Saturday, May 4, 2024
5/4/2024
Project Summary Alzheimer's disease (AD) is a major public health concern in the US, and there is an urgent need for reliable, inexpensive, and non-invasive biomarkers to identify individuals at risk for AD. This project aims to develop innovative computational strategies for precision medicine in AD. Specifically, we will harmonize several large longitudinal clinical datasets, identify DNA methylation (DNAm) biomarkers for cognitive reserve (CR), and build DNAm-based prediction models for AD. In this project, we will improve the accuracy of DNAm-based prediction models by leveraging knowledge of cognitive reserve, harmonizing multiple datasets, and training and testing prediction models using samples from longitudinal studies. The DNAm-based prediction models will provide an inexpensive and convenient approach for identifying subjects most likely to progress to clinical AD, reducing heterogeneity in patients selected for clinical trials, and facilitating personalized treatment strategies in AD. Additionally, identifying DNAm markers for CR will help develop novel therapeutic targets and lifestyle interventions for preventing dementia. The successful completion of the project will also provide the community with harmonized datasets for AD research, as well as computational methods and tools that can be easily adapted and applied to analyze datasets in other types of dementia.
HHS’ Tracking Accountability in Government Grants System (TAGGS) website provides access to detailed descriptions of grants, loans, aggregated direct payments and other types of financial assistance awarded by the HHS Operating Divisions (OPDIVs) and the Office of the Secretary Staff Divisions (STAFFDIVs).
