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Purine metabolism disruption links pathology and cognitive decline in Alzheimer’s disease
Xiaohang Qian, Zhongxuan Wang, Siyue Chen, Yang Xue, Yawen Yang, Peijing Cui, Miao Zhang, Huidong Tang
Xiaohang Qian, Zhongxuan Wang, Siyue Chen, Yang Xue, Yawen Yang, Peijing Cui, Miao Zhang, Huidong Tang
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Research Article Aging Metabolism Neuroscience

Purine metabolism disruption links pathology and cognitive decline in Alzheimer’s disease

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Abstract

Purine metabolism dysregulation has been implicated in Alzheimer’s disease (AD), but its temporal dynamics and mechanistic links to core pathologies remain unclear. This translational study integrated a longitudinal preclinical AD mouse model and clinical cohort investigations to define the role of purine metabolism in AD progression. In APPswe/PSEN1dE9 (APP/PS1) mice, serum-untargeted metabolomics identified purine metabolism as the most notably altered pathway, with metabolite levels (e.g., adenine, adenosine) shifting dynamically across disease stages alongside increasing amyloid-β (Aβ) burden. In the pathology-defined clinical cohort, targeted analysis revealed that serum uric acid and allantoin were specifically depleted in the Aβ+ cognitively impaired (CI) group and correlated strongly with higher brain Aβ load, increased neuroinflammation, and poorer cognitive scores. Formal mediation analysis elucidated a plausible mechanistic cascade: the association of uric acid/allantoin with cognitive impairment was primarily mediated by Aβ pathology. Two-year longitudinal data further suggest that changes in specific purine metabolites might predict the rate of cognitive decline. Allantoin supplementation reduced Aβ pathology through promoting microglial phagocytosis of Aβ in APP/PS1 mice. Our findings identified purine metabolism as a key hub connecting Aβ pathology, neuroinflammation, and clinical progression in AD.

Authors

Xiaohang Qian, Zhongxuan Wang, Siyue Chen, Yang Xue, Yawen Yang, Peijing Cui, Miao Zhang, Huidong Tang

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Figure 2

Metabolic profile differences in serum of APP/PS1 mice at different ages.

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Metabolic profile differences in serum of APP/PS1 mice at different ages...
(A–C) Immunofluorescence and quantification of 4G8. Scale bars: 2,000 μm (n = 3 per group). (D) PCA of metabolites in serum of 5-, 10-, and 15-month APP/PS1mice (n = 6 per group). (E) Analysis of serum differential metabolites between 5-, 10-, and 15-month APP/PS1mice. (F–H) KEGG enrichment analysis of different metabolites in serum between APP/PS1 and WT mice. (I–T) The differences in metabolites related to purine metabolism between the serum of APP/PS1 and WT mice. APP/PS1, APPswe/PSEN1dE9; PCA, Principal Component Analysis; KEGG, Kyoto Encyclopedia of Genes and Genomes. Data are presented as mean ± SD. Statistics were analyzed by Kruskal-Wallis test followed by Dunn’s multiple comparisons test or 1-way ANOVA followed by Tukey’s multiple comparisons test based on the normality of the data distribution. *P < 0. 05, **P < 0.01, ***P < 0.001, ****P < 0.0001.

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