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Translational Capabilities: Genome-scale metabolic models (Milestone 4.M)

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.


Success Criteria

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.

This information is current as of March 2022.


Research Implementation Area
Translational Tools, Infrastructure, and Capabilities
Timeline
2018–2022
Status
In Progress

Accomplishments/Implementation Activities

Funding Initiatives

Research Programs and Resources

Research Highlights

Relevant Recommendations

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