{"title":"滑膜液蛋白质组学和血清代谢组学揭示骨关节炎的分子和代谢变化","authors":"P. Yadav","doi":"10.31579/2693-4779/167","DOIUrl":null,"url":null,"abstract":"Background: Osteoarthritis (OA) is a common joint disorder with a complex and multifactorial pathogenesis. Proteomics analysis using two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) enables high-throughput identification of differentially expressed proteins related to OA. However, the etiology, pathophysiology, and early diagnostic markers of OA are still poorly understood. Methods: Synovial fluid protein biomarkers were compared between OA patients and healthy controls. It was fractionated using DEAE cellulose and Sephadex G-200 columns, followed by SDS‒PAGE and 2D-PAGE for visualization and identification. Mass spectrometry and Mascot were used for protein analysis, and serum metabolite profiles were also investigated using 1D 1H CPMG NMR spectra. Multivariate data analysis, including PCA and PLS-DA, was performed to detect metabolic differences between groups. Results: Proteomics analysis revealed differential expression of synovial fluid proteins, such as serine protease inhibitors, complement components, and apolipoproteins, which may be involved in inflammation and cartilage breakdown. Additionally, serum metabolite profiles differed significantly between OA patients and controls, involving amino acid, lipid, glucose, and energy metabolism. The pathway analysis indicated disruption of the metabolic pathways associated with these metabolites. Conclusions: This study provides insights into the molecular and metabolic changes in OA. Protein biomarkers and serum metabolite alterations enhance the understanding of OA pathogenesis and offer potential opportunities for early diagnosis and disease management. Further validation and translation of these findings into clinical applications are needed for improved OA detection and intervention strategies.","PeriodicalId":518029,"journal":{"name":"Clinical Research and Clinical Trials","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2024-02-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Synovial Fluid Proteomics and Serum Metabolomics Reveal Molecular and Metabolic Changes in Osteoarthritis\",\"authors\":\"P. Yadav\",\"doi\":\"10.31579/2693-4779/167\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Background: Osteoarthritis (OA) is a common joint disorder with a complex and multifactorial pathogenesis. Proteomics analysis using two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) enables high-throughput identification of differentially expressed proteins related to OA. However, the etiology, pathophysiology, and early diagnostic markers of OA are still poorly understood. Methods: Synovial fluid protein biomarkers were compared between OA patients and healthy controls. It was fractionated using DEAE cellulose and Sephadex G-200 columns, followed by SDS‒PAGE and 2D-PAGE for visualization and identification. Mass spectrometry and Mascot were used for protein analysis, and serum metabolite profiles were also investigated using 1D 1H CPMG NMR spectra. Multivariate data analysis, including PCA and PLS-DA, was performed to detect metabolic differences between groups. Results: Proteomics analysis revealed differential expression of synovial fluid proteins, such as serine protease inhibitors, complement components, and apolipoproteins, which may be involved in inflammation and cartilage breakdown. Additionally, serum metabolite profiles differed significantly between OA patients and controls, involving amino acid, lipid, glucose, and energy metabolism. The pathway analysis indicated disruption of the metabolic pathways associated with these metabolites. Conclusions: This study provides insights into the molecular and metabolic changes in OA. Protein biomarkers and serum metabolite alterations enhance the understanding of OA pathogenesis and offer potential opportunities for early diagnosis and disease management. Further validation and translation of these findings into clinical applications are needed for improved OA detection and intervention strategies.\",\"PeriodicalId\":518029,\"journal\":{\"name\":\"Clinical Research and Clinical Trials\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-02-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Clinical Research and Clinical Trials\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.31579/2693-4779/167\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Clinical Research and Clinical Trials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.31579/2693-4779/167","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
背景:骨关节炎(OA)是一种常见的关节疾病,其发病机制复杂且多因素。利用二维凝胶电泳(2DE)和质谱(MS)进行蛋白质组学分析,可以高通量鉴定与 OA 有关的差异表达蛋白质。然而,人们对 OA 的病因、病理生理学和早期诊断标志物仍然知之甚少。研究方法比较 OA 患者和健康对照组的滑膜液蛋白质生物标记物。使用 DEAE 纤维素和 Sephadex G-200 柱对其进行分馏,然后用 SDS-PAGE 和 2D-PAGE 进行可视化和鉴定。蛋白质分析使用了质谱和 Mascot,血清代谢物谱也使用了 1D 1H CPMG NMR 光谱进行了研究。进行了多变量数据分析,包括 PCA 和 PLS-DA,以检测组间代谢差异。结果蛋白质组学分析表明,滑液蛋白质的表达存在差异,如丝氨酸蛋白酶抑制剂、补体成分和脂蛋白,它们可能与炎症和软骨破坏有关。此外,OA 患者和对照组之间的血清代谢物谱差异显著,涉及氨基酸、脂质、葡萄糖和能量代谢。通路分析表明,与这些代谢物相关的代谢通路遭到了破坏。结论:这项研究有助于深入了解 OA 的分子和代谢变化。蛋白质生物标志物和血清代谢物的改变加深了人们对 OA 发病机制的了解,并为早期诊断和疾病管理提供了潜在的机会。需要进一步验证这些发现并将其转化为临床应用,以改进 OA 检测和干预策略。
Synovial Fluid Proteomics and Serum Metabolomics Reveal Molecular and Metabolic Changes in Osteoarthritis
Background: Osteoarthritis (OA) is a common joint disorder with a complex and multifactorial pathogenesis. Proteomics analysis using two-dimensional gel electrophoresis (2DE) and mass spectrometry (MS) enables high-throughput identification of differentially expressed proteins related to OA. However, the etiology, pathophysiology, and early diagnostic markers of OA are still poorly understood. Methods: Synovial fluid protein biomarkers were compared between OA patients and healthy controls. It was fractionated using DEAE cellulose and Sephadex G-200 columns, followed by SDS‒PAGE and 2D-PAGE for visualization and identification. Mass spectrometry and Mascot were used for protein analysis, and serum metabolite profiles were also investigated using 1D 1H CPMG NMR spectra. Multivariate data analysis, including PCA and PLS-DA, was performed to detect metabolic differences between groups. Results: Proteomics analysis revealed differential expression of synovial fluid proteins, such as serine protease inhibitors, complement components, and apolipoproteins, which may be involved in inflammation and cartilage breakdown. Additionally, serum metabolite profiles differed significantly between OA patients and controls, involving amino acid, lipid, glucose, and energy metabolism. The pathway analysis indicated disruption of the metabolic pathways associated with these metabolites. Conclusions: This study provides insights into the molecular and metabolic changes in OA. Protein biomarkers and serum metabolite alterations enhance the understanding of OA pathogenesis and offer potential opportunities for early diagnosis and disease management. Further validation and translation of these findings into clinical applications are needed for improved OA detection and intervention strategies.