摘要
糖尿病视网膜病变(diabetic retinopathy,DR)是由糖尿病引起的常见致盲性眼病,也是全球成年人获得性视力丧失的主要原因。DR早期无症状,患者常因视力受损后再就诊而失去最佳治疗时机。传统DR检查方法存在局限性,不利于大规模快速筛查。生物标志物具有特异性和敏感性,能反映疾病所处阶段,寻找潜在生物标志物对DR早期诊断意义重大。本研究基于知识导向策略,从文献中筛选出142个与DR相关的潜在生物标志物,根据其物理化学性质,采用Merck Supelco Discovery HS F5色谱柱(100 mm×2.1 mm,3μm)分离代谢物,建立了基于超高效液相色谱-串联质谱(UHPLC-MS/MS)的正、负离子切换扫描分析的拟靶向分析方法,提高了分析的覆盖度和通量。以8种同位素内标对方法学进行考察,结果显示其在正、负离子模式下线性关系良好,线性范围达3个数量级以上,相关系数(r^(2))均在0.995以上;3个浓度水平下提取回收率为75%~108%,相对标准偏差(RSD)小于13%;在正、负离子模式下,3个浓度水平下所有同位素内标的日内精密度RSD小于5%的个数占总数的91%,日间精密度RSD小于10%的个数占总数的91%,RSD最高不超过16.3%,表明方法精密度良好。对137例血清样本进行分析,筛选出85个差异代谢物,进一步分析发现胆碱和12-羟基二十碳四烯酸作为组合标志物能有效区分DR和无糖尿病视网膜病变的糖尿病患者。本研究开发的基于知识导向策略的拟靶向代谢组学分析方法为DR筛查和诊断提供了参考依据。
Diabetic retinopathy(DR)is a common blinding eye disease caused by diabetes mellitus and is the leading cause of acquired vision loss in adults worldwide.DR is asymptomatic in its early stages,and patients often miss the optimal treatment window by the time they seek medical attention due to vision impairment.Traditional methods used for DR diagnosis have inherent limitations and are not conducive to large-scale rapid screening.Biomarkers can reflect the stage of the disease owing to their specificity and sensitivity,which is crucial for the early diagnosis of DR.In the present study,142 potential literature-based biomarkers associated with DR were included in a knowledgedirected strategy.And metabolites with different physicochemical properties were chromatographically separated using a 100-mm Discovery HS F5 column.A pseudo-targeted metabolomics method based on ultra-high performance liquid chromatography-tandem mass spectrometry(UHPLCMS/MS)that simultaneously scans positive and negative ions was established to improve analysis coverage and throughput.The method was validated using eight representative isotope-labeled internal standards as analytical targets.All isotope-labeled internal standards exhibited satisfactory linearities in both positive-and negative-ionization modes,with linear dynamic ranges spanning over three orders of magnitude and correlation coefficients(r^(2))above 0.995.Extraction recoveries ranged between 75%and 108%at three distinct concentration levels with relative standard deviations(RSDs)below 13%.Notably,91%of the isotope-labeled internal standards exhibited intra-day precision with RSDs of less than 5%across both ionization modes.Similarly,91%of the analytes demonstrated interday precision with RSDs of less than 10%,with all below 16.3%,indicating good method precision.The developed method was used to analyze 137 serum samples,including 40 DR-free patients with diabetes mellitus(NDR)and 97 patients with DR to investigate the practicality of the method.Quality control(QC)samples were used to evaluate the data,which revealed that the instrument was stable during the analytical sequence.Partial least squares discriminant analysis(PLS-DA)models were constructed to identify and differentiate between the metabolic profiles of the DR and NDR groups with the aim of providing a statistical basis for the classification and diagnosis of DR based on metabolic differences observed in the serum samples.The NDR group and DR groups of varying clinical grades were well separated.A total of 85 differential metabolites were identified between NDR and DR groups using nonparametric tests.Further analysis led to the selection of choline and 12-hydroxyeicosatetraenoic acid(12-HETE)as two markers that effectively distinguished the DR and NDR groups.In addition,the markers exhibited a good ability to distinguish between DR and NDR patients when used in combination.The pseudo-targeted metabolomics-based knowledgedirected method developed in this study provides a reference for screening and diagnosing DR.
作者
侯衍青
迟翔宇
杜庭沪
燕增旗
侯带迪
胡春秀
刘月星
刘心昱
许国旺
HOU Yanqing;CHI Xiangyu;DU Tinghu;YAN Zengqi;HOU Daidi;HU Chunxiu;LIU Yuexing;LIU Xinyu;XU Guowang(School of Chemistry,Dalian University of Technology,Dalian 116024,China;Liaoning Province Key laboratory of Metabolomics,Dalian Institute of Chemical Physics,Chinese Academy of Science,Dalian 116023,China;Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine,Shanghai Diabetes Institute,Shanghai 200233,China;Tianjin Weigao Medical Technology Co.,Ltd.,Tianjin 300500,China;China Medical University,Shenyang 110122,China)
出处
《色谱》
北大核心
2026年第3期312-328,共17页
Chinese Journal of Chromatography
基金
国家重点研发计划(2022YFC3401200)。
关键词
糖尿病视网膜病变
代谢组学
超高效液相色谱-串联质谱
疾病标志物
diabetic retinopathy(DR)
metabolomics
ultra-high performance liquid chromatography-tandem mass spectrometry(UHPLC-MS/MS)
disease markers
