The role of mechanobiology in progression of rotator cuff muscle atrophy and degeneration

Abstract

Rotator cuff (RC) muscles undergo several detrimental changes following mechanical unloading resulting from RC tendon tear. In this review, we highlight the pathological causes and consequences of mechanical alterations at the whole muscle, muscle fiber, and muscle resident cell level as they relate to RC disease progression. In brief, the altered mechanical loads associated with RC tear lead to architectural, structural, and compositional changes at the whole-muscle and muscle fiber level. At the cellular level, these changes equate to direct disruption of mechanobiological signaling, which is exacerbated by mechanically regulated biophysical and biochemical changes to the cellular and extra-cellular environment (also known as the stem cell "niche"). Together, these data have important implications for both pre-clinical models and clinical practice. In pre-clinical models, it is important to recapitulate both the atrophic and degenerative muscle loss found in humans using clinically relevant modes of injury. Clinically, understanding the mechanics and underlying biology of the muscle will impact both surgical decision-making and rehabilitation protocols, as interventions that may be good for atrophic muscle will have a detrimental effect on degenerating muscle, and vice versa. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:546-556, 2018.

Heterogeneous muscle gene expression patterns in patients with massive rotator cuff tears

“…However, the same analysis did not find any significant relationship between fat or fibrous tissue content and any gene family, suggesting that gene expression levels are not necessarily reflective of underlying tissue composition, as is often assumed. At a high level, this suggests that even when accounting for tissue composition, the mechanical and biochemical milieu of the torn RC effect gene expression in multiple cell and tissue types relevant to RC disease progression[ 22 ] independent of their relative quantity.…”

“…While strategies have been developed for deconvolution of gene expression data, they rely on accurate understanding of both sample composition and expression in each individual cell population[ 35 ]. Even in healthy muscle this strategy would be complicated; fluorescence assisted cell sorting (FACS) could isolate and assay the subset of mononuclear cells expected to be found in the muscle, but there is often debate regarding the relationship between cell surface markers and specific cell populations[ 22 , 36 – 38 ] and the isolation process itself may alter expression profiles in the cells of interest. Beyond that, the arguably most important cells, the multi-nucleated muscle fibers, would be lost in this process, as FACS cannot isolate myonuclei.…”

“…Despite the fact that histological parameters other than muscle content are not linear predictors of gene expression, which may be explained by the chronicity of disease[ 23 , 39 ] relative to the phase of active remodeling[ 40 ], these data nonetheless demonstrate the importance of interpreting gene expression data in the context of biopsy composition[ 11 , 14 ]; without definitive evidence for the presence of muscle, there would be no basis for even the broad interpretations presented above. More generally, the disconnect between gene expression and histological findings (where even muscle presence and fat content are only modest predictors of expression levels and sample clustering) further complicates the interpretation of gene expression data not only in this and previous studies[ 7 , 8 ], but throughout the RC disease literature, where complex interactions of the mechanical and biological environment have a significant impact on several of the tissue types central to RC muscle pathology[ 22 ].…”

“…In the same vein, the relatively poor predictive ability of histological parameters outside of muscle content remains a limitation, and points to one of the overarching limitations of studying clinical samples, which is an inherent inability to resolve the time course of disease in the majority of patients[ 41 ]. To adequately address these limitations will require either development of a new animal model or validation of an existing model that adequately recapitulates both the atrophic and degenerative phases of human disease[ 22 ]. Such a model may then be employed to more accurately define the time course of disease, including the relationship between observed changes in gene expression as they relate to sample composition over time.…”

Musculoskeletal mechanobiology: A new era for MechanoMedicine

“…With this goal in mind, we are pleased to introduce this special issue in Musculoskeletal Mechanobiology. This special issue begins with several outstanding reviews that provide updates on the significance of mechanobiology in musculoskeletal research involving cartilage, tendon, muscle and bone, [1][2][3][4][5][6][7][8][9][10] and that span topics from the role of candidate mechanosensors and chemical mediators, 1,5,9,10 in vitro and in vivo models of tissue injury and repair, 3,4 and supporting technologies. 6,7 The majority of original articles following the review papers are related to the mechanobiology of bone and cartilage, [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] tissues whose physical regulation have traditionally garnered intensive research focus, followed by complementary research papers in areas of growing prominence: Ligaments, intervertebral discs, and stem cells.…”