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

Overview

abstract

  • 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.

publication date

  • April 28, 2022

Research

keywords

  • Alzheimer Disease
  • Neurodegenerative Diseases

Identity

PubMed Central ID

  • PMC10402890

Scopus Document Identifier

  • 85128973194

Digital Object Identifier (DOI)

  • 10.1002/alz.12675

PubMed ID

  • 35481667

Additional Document Info

volume

  • 19

issue

  • 2