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Investigation and deployment of novel Bayesian inference algorithms in CAVATICA for identifying genomic variants underlying congenital heart defects in Down syndrome individuals

Award Number: R03HL168984
ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 05/01/2023
PERIOD OF PERFORMANCE END DATE: 04/30/2026

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Investigation and deployment of novel Bayesian inference algorithms in CAVATICA for identifying genomic variants underlying congenital heart defects in Down syndrome individuals - Project Summary/Abstract Individuals with Down syndrome (DS) tend to have many cooccurring conditions across the life span, such as Alzheimer’s disease, autism and congenital heart defects (CHD). Very strikingly, DS is a strong risk factor for CHD. Compared to the general population, children with DS have a 2000-fold increased risk of developing atrioventricular septal defects (AVSD), a type of CHD. Here, we propose to systematically apply and evaluate an individualized Bayesian inference (IBI) framework to the harmonized clinical and whole genome sequencing (WGS) data by the Kids First (KF) and INCLUDE programs to identify significant variants underlying CHD in patients without and with DS, and to understand why there is an increased risk for DS patients to develop CHD. Compared to the population-based genome wide association studies (GWAS), IBI considers the inter-individual genomic heterogeneity and infers personalized significant variants for advancing precision medicine; IBI is also capable of detecting rare or low-frequency variants by focusing on each individual’s genome that may have been missed by the parallel GWAS analysis in the same cohort. Specific Aim 1: Apply and validate the IBI framework in an integrated KF and INCLUDE cohort and further identify significant genomic variants underlying CHD in DS patients. Specific Aim 2: Build and deploy in CAVATICA a standardized novel workflow of IBI to share with the KF and INCLUDE community for identifying significant genomic variants of pediatric conditions. If successful, this project will produce a novel, validated, standardized and shareable workflow of IBI for inferring significant variants of diseases in an individual-specific manner, which has a great potential in advancing personalized medicine for conditions that affect DS individuals and the general population. The publication of this impactful IBI workflow on CAVATIVA may also attract new users and significantly increase utilization of KF and INCLUDE data. Moreover, our efforts may lead to new insights on probable genomic causes that underlie the high prevalence of CHD in DS individuals, and further inform the design of personalized prevention or treatment strategies for these 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: 2025 ( Subtotal = $0 )
2025	2023	UNIVERSITY OF MISSOURI SYSTEM	300 W. 12TH STREET	ROLLA	MO	65409	PHELPS	USA	Cardiovascular Diseases Research	000	1	2/25/2025	NEW	$0
2025	2023	UNIVERSITY OF FLORIDA	1523 UNION RD RM 207	GAINESVILLE	FL	32611	ALACHUA	USA	Cardiovascular Diseases Research	001	2	6/3/2025	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$0
														Subtotal = $0

Issue Date FY: 2024 ( Subtotal = $0 )
2024	2023	UNIVERSITY OF FLORIDA	1523 UNION RD RM 207	GAINESVILLE	FL	32611	ALACHUA	USA	Cardiovascular Diseases Research	001	2	4/18/2024	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$284,410
2024	2023	UNIVERSITY OF MISSOURI SYSTEM	300 W. 12TH STREET	ROLLA	MO	65409	PHELPS	USA	Cardiovascular Diseases Research	000	1	4/18/2024	NEW	-$284,410
														Subtotal = $0

Issue Date FY: 2023 ( Subtotal = $308,927 )
2023	2023	UNIVERSITY OF MISSOURI SYSTEM	300 W 12TH ST	ROLLA	MO	65409	PHELPS	USA	Cardiovascular Diseases Research	000	1	4/7/2023	NEW	$308,927
														Subtotal = $308,927

Grand Total All Awards = $308,927

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Investigation and deployment of novel Bayesian inference algorithms in CAVATICA for identifying genomic variants underlying congenital heart defects in Down syndrome individuals

Award Number: R03HL168984

ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 05/01/2023

PERIOD OF PERFORMANCE END DATE: 04/30/2026

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