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 - Funding Information:
We thank Drs. Matthias Arnold (MA) and Gabi Kasternmuller (GK) from Institute of Bioinformatics and Systems Biology, Helmholtz Zentrum München for their discussions. Additionally, MA, RK‐D, and GK are supported by NIA grants RF1 AG058942 and R01 AG057452. MA and GK are also supported by funding from Qatar National Research Fund NPRP8‐061‐3‐011. Its contents are solely the responsibility of the authors and do not necessarily represent the official view of the NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Funding Information:
Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI; National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH‐12‐2‐0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: AbbVie; Alzheimer's Association; Alzheimer's Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen; Bristol‐Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann‐La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd; Janssen Alzheimer Immunotherapy Research & Development, LLC; Johnson & Johnson Pharmaceutical Research & Development LLC; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale Diagnostics, LLC; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda Pharmaceutical Company; and Transition Therapeutics. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health ( www.fnih.org ). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Therapeutic Research Institute at the University of Southern California. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This research was supported by grants from the National Institutes of Health and partnership with Alzheimer's Disease Metabolomics Consortium (ADMC; grant numbers RF1AG057457 and R56AG062620 to R.C., RF1AG059093 to R.B., R.C. and R.K., R01AG057931 to R.B. and R.C, RF1AG55549, R01NS107265 and R01AG062135 to E.T.). The results published here are in whole or in part based on data obtained from the AD Knowledge Portal ( https://adknowledgeportal.org ). Metabolomics data are provided by the Alzheimer's Disease Metabolomics Consortium (ADMC) and funded wholly or in part by the following grants and supplements thereto: NIA R01AG046171, RF1AG051550, RF1AG057452, R01AG059093, RF1AG058942, U01AG061359, U19AG063744, and FNIH: #DAOU16AMPA awarded to Dr. Kaddurah‐Daouk at Duke University in partnership with a large number of academic institutions. As such, the investigators within the ADMC, not listed specifically in this publication's author's list, provided data along with its pre‐processing and prepared it for analysis, but did not participate in analysis or writing of this manuscript. A complete listing of ADMC investigators can be found at: https://sites.duke.edu/adnimetab/team/ .
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 -