Mapping alzheimer's disease genes across multi-omics, tissues, and cell types using deep-learning-enhanced methods

Active Project Grant Awarded Last action

Award ID
F31AG097038
Recipient
Awarding agency
Obligated
$50,114

Award facts

Assistance listing
93.866 Aging Research
Completion date 0% complete
Place of performance
Illinois, USA

Award details come from USAspending.gov.

Description

As the agency reported it.

Abstract
Transcriptome-wide association studies (TWASS) identify gene-trait associations by integrating data from genome-wide association studies and expression quantitative trait locus (EQTL) studies. In addition to gene expression, twas methods have expanded to map other trait/disease-associated molecular phenotypes by using multi-omics molecular QTL (XQTL) data. To account for context-specificity, twas methods have also been widely used to map risk genes across multiple tissues and cell types. These integrative efforts have significantly improved the precision in mapping risk genes and enhanced our understanding of the molecular mechanisms underlying complex diseases. However, a significant challenge is the limited availability and small sample sizes of XQTL and single-cell EQTL data, which constrain the statistical power for detecting true associations in specific contexts using existing twas methods. In aim 1 of this project, we propose to develop a deep learning-enhanced integrative twas framework for integrating multi-omics, multi-tissue and multi-cell-type data to map risk genes and CIS-regulated molecular phenotypes associated with complex diseases and related outcomes. Our approach builds on the rationale that disease-associated genes are likely to exhibit CO-occurring associations across multiple relevant tissues, cell types, and omics data types, and on related traits and comorbidities. By jointly modeling latent indicators of non-zero gene-trait effects across cellular contexts and omics data types, we aim to enhance the detection of true and replicable gene-trait associations. In aim 2, we will apply the proposed integrative twas framework to map gene expression and other CIS-regulated molecular phenotypes including alternative splicing, DNA methylation, protein abundance, and alternative polyadenylation associated with alzheimer's disease (ad) and related traits. In aim 3, we will apply alternative approaches and use experimental validation to validate the identified genes. This project will develop powerful integrative twas methods and software, identify and validate genes associated with ad and related traits, and provide training opportunities in methodology, data analysis, and experimental validation.

Quick answers

Who received award F31AG097038?

F31AG097038 was awarded to The University Of Chicago by National Institute on Aging (National Institutes of Health) on December 15, 2026.

How much is award F31AG097038 worth?

$50,114 has been obligated on F31AG097038.

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