Autor: |
Gross, Thomas J, Cheema, Amrita K, Fiandaca, Massimo S, Federoff, Howard J, Ringman, John M, Mapstone, Mark |
Zdroj: |
Alzheimer's & Dementia: The Journal of the Alzheimer's Association; Jun2023 Supplement 1, Vol. 19, p1-2, 2p |
Abstrakt: |
Background: Metabolic dysregulation has been implicated in the pathobiology of Alzheimer's disease (AD), including familial autosomal dominant AD (ADAD). Recent metabolic neuroimaging of preclinical ADAD mutation carriers has suggested that levels of the reactive glial marker myo‐inositol increase with proximity to expected age at dementia onset. It remains unclear, however, if similar metabolic change related to anticipated phenoconversion can be observed at network‐scale in the peripheral plasma metabolome of ADAD mutation carriers. Method: We collected peripheral blood plasma from ADAD mutation carriers with and without objective cognitive decline (ncarrier = 55) who participated in a longitudinal kindred study. We used untargeted liquid chromatography‐ mass spectrometry (LC‐MS) metabolomics to infer putative metabolic pathway and protein disruptions associated with impending dementia diagnosis at whole‐genome scale. Spearman 흆 correlation coefficients were determined for each identified mass feature in relation to clinical, family‐wise estimated years to diagnosis prior to the submission of these summary statistics to metabolomic modeling. Result: A total of 91 LC‐MS mass features were significantly correlated with estimated years to dementia onset, nominal p's <.05. Pathway‐based, genome‐scale metabolomic modeling analysis revealed a de novo plasma metabolomic activity network composed of interconnected lipid and small, polar metabolite hubs. These same correlations were also submitted to gene‐inferring, whole‐genome metabolomic modeling using PIUmet. Intriguingly, mRNA expression of prioritized genes was not limited to the brain and involved multiple peripheral tissues. In the CNS itself, however, genes prioritized by PIUMet metabolomic modeling frequently demonstrated expression in glia. Conclusion: Consistent with prior metabolic findings in ADAD mutation carriers, network alterations to the peripheral plasma metabolome correspond with increasing proximity to expected age of dementia onset. Because neuroinflammation has been previously described as an immunometabolic process in pathological aging, emerging metabolic network disintegrity in ADAD may index reactive glial pathobiology previously suggested by prior metabolic investigations of this population. These perturbed networks inferred from participant blood plasma suggest targetable CNS‐peripheral metabolic dyshomeostases which otherwise precipitate pathobiological "failures of compensation" and concomitant cognitive decline in carriers of Mendelian ADAD mutations. [ABSTRACT FROM AUTHOR] |
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