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Molecular Mechanisms of Atrial Fibrillation: A Multimodal Analysis

Award Number: R01HL170520
ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 04/01/2024
PERIOD OF PERFORMANCE END DATE: 03/31/2029

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Molecular Mechanisms of Atrial Fibrillation: A Multimodal Analysis - Abstract Atrial fibrillation (AF) is the most common arrhythmia especially in the aging population. It is associated with increased risk of mortality and morbidity. At the present time, management of AF has focused on risk factor modification, rate or rhythm control and anticoagulation. Evolution of clinical trials in the management of AF have revealed that ablation seems superior in reducing the burden of AF and controlling the symptoms compared to pharmaceutical agents. However, the benefit of ablation decreases over time and patients frequently require more than one ablation. Earlier ablation in the course of the disease is more beneficial as failure of therapy is related to duration of AF and size of left atrium. After two decades of investigations with varying methods of ablation, we have only marginally improved the clinical outcome. The ablation procedure is time consuming and only a fraction of patients are undergoing this procedure. A robust criterion of prediction of successful ablation will be beneficial for patient selection and maximize the utilization of invasive therapies. With this highly collaborative and multiscale study, our long-term goal is to develop effective models and discover factors that indicate severity of AF that can be helpful as therapeutic targets and to predict prognosis. Our objective is to identify patients who have increased risk of recurrence after ablation for AF by taking advantage of the intracardiac electrograms from left atrial map and inflammatory biomarkers from blood samples obtained pre-procedure. The central hypothesis is that domain-specific machine learning/ artificial intelligence algorithms derived from multimodal data can predict the type of AF, severity of AF as indicated by abnormal areas in the left atrium and clinical outcomes of AF ablation. To directly test the hypothesis, we will enroll prospective consecutive consenting patients who present for AF ablation therapy. Pre-and post-ablation left atrial map and blood samples drawn for biomarker analyses will be used for study purposes.


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 = $500,891 )
2025	2024	UNIVERSITY OF ARIZONA	845 N PARK AVE RM 538	TUCSON	AZ	85721	PIMA	USA	Cardiovascular Diseases Research	001	2	5/1/2025	CHANGE OF GRANTEE / TRAINING INSTITUTION / AWARDING INSTITUTION	$500,891
2025	2024	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR STE 300	DAVIS	CA	95618	YOLO	USA	Cardiovascular Diseases Research	000	1	4/30/2025	NEW	$0
														Subtotal = $500,891

Issue Date FY: 2024 ( Subtotal = $768,911 )
2024	2024	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR, STE 300	DAVIS	CA	95618	YOLO	USA	Cardiovascular Diseases Research	000	1	3/15/2024	NEW	$692,019
2024	2024	UNIVERSITY OF CALIFORNIA, DAVIS	1850 RESEARCH PARK DR STE 300	DAVIS	CA	95618	YOLO	USA	Cardiovascular Diseases Research	001	1	6/21/2024	NEW	$76,892
														Subtotal = $768,911

Grand Total All Awards = $1,269,802

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Molecular Mechanisms of Atrial Fibrillation: A Multimodal Analysis

Award Number: R01HL170520

ORGANIZATION: NATIONAL HEART, LUNG, & BLOOD INSTITUTE

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

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

PERIOD OF PERFORMANCE START DATE: 04/01/2024

PERIOD OF PERFORMANCE END DATE: 03/31/2029

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