R33AG083003

Precision medicine digital twins for Alzheimer’s target and drug discovery and longevity - Project summary

Alzheimer’s disease (AD) is a devastating neurodegenerative disease and it is lack of effective disease-modifying treatments.

Medical digital twins are computational disease models for target identification and drug discovery.

However, how to organize and prioritize drug targets and candidate AD treatments in digital twins at drugome-wide and genome-wide scales are challenging.

Our team developed ALZGPS, a genome-wide positioning systems platform to catalyze multi-omics for AD drug discovery.

We also created the Alzheimer’s Cell Atlas (TACA), a single-cell transcriptomics and network pathobiology map for target identification and drug repurposing at brain cellulome-wide scales.

We demonstrated that systematic identification and characterization of underlying pathogenesis and disease progression at cellulome- and genome-wide scales will serve as a foundation for identifying and validating disease-modifying targets and treatments in AD or even longevity.

We hypothesize that the digital twins tools for coordinated acquisition and seamless curation of multimodal data will be transferrable to any aging therapeutic development domains and will be applicable beyond digital twins, to expand artificial intelligence (AI) and machine learning (AI ML) workflows in AD target and drug discovery.

We thus posit that a drugome-wide and genome-wide, precision medicine digital twins platform that identifies likely causal AD genes and networks from human genome sequencing and multi-omics findings enables a more complete mechanistic understanding of AD pathobiology and the rapid development of disease-modifying targets and treatments with great success.

Our goal is to ethically acquire and responsibly disseminate comprehensive patient-specific multimodal data sets, which will form the basis for scientific, technological, and translational studies to design and evaluate digital twins, and explore their integration to AD target and drug discovery.

Aim 1 will develop and test an interpretable mechanistic deep learning framework to identify disease-modifying targets and networks for AD and longevity.

We will develop a human protein-protein interactome network topology-based deep learning framework (R21 phase) and identify putative drug targets for AD and longevity through integrating multimodal data (genetics, genomics, transcriptomics, proteomics, and clinical) from AD sequencing project (ADSP), the AD knowledge portal, longevity consortium, and the Accelerating Medicines Partnership-AD (R33 phase).

Aim 2 will develop and apply AI ML technologies for collaborative end-to-end analyses of single-cell multi-ome data.

We will develop and implement a graph embedded Gaussian mixture variational autoencoder network algorithm (R21 phase) and identify AD cell type-specific genes/targets, regulatory networks, and ligand-receptor interactions (R33 phase).

Aim 3 will implement and test precision medicine digital twins for drug repurposing in AD and AD-related dementia (R33 phase).

All digital twins codes, toolbox packages, and data developed will be shared through the ADSP and the AD knowledge portal based on the FAIR principles.

This project is highly feasible and potentially transformative for both Alzheimer’s data science and precision medicine.

Cleveland Clinic Lerner College Of Medicine Of Case Western Reserve University

TO ENCOURAGE BIOMEDICAL, SOCIAL, AND BEHAVIORAL RESEARCH AND RESEARCH TRAINING DIRECTED TOWARD GREATER UNDERSTANDING OF THE AGING PROCESS AND THE DISEASES, SPECIAL PROBLEMS, AND NEEDS OF PEOPLE AS THEY AGE. THE NATIONAL INSTITUTE ON AGING HAS ESTABLISHED PROGRAMS TO PURSUE THESE GOALS. THE DIVISION OF AGING BIOLOGY EMPHASIZES UNDERSTANDING THE BASIC BIOLOGICAL PROCESSES OF AGING. THE DIVISION OF GERIATRICS AND CLINICAL GERONTOLOGY SUPPORTS RESEARCH TO IMPROVE THE ABILITIES OF HEALTH CARE PRACTITIONERS TO RESPOND TO THE DISEASES AND OTHER CLINICAL PROBLEMS OF OLDER PEOPLE. THE DIVISION OF BEHAVIORAL AND SOCIAL RESEARCH SUPPORTS RESEARCH THAT WILL LEAD TO GREATER UNDERSTANDING OF THE SOCIAL, CULTURAL, ECONOMIC AND PSYCHOLOGICAL FACTORS THAT AFFECT BOTH THE PROCESS OF GROWING OLD AND THE PLACE OF OLDER PEOPLE IN SOCIETY. THE DIVISION OF NEUROSCIENCE FOSTERS RESEARCH CONCERNED WITH THE AGE-RELATED CHANGES IN THE NERVOUS SYSTEM AS WELL AS THE RELATED SENSORY, PERCEPTUAL, AND COGNITIVE PROCESSES ASSOCIATED WITH AGING AND HAS A SPECIAL EMPHASIS ON ALZHEIMER'S DISEASE. SMALL BUSINESS INNOVATION RESEARCH (SBIR) PROGRAM: TO EXPAND AND IMPROVE THE SBIR PROGRAM, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, TO INCREASE SMALL BUSINESS PARTICIPATION IN FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION. SMALL BUSINESS TECHNOLOGY TRANSFER (STTR) PROGRAM: TO STIMULATE AND FOSTER SCIENTIFIC AND TECHNOLOGICAL INNOVATION THROUGH COOPERATIVE RESEARCH DEVELOPMENT CARRIED OUT BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO FOSTER TECHNOLOGY TRANSFER BETWEEN SMALL BUSINESS CONCERNS AND RESEARCH INSTITUTIONS, TO INCREASE PRIVATE SECTOR COMMERCIALIZATION OF INNOVATIONS DERIVED FROM FEDERAL RESEARCH AND DEVELOPMENT, AND TO FOSTER AND ENCOURAGE PARTICIPATION OF SOCIALLY AND ECONOMICALLY DISADVANTAGED SMALL BUSINESS CONCERNS AND WOMEN-OWNED SMALL BUSINESS CONCERNS IN TECHNOLOGICAL INNOVATION.

93.866 - Aging Research

National Institute on Aging (NIA) [HHS - NIH]

Cleveland, Ohio 44195 United States

Single Zip Code

Transformative Artificial Intelligence and Machine Learning Based Strategies to Identify Determinants of Exceptional Health and Life Span (R21/R33 Clinical Trial Not Allowed) (RFA-AG-23-033)