DataSheet_1_Untargeted metabolomics reveals dynamic changes in metabolic profiles of rat supraspinatus tendon at three different time points after diabetes induction.zip

ObjectiveTo investigate the dynamic changes of metabolite composition in rat supraspinatus tendons at different stages of diabetes by untargeted metabolomics analysis.MethodsA total of 80 Sprague–Dawley rats were randomly divided into normal (NG, n = 20) and type 2 diabetes mellitus groups (T2DM, n = 60) and subdivided into three groups according to the duration of diabetes: T2DM-4w, T2DM-12w, and T2DM-24w groups; the duration was calculated from the time point of T2DM rat model establishment. The three comparison groups were set up in this study, T2DM-4w group vs. NG, T2DM-12w group vs. T2DM-4w group, and T2DM-24w group vs. T2DM-12w group. The metabolite profiles of supraspinatus tendon were obtained using tandem mass spectrometry. Metabolomics multivariate statistics were used for metabolic data analysis and differential metabolite (DEM) determination. The intersection of the three comparison groups’ DEMs was defined as key metabolites that changed consistently in the supraspinatus tendon after diabetes induction; then, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed.ResultsT2DM-4w group vs. NG, T2DM-12w group vs. T2DM-4w group, and T2DM-24w group vs. T2DM-12w group detected 94 (86 up-regulated and 8 down-regulated), 36 (13 up-regulated and 23 down-regulated) and 86 (24 up-regulated and 62 down-regulated) DEMs, respectively. Seven key metabolites of sustained changes in the supraspinatus tendon following induction of diabetes include D-Lactic acid, xanthine, O-acetyl-L-carnitine, isoleucylproline, propoxycarbazone, uric acid, and cytidine, which are the first identified biomarkers of the supraspinatus tendon as it progresses through the course of diabetes. The results of KEGG pathway enrichment analysis showed that the main pathway of supraspinatus metabolism affected by diabetes (p < 0.05) was purine metabolism. The results of the KEGG metabolic pathway vs. DEMs correlation network graph revealed that uric acid and xanthine play a role in more metabolic pathways.ConclusionUntargeted metabolomics revealed the dynamic changes of metabolite composition in rat supraspinatus tendons at different stages of diabetes, and the newly discovered seven metabolites, especially uric acid and xanthine, may provide novel research to elucidate the mechanism of diabetes-induced tendinopathy.

本研究旨在通过非靶向代谢组学分析，探究糖尿病不同阶段大鼠肩袖肌腱代谢物组成的动态变化。方法：共选取80只Sprague-Dawley大鼠，随机分为正常组（NG，n=20）和2型糖尿病模型组（T2DM，n=60），并根据糖尿病病程将其细分为T2DM-4w、T2DM-12w和T2DM-24w三个亚组；病程计算自建立T2DM大鼠模型的时间点。本研究设立了三个对比组，分别为T2DM-4w组与NG组、T2DM-12w组与T2DM-4w组、T2DM-24w组与T2DM-12w组。利用串联质谱法获取肩袖肌腱的代谢物谱。采用代谢组学多元统计分析代谢数据并确定差异代谢物（DEM）。将三个对比组DEM的交集定义为糖尿病诱导后肩袖肌腱中持续变化的标志性代谢物；随后，进行京都基因与基因组百科全书（KEGG）通路富集分析。结果：T2DM-4w组与NG组、T2DM-12w组与T2DM-4w组、T2DM-24w组与T2DM-12w组分别检测到94（86个上调和8个下调）、36（13个上调和23个下调）和86（24个上调和62个下调）个DEM。在糖尿病诱导后肩袖肌腱中持续变化的七个关键代谢物包括D-乳酸、黄嘌呤、O-乙酰-L-肉碱、异亮氨酰丙氨酸、丙氧基卡巴踪、尿酸和胞嘧啶，这七种代谢物是首次被鉴定为肩袖肌腱在糖尿病病程中的生物标志物。KEGG通路富集分析结果显示，受糖尿病影响的肩袖代谢主要通路为嘌呤代谢（p < 0.05）。KEGG代谢通路与DEM相关网络图结果显示，尿酸和黄嘌呤在更多代谢通路中发挥作用。结论：非靶向代谢组学揭示了糖尿病不同阶段大鼠肩袖肌腱代谢物组成的动态变化，新发现的七个代谢物，尤其是尿酸和黄嘌呤，可能为阐明糖尿病诱导的肌腱病机制提供新的研究方向。