The metabolic landscape in chronic rotator cuff tear reveals tissue‐region‐specific signatures. Issue 1 (5th December 2021) - Olie, Cyriel Sebastiaan; van Zeijl, René; el Abdellaoui, Salma; Kolk, Arjen; Overbeek, Celeste; Nelissen, Rob G.H.H.; Heijs, Bram; Raz, Vered
Abstract: Background: Degeneration of shoulder muscle tissues often result in tearing, causing pain, disability and loss of independence. Differential muscle involvement patterns have been reported in tears of shoulder muscles, yet the molecules involved in this pathology are poorly understood. The spatial distribution of biomolecules across the affected tissue can be accurately obtained with matrix‐assisted laser desorption/ionization mass spectrometry imaging (MALDI‐MSI). The goal of this pilot study was to decipher the metabolic landscape across shoulder muscle tissues and to identify signatures of degenerated muscles in chronic conditions. Methods: Paired biopsies of two rotator cuff muscles, torn infraspinatus and intact teres minor, together with an intact shoulder muscle, the deltoid, were collected during an open tendon transfer surgery. Five patients, average age 65.2 ± 3.8 years, were selected for spatial metabolic profiling using high‐spatial resolution (MALDI‐TOF) and high‐mass resolution (MALDI‐FTICR) MSI in negative or positive ion mode. Metabolic signatures were identified using data‐driven analysis. Verifications of spatial localization for selected metabolic signatures were carried out using antibody immunohistology. Results: Data‐driven analysis revealed major metabolic differences between intact and degenerated regions across all muscles. The area of degenerated regions, encompassed of fat, inflammation and fibrosis, significantly increased in both rotator cuff muscles, teres minor (27.9%) and infraspinatus (22.8%), compared with the deltoid (8.7%). The intact regions were characterized by 49 features, among which lipids were recognized. Several of the identified lipids were specifically enriched in certain myofiber types. Degenerated regions were specifically marked by the presence of 37 features. Heme was the most abundant metabolite in degenerated regions, whereas Heme oxygenase‐1 (HO‐1), which catabolizes heme, was found in intact regions. Higher HO‐1 levels correlated with lower heme accumulation. Conclusions: Degenerated regions are distinguished from intact regions by their metabolome profile. A muscle‐specific metabolome profile was not identified. The area of tissue degeneration significantly differs between the three examined muscles. Higher HO‐1 levels in intact regions concurred with lower heme levels in degenerated regions. Moreover, HO‐1 levels discriminated between dysfunctional and functional rotator cuff muscles. Additionally, the enrichment of specific lipids in certain myofiber types suggests that lipid metabolism differs between myofiber types. The signature metabolites can open options to develop personalized treatments for chronic shoulder muscles degeneration.