Title |
Molecular signatures of age-associated chronic degeneration of shoulder muscles
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Published in |
Oncotarget, February 2016
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DOI | 10.18632/oncotarget.7382 |
Pubmed ID | |
Authors |
Yotam Raz, Jan Ferdinand Henseler, Arjen Kolk, Zuotian Tatum, Niels Kuipers Groosjohan, Nisha E. Verwey, Wibowo Arindrarto, Szymon M. Kielbasa, Jochem Nagels, Peter A. C. 't Hoen, Rob G. H. H. Nelissen, Vered Raz |
Abstract |
Chronic muscle diseases are highly prevalent in the elderly causing severe mobility limitations, pain and frailty. The intrinsic molecular mechanisms are poorly understood due to multifactorial causes, slow progression with age and variations between individuals. Understanding the underlying molecular mechanisms could lead to new treatment options which are currently limited. Shoulder complaints are highly common in the elderly, and therefore, muscles of the shoulder's rotator cuff could be considered as a model for chronic age-associated muscle degeneration. Diseased shoulder muscles were characterized by muscle atrophy and fatty infiltration compared with unaffected shoulder muscles. We confirmed fatty infiltration using histochemical analysis. Additionally, fibrosis and loss of contractile myosin expression were found in diseased muscles. Most cellular features, including proliferation rate, apoptosis and cell senescence, remained unchanged and genome-wide molecular signatures were predominantly similar between diseased and intact muscles. However, we found down-regulation of a small subset of muscle function genes, and up-regulation of extracellular region genes. Myogenesis was defected in muscle cell culture from diseased muscles but was restored by elevating MyoD levels. We suggest that impaired muscle functionality in a specific environment of thickened extra-cellular matrix is crucial for the development of chronic age-associated muscle degeneration. |
X Demographics
Geographical breakdown
Country | Count | As % |
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Unknown | 1 | 100% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Unknown | 46 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
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Student > Ph. D. Student | 8 | 17% |
Researcher | 5 | 11% |
Student > Bachelor | 5 | 11% |
Student > Master | 5 | 11% |
Student > Postgraduate | 4 | 9% |
Other | 10 | 22% |
Unknown | 9 | 20% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 14 | 30% |
Nursing and Health Professions | 8 | 17% |
Biochemistry, Genetics and Molecular Biology | 3 | 7% |
Engineering | 3 | 7% |
Sports and Recreations | 2 | 4% |
Other | 2 | 4% |
Unknown | 14 | 30% |