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第43卷第3期                           南京医科大学学报(自然科学版)
                  2023年3月                   Journal of Nanjing Medical University(Natural Sciences)     ·371 ·


               ·临床研究·

                系统性红斑狼疮与类风湿关节炎患者血清代谢谱的比较研究



                葛   可,杜 莹,张东东,王 赟,唐小军,冯学兵,王丹丹                     *
                南京大学医学院附属鼓楼医院风湿免疫科,江苏 南京                    210008




               [摘   要] 目的:研究系统性红斑狼疮(systemic lupus erythematosus,SLE)和类风湿关节炎(rheumatoid arthritis,RA)患者的血
                清代谢谱特征,解析两种疾病可能存在的代谢差异。方法:收集SLE、RA患者及健康志愿者的血清样本,通过亲水相互作用超
                高效液相色谱⁃四级杆飞行时间质谱联用技术(hydrophilic interaction and ultra⁃high performance liquid chromatography coupled
                with quadrupole⁃time⁃of⁃flight mass spectrometry,HILIC UHPLC⁃Q⁃TOF MS)对样本进行全谱分析,经正交偏最小二乘判别分析
               (orthogonal partial least squares⁃discriminant analysis,OPLS⁃DA)模型结合单变量统计方法筛选组间差异代谢物,受试者工作特
                征(receiver operating characteristic,ROC)曲线分析候选代谢标志物的诊断效力。通过对差异代谢物进行KEGG通路富集分析
                观察主要差异代谢途径。结果:SLE、RA患者与健康人群的血清代谢谱有明显差异,筛选出5种可能作为疾病潜在诊断靶标的
                差异代谢物,分别是1⁃棕榈酰基⁃2⁃羟基⁃sn⁃甘油⁃3⁃磷酸乙醇胺、牛磺酸、十六烷二酸、(+⁃)12⁃羟基二十碳四烯酸(12⁃hydroxye⁃
                icosantetraenoic acid,12⁃HETE)以及次黄嘌呤。KEGG 通路富集分析发现了逆行内源性大麻素信号等 7 条显著差异代谢通
                路。结论:非靶向代谢组学研究方法可用于比较SLE、RA以及健康人群之间的血清代谢谱差异,分析、筛选出潜在代谢标志物
                及差异代谢通路,有望为上述疾病的诊疗提供新思路。
               [关键词] 非靶向代谢组学;系统性红斑狼疮;类风湿关节炎
               [中图分类号] R593.2                   [文献标志码] A                       [文章编号] 1007⁃4368(2023)03⁃371⁃09
                doi:10.7655/NYDXBNS20230311


                A comparative study on serum metabolic profiles of patients with systemic lupus
                erythematosus and rheumatoid arthritis

                GE Ke,DU Ying,ZHANG Dongdong,WANG Yun,TANG Xiaojun,FENG Xuebing,WANG Dandan        *
                Department of Rheumatology and Immunology,Affiliated Drum Tower Hospital,Medical School of Nanjing
                University,Nanjing 210008,China


               [Abstract] Objective:The current study aims to explore the potential metabolic differences caused by systemic lupus erythematosus
               (SLE)and rheumatoid arthritis(RA),the characteristics of serum metabolic profiles of patients with SLE and RA were analyzed.
                Methods:Serum samples were respectively collected from SLE patients,RA patients,and healthy volunteers. Hydrophilic interaction
                and ultra⁃high performance liquid chromatography coupled with quadrupole⁃time⁃of⁃flight mass spectrometry(HILIC UHPLC⁃Q⁃TOF
                MS)was performed to analyze the full spectrum of these serum samples. The significantly altered metabolites were enriched by
                orthogonal partial least squares⁃discriminant analysis(OPLS⁃DA)models combined with univariate statistical analysis. The receiver
                operating characteristic(ROC)curve was used to evaluate the diagnostic efficacy of the candidate serum metabolite biomarkers. KEGG
                pathway enrichment analysis was conducted to uncover the significantly altered pathways in each disease group. Results:The serum
                profiles showed remarkable differences among the SLE group,RA group,and the control group. Five significantly altered metabolites,
                including 1⁃palmitoyl⁃2⁃hydroxy⁃sn⁃glycero⁃3⁃phosphoethanolamine,taurine,hexadecanedioic acid,(+⁃)12⁃hydroxyeicosantetraenoic
                acid(12 ⁃ HETE)and hypoxanthine,were proposed as potential diagnostic biomarkers. Furthermore,7 KEGG pathways,such as
                retrograde endocannabinoid signaling pathway,significantly altered in the SLE group when compared with the control group or RA
                group. Conclusion:Untargeted metabolomics study could be used to reveal the discrepancy of serum metabolic profiles among SLE
                patients,RA patients,and healthy people. The screened metabolite biomarkers and significantly altered pathways are expected to

               [基金项目] 国家重点研发计划“精准医学研究重点专项”项目(2017YFC0909003)
                ∗
                通信作者(Corresponding author),E⁃mail:dandanwangffd@nju.edu.cn
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