Epistatic interaction of PDE4DIP and DES mutations in familial atrial fibrillation with slow conduction

Background: The genetic causes of atrial fibrillation (AF) with slow conduction are unknown. Methods: Eight kindreds with familial AF and slow conduction, including a family affected by early onset AF, heart block and incompletely penetrant non-ischemic cardiomyopathy (NICM) underwent whole exome sequencing. Results: A known pathogenic mutation in the desmin (DES) gene resulting in S13F substitution at a PKC phosphorylation site was identified in all four members of the kindred with early-onset AF and heart block, while only two developed NICM. Higher penetrance of the mutation for AF and heart block prompted the screening for DES modifier(s). A second deleterious mutation in the phosphodiesterase 4D interacting-protein (PDE4DIP) gene resulting in A123T substitution segregated with early onset AF, heart block and the DES mutation. Three additional novel deleterious PDE4DIP mutations were identified in four other unrelated kindreds. Characterization of PDE4DIP in vitro suggested impaired compartmentalization of PKA and PDE4D characterized by reduced colocalization with PDE4D, increased cAMP activation leading to higher PKA phosphorylation of the β2-adrenergic-receptor, and decreased PKA phosphorylation of Desmin in response to isoproterenol stimulation compared to wildtype PDE4DIP. Conclusion: Our findings identify an epistatic interaction between DES and PDE4DIP variants, increasing the penetrance for conduction disease and arrhythmia.

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Familial atrial rapid fibrillation associated with double mutations of SCN5A and KCNQ1

Cardiology in the Young ◽

10.1017/s1047951121000615 ◽

2021 ◽

pp. 1-3

Author(s):

Miwa Kanai ◽

Keiko Toyohara ◽

Morio Shoda

Keyword(s):

Atrial Fibrillation ◽

Paediatric Population ◽

Familial Case ◽

Familial Atrial Fibrillation

Abstract Familial atrial fibrillation is inherited and sporadically occurs in the paediatric population. Generally, fibrillated wavelets are reported at a frequency of approximately 6 Hz. Herein, we report a familial case presenting rapidly fibrillated wavelets at frequencies of approximately 12 to 30 Hz associated with KCNQ1 and SCN5A mutations.

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Abstract 18637: Recurrence Quantification Analysis to Distinguish Active From Passive Mechanisms of CFAEs During Catheter Ablation of Atrial Fibrillation

Circulation ◽

10.1161/circ.132.suppl_3.18637 ◽

2015 ◽

Vol 132 (suppl_3) ◽

Author(s):

Alex Baher ◽

Anil K Gehi ◽

Prabhat Kumar ◽

Eugene Chung ◽

Benjamin H Buck ◽

...

Keyword(s):

Atrial Fibrillation ◽

Catheter Ablation ◽

Recurrence Quantification Analysis ◽

Slow Conduction ◽

Recurrence Quantification ◽

Quantification Analysis ◽

Mean Cycle ◽

Recurrent Patterns ◽

Wave Break ◽

Complex Fractionated Atrial Electrograms

Background: Ablation of complex fractionated atrial electrograms (CFAEs) is controversial, primarily because of difficulty in visually distinguishing CFAEs representing an active site of driver activity from a passive site of double potentials, wave break, and/or slow conduction. We hypothesized that CFAEs within rotors in atrial fibrillation (AF) would exhibit highly recurrent behavior compared with CFAEs remote from these driver regions. Methods: Active and passive mechanisms of CFAE formation were simulated in several 2D 7.5 x 7.5 cm modified Luo-Rudy 1 models. CFAEs within areas of rotors were considered active, while those caused by wave break, slow conduction or double potentials remote from rotors were considered passive. Clinical signals were also collected during catheter ablation of paroxysmal AF (n=8 patients). An active driver CFAE site was defined by termination of AF with ablation followed by non-inducibility. A passive site was defined as CFAE occurring remotely. Detection of CFAEs was based on mean cycle length (MCL) calculated from 4 second windows using -dV/dt for detection (40ms refractory period/10ms maximum EGM width for simulations; 45ms/15ms respectively for clinical signals). Recurrence quantification analysis (RQA) was performed on discrete time series of simulated and clinical CFAE activations. Results: RQA was performed on 20 simulated EGMs. MCL was similar in both active and passive CFAEs (74±11ms and 78±6ms respectively, p=NS), but recurrence was significantly higher in active compared to passive sites (%recurrence: 61±22% active, 4±6% passive, p<0.01). In patients with AF, the driver sites were all located within the pulmonary vein antra while passive CFAEs were remote. The MCL of CFAEs at active driver sites was similar to that of passive sites (100±13ms active, 98±17ms passive, p=NS), but recurrence was significantly higher in the active driver sites (%recurrence: 18±15% active, 2±1% passive, p=0.02). Conclusion: CFAEs may occur due to either active or passive mechanisms. Sites within rotors or focal drivers of AF are more likely to exhibit recurrent patterns. RQA may be a powerful tool to differentiate driver from bystander CFAEs enabling more efficient targeting for ablation.

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