Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease

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dc.contributor.authorChang, Rui
dc.contributor.authorTrushina, Eugenia
dc.contributor.authorZhu, Kuixi
dc.contributor.authorZaidi, Syed Shujaat Ali
dc.contributor.authorLau, Branden M.
dc.contributor.authorKueider-Paisley, Alexandra
dc.contributor.authorMoein, Sara
dc.contributor.authorHe, Qianying
dc.contributor.authorAlamprese, Melissa L.
dc.contributor.authorVagnerova, Barbora
dc.contributor.authorTang, Andrew
dc.contributor.authorVijayan, Ramachandran
dc.contributor.authorLiu, Yanyun
dc.contributor.authorSaykin, Andrew J.
dc.contributor.authorBrinton, Roberta D.
dc.contributor.authorKaddurah-Daouk, Rima
dc.contributor.authorAlzheimer’s Disease Neuroimaging Initiative
dc.contributor.authorAlzheimer’s Disease Metabolomics Consortium
dc.contributor.departmentRadiology and Imaging Sciences, School of Medicine
dc.date.accessioned2024-02-28T11:08:38Z
dc.date.available2024-02-28T11:08:38Z
dc.date.issued2023
dc.description.abstractIntroduction: Late-onset Alzheimer's disease (LOAD) is a complex neurodegenerative disease characterized by multiple progressive stages, glucose metabolic dysregulation, Alzheimer's disease (AD) pathology, and inexorable cognitive decline. Discovery of metabolic profiles unique to sex, apolipoprotein E (APOE) genotype, and stage of disease progression could provide critical insights for personalized LOAD medicine. Methods: Sex- and APOE-specific metabolic networks were constructed based on changes in 127 metabolites of 656 serum samples from the Alzheimer's Disease Neuroimaging Initiative cohort. Results: Application of an advanced analytical platform identified metabolic drivers and signatures clustered with sex and/or APOE ɛ4, establishing patient-specific biomarkers predictive of disease state that significantly associated with cognitive function. Presence of the APOE ɛ4 shifts metabolic signatures to a phosphatidylcholine-focused profile overriding sex-specific differences in serum metabolites of AD patients. Discussion: These findings provide an initial but critical step in developing a diagnostic platform for personalized medicine by integrating metabolomic profiling and cognitive assessments to identify targeted precision therapeutics for AD patient subgroups through computational network modeling.
dc.eprint.versionAuthor's manuscript
dc.identifier.citationChang R, Trushina E, Zhu K, et al. Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease. Alzheimers Dement. 2023;19(2):518-531. doi:10.1002/alz.12675
dc.identifier.urihttps://hdl.handle.net/1805/38964
dc.language.isoen_US
dc.publisherWiley
dc.relation.isversionof10.1002/alz.12675
dc.relation.journalAlzheimer's & Dementia
dc.rightsPublisher Policy
dc.sourcePMC
dc.subjectAlzheimer's Disease Neuroimaging Initiative
dc.subjectApolipoprotein E ε4
dc.subjectComputational systems biology
dc.subjectLate-onset Alzheimer's disease
dc.subjectMetabolic biomarkers
dc.subjectMetabolic network
dc.subjectMetabolomics
dc.subjectPrecision medicine
dc.subjectSex-specific metabolic changes
dc.titlePredictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease
dc.typeArticle
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