10.1016/j.cell.2022.11.001

45. Takasugi M, Nonaka Y, Takemura K, et al. An atlas of the aging mouse proteome reveals the features of age-related post-transcriptional dysregulation. Nat Commun 2024;15:8520. DOI: https://doi.org/10.1038/s41467-024-52845-x

46. Scifo E, Morsy S, Liu T, et al. Proteomic aging signatures across mouse organs and life stages. EMBO J 2025;44:4631–60. DOI: https://doi.org/10.1038/s44318-025-00509-x

47. Morsy S, Scifo E, Xie K, et al. Deciphering the transcriptomic signatures of aging across organs in mice. Aging Cell 2026;25:e70357. DOI: https://doi.org/10.1111/acel.70357

48. Wang Q, Xu Z, Ding X, et al. Ten mouse organs proteome and metabolome atlas from adult to aging. Genome Med 2025;17:116. DOI: https://doi.org/10.1186/s13073-025-01535-4

Ethics Approval

The German Center for Neurodegenerative Diseases (DZNE) committee approved the presnet study (AZ-2024-254, 26.4.2024). For the German animal welfare protocol, the veterinary office carries out routine monthly inspections of the DZNE in Bonn. Animal facilities are monitored every 3 months according to the guidelines of the Federation of European Laboratory Animal Science Associations (FELASA).

CRediT authorship contribution

Paul Dowling, Dieter Swandulla and Kay Ohlendieck were involved in the conceptualization and initiation of this project, as well as the design of the research strategy. Margit Zweyer, Felix Nebeling and Paul Dowling were involved in the preparation of muscle tissues and performed the biochemical experiments and analyzed the data. Paul Dowling and Kay Ohlendieck performed the mass spectrometric and bioinformatic analysis. All authors were involved in the writing and final editing of the manuscript.

Supporting Agencies

This work was supported by a project grant from the Kathleen Lonsdale Institute for Human Health Research, Maynooth University, and equipment funding was provided under research infrastructure calls by Science Foundation Ireland (SFI-12/RI/2346/3) and Research Ireland (23/RI/1203).

Data Availability Statement

All data generated or analyzed during this study are included in the article. Further inquiries can be directed to the corresponding author.

How to Cite



1.
Dowling P, Zweyer M, Nebeling F, Swandulla D, Ohlendieck K. Proteomic and bioinformatic profiling of the aging mouse heart-diaphragm system. Eur J Transl Myol [Internet]. 2026 Oct. 2 [cited 2026 Oct. 5]; Available from: https://www.pagepressjournals.org/bam/article/view/16061