Clinical and molecular genetic risk determinants in adult long QT syndrome type 1 and 2 patients

长QT综合征 危险系数 QT间期 内科学 医学 心源性猝死 比例危险模型 赫尔格 心脏病学 置信区间 钾通道
作者
Mikael Koponen,Aki S. Havulinna,Annukka Marjamaa,Annukka M. Tuiskula,Veikko Salomaa,Päivi J. Laitinen-Forsblom,Kirsi Piippo,Lauri Toivonen,Kimmo Kontula,Matti Viitasalo,Heikki Swan
出处
期刊:BMC Medical Genetics [BioMed Central]
卷期号:19 (1) 被引量:9
标识
DOI:10.1186/s12881-018-0574-0
摘要

Long QT syndrome (LQTS) is an inherited cardiac disorder predisposing to sudden cardiac death (SCD). We studied factors affecting the clinical course of genetically confirmed patients, in particular those not receiving β-blocker treatment. In addition, an attempt was made to associate risk of events to specific types of KCNQ1 and KCNH2 mutations. A follow-up study covering a mean of 18.6 ± 6.1 years was conducted in 867 genetically confirmed LQT1 and LQT2 patients and 654 non-carrier relatives aged 18–40 years. Cox regression models were used to evaluate the contribution of clinical and genetic risk factors to cardiac events. In mutation carriers, risk factors for cardiac events before initiation of β-blocker included LQT2 genotype (hazard ratio [HR] = 2.1, p = 0.002), female gender (HR = 3.2, p < 0.001), a cardiac event before the age of 18 years (HR = 5.9, p < 0.001), and QTc ≥500 ms (vs < 470 ms, HR = 2.7, p = 0.001). LQT1 patients carrying the KCNQ1 D317N mutation were at higher risk (HR = 3.0–3.9, p < 0.001–0.03) compared to G589D, c.1129-2A > G and other KCNQ1 mutation carriers after adjusting for gender, QTc duration, and cardiac events before age 18. KCNH2 c.453delC, L552S and R176W mutations associated with lower risk (HR = 0.11–0.23, p < 0.001) than other KCNH2 mutations. LQT2 (compared to LQT1), female gender, a cardiac event before age 18, and long QT interval increased the risk of cardiac events in LQTS patients aged 18 to 40 years. The nature of the underlying mutation may be associated with risk variation in both LQT1 and LQT2. The identification of high-risk and low-risk mutations may enhance risk stratification.

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