Translational Capabilities: Genome-scale metabolic models

Support the development of genome-scale metabolic models to capture the heterogeneity of metabolic transitions from healthy to pathologic brain aging and use the metabolome as a functional readout for other omics data to delineate pathways implicated in disease initiation and progression and to identify disease subtypes.

2024 RFA-AG-17-054: Enhancing the Target and Biomarker Discovery Efforts of the AMP AD and M2OVE-AD Consortia (R01) 4.M Achieved Support the development of genome-scale metabolic models to capture the heterogeneity of metabolic transitions... DN 2018 AD Summit: 3H and 2H News: Decoding the molecular ties between vascular disease and Alzheimer’s - NIH consortium uses big data, team science to uncover complex interplay of factors Translational Tools, Infrastructure, and Capabilities Molecular Mechanisms of the Vascular Etiology of Alzheimer's Disease (M²OVE-AD) Consortium Enhancing the Target and Biomarker Discovery Efforts of the AMP AD and M2OVE-AD Consortia Metabolic Network Analysis of Biochemical Trajectories in Alzheimer's Disease The Alzheimer’s Disease Atlas

Provide support for:

  • generation of high-quality, targeted and non-targeted metabolomic profiling data across diverse, human cohorts (spanning midlife through extreme old age) for which genetic and rich clinical data are available.
  • development of analytical methods needed to integrate metabolomic data with genetic, molecular imaging and other clinical data.
  • development of open-source, genome-scale, metabolic models for use in target validation and disease sub-classification.

Summary of Key Accomplishments

The AD Metabolomics Consortium, an international network of academic centers supported through multiple NIA funding initiatives, has generated rich, high-quality, metabolomics and lipidomics data from multiple studies. This data has been integrated with other molecular data types and used to develop models of metabolic dysregulation in AD, including the AD Atlas, a data integration open-source analytical tool for investigating AD/ADRD. The tools developed by the Consortium are being used to inform the selection of therapeutic targets and understand the different stages of the disease and different disease subtypes.

The key accomplishments summary is current as of March 2022.