TY - JOUR
T1 - Predictive metabolic networks reveal sex- and APOE genotype-specific metabolic signatures and drivers for precision medicine in Alzheimer's disease
AU - for the Alzheimer's Disease Neuroimaging Initiative and the Alzheimer's Disease Metabolomics Consortium
AU - Chang, Rui
AU - Trushina, Eugenia
AU - Zhu, Kuixi
AU - Zaidi, Syed Shujaat Ali
AU - Lau, Branden M.
AU - Kueider-Paisley, Alexandra
AU - Moein, Sara
AU - He, Qianying
AU - Alamprese, Melissa L.
AU - Vagnerova, Barbora
AU - Tang, Andrew
AU - Vijayan, Ramachandran
AU - Liu, Yanyun
AU - Saykin, Andrew J.
AU - Brinton, Roberta D.
AU - Kaddurah-Daouk, Rima
N1 - Publisher Copyright:
© 2022 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.
PY - 2023/2
Y1 - 2023/2
N2 - Introduction: 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.
AB - Introduction: 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.
KW - Alzheimer's Disease Neuroimaging Initiative
KW - apolipoprotein E ε4
KW - computational systems biology
KW - late-onset Alzheimer's disease
KW - metabolic biomarkers
KW - metabolic network
KW - metabolomics
KW - precision medicine
KW - sex-specific metabolic changes
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U2 - 10.1002/alz.12675
DO - 10.1002/alz.12675
M3 - Article
AN - SCOPUS:85128973194
SN - 1552-5260
VL - 19
SP - 518
EP - 531
JO - Alzheimer's and Dementia
JF - Alzheimer's and Dementia
IS - 2
ER -