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DOI 10.1002/pmic.70170

Медицинская библиотека · Proteomics · 2026

Disease-Specific Glycopattern Signatures of Serum Small Extracellular Vesicles in Depression, Schizophrenia, and Glioblastoma.

Gong Jinye, Li Zonglin, Ding Jiangbo, Chen Shuyi, Ramzan Muhammad Anas, Wang Wanqi, Liu Liying, Qin Yannan

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Аннотация

Serum small extracellular vesicles (sEVs) carry glycoproteins that reflect the pathophysiological states of their cells of origin, yet their glycomic profiles in neuropsychiatric disorders remain largely unexplored. Here, we isolated sEVs from healthy controls and patients with depressive disorder (DD), schizophrenia (SCZ), or brain glioma (BG), and characterized their glycopatterns using a high-throughput lectin microarray. Concentrations and CD81 expression of sEVs were significantly elevated across all disease groups relative to healthy controls. Lectin microarray analysis revealed both shared and disease-specific glycan alterations: PSA-recognized glycans (high-mannose and core-fucosylated structures) were consistently downregulated in all three conditions, whereas STA-binding glycans (GlcNAc oligomers and core GlcNAc of N-glycans) were upregulated in SCZ and BG but slightly decreased in DD. Disease-specific lectin signatures-including UEA-I, PHA-L, and DBA in DD, and ACA in SCZ-enabled clear discrimination among the four groups. The STA/PSA fluorescence ratio, validated in individual samples via sEVs microarray, effectively distinguished SCZ and BG from DD and controls. These findings establish that serum sEVs harbor disease-specific glycopatterns capable of differentiating depression, schizophrenia, and glioblastoma, offering a minimally invasive diagnostic approach and providing insights into glycan-related mechanisms underlying these disorders.

Для цитирования: Gong Jinye, Li Zonglin, Ding Jiangbo, Chen Shuyi, Ramzan Muhammad Anas, Wang Wanqi, Liu Liying, Qin Yannan. Disease-Specific Glycopattern Signatures of Serum Small Extracellular Vesicles in Depression, Schizophrenia, and Glioblastoma.. Proteomics. 2026. DOI: 10.1002/pmic.70170.
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