Cetaceans evolution:insights from the genome sequences of common minke whales

Background: Whales have captivated the human imagination for millennia. These incredible cetaceans are the only mammals that have adapted to life in the open oceans and have been a source of human food, fuel and tools around the globe. The transition from land to water has led to various aquatic specializations related to hairless skin and ability to regulate their body temperature in cold water. Results: We present four common minke whale (Balaenoptera acutorostrata) genomes with depth of ×13 ~ ×17 coverage and perform resequencing technology without a reference sequence. Our results indicated the time to the most recent common ancestors of common minke whales to be about 2.3574 (95% HPD, 1.1521 - 3.9212) million years ago. Further, we found that genes associated with epilation and tooth-development showed signatures of positive selection, supporting the morphological uniqueness of whales. Conclusions: This whole-genome sequencing offers a chance to better understand the evolutionary journey of one of the largest mammals on earth

Clinical and genetic relationships between the QTc interval and risk of a stroke among atrial fibrillation patients undergoing catheter ablation

Abstract Background and objectives A prolonged QTc interval is associated with an increased risk of a stroke or atrial fibrillation (AF). However, its direct causal relationship with AF associated a stroke has not been proven yet. To examine whether QTc interval is causally linked with risk of stroke in AF patients, we used the Mendelian randomization analysis. Subjects and methods Among 2742 patients (73.6% male; 58.2 ± 11.0 years old; 69.5% with paroxysmal AF) who underwent AF catheter ablation, we analyzed 1766 patients who had preablation sinus rhythm electrocardiograms off antiarrhythmic drugs after excluding amiodarone users. Among them, 1213 subjects had genome-wide association study dataset analyzable for the Mendelian randomization. We explored the mechanistic relationships between QTc interval (ms) and the risk of a stroke by analyzing the Mendelian randomization (1213 subjects) after reviewing 35 genetic polymorphisms associated with the QTc in 31 European descent studies. Results Among the patients in the higher quartile with a higher QTc, CHA2DS2-VASc score (p < 0.001), and age (p < 0.001), the proportions of a prior stroke (p < 0.001), females, heart failure, and persistent AF were significantly higher than in those in the lower quartile. The QTc was independently associated with the CHA2DS2-VASc score (β, 4.63E−5; 95% confidence interval, 3.57E−6–8.90E−5; p = 0.034) and ischemic strokes (odds ratio, 1.01; 95% confidence interval, 1.00–1.01; p = 0.027). However, there was no direct causal relationship between the QTc and CHA2DS2-VASc score or a prior stroke in either the one-sample or two-sample Mendelian randomizations. Conclusion The QTc was independently associated with the CHA2DS2-VASc score and strokes among the patients with AF who underwent catheter ablation, despite no genetically direct causal relationship

Image_1_Association of ZFHX3 Genetic Polymorphisms and Extra-Pulmonary Vein Triggers in Patients With Atrial Fibrillation Who Underwent Catheter Ablation.TIF

Background: The ZFHX3 gene (16q22) is the second most highly associated gene with atrial fibrillation (AF) and is related to inflammation and fibrosis. We hypothesized that ZFHX3 is associated with extra-pulmonary vein (PV) triggers, left atrial (LA) structural remodeling, and poor rhythm outcomes of AF catheter ablation (AFCA).Methods: We included 1,782 patients who underwent a de novo AFCA (73.5% male, 59.4 ± 10.8 years old, 65.9% paroxysmal AF) and genome-wide association study and divided them into discovery (n = 891) and replication cohorts (n = 891). All included patients underwent isoproterenol provocation tests and LA voltage mapping. We analyzed the ZFHX3, extra-PV trigger-related factors, and rhythm outcomes.Result: Among 14 single-nucleotide polymorphisms (SNPs) of ZFHX3, rs13336412, rs61208973, rs2106259, rs12927436, and rs1858801 were associated with extra-PV triggers. In the overall patient group, extra-PV triggers were independently associated with the ZFHX3 polygenic risk score (PRS) (OR 1.65 [1.22–2.22], p = 0.001, model 1) and a low LA voltage (OR 0.74 [0.56–0.97], p = 0.029, model 2). During 49.9 ± 40.3 months of follow-up, clinical recurrence of AF was significantly higher in patients with extra-PV triggers (Log-rank p Conclusion: The extra-PV triggers had significant associations with both ZFHX3 genetic polymorphisms and acquired LA remodeling. Although extra-PV triggers were an independent predictor of AF recurrence after AFCA, the studied AF risk SNPs intronic in ZFHX3 were not associated with AF recurrence.</p

Data_Sheet_1_Association of ZFHX3 Genetic Polymorphisms and Extra-Pulmonary Vein Triggers in Patients With Atrial Fibrillation Who Underwent Catheter Ablation.docx

Background: The ZFHX3 gene (16q22) is the second most highly associated gene with atrial fibrillation (AF) and is related to inflammation and fibrosis. We hypothesized that ZFHX3 is associated with extra-pulmonary vein (PV) triggers, left atrial (LA) structural remodeling, and poor rhythm outcomes of AF catheter ablation (AFCA).Methods: We included 1,782 patients who underwent a de novo AFCA (73.5% male, 59.4 ± 10.8 years old, 65.9% paroxysmal AF) and genome-wide association study and divided them into discovery (n = 891) and replication cohorts (n = 891). All included patients underwent isoproterenol provocation tests and LA voltage mapping. We analyzed the ZFHX3, extra-PV trigger-related factors, and rhythm outcomes.Result: Among 14 single-nucleotide polymorphisms (SNPs) of ZFHX3, rs13336412, rs61208973, rs2106259, rs12927436, and rs1858801 were associated with extra-PV triggers. In the overall patient group, extra-PV triggers were independently associated with the ZFHX3 polygenic risk score (PRS) (OR 1.65 [1.22–2.22], p = 0.001, model 1) and a low LA voltage (OR 0.74 [0.56–0.97], p = 0.029, model 2). During 49.9 ± 40.3 months of follow-up, clinical recurrence of AF was significantly higher in patients with extra-PV triggers (Log-rank p Conclusion: The extra-PV triggers had significant associations with both ZFHX3 genetic polymorphisms and acquired LA remodeling. Although extra-PV triggers were an independent predictor of AF recurrence after AFCA, the studied AF risk SNPs intronic in ZFHX3 were not associated with AF recurrence.</p

Data_Sheet_1_Computational Modeling for Antiarrhythmic Drugs for Atrial Fibrillation According to Genotype.docx

Background: The efficacy of antiarrhythmic drugs (AAD) can vary in patients with atrial fibrillation (AF), and the PITX2 gene affects the responsiveness of AADs. We explored the virtual AAD (V-AAD) responses between wild-type and PITX2+/−-deficient AF conditions by realistic in silico AF modeling.Methods: We tested the V-AADs in AF modeling integrated with patients' 3D-computed tomography and 3D-electroanatomical mapping, acquired in 25 patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal type). The ion currents for the PITX2+/− deficiency and each AAD (amiodarone, sotalol, dronedarone, flecainide, and propafenone) were defined based on previous publications.Results: We compared the wild-type and PITX2+/− deficiency in terms of the action potential duration (APD90), conduction velocity (CV), maximal slope of restitution (Smax), and wave-dynamic parameters, such as the dominant frequency (DF), phase singularities (PS), and AF termination rates according to the V-AADs. The PITX2+/−-deficient model exhibited a shorter APD90 (p +/−-deficient than wild-type AF. PITX2+/−-deficient AF was easier to terminate with class IC AADs than the wild-type AF (p = 0.018).Conclusions: The computational modeling-guided AAD test was feasible for evaluating the efficacy of multiple AADs in patients with AF. AF wave-dynamic and electrophysiological characteristics are different among the PITX2-deficient and the wild-type genotype models.</p

Image_1_Computational Modeling for Antiarrhythmic Drugs for Atrial Fibrillation According to Genotype.TIF

Background: The efficacy of antiarrhythmic drugs (AAD) can vary in patients with atrial fibrillation (AF), and the PITX2 gene affects the responsiveness of AADs. We explored the virtual AAD (V-AAD) responses between wild-type and PITX2+/−-deficient AF conditions by realistic in silico AF modeling.Methods: We tested the V-AADs in AF modeling integrated with patients' 3D-computed tomography and 3D-electroanatomical mapping, acquired in 25 patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal type). The ion currents for the PITX2+/− deficiency and each AAD (amiodarone, sotalol, dronedarone, flecainide, and propafenone) were defined based on previous publications.Results: We compared the wild-type and PITX2+/− deficiency in terms of the action potential duration (APD90), conduction velocity (CV), maximal slope of restitution (Smax), and wave-dynamic parameters, such as the dominant frequency (DF), phase singularities (PS), and AF termination rates according to the V-AADs. The PITX2+/−-deficient model exhibited a shorter APD90 (p +/−-deficient than wild-type AF. PITX2+/−-deficient AF was easier to terminate with class IC AADs than the wild-type AF (p = 0.018).Conclusions: The computational modeling-guided AAD test was feasible for evaluating the efficacy of multiple AADs in patients with AF. AF wave-dynamic and electrophysiological characteristics are different among the PITX2-deficient and the wild-type genotype models.</p

DataSheet1_Corrigendum: Computational modeling for antiarrhythmic drugs for atrial fibrillation according to genotype.docx

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Image_4_Computational Modeling for Antiarrhythmic Drugs for Atrial Fibrillation According to Genotype.TIF

Background: The efficacy of antiarrhythmic drugs (AAD) can vary in patients with atrial fibrillation (AF), and the PITX2 gene affects the responsiveness of AADs. We explored the virtual AAD (V-AAD) responses between wild-type and PITX2+/−-deficient AF conditions by realistic in silico AF modeling.Methods: We tested the V-AADs in AF modeling integrated with patients' 3D-computed tomography and 3D-electroanatomical mapping, acquired in 25 patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal type). The ion currents for the PITX2+/− deficiency and each AAD (amiodarone, sotalol, dronedarone, flecainide, and propafenone) were defined based on previous publications.Results: We compared the wild-type and PITX2+/− deficiency in terms of the action potential duration (APD90), conduction velocity (CV), maximal slope of restitution (Smax), and wave-dynamic parameters, such as the dominant frequency (DF), phase singularities (PS), and AF termination rates according to the V-AADs. The PITX2+/−-deficient model exhibited a shorter APD90 (p +/−-deficient than wild-type AF. PITX2+/−-deficient AF was easier to terminate with class IC AADs than the wild-type AF (p = 0.018).Conclusions: The computational modeling-guided AAD test was feasible for evaluating the efficacy of multiple AADs in patients with AF. AF wave-dynamic and electrophysiological characteristics are different among the PITX2-deficient and the wild-type genotype models.</p

Image_3_Computational Modeling for Antiarrhythmic Drugs for Atrial Fibrillation According to Genotype.TIF

Background: The efficacy of antiarrhythmic drugs (AAD) can vary in patients with atrial fibrillation (AF), and the PITX2 gene affects the responsiveness of AADs. We explored the virtual AAD (V-AAD) responses between wild-type and PITX2+/−-deficient AF conditions by realistic in silico AF modeling.Methods: We tested the V-AADs in AF modeling integrated with patients' 3D-computed tomography and 3D-electroanatomical mapping, acquired in 25 patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal type). The ion currents for the PITX2+/− deficiency and each AAD (amiodarone, sotalol, dronedarone, flecainide, and propafenone) were defined based on previous publications.Results: We compared the wild-type and PITX2+/− deficiency in terms of the action potential duration (APD90), conduction velocity (CV), maximal slope of restitution (Smax), and wave-dynamic parameters, such as the dominant frequency (DF), phase singularities (PS), and AF termination rates according to the V-AADs. The PITX2+/−-deficient model exhibited a shorter APD90 (p +/−-deficient than wild-type AF. PITX2+/−-deficient AF was easier to terminate with class IC AADs than the wild-type AF (p = 0.018).Conclusions: The computational modeling-guided AAD test was feasible for evaluating the efficacy of multiple AADs in patients with AF. AF wave-dynamic and electrophysiological characteristics are different among the PITX2-deficient and the wild-type genotype models.</p

Image_2_Computational Modeling for Antiarrhythmic Drugs for Atrial Fibrillation According to Genotype.TIF

Background: The efficacy of antiarrhythmic drugs (AAD) can vary in patients with atrial fibrillation (AF), and the PITX2 gene affects the responsiveness of AADs. We explored the virtual AAD (V-AAD) responses between wild-type and PITX2+/−-deficient AF conditions by realistic in silico AF modeling.Methods: We tested the V-AADs in AF modeling integrated with patients' 3D-computed tomography and 3D-electroanatomical mapping, acquired in 25 patients (68% male, 59.8 ± 9.8 years old, 32.0% paroxysmal type). The ion currents for the PITX2+/− deficiency and each AAD (amiodarone, sotalol, dronedarone, flecainide, and propafenone) were defined based on previous publications.Results: We compared the wild-type and PITX2+/− deficiency in terms of the action potential duration (APD90), conduction velocity (CV), maximal slope of restitution (Smax), and wave-dynamic parameters, such as the dominant frequency (DF), phase singularities (PS), and AF termination rates according to the V-AADs. The PITX2+/−-deficient model exhibited a shorter APD90 (p +/−-deficient than wild-type AF. PITX2+/−-deficient AF was easier to terminate with class IC AADs than the wild-type AF (p = 0.018).Conclusions: The computational modeling-guided AAD test was feasible for evaluating the efficacy of multiple AADs in patients with AF. AF wave-dynamic and electrophysiological characteristics are different among the PITX2-deficient and the wild-type genotype models.</p