Epigenetic and Transcriptional Networks Underlying Atrial Fibrillation. Issue 1 (19th June 2020)

• Record Type: Journal Article
• Authors: van Ouwerkerk, Antoinette F.; Hall, Amelia W.; Kadow, Zachary A.; Lazarevic, Sonja; Reyat, Jasmeet S.; Tucker, Nathan R.; Nadadur, Rangarajan D.; Bosada, Fernanda M.; Bianchi, Valerio; Ellinor, Patrick T.; Fabritz, Larissa; Martin, James F.; de Laat, Wouter; Kirchhof, Paulus; Moskowitz, Ivan P.; Christoffels, Vincent M.
• Is Part Of: Circulation research. Volume 127:Issue 1(2020)
• Publication Date: 2020-06-19
• Subjects: atrial fibrillation -- myocytes, cardiac -- genetic variation -- genome-wide association study -- transcription factors; Cardiovascular system -- Periodicals; Blood -- Circulation -- Periodicals; Blood Circulation; Cardiovascular System; Vascular Diseases; Sang -- Circulation -- Périodiques; Appareil cardiovasculaire -- Périodiques; 612.1
• DOI: 10.1161/CIRCRESAHA.120.316574
• Languages: English
• ISSNs: 0009-7330

Abstract

Abstract : Genome-wide association studies have uncovered over a 100 genetic loci associated with atrial fibrillation (AF), the most common arrhythmia. Many of the top AF-associated loci harbor key cardiac transcription factors, including PITX2, TBX5, PRRX1, and ZFHX3. Moreover, the vast majority of the AF-associated variants lie within noncoding regions of the genome where causal variants affect gene expression by altering the activity of transcription factors and the epigenetic state of chromatin. In this review, we discuss a transcriptional regulatory network model for AF defined by effector genes in Genome-wide association studies loci. We describe the current state of the field regarding the identification and function of AF-relevant gene regulatory networks, including variant regulatory elements, dose-sensitive transcription factor functionality, target genes, and epigenetic states. We illustrate how altered transcriptional networks may impact cardiomyocyte function and ionic currents that impact AF risk. Last, we identify the need for improved tools to identify and functionally test transcriptional components to define the links between genetic variation, epigenetic gene regulation, and atrial function.