How Will Genetics Inform the Clinical Care of Atrial Fibrillation?

Abstract

Susceptibility to atrial fibrillation (AF) is determined by well-recognized risk factors such as diabetes mellitus or hypertension, emerging risk factors such as sleep apnea or inflammation, and increasingly well-defined genetic variants. As discussed in detail in a companion article in this series, studies in families and in large populations have identified multiple genetic loci, specific genes, and specific variants increasing susceptibility to AF. Since it is becoming increasingly inexpensive to obtain genotype data and indeed whole genome sequence data, the question then becomes to define whether using emerging new genetics knowledge can improve care for patients both before and after development of AF. Examples of improvements in care could include identifying patients at increased risk for AF (and thus deploying increased surveillance or even low-risk preventive therapies should these be available), identifying patient subsets in whom specific therapies are likely to be effective or ineffective or in whom the driving biology could motivate the development of new mechanism-based therapies or identifying an underlying susceptibility to comorbid cardiovascular disease. While current guidelines for the care of patients with AF do not recommend routine genetic testing, this rapidly increasing knowledge base suggests that testing may now or soon have a place in the management of select patients. The opportunity is to generate, validate, and deploy clinical predictors (including family history) of AF risk, to assess the utility of incorporating genomic variants into those predictors, and to identify and validate interventions such as wearable or implantable device-based monitoring ultimately to intervene in patients with AF before they present with catastrophic complications like heart failure or stroke.

Keywords: atrial fibrillation; genetics; humans; hypertension; risk factors.

Figures

Figure 1.. Results from a recent AF GWAS.

The 4q25 AF susceptibility locus is one of the most significant genetic associations detected for any phenotype with a P-value equal to 3.4×10−155. 22 other loci at which common variants are associated with AF at the genome-wide significance level (P<5 × 10−8) are shown. Figure courtesy of Patrick Ellinor.

Figure 2.. The evolution of polygenic risk scores for AF.

Early experience with PRS in AF used 3 SNVs from the 4q25 locus (Panel A) compared to a recent PRS in AF that used 6,730,541 SNVs (Panel B). Panel A: Reproduced with permission from Circulation. 2010. 122(10): 976–984. Copyright © 2010 American Heart Association. All rights reserved. Panel B: Reproduced with permission from Nature Genetics. 2018. 50(9): 1219–1224. Copyright © 2018 Nature Publishing Group. All rights reserved

Figure 3.. Leveraging genetics for biomarker research.

Using a population that has both GWAS data and a biomarker measured (e.g. TSH), a PRS can be derived to predict that biomarker’s value in any separate population with GWAS data. Using this “virtual biomarker” approach, a PRS for TSH was shown to be associated with thyroid disorders and AF. Reproduced with permission from JAMA. 2019. 4(2):136–143. Copyright © 2019 American Medical Association. All rights reserved.

Figure 4.. The association of titin (TTN) LOF in patients with AF.

The odds of having TTN LOF compared to control participants increases with younger age at AF diagnosis and was found to be highest in individuals diagnosed before the age of 30 years. Reproduced and modified with permission from JAMA. 2019. 320 (22): 2354–2364. Copyright © 2019 American Medical Association. All rights reserved.

Figure 5.. Rare Inherited Disorders Associated with AF.

Displayed are examples of up to 3 genes associated with each inherited disorder, many of which have independently been linked with AF. * Genes associated with AF in linkage analysis. § Gene association with AF in rare variant association study. Ϯ Genes associated with high frequency of AF in corresponding disease. CM- cardiomyopathy. LV- left ventricular. CPVT- catecholaminergic polymorphic VT.

Figure 6.. Proposed evaluation of individuals with AF onset before age 45 or with a family history of early onset AF.

*The presence of a causative factor does not preclude evaluating the individual for a genetic etiology if the clinical features or family history suggest an underlying genetic susceptibility exits. † Gene-guided management includes additional diagnostic testing (e.g. sodium-channel blocker challenge, signal averaged ECG) or treatments (e.g. physical activity restrictions, implantable cardioverter defibrillators) for specific inherited syndromes. EPS- electrophysiology study. PE- pulmonary embolism. MI- myocardial infarction. SVT- supraventricular tachycardia. AVNRT- atrioventricular nodal reentrant tachycardia. AVRT- atrioventricular reentrant tachycardia.

Figure 7.. Proposed evaluation for early-onset AF that integrates family history and genetic risk assessment with traditional clinical risk assessment.

HF- heart failure. SCD- sudden cardiac death. DCM- dilated cardiomyopathy. RCTs- randomized controlled trials.