<HashMap><database>JPOST Repository</database><file_versions><headers><Content-Type>application/xml</Content-Type></headers><body><files><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Cys-80_2_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240606-DZP_Amphion-80_3_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Mal-80_3_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240606-DZP_Amphion-71_3_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240606-DZP_Amphion-71_2_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240606-DZP_Amphion-71_1_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Amide-80_3_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Amide-70_3_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Amide-70_2_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Amide-80_1_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Amide-80_2_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Amide-70_1_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Mal-80_2_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Mal-80_1_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240606-DZP_Amphion-80_2_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240606-DZP_Amphion-80_1_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240625-DZP_Cys-70_1_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240625-DZP_Cys-70_2_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Cys-80_3_GlycoPeptideQuantificationArea.txt</Txt><Txt>https://storage.jpostdb.org/JPST003920/files/HF_20240604-DZP_Cys-80_1_GlycoPeptideQuantificationArea.txt</Txt></files><type>primary</type></body><statusCode>OK</statusCode><statusCodeValue>200</statusCodeValue></file_versions><scores/><additional><omics_type>Proteomics</omics_type><submitter>Zhenpeng Deng, Mingliang Ye</submitter><species>Homo Sapiens (human)</species><full_dataset_link>https://repository.jpostdb.org/entry/JPST003920</full_dataset_link><submitter_affiliation>Dalian Institute of Chemical Physics</submitter_affiliation><sample_protocol></sample_protocol><repository>jPOST</repository><data_protocol></data_protocol></additional><is_claimable>false</is_claimable><name>Development of Complementary Enrichment Strategies for Analysis of N-Linked Intact Glycopeptides and Potential Site-Specific Glycoforms in Alzheimer's Disease</name><description>Protein glycosylation is a critical post-translational modification, and knowledge of site-specific glycoforms is essential for developing biomarkers and therapeutic drugs. Although LC-MS/MS-based glycoproteomics strategies enable the identification of site-specific glycoforms at proteomics scale, its coverage is still low largely because of the poor glycopeptide enrichment performance. HILIC is thought to allow "unbiased" enrichment of intact glycopeptides, and it is broadly used to analyze the site-specific glycoforms at proteomics scale. To maximize glycopeptide capturing, the samples are always loaded onto HILIC with high acetonitrile (ACN) content (typically 80%). In this study, we found that some HILIC columns could effectively capture glycopeptides at around 70% ACN. We further demonstrated that the system could identify the highly hydrophilic glycopeptides that can not be achieved by conventional methods. The excellent complementarity of 70% ACN enrichment methods greatly enhances the coverage (>20%) of N-glycoproteome identification in human blood. The developed methods were further applied to investigate the N-glycosylation changes in the plasma of Alzheimer's disease (AD) and mild cognitive impairment (MCI) patients. It was found that fucosylated glycopeptides were up-regulated and sialylated glycopeptides were down-regulated as the disease progressed. Altered glycosylation patterns were detected for a number of site-specific glycoforms, which serve as potentially interesting targets for further glycosylation-based AD progression. Our results reveal that complementary strategies offers a comprehensive approach to studying in N-glycoproteomics, paving the way for in-depth glycoproteomics analysis.</description><dates><publication>Tue Jul 07 00:00:00 BST 2026</publication></dates><accession>PXD065875</accession><cross_references><TAXONOMY>9606</TAXONOMY></cross_references></HashMap>