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- W4367302607 abstract "<h3>Objective:</h3> Identify metabolites associated with clinical diagnosis and pathology of Alzheimer’s Disease (AD) <h3>Background:</h3> We investigated metabolites in plasma to capture systemic biochemical changes associated with AD diagnosed clinically and then using plasma biomarkers. <h3>Design/Methods:</h3> Exogenous and endogenous metabolites in plasma were measured in 300 clinical AD and 430 healthy non-demented individuals of Caribbean Hispanic ancestry using untargeted liquid-chromatography, performed on HILIC (+ ionization) and C18 (− ionization) columns, coupled to a Thermo Orbitrap HF-X mass spectrometer. Genome-wide SNP data and plasma biomarkers including Ab40, Ab42, P-tau181 and Neurofilament light chain (NfL) were obtained on all participants. Metabolite association with AD and P-tau181 levels were tested after adjustment for age and sex. Metabolites associated with P-tau181 levels (but not with NfL, a non-specific marker of neurodegeneration) were categorized as AD-specific. <h3>Results:</h3> Over 4000 metabolomic features were measured with high accuracy in the sample. 96 metabolites were associated with P-tau181 levels, but no metabolites survived multiple testing correction for association with clinical AD alone. Features putatively annotated as phosphatidylcholine (4.11E-07) and Carotamine (p=1.2e-05) were strongly associated P-tau181 levels. We observed similar results when using a diagnostic cutoff of P-tau181 levels for AD as the outcome. Metabolites associated with P-tau181 levels were enriched in amino acid metabolism, glutathione metabolism, tryrosine metabolism and hexose phosphorylation pathways. Ramipril (p=2.9e-04) and glycerophosphocholine (p=9.9e-04) were among the top associated with AD diagnosis. PLS-DA analysis identified biopterin metabolism, glycosphingolipid biosynthesis and tyrosine metabolism as the most discriminating pathways between AD and healthy controls when augmented by biomarkers. <h3>Conclusions:</h3> Metabolites specifically lipids and those involved in cardiovascular function were associated with AD and P-tau181 levels. Metabolite profiling can identify perturbed pathways in clinical and pre-clinical AD and integration with genome-wide SNP data will identify mechanisms underlying genetic association with disease. <b>Disclosure:</b> Dr. Kalia has nothing to disclose. Mrs. Reyes-Dumeyer has nothing to disclose. Mr. DUBEY has nothing to disclose. Dr. Nandakumar has nothing to disclose. Dr. Lee has nothing to disclose. Rafael Lantigua has nothing to disclose. Dr. Medrano has nothing to disclose. Dr. Rivera Mejia has nothing to disclose. Dr. Honig has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Eisai. Dr. Honig has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Biogen. Dr. Honig has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Medscape. Dr. Honig has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Prevail. Dr. Honig has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Cortexyme. Dr. Honig has received personal compensation in the range of $10,000-$49,999 for serving as an Expert Witness for Legal Firms . The institution of Dr. Honig has received research support from Roche. The institution of Dr. Honig has received research support from Eisau. Dr. Honig has received research support from Alector. The institution of Dr. Honig has received research support from Transposon. Dr. Mayeux has nothing to disclose. Badri Vardarajan has received personal compensation in the range of $10,000-$49,999 for serving as a Consultant for Kodikaz Therapeutics." @default.
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- W4367302607 date "2023-04-25" @default.
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- W4367302607 title "Plasma metabolites associated with clinically diagnosed Alzheimer’s Disease and the association is augmented using blood-based biomarkers. (P10-6.003)" @default.
- W4367302607 doi "https://doi.org/10.1212/wnl.0000000000203770" @default.
- W4367302607 hasPublicationYear "2023" @default.
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