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BackgroundNeuroinflammation plays an important role in the pathogenesis of Alzheimer's disease, but systemic immune alterations preceding clinical onset remain insufficiently characterized. Peripheral immune and vascular inflammatory processes may influence the central nervous system through endothelial dysfunction and blood-brain barrier vulnerability. Serum proteomics offers a minimally invasive approach to identify such early systemic changes.ObjectiveIn this population-based longitudinal cohort study, we analyzed baseline serum proteomic profiles from cognitively normal older adults who were prospectively followed for up to five years for incident Alzheimer's disease.MethodsSerum samples obtained during the preclinical phase were analyzed using a high-throughput affinity-based proteomic platform. Differential protein abundance, pathway enrichment analyses, and regularized machine learning models were applied to identify coordinated biological alterations associated with future disease onset.ResultsAlthough no individual proteins reached false discovery rate-corrected significance, pathway-level analyses revealed biologically coherent patterns. Proteins involved in immune resolution, Fc receptor-mediated phagocytosis, endosomal trafficking, and vascular repair signaling were downregulated, whereas pathways related to neutrophil activation and neutrophil extracellular trap formation were upregulated. Machine learning models using sparse feature selection demonstrated that a small subset of serum proteins could discriminate individuals who later developed Alzheimer's disease, although confidence intervals indicated limited model stability.ConclusionsSystemic immune dysregulation and vascular inflammation are detectable years before the clinical onset of Alzheimer's disease and may contribute to neuroinflammatory vulnerability. Serum proteomics may provide insights into early peripheral processes associated with future disease risk.
Iga et al. (Wed,) studied this question.