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Large Scale Screening and Quantitative Analysis of Site-Specific N-Glycopeptides from Human Serum in Early Alzheimer’s Disease Using LC-HCD-PRM-MS

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...

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Detalles Bibliográficos
Autores principales: Pan, Lingyun, Lin, Yu, Zhu, Jianhui, Zhang, Jie, Tan, Zhijing, Lubman, David M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10289803/
https://www.ncbi.nlm.nih.gov/pubmed/37362028
Descripción
Sumario: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.