Plasma proteome profiling of healthy subjects undergoing bed rest reveals unloading‐dependent changes linked to muscle atrophy

Abstract

Abstract Background Inactivity and unloading induce skeletal muscle atrophy, loss of strength and detrimental metabolic effects. Bed rest is a model to study the impact of inactivity on the musculoskeletal system. It not only provides information for bed‐ridden patients care, but it is also a ground‐based spaceflight analogue used to mimic the challenges of long space missions for the human body. In both cases, it would be desirable to develop a panel of biomarkers to monitor muscle atrophy in a minimally invasive way at point of care to limit the onset of muscle loss in a personalized fashion. Methods We applied mass spectrometry‐based proteomics to measure plasma protein abundance changes in response to 10 days of bed rest in 10 young males. To validate the correlation between muscle atrophy and the significant hits emerging from our study, we analysed in parallel, with the same pipeline, a cohort of cancer patients with or without cachexia and age‐matched controls. Our analysis resulted in the quantification of over 500 proteins. Results Unloading affected plasma concentration of proteins of the complement cascade, lipid carriers and proteins derived from tissue leakage. Among the latter, teneurin‐4 increased 1.6‐fold in plasma at bed rest day 10 (BR10) compared with BR0 (6.E9 vs. 4.3E9, P = 0.02) and decreased to 0.6‐fold the initial abundance after 2 days of recovery at normal daily activity (R + 2, 2.7E9, P = 3.3E‐4); the extracellular matrix protein lumican was decreased to 0.7‐fold (1.2E9 vs. 8.5E8, P = 1.5E‐4) at BR10 and remained as low at R + 2. We identified six proteins distinguishing subjects developing unloading‐mediated muscle atrophy (decrease of >4% of quadriceps cross‐sectional area) from those largely maintaining their initial muscle mass. Among them, transthyretin, a thyroid hormone‐binding protein, was significantly less abundant at BR10 in the plasma of subjects with muscle atrophy compared with those with no atrophy (1.6E10 vs. 2.6E10, P = 0.001). Haptoglobin‐related protein was also significantly reduced in the serum of cancer patients with cachexia compared with that of controls. Conclusions Our findings highlight a combination or proteomic changes that can be explored as potential biomarkers of muscle atrophy occurring under different conditions. The panel of significant proteomic differences distinguishing atrophy‐prone and atrophy‐resistant subjects after 10 days of bed rest need to be tested in a larger cohort to validate their potential to predict inactivity‐triggered muscle loss in humans.

Keywords

• Proteomics
• Plasma
• Skeletal muscle
• Bed rest
• Atrophy
• Cachexia