Project Grant R01AG092459
- This $1,012,879 Project Grant was awarded by the National Institute on Aging (CFDA 93.866 - Aging Research) to New York University (NYU) to develop three novel statistical machine learning methods for Alzheimer's disease (AD) research using multi-view imaging, genomic, and clinical data. The specific aims include: 1) developing a multi-view data decomposition method to construct brain and genomic networks across AD statuses, 2) developing an optimal false discovery rate control method to...
- This federal Project Grant award from the National Institute on Aging (CFDA 93.866 - Aging Research) to the University of Southern California provides $622,401 over 5 years starting January 1, 2025 to research causal models of brain biomarker changes leading to Alzheimer's disease and related dementias (ADRD). The project aims to: 1) fit novel deep learning models to predict ADRD pathology from diffusion MRI data, 2) generate individualized brain morphology prediction maps as "digital...
- This Project Grant award from the National Institutes of Health (NIH) National Institute on Aging (CFDA 93.866 - Aging Research) will support research to investigate the role of transposable elements (TEs) in Alzheimer's disease (AD) and related dementias (ADRD). The $303,449 award to the Regents of the University of Michigan will leverage large genomic and clinical datasets to analyze the prevalence and functional impact of TEs on AD and ADRD phenotypes. The project aims to develop a predictive...
- This Project Grant award of $762,636 from the National Institute on Aging (CFDA 93.866 - Aging Research) supports research by The Leland Stanford Junior University to develop interpretable machine learning (ML) methods for analyzing the genetics of Alzheimer's disease (AD). The objective is to discover causal genetic variants that could lead to new AD therapies. The work involves pairing rigorous feature selection in ML with causal inference to identify genetic variants that influence AD risk,...
- This $287,118 Project Grant was awarded on September 1, 2023 by the National Institute on Aging (NIA) under the Aging Research (CFDA 93.866) grant program. The grant will fund the development of techniques to use deep transfer learning and multimodal data, including brain MRIs, genetic information, and cognitive tests, to enable the early detection and forecasting of Alzheimer's disease progression. The University of Massachusetts (UMass), as the prime awardee, will create an end-to-end...
- This federal Project Grant award of $817,357 from the National Institute on Aging (CFDA 93.866 - Aging Research) aims to harness novel machine learning approaches for behavioral segmentation and brain signal integration in humanized models of Alzheimer's disease. The key products and services to be delivered under this grant include: Further validation of the grantee's "Variational Animal Motion Embedding (VAME)" machine learning platform for comprehensive behavioral phenotyping of...
- This four-year $1.15 million Project Grant from the National Science Foundation's Computer and Information Science and Engineering program (CFDA 47.070) supports research at the University of Michigan to develop techniques for learning from longitudinal observational clinical data in the presence of noise and confounding to tackle progressive diseases. The University will create shareable electronic health record-based definitions of mild cognitive impairment and Alzheimer's disease, and develop...
- The Project Grant titled "The Role of Neighborhood Social Exposome Dynamics in Risk and Resilience to Alzheimer's Disease and Related Dementias" was awarded by the National Institute on Aging (NIA), under CFDA Program 93.866 - Aging Research. The $3,039,714 grant, with a performance period from September 15, 2025 to September 14, 2029, will investigate the pathways between 30 years of neighborhood-level social exposome change, individual modifiable Alzheimer's disease and related...
- This federal Project Grant award of $372,690, provided by the National Institute on Aging (CFDA 93.866 Aging Research), aims to comprehensively understand the heterogeneous causal pathophysiology of Alzheimer's disease (AD). The key objectives are to: (1) develop new statistical methods for uncovering heterogeneous causal relationships among amyloid-beta, tau accumulation, and cognition across diverse AD datasets; (2) apply these methods to reveal optimal treatment windows and target populations...
- This Project Grant award from the National Institute on Aging (CFDA 93.866 - Aging Research) for $791,086 aims to develop computational models that can predict the presence of non-Alzheimer's disease neuropathological changes, such as Lewy body disease, TDP-43 proteinopathy, and cerebral amyloid angiopathy, in individuals with Alzheimer's disease neuropathological changes. The project will leverage data from autopsy-confirmed datasets, in vivo neuroimaging, and clinical assessments to build...
This Project Grant award of $640,067 from the National Institute on Aging (CFDA 93.866 Aging Research) will fund the development of novel multimodal variational autoencoder (VAE) models to learn factors associated with cognitive resilience to Alzheimer's disease (AD) and related dementias. The University of Michigan, the awardee, will employ generative methods to discover new factors from existing multimodal data (molecular, anatomic, functional imaging, cognitive) and model dynamic relationships among these factors in a latent space. This will enable predicting the effects of perturbations to the latent factors and offer a means of testing complex genetic or environmental interventions prior to experimental trials. The project aims to accelerate the design of new therapies by providing a deeper mechanistic understanding of individual differences in disease progression across biological scales.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $640.1k | 7/24/25 |