Pan Lingyun, Lin Yu, Zhu Jianhui, Zhang Jie, Tan Zhijing, Lubman David M
Department of Surgery, University of Michigan Medical Center, Ann Arbor, MI 48109, United States.
Experiment Center for Science & Technology, Shanghai University of Traditional Chinese Medicine, Shanghai 201203, China.
J Proteomics Bioinform. 2022;15(5). Epub 2022 Jun 27.
Glycopeptide analysis by mass spectrometry may provide an important opportunity in discovery of biomarkers to aid in early detection of Alzheimer's Disease (AD). In this work, we have used a NanoLC-Stepped-HCD-DDA-MS/MS platform and a NanoLC-Stepped-HCD-PRM-MS platform for large-scale screening and quantification of novel N-glycopeptide biomarkers for early detection of AD in patient serum. N-glycopeptides were retrieved from 10 μL of serum in patients with mild cognitive impairment (MCI, a prodromal phase of AD) and normal controls, respectively, after trypsin digestion, glycopeptide enrichment, fractionation, and NanoLC-Stepped-HCD-DDA-MS/MS or NanoLC-Stepped-HCD-PRM-MS analysis. Using a combination of Byonic, Byologic and Skyline softwares, we were able to accomplish both identification and label-free quantitation of site-specific N-glycopeptides between MCI and normal controls. Differential quantitation analysis by Byologic showed that 29 N-glycopeptides derived from 16 glycoproteins were significantly changed in MCI compared to normal controls. Further, HCD-PRM-MS quantitative analysis of the selected N-glycopeptide candidates confirmed that EHEGAIYPDN138TTDFQR_HexNAc(4)Hex(5)-Fuc(2)NeuAc(1) from CERU, and VCQDCPLLAPLN156DTR_HexNAc(4)Hex(5)NeuAc(2) from AHSG can significantly discriminate MCI from normal controls. These two glycopeptides had the area under the receiver operating characteristic curve (AUC) of 0.850 (95% CI, 0.66-1.0) and 0.867 (95% CI, 0.68-1.0), respectively (p<0.05). The result demonstrates that changes in the expression level of the N-glycopeptides provide potential serum biomarkers for detection of AD at a very early stage.
通过质谱法进行糖肽分析可能为发现生物标志物提供重要机会,以辅助阿尔茨海默病(AD)的早期检测。在这项工作中,我们使用了纳升液相色谱 - 阶梯式高能碰撞解离 - 数据依赖采集质谱/质谱平台和纳升液相色谱 - 阶梯式高能碰撞解离 - 平行反应监测质谱平台,对患者血清中用于AD早期检测的新型N - 糖肽生物标志物进行大规模筛选和定量分析。分别从轻度认知障碍(MCI,AD的前驱阶段)患者和正常对照的10μL血清中提取N - 糖肽,经过胰蛋白酶消化、糖肽富集、分级分离以及纳升液相色谱 - 阶梯式高能碰撞解离 - 数据依赖采集质谱/质谱或纳升液相色谱 - 阶梯式高能碰撞解离 - 平行反应监测质谱分析。使用Byonic、Byologic和Skyline软件相结合的方法,我们能够完成MCI和正常对照之间位点特异性N - 糖肽的鉴定和无标记定量分析。Byologic的差异定量分析表明,与正常对照相比,来自16种糖蛋白的29种N - 糖肽在MCI中发生了显著变化。此外,对所选N - 糖肽候选物的高能碰撞解离 - 平行反应监测质谱定量分析证实,来自CERU的EHEGAIYPDN138TTDFQR_HexNAc(4)Hex(5)-Fuc(2)NeuAc(1)和来自AHSG的VCQDCPLLAPLN156DTR_HexNAc(4)Hex(5)NeuAc(2)能够显著区分MCI和正常对照。这两种糖肽的受试者工作特征曲线下面积(AUC)分别为0.850(95%置信区间,0.66 - 1.0)和0.867(95%置信区间,0.68 - 1.0)(p<0.05)。结果表明,N - 糖肽表达水平的变化为AD极早期检测提供了潜在的血清生物标志物。