Predictors of arrhythmia recurrence in patients with non-valvular atrial fibrillation after sinus rhytmh restoring: the role of the rs10465885 polymrphism in connexin-40 gene

Main Article Content

T. V. Mikhalieva
O. S. Sychov
T. V. Getman
V. H. Hurianov
K. O. Mikhaliev

Abstract

The aim – to determine the predictors of arrhythmia recurrence in patients with non-valvular atrial fibrillation (AF) after the sinus rhythm (SR) restoring, and to establish the role of the rs10465885 polymorphism in connexin-40 (Cx40) gene.
Material and methods. We enrolled 104 patients (pts) with non-sustained non-valvular AF (average age (53±10) years, 80 (76.9 %) men). The distribution of rs10465885 polymorphic variants in Cx40 gene (n=73) was as follows:
TT – 17 (23.3 %) pts, CT – 33 (45.2 %), СС – 23 (31.5 %). We analyzed 122 cases of SR restoring: 32 (26.2 %) – pharmacological cardioversion (29 pts); 63 (51.6 %) – electrical cardioversion (ECV) (53 pts); 27 (22.2 %) – radiofrequency catheter ablation (RFA) (22 pts). The follow-up median was 23 months. According to the phenotypic parameters, associated with rs10465885, the sample of 104 pts (122 SR restoring cases) was stratified into 4 phenotypic clusters (PC): PC1 – 43 pts (57 SR restoring cases), PC2 – 24 (26); PC3 – 18 (20); and PC4 – 19 (19). According to PC and rs10465885 status (carriage or relatively high probability of non-CC or CC variant), the sample of 104 pts (122 SR restoring cases) was stratified into 4 integral clusters (IC): IC1 (PC1 + non-СС) – 26 pts (32 SR restoring cases); IC2 (PC1 + СС) – 17 (25); IC3 (combined group [РC234] + non-СС) – 49 (50); IC4 (РC234 + СС) – 12 (15).
Results. The risk of AF recurrence after ECV was 1,429 times higher than that of RFA. In addition, the risk of AF recurrence after restoration of SR in patients with the CHA2DS2-VASc scale score 1 was 1,550 times lower than in patients with 0 and ≥ 2 score. PC1, in comparison with PC234, was associated with a higher frequency of rs10465885 СС variant (taking into account the pts with a relatively high probability of СС carriage). PC1 was presented mainly by men under 40 years of age, with no pronounced structural and functional changes of the left ventricle. Additionally, PC1 was characterized by an earlier AF onset, the higher prevalence of subclinical AF, and a lower risk of stroke by the CHA2DS2-VASc scale. IC2 (vs IC4) was most significantly associated factor with the AF recurrence at 90 and 180 days after SR restoring.
Conclusions. The variant of SR restoring and the CHA2DS2-VASc score were the predictors of AF-free survival. The carriage (or relatively high probability of carriage) of the polymorphic variant rs10465885 СС in Cx40 gene additionally increases the risk of arrhythmia recurrence at the 3- and 6-month follow-up after SR restoration in patients with non-valvular AF and the PC1 features (as compared to PC234).

Article Details

Keywords:

atrial fibrillation, recurrence, sinus rhythm, rs10465885, connexin-40

References

Лях Ю.Е., Гурьянов В.Г., Хоменко В.Н., Панченко О.А. Основы компьютерной биостатистики. Анализ информации в биологии, медицине и фармации статистическим пакетом Medstat.– Донецк: Издатель Папакица Е.К., 2006.– 214 с.

Міхалєва Т.В., Сичов О.С., Гетьман Т.А. та ін. Гендерні аспекти фібриляції передсердь неклапанного генезу: поліморфізм rs10465885 гена конексину-40, фенотипові кластери пацієнтів та клінічні характеристики аритмії: матеріали VII Науково-практичної конференції Асоціації аритмологів України, (Київ, 18–19 травня 2017 р.) // Аритмологія.– 2017.– № 2.– С. 42-43.

Режим доступу: https://www.ensembl.org/Homo_sapiens/Variation/Explore?db=core;r=1:147760132-147761132;v=rs10465885;vdb=variation;vf=5960621.

Режим доступу: https://www.lifetechnologies.com/order/genome-database/browse/genotyping/keyword/rs10465885?ICID=uc-snp-rs10465885.

Сычев О.С., Михалева Т.В., Талаева Т.В. и др. Аллельный полиморфизм гена коннексина-40 (rs10465885) у пациентов с фибрилляцией предсердий неклапанного генеза // Укр. кардіол. журн.– 2015.– № 1.– С. 27–39.

Bapat A., Anderson C., Ellinor P., Lubitz S. Genomic basis of atrial fibrillation // Heart.– Published Online First: 11 September 2017.

Calkins H., Hindricks G., Cappato R. et al. 2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation // Heart Rhythm.– 2017.– Vol. 14 (10).– P. e275–e444.

Calkins H., Kuck K., Cappato R. et al. 2012 HRS/EHRA/ECAS Expert Consensus Statement on Catheter and Surgical Ablation of Atrial Fibrillation: Recommendations for Patient Selection, Procedural Techniques, Patient Management and Follow-up, Definitions, Endpoints, and Research Trial Design // J. Intervent. Cardiac Electrophysiology.– 2012.– Vol. 33 (2).– P. 171–257.

Camm J., Savelieva I., Potpara T. et al. The changing circumstance of atrial fibrillation – progress towards precision medicine // J. Intern. Medicine.– 2016.– Vol. 279.– P. 412–427.

Christophersen I., Holmegard H., Jabbari J. et al. Rare Variants in GJA5 Are Associated With Early-Onset Lone Atrial Fibrillation // Canad. J. Cardiology.– 2013.– Vol. 29.– P. 111–116.

Fatkin D., Santiago C., Huttner I. et al. Genetics of Atrial Fibrillation: State of the Art in 2017 // Heart, Lung and Circula­­­tion.– 2017.– Vol. 26 (9).– P. 894–901.

Gemel J., Levy A., Simon A. et al. Connexin40 abnormalities and atrial fibrillation in the human heart // J. Molec. Cell. Cardiology.– 2014.– Vol. 76.– P. 159–168.

Hall J., Ryan J., Bray B. et al. Merging Electronic Health Record Data and Genomics for Cardiovascular Research: A Science Advisory From the American Heart Association // Circulation: Cardiovascular Genetics.– 2016.– Vol 9 (2).– P. 192–202.

Haykin S. Neural Networks and Learning Machines.– Lon­­don: Pearson; 3rd edition, 2008.– 936 p.

Huang H., Darbar D. Genotype influence in responses to therapy for atrial fibrillation // Eхpert Review Cardiovasc. Therapy.– 2016.– Vol. 14 (10).– P. 1119–1131.

Jacobs V., May H., Bair T. et al. The impact of risk score (CHADS2 versus CHA2DS2-VASc) on long-term outcomes after atrial fibrillation ablation // Heart Rhythm.– 2015.– Vol. 12 (4).– P. 681–686.

Kao D., Stevens L., Hinterberg M., Görg C. Phenotype-Specific Association of Single-Nucleotide Polymorphisms with Heart Failure and Preserved Ejection Fraction: a Genome-Wide Association Analysis of the Cardiovascular Health Study // J. Cardiovasc. Translational Research.– 2017.– Vol. 10 (3).– P. 285–294.

Kiliszek M., Kozluk E., Franaszczyk M. et al. The 4q25, 1q21, and 16q22 polymorphisms and recurrence of atrial fibrillation after pulmonary vein isolation // Archives of Medical Science.– 2016.– Vol. 12 (1).– P. 38-44.

Kirchhof P., Breithardt G., Bax J. et al. A roadmap to improve the quality of atrial fibrillation management: proceedings from the fifth Atrial Fibrillation Network/European Heart Rhythm Association consensus conference // Europace.– 2016.– Vol. 18.– P. 37–50.

Lang R., Badano L., Mor-Avi V. et al. Recommendations for Cardiac Chamber Quantification by Echocardiography in Adults: An Update from the American Society of Echocardiography and the European Association of Cardiovascular Imaging // J. Amer. Soc. Echocardiography.– 2015.– Vol. 28 (1).– P. 1–39.e14.

Mikhalieva T., Sychov O., Getman T. et al. Integral clusters of patients with non-valvular atrial fibrillation, based on rs10465885 polymorphism in connexin-40 gene and phenotype: the risk of arrhythmia recurrence after sinus rhythm restoring // Eur. Heart J.– 2016.– Vol. 37 (Suppl. 1).– P. 884.

Pérez-Serra A., Campuzano O., Brugada R. Update about atrial fibrillation genetics // Current Opinion in Cardiology.– 2017.– Vol. 32 (3).– P. 246–252.

Roberts J., Marcus G. The burgeoning field of ablatogenomics // Circulation: Arrhythmia and Electrophysiology.– 2015.– Vol. 8 (2).– P. 258–260.

Shoemaker M., Bollmann A., Lubitz S. et al. Common Genetic Variants and Response to Atrial Fibrillation Ablation // Circulation: Arrhythmia and Electrophysiology.– 2015.– Vol. 8 (2).– P. 296–302.

Tada H, Kawashiri M, Yamagishi M, Hayashi K. Atrial fibrillation: an inherited cardiovascular disease – a commentary on genetics of atrial fibrillation: from families to genomes // J. Human Genetics.– 2016.– Vol. 61.– P. 3–4.

Tao Y., Zhang M., Li L. et al. Pitx2, an atrial fibrillation predisposition gene, directly regulates ion transport and intercalated disc genes // Circulation: Cardiovascular Genetics.– 2014.– Vol. 7 (1).– P. 23–32.

The Task Force for the Management of Atrial Fibrillation of the European Society of Cardiology (ESC). Guidelines for the management of atrial fibrillation // Eur. Heart J.– 2010.– Vol. 31.– P. 2369–2429.

The Task Force for the management of atrial fibrillation of the European Society of Cardiology (ESC). 2016 ESC Guidelines for the management of atrial fibrillation developed in collaboration with EACTS // Eur. Heart J.– 2016.– Vol. 37.– P. 2893–2962.

The Task Force on the management of stable coronary artery disease of the European Society of Cardiology. 2013 ESC guidelines on the management of stable coronary artery disease // Eur. Heart J.– 2013.– Vol. 34.– P. 2949–3003.

Tribulova N., Egan Benova T., Szeiffova Bacova B. et al. New aspects of pathogenesis of atrial fibrillation: remodeling of intercalated discs // J. Physiol. Pharmacology.– 2015.– Vol. 66 (5).– P. 625–634.

Weng L., Lunetta K., Müller-Nurasyid M. et al. Genetic Interactions with Age, Sex, Body Mass Index, and Hypertension in Relation to Atrial Fibrillation: The AFGen Consortium // Scientific Reports.– 2017.– Vol. 7 (1): 11303.

Wirka R., Gore S., Van Wagoner D. et al. A Common Connexin-40 Gene Promoter Variant Affects Connexin-40 Expression in Human Atria and Is Associated With Atrial Fibrillation // Circulation: Arrhythmia and Electrophysiology.– 2011.– Vol. 4 (1).– P. 87–93.

Xiao J., Liang D., Chen Y.. The genetics of atrial fibrillation: from the bench to the bedside // Annual Review of Genomics and Human Genetics.– 2011.– Vol. 12.– P. 73–96.

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