Atrial fibrillation (AF) is the most common arrhythmia and affects about 3 million Americans, a number that is expected to rise to between 6 and 12 million by 2050. AF is a major public health burden as it is associated with a five-fold increased stroke risk, doubling in dementia risk, tripling in heart failure risk and nearly two-fold increasein mortality. Furthermore, the estimated excess cost of AF in the US is nearly $26 billion annually. Despite the profound socioeconomic costs of AF, our understanding of the fundamental mechanisms for the arrhythmia remains limited. Studies have consistently demonstrated that AF, and particularly early onset AF, is heritable. In recent years, we have led the international AFGen Consortium consisting of investigators from over 30 studies. We have identified multiple genetic loci through genome-wide association studies. We now propose a resource efficient program to conduct analyses of extant exome chip and exome sequencing data from AFGen cohorts. We will conduct bioinformatics-informed replication for genomic variant discovery in independent AF cases and controls followed by functional evaluation of the top genes.
Our specific aims are:
Aim 1. To discover AF-associated variants using extant exome chip data from 21 studies.
Aim 2. To discover AF-associated variants in extant exome sequencing data from 7 studies.
Aim 3. To replicate AF variants and genes identified in exome chip and exome sequencing projects by: A) Replicating the top 400 SNPs in 5,366 independent AF cases and 9,792 referents without AF; B) Replicating the top 10 genes associated with AF by candidate gene screening in 3,000 individuals with AF and 3,000 individuals without AF.
Aim 4. To characterize the electrophysiological phenotype of the top 25 newly identified AF genes in stem cell-derived cardiomyocytes, a zebrafish model system, and by cellular electrophysiology. We have developed innovative techniques for serial assessment of gene knockout or overexpression in induced pluripotent stem cell-derived cardiomyocytes. We will also examine the cardiac effects of gene knockdown or overexpression in zebrafish, followed by analyses of the atrial action potential duration, heart rate, and contractile function. Finally, if the AF varant resides in an ion channel, we will study the variant using patch clamp electrophysiology. We bring together a highly productive, multi-disciplinary, international consortium of AF investigator with expertise in AF epidemiology, AF genetics, bioinformatics, statistical genetics, developmental biology, and cellular electrophysiology. We anticipate that our translational approach will facilitate a greater understanding of the molecular basis of this common and morbid arrhythmia. Identification of causative variants may enhance risk stratification, and will provide preventive and therapeutic targets for drug discovery in the broader scientific and pharmaceutical community.

Public Health Relevance

Atrial fibrillation affects about 3 million Americans and increases the risk of stroke and death, but relatively little is known about the underlying mechanisms leading to the arrhythmia. The goals of our application are to identify new genetic variants associated with atrial fibrillation and to perform functional studies on these variants in basic science models. Finding causal variants will provide targets for drug discovery to prevent and treat atrial fibrillation.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL128914-01
Application #
8945634
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Lathrop, David A
Project Start
2015-08-01
Project End
2019-05-31
Budget Start
2015-08-01
Budget End
2016-05-31
Support Year
1
Fiscal Year
2015
Total Cost
Indirect Cost
Name
Boston University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
604483045
City
Boston
State
MA
Country
United States
Zip Code
Khurshid, Shaan; Choi, Seung Hoan; Weng, Lu-Chen et al. (2018) Frequency of Cardiac Rhythm Abnormalities in a Half Million Adults. Circ Arrhythm Electrophysiol 11:e006273
Nayor, Matthew; Enserro, Danielle M; Xanthakis, Vanessa et al. (2018) Comorbidities and Cardiometabolic Disease: Relationship With Longitudinal Changes in Diastolic Function. JACC Heart Fail 6:317-325
Long, Michelle T; Pedley, Alison; Massaro, Joseph M et al. (2018) A simple clinical model predicts incident hepatic steatosis in a community-based cohort: The Framingham Heart Study. Liver Int 38:1495-1503
Fetterman, Jessica L; Liu, Chunyu; Mitchell, Gary F et al. (2018) Relations of mitochondrial genetic variants to measures of vascular function. Mitochondrion 40:51-57
Vasan, Ramachandran S; Xanthakis, Vanessa; Lyass, Asya et al. (2018) Epidemiology of Left Ventricular Systolic Dysfunction and Heart Failure in the Framingham Study: An Echocardiographic Study Over 3 Decades. JACC Cardiovasc Imaging 11:1-11
Li, Wenyuan; Nyhan, Marguerite M; Wilker, Elissa H et al. (2018) Recent exposure to particle radioactivity and biomarkers of oxidative stress and inflammation: The Framingham Heart Study. Environ Int 121:1210-1216
Roselli, Carolina; Chaffin, Mark D; Weng, Lu-Chen et al. (2018) Multi-ethnic genome-wide association study for atrial fibrillation. Nat Genet 50:1225-1233
Staerk, Laila; Wang, Biqi; Preis, Sarah R et al. (2018) Lifetime risk of atrial fibrillation according to optimal, borderline, or elevated levels of risk factors: cohort study based on longitudinal data from the Framingham Heart Study. BMJ 361:k1453
Prins, Bram P; Mead, Timothy J; Brody, Jennifer A et al. (2018) Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6. Genome Biol 19:87
Bapat, Aneesh; Anderson, Christopher D; Ellinor, Patrick T et al. (2018) Genomic basis of atrial fibrillation. Heart 104:201-206

Showing the most recent 10 out of 67 publications