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AI-powered cross-level cross-species omics data integration to elucidate mechanisms of EL

Award Number: R33AG083302
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/15/2023
PERIOD OF PERFORMANCE END DATE: 07/31/2028

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AI-powered cross-level cross-species omics data integration to elucidate mechanisms of EL - Abstract It is a formidable task to identify the molecular causes of complicated traits such as exceptional longevity (EL). The majority of machine learning algorithms generate mathematical correlations between genotypes and phenotypes, but may fail to infer physiologically significant causes. A mechanistic understanding of how individual molecular components work together in a system and how the system is affected and adapted to the molecular change requires knowledge of molecular interactions across all biological levels, from DNAs to RNAs to proteins to metabolites to organismal phenotypes. By integrating multi-omics data, recent approaches in multi-modal machine learning and multi-layer network model promise to address this deficiency. However, existing machine learning approaches are hampered by high-dimensionality, non-uniformity, numerous confounders, and biological differences in multi-omics data across data resources, data domains, and species as well as lack of interpretability due to the black-box nature of machine learning models. We will develop a transformative deep learning framework to address challenges for multi-omics data integration and predictive modeling of causal genotype-EL associations. This project is established on our substantial preliminary results, successes in systems pharmacology for Alzheimer's disease drug discovery and using C. elegans as disease and aging models, and close collaborations between experimental and computational laboratories. We shall overcome several obstacles in order to discover the molecular mechanisms of EL. We will develop and validate novel algorithms to 1) harmonize non-uniform data sets by removing environmental and biological confounding factors (e.g., age, species, etc.) and technical biases (e.g., batch effect), 2) explicitly model the biological information flow from DNAs to RNAs to proteins to metabolites to organismal phenotypes, and 3) determine causal genetic factors and molecular interactions underlying EL. Specifically, we will: (1) develop MuLGIT, a causal deep learning-powered cross-layer multi-omics harmonization and integration framework that follows the central dogma of biology for deciphering the molecular interplays underlying EL; (2) develop a transfer learning method PATH-AE for cross-species omics data integration and modeling for elucidating evolutionarily conserved and species-specific molecular determinants of EL; (3) identify molecular targets and pharmaceutical agents of EL by merging new methodologies for multi-omics data integration with state-of-the- art methods for chemical genomics and perturbation genomics; and (4) experimentally validate computational predictions using C. elegans models. Completion of this project will allow us to identify novel biomarkers, druggable targets, and pharmacological agents associated with remarkable lifespan (EL).


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $47,194 )
2026	2025	RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK	695 PARK AVE	NEW YORK	NY	10065	NEW YORK	USA	Aging Research	000	2	1/9/2026	EXTENSION WITH OR WITHOUT FUNDS	-$1,233,687
2026	2025	NORTHEASTERN UNIVERSITY	360 HUNTINGTON AVE	BOSTON	MA	02115	SUFFOLK	USA	Aging Research	001	3	1/12/2026	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$1,280,881
														Subtotal = $47,194

Issue Date FY: 2025 ( Subtotal = $1,233,687 )
2025	2025	RESEARCH FOUNDATION OF THE CITY UNIVERSITY OF NEW YORK	695 PARK AVE	NEW YORK	NY	10065	NEW YORK	USA	Aging Research	000	2	8/4/2025	EXTENSION WITH OR WITHOUT FUNDS	$1,233,687
														Subtotal = $1,233,687

Grand Total All Awards = $1,280,881

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AI-powered cross-level cross-species omics data integration to elucidate mechanisms of EL

Award Number: R33AG083302

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 08/15/2023

PERIOD OF PERFORMANCE END DATE: 07/31/2028

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