Genotype-phenotype correlation in the long-QT syndrome: Gene-specific triggers for life-threatening arrhythmias

Schwartz P.J. ; Priori S.G. ; Spazzolini C. ; Moss A.J. ; Michael Vincent G. ; Napolitano C. ; Denjoy I. ; Guicheney P. ; Breithardt G. ; Keating M.T. ; Towbin J.A. ; Beggs A.H. ; Brink P. ; Wilde A.A.M. ; Toivonen L. ; Zareba W. ; Robinson J.L. ; Timothy K.W. ; Corfield V. ; Wattanasirichaigoon D. ; Corbett C. ; Haverkamp W. ; Schulze-Bahr E. ; Lehmann M.H. ; Schwartz K. ; Coumel P. ; Bloise R. (2001)


Background - The congenital long-QT syndrome (LQTS) is caused by mutations on several genes, all of which encode cardiac ion channels. The progressive understanding of the electrophysiological consequences of these mutations opens unforeseen possibilities for genotype-phenotype correlation studies. Preliminary observations suggested that the conditions ("triggers") associated with cardiac events may in large part be gene specific. Methods and Results - We identified 670 LQTS patients of known genotype (LQT1, n=371; LQT2, n=234; LQT3, n=65) who had symptoms (syncope, cardiac arrest, sudden death) and examined whether 3 specific triggers (exercise, emotion, and sleep/rest without arousal) differed according to genotype. LQT1 patients experienced the majority of their events (62%) during exercise, and only 3% occurred during rest/sleep. These percentages were almost reversed among LQT2 and LQT3 patients, who were less likely to have events during exercise (13%) and more likely to have events during rest/sleep (29% and 39%). Lethal and nonlethal events followed the same pattern. Corrected QT interval did not differ among LQT1, LQT2, and LQT3 patients (498,497, and 506 ms, respectively). The percent of patients who were free of recurrence with β-blocker therapy was higher and the death rate was lower among LQT1 patients (81% and 4%, respectively) than among LQT2 (59% and 4%, respectively) and LQT3 (50% and 17%, respectively) patients. Conclusions - Life-threatening arrhythmias in LQTS patients tend to occur under specific circumstances in a gene-specific manner. These data allow new insights into the mechanisms that relate the electrophysiological consequences of mutations on specific genes to clinical manifestations and offer the possibility of complementing traditional therapy with gene-specific approaches.

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