Lingyun Pan, Yu Lin, Jianhui Zhu, Jie Zhang, Zhijing Tan, David M Lubman
{"title":"Large Scale Screening and Quantitative Analysis of Site-Specific N-Glycopeptides from Human Serum in Early Alzheimer's Disease Using LC-HCD-PRM-MS.","authors":"Lingyun Pan, Yu Lin, Jianhui Zhu, Jie Zhang, Zhijing Tan, David M Lubman","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>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.</p>","PeriodicalId":73911,"journal":{"name":"Journal of proteomics & bioinformatics","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289803/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of proteomics & bioinformatics","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2022/6/27 0:00:00","PubModel":"Epub","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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.