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Several studies have shown that lean mass, in particular muscle mass, is an excellent predictive survival factor in many diseases. A better knowledge of the mechanisms responsible for muscle atrophy and the identification of atrophic process markers are deeply needed for the development of new anti-atrophic therapies. Either as drugs used to treat several medical conditions or as endocrine hormones released in response to many stress situations (e.g., sepsis, cancer, insulinopenia…), glucocorticoids (GC) are recognized to play a major role in skeletal muscle atrophy. Indeed, the inhibition of GC action by a receptor antagonist (RU486) or by muscle-specific invalidation of the GC receptor inhibits the muscle atrophy in these stress situations. Therefore, all these data clearly indicate that GC play a major role in skeletal muscle atrophy observed in several conditions. Emerging evidence has revealed that the skeletal muscle has a secretory function. Human skeletal muscle secretome was first estimated at about 300 proteins by computational analysis and proteomic analysis have recently confirmed these results. Some of these secreted proteins, conceptualized as myokines, can act locally on muscle cells through autocrine/paracrine loops and on surrounding tissues such as muscle blood vessels or can be released into the blood stream to produce systemic effects. One prominent example is interleukin (IL)-6 which is released into circulation by contracting skeletal muscle and can regulate metabolic and inflammatory processes. As IL-6, several other potential myokines have been identified including IL-8, IL-15, insulin-growth factor I (IGF-I), follistatin-like 1 (FSTL1) or fibroblast-growth factor (FGF)-21. Moreover, secreted proteins may also reflected metabolic changes which take place in muscle cells. Indeed, myoblast differentiation is accompanied by dramatic changes in the secreted proteins profile as increased expression of Semaphorins, IGF-I, matrix metalloproteinase (MMP)-2 or Collagens. Thereby, the investigators hypothesized that skeletal muscle atrophy induced by GC is associated with specific alterations of the muscle secretome. The aim of this project is to identify the GC-induced changes in the secretome of human skeletal muscle cells in culture (in vitro approach) and to determine how these changes translate into the circulation of subjects exposed to high concentrations of GC (Cushing's syndrome) (in vivo approach). Characterization of these changes in human subjects should allow to better understand the cellular mechanisms involved in muscle atrophy and might lead to identify circulating biomarkers associated with skeletal muscle atrophy, as telopeptides are for bone tissue.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| patients with Cushing's syndrome | Patients were selected by the PI at the diagnosis. | ||
| control patients | Selected patients are matched for age and sex. |
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| Measure | Description | Time Frame |
|---|---|---|
| Measurement of BMI in kg/m^2 | Measurement of weight in kilograms and height in meters to determine BMI as BMI=weight/height^2 | 1 day (one assessment at diagnosis) |
| Evaluation of quality of life of Cushing's patients | The CushingQoL questionnaire was used to evaluate quality of life of Cushing's patients | 1 day (one assessment at diagnosis) |
| Measure of body lean mass of Cushing's and control patients | Bioelectrical Impedance Vector Analysis (BIA) was used for evaluation of lean and fat mass. | 1 day (one assessment at diagnosis) |
| Muscle strenght measurement of Cushing's and control patients | Evalutation by dynamometer "Jamar type" | 1 day (one assessment at diagnosis) |
| Measurement of Mid-arm muscle circumference (MAMC, cm) | Measurement of triceps skinfold thickness (TSF, in cm), and midarm circumference (MAC, in cm) to determine the MAMC according to the following formula: MAMC= MAC - (Pi x TSF). MAMC is a bedside anthropometric measurement that estimates somatic protein reserve, an early indicator of nutritional depletion. | 1 day (one assessment at diagnosis) |
| Evaluation of daily energy expenditure (DEE) of Cushing's and control patients | Evaluation of DEE by completing the QAPSE questionnaire. | 1 day (one assessment at diagnosis) |
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Inclusion Criteria:
Exclusion Criteria:
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Patients with Cushing's syndrome are caracterised by elevated circulating glucocorticoid levels generally due to a pitiutary or adrenal adenoma. These patients were compared to heathly control patients who are matched for age and sex.
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| Name | Affiliation | Role |
|---|---|---|
| Marie De Barsy, Nurse | Cliniques Universitaires St Luc | Study Chair |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| De Barsy Marie | Brussels | 1200 | Belgium |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 23897689 | Background | Pedersen BK. Muscle as a secretory organ. Compr Physiol. 2013 Jul;3(3):1337-62. doi: 10.1002/cphy.c120033. | |
| 23806868 | Background | Schakman O, Kalista S, Barbe C, Loumaye A, Thissen JP. Glucocorticoid-induced skeletal muscle atrophy. Int J Biochem Cell Biol. 2013 Oct;45(10):2163-72. doi: 10.1016/j.biocel.2013.05.036. Epub 2013 Jun 24. |
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| ID | Term |
|---|---|
| D003480 | Cushing Syndrome |
| ID | Term |
|---|---|
| D000308 | Adrenocortical Hyperfunction |
| D000307 | Adrenal Gland Diseases |
| D004700 | Endocrine System Diseases |
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blood
| 22247067 | Background | Stastna M, Van Eyk JE. Secreted proteins as a fundamental source for biomarker discovery. Proteomics. 2012 Feb;12(4-5):722-35. doi: 10.1002/pmic.201100346. Epub 2012 Jan 19. |
| 20164322 | Result | Baracos VE, Reiman T, Mourtzakis M, Gioulbasanis I, Antoun S. Body composition in patients with non-small cell lung cancer: a contemporary view of cancer cachexia with the use of computed tomography image analysis. Am J Clin Nutr. 2010 Apr;91(4):1133S-1137S. doi: 10.3945/ajcn.2010.28608C. Epub 2010 Feb 17. |
| 16342272 | Result | Bortoluzzi S, Scannapieco P, Cestaro A, Danieli GA, Schiaffino S. Computational reconstruction of the human skeletal muscle secretome. Proteins. 2006 Mar 15;62(3):776-92. doi: 10.1002/prot.20803. |
| 23733748 | Result | Braun TP, Grossberg AJ, Krasnow SM, Levasseur PR, Szumowski M, Zhu XX, Maxson JE, Knoll JG, Barnes AP, Marks DL. Cancer- and endotoxin-induced cachexia require intact glucocorticoid signaling in skeletal muscle. FASEB J. 2013 Sep;27(9):3572-82. doi: 10.1096/fj.13-230375. Epub 2013 Jun 3. |
| 24939997 | Result | Gueugneau M, Coudy-Gandilhon C, Theron L, Meunier B, Barboiron C, Combaret L, Taillandier D, Polge C, Attaix D, Picard B, Verney J, Roche F, Feasson L, Barthelemy JC, Bechet D. Skeletal muscle lipid content and oxidative activity in relation to muscle fiber type in aging and metabolic syndrome. J Gerontol A Biol Sci Med Sci. 2015 May;70(5):566-76. doi: 10.1093/gerona/glu086. Epub 2014 Jun 17. |
| 20631206 | Result | Henningsen J, Rigbolt KT, Blagoev B, Pedersen BK, Kratchmarova I. Dynamics of the skeletal muscle secretome during myoblast differentiation. Mol Cell Proteomics. 2010 Nov;9(11):2482-96. doi: 10.1074/mcp.M110.002113. Epub 2010 Jul 14. |
| 19759515 | Result | Hu Z, Wang H, Lee IH, Du J, Mitch WE. Endogenous glucocorticoids and impaired insulin signaling are both required to stimulate muscle wasting under pathophysiological conditions in mice. J Clin Invest. 2009 Oct;119(10):3059-69. doi: 10.1172/JCI38770. Epub 2009 Sep 14. |
| 23000592 | Result | Le Bihan MC, Bigot A, Jensen SS, Dennis JL, Rogowska-Wrzesinska A, Laine J, Gache V, Furling D, Jensen ON, Voit T, Mouly V, Coulton GR, Butler-Browne G. In-depth analysis of the secretome identifies three major independent secretory pathways in differentiating human myoblasts. J Proteomics. 2012 Dec 21;77:344-56. doi: 10.1016/j.jprot.2012.09.008. Epub 2012 Sep 20. |
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| 21392121 | Result | Neves M Jr, Barreto G, Boobis L, Harris R, Roschel H, Tricoli V, Ugrinowitsch C, Negrao C, Gualano B. Incidence of adverse events associated with percutaneous muscular biopsy among healthy and diseased subjects. Scand J Med Sci Sports. 2012 Apr;22(2):175-8. doi: 10.1111/j.1600-0838.2010.01264.x. Epub 2011 Mar 10. |
| 12044826 | Result | Piccoli A. Patterns of bioelectrical impedance vector analysis: learning from electrocardiography and forgetting electric circuit models. Nutrition. 2002 Jun;18(6):520-1. doi: 10.1016/s0899-9007(02)00771-2. No abstract available. |
| 22739109 | Result | Schakman O, Dehoux M, Bouchuari S, Delaere S, Lause P, Decroly N, Shoelson SE, Thissen JP. Role of IGF-I and the TNFalpha/NF-kappaB pathway in the induction of muscle atrogenes by acute inflammation. Am J Physiol Endocrinol Metab. 2012 Sep 15;303(6):E729-39. doi: 10.1152/ajpendo.00060.2012. Epub 2012 Jun 26. |
| 18426820 | Result | Webb SM, Badia X, Barahona MJ, Colao A, Strasburger CJ, Tabarin A, van Aken MO, Pivonello R, Stalla G, Lamberts SW, Glusman JE. Evaluation of health-related quality of life in patients with Cushing's syndrome with a new questionnaire. Eur J Endocrinol. 2008 May;158(5):623-30. doi: 10.1530/EJE-07-0762. |