Reveals metabolic alterations and immune interactions in late-onset Alzheimer's, suggesting new biomarkers.
Background Immuno-metabolic dysregulation contributes to Alzheimer’s disease (AD) pathogenesis, yet the peripheral metabolic landscape and its interplay with neuroinflammation remain poorly characterized in treatment-naïve, late-stage patients. This study aimed to delineate plasma metabolic alterations and immuno-metabolic interactions in Chinese first-time outpatients with late-onset AD (CFTO-LOAD). Methods Untargeted metabolomics and ELISA were applied to plasma from 35 CFTO-LOAD patients and 35 sex-matched cognitively healthy controls (CHCs) to quantify metabolites, cytokines (TNF-α, IL-17, IL-9), and soluble Aβ/Tau markers. Results A total of 875 differentially abundant metabolites (DAMs) were identified in CFTO-LOAD, comprising 227 upregulated and 648 downregulated species ( P < 0.05), predominantly lipids, fatty acids (e.g., dodecanoic acid, arachidonic acid), and amino acids (e.g., L-arginine, L-leucine). KEGG analysis revealed enrichment in fatty acid and amino acid metabolism, GABAergic synapse, and intestinal immune network pathways. CFTO-LOAD patients exhibited elevated pro-inflammatory cytokines TNF-α and IL-17 ( P adj < 0.05), reduced IL-9 ( P adj < 0.001), increased soluble p-Tau, p-Tau181, and p-Tau217 ( P adj < 0.01), and decreased Aβ42/Aβ40 ratio ( P adj < 0.001). Linear regression identified significant correlations between differential metabolites and immune/pathological markers, including positive associations of dodecanoic acid with TNF-α ( r = 0.34, P adj < 0.05) and arachidonic acid with Aβ42/Aβ40 ratio ( r = 0.30, P adj < 0.05), and negative associations of arachidonic acid with p-Tau217 ( r = −0.43, P adj < 0.01) and sphinganine 1-phosphate with TNF-α ( r = −0.28, P adj < 0.05). Conclusion These findings characterize the peripheral immuno-metabolic landscape in treatment-naïve late-onset AD, identifying metabolic mediators that may mechanistically link neuroinflammation to Aβ and Tau pathology. This provides a foundation for biomarker development and therapeutic targeting in late-stage disease, pending independent validation.
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Wang et al. (2026) studied this question.
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