A lipid metabolite lipidomics assay for prediction and severity evaluation of rotator cuff injury

Rotator cuff injury can be caused by local inflammation and fibrosis of musculotendinous cuff. Hypercholesterolemia can lead to physiological changes of rotator cuff that resemble rotator cuff injury. However, the relationship between lipid metabolism and rotator cuff injury and its potential pathological mechanism remain unclear. Herein, we aimed to investigate the correlation between the plasma lipidome, rotator cuff injury, and successive fatty infiltration pathology, and hoped to identify biomarkers for predicting higher risk or higher severity rotator cuff injury by assessing metabolic perturbations and dyslipidemia using lipidomics.

We quantitatively analyzed 60 lipids species of seven lipids classes and subclasses from 66 subjects using lipidomics. Subjects were divided into four groups: (1) normal rotator cuff with normal clinical routine serum lipid test results (NN group = 13); (2) normal rotator cuff with abnormal clinical routine serum lipid test results (NA group = 10); (3) rotator cuff tear with normal routine serum lipid test results (RN group = 30); (4) rotator cuff tear with abnormal routine serum lipid test results (RA group = 13). Independent-sample t-tests and Kruskal-Wallis tests were used to compare lipid metabolite levels in serum between different groups in patients with rotator cuff tears. The orthogonal partial least squares-discriminant analysis (OPLS-DA) model was used to verify the ability of five lysophosphatidylcholines (LPCs) to distinguish rotator cuff injuries. In the rotator cuff tear group, magnetic resonance imaging (MRI) was used to classify fatty infiltration according to Goutallier's classification. Kruskal-Wallis tests were used to analyze molecular differences between high-grade (grade 3-4) and low-grade (grade 0-2) fatty infiltration groups. Receiver operator characteristic (ROC) curves were drawn for each diagnostic method via different metabolites. The area under the curve (AUC), cutoff, specificity, sensitivity, and accuracy of each diagnostic criterion were calculated.

Our results showed that some rotator cuff injury patients yielded unique lipidomic profiles. Based on Kruskal-Wallis tests, our results showed significant differences in three lipid molecules, 17:1 Lyso PI, 18:0-22:6 PE, and 18:3 (Cis) PC, among all four groups independent of clinical blood lipid levels. Also, independent of clinical blood lipid levels, two lipid molecules, 22:0 Lyso PC and 24:0 Lyso PC, were significantly different between the two groups based on Independent sample t-tests. Kruskal-Wallis test results showed that in the rotator cuff tear group, two metabolites (24:0 SM and 16:0 ceramide) differed between high-grade and low-grade fatty infiltration. The AUC values for 22:0 Lyso PC, 24:0 Lyso PC, 18:0-22:6 PE, 24:0 SM, and 16:0 ceramide were 0.6036, 0.6757, 0.6712, 0.8333, and 0.8981, respectively.

The results provide insight into how the metabolic mechanisms associated with dyslipidemia impact rotator cuff diseases. Five lipid molecules, 17:1 Lyso PI, 18:0-22:6 PE, 18:3 (Cis) PC, 22:0 Lyso PC, and 24:0 Lyso PC, were closely related to rotator cuff tear based on two statistical analysis methods, independent of clinical routine serum lipid test results, which indicates that lipidomics assays are more sensitive than conventional lipid tests, and more suitable for studying rotator cuff lipid metabolism. In addition, two lipid metabolites, 24:0 SM and 16:0 ceramide, are potentially useful for predicting fatty infiltration severity. Further research with a larger number of samples is needed to verify whether these two metabolites can serve as potential markers of severe fatty infiltration. The findings illuminate how metabolic mechanisms associated with dyslipidemia affect rotator cuff disease.