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Novel Statistical Methods for Multi-omics Data Integration in Alzheimer's Disease

Award Number: R03AG070669
ORGANIZATION: NATIONAL INSTITUTE ON AGING
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 01/01/2021
PERIOD OF PERFORMANCE END DATE: 08/31/2023

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Novel Statistical Methods for Multi-omics Data Integration in Alzheimer's Disease - Novel Statistical Methods for Multi-omics Data Integration in Alzheimer's Disease Principal Investigators: Chong Wu, Ph.D. (contact); Jonathan Bradley, Ph.D. Summary A fundamental public health need is to understand the genetic basis of Alzheimer’s disease (AD) to enable enhanced screening and preventive therapies. To date, genome-wide association studies (GWAS) have identified more than 30 late-onset AD risk loci. These identified risk loci only explain a modest proportion of the late-onset AD heritability, which motivates the development of transcriptome-wide association studies (TWASs). TWASs test for predicted gene expression-trait associations by leveraging individual-level gene expression reference data and successfully enhanced the discovery of genetic risk loci for many complex traits, including late-onset AD. Even though many TWASs related methods have been proposed and investigated, critical gaps remain. First, existing TWAS methods predominantly require expression reference panels, which can be limited in sample size and create a challenge when developing prediction models. Second, while many expression prediction models have been built, no statistical method has been proposed to build a new expression prediction model that combines/uses existing expression prediction models. These critical gaps in knowledge deter the statistical power of detecting gene-trait associations by TWAS, which is ultimately needed to gain potentially transformative insight into the genetic basis of AD. In response to PAS-19-391, this project’s overall objective is to develop statistical methods and software for improving the power of TWAS and offering biological insights into AD. Our central hypothesis is to maximize the power of TWAS either by using eQTL summary data with much larger sample sizes as the expression reference panel or by leveraging existing expression prediction models. To test our central hypothesis, we will 1) develop expression prediction models by leveraging eQTL summary data, 2) develop expression models by integrating existing expression prediction models, and 3) develop open-source, cross-platform, publicly available, easy-to-use software to implement the proposed methods. The overarching aim of this study not only enhances the power of the widely used method TWASs but also offers biological insights into AD pathology. The proposed new methods can also be applied to other complex diseases.


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: 2024 ( Subtotal = -$1,165 )
2024	2022	FLORIDA STATE UNIVERSITY	874 TRADITIONS WAY	TALLAHASSEE	FL	32306	LEON	USA	Aging Research	000	2	2/21/2024	NON-COMPETING CONTINUATION	-$1,165
														Subtotal = -$1,165

Issue Date FY: 2022 ( Subtotal = $147,907 )
2022	2022	FLORIDA STATE UNIVERSITY	874 TRADITIONS WAY	TALLAHASSEE	FL	32306	LEON	USA	Aging Research	000	2	1/24/2022	NON-COMPETING CONTINUATION	$133,116
2022	2022	FLORIDA STATE UNIVERSITY	874 TRADITIONS WAY	TALLAHASSEE	FL	32306	LEON	USA	Aging Research	001	2	4/25/2022	NON-COMPETING CONTINUATION	$14,791
														Subtotal = $147,907

Issue Date FY: 2021 ( Subtotal = $147,966 )
2021	2021	FLORIDA STATE UNIVERSITY	874 TRADITIONS WAY	TALLAHASSEE	FL	32306	LEON	USA	Aging Research	001	1	1/7/2021	NEW	$0
2021	2021	FLORIDA STATE UNIVERSITY	874 TRADITIONS WAY	TALLAHASSEE	FL	32306	LEON	USA	Aging Research	000	1	12/23/2020	NEW	$147,966
														Subtotal = $147,966

Grand Total All Awards = $294,708

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Novel Statistical Methods for Multi-omics Data Integration in Alzheimer's Disease

Award Number: R03AG070669

ORGANIZATION: NATIONAL INSTITUTE ON AGING

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 01/01/2021

PERIOD OF PERFORMANCE END DATE: 08/31/2023

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