N-Glycosylation and Alzheimer's disease: A 2001–2025 global bibliometric landscape revealing emerging diagnostic trends

Background: Alzheimer's disease (AD) lacks effective early diagnostic tools. N-glycosylation dysregulation involving the enzyme MGAT3 is implicated in AD pathogenesis, with untapped clinical potential for biomarker development. Objective: To identify and validate MGAT3-associated diagnostic biomarkers for AD using integrative multi-disciplinary approaches. Methods: Bibliometric analysis of N-glycosylation-AD research; large-scale GEO dataset preprocessing, WGCNA-integrated bioinformatics, machine learning, and penalized regression in well-characterized independent training/validation sets. Results: as the core journal; Taniguchi N and Kizuka Y as key authors; Lee JH (2010) and Zielinska DF (2010) as highly cited works; key keywords including "bisecting GlcNAc" and "MGAT3/GnT-III"; and thematic shifts toward amyloid pathology, MGAT3-driven glycosylation, and neuronal signaling pathways. ATP6V1G2 and CHST6 emerged as core MGAT3-associated biomarkers with a strong antagonistic relationship (r = -0.63). Both demonstrated robust standalone diagnostic efficacy (AUC > 0.72) across diverse patient subgroups in the training set, with the CHST6 + ATP6V1G2 + PCSK1 combination achieving AUC 0.755. Validation confirmed ATP6V1G2 as the consistently top single biomarker (AUC = 0.761), while the ATP6V1G2 + ENO2 + SEZ6L2 panel reached peak AUC 0.764. ATP6V1G2 was significantly downregulated and CHST6 markedly upregulated in AD cohorts, with clinical utility validated via nomograms for risk stratification, decision curve analysis (net benefit 0.20-0.25), and >80% reliable correspondence between high-risk individuals and confirmed AD cases. Conclusions: MGAT3-associated biomarkers (ATP6V1G2, CHST6) and their combinations offer promising AD diagnostic potential, advancing insights into N-glycosylation-mediated disease mechanisms.