Prospective Identification of Long QT Syndrome in Fetal Life

University of Colorado, Denver25 enrolled

Overview

The postnatal diagnosis of Long QT Syndrome (LQTS) is suggested by a prolonged QT interval on 12 lead electrocardiogram (ECG), strengthened by a positive family history and/or characteristic arrhythmias and confirmed by genetic testing. However, for several reasons such LQTS testing cannot be performed successfully before birth. First, fetal ECG is not possible and direct measure of the fetal QT interval by magnetocardiography is limited to fewer than 10 sites world-wide. Second, while genetic testing can be performed in utero, there is risk to the pregnancy and the fetus. Third, although some fetuses present with arrhythmias easily recognized as LQTS (torsade des pointes (TdP) and/or 2° atrioventricular (AV) block, this is uncommon, occurring in \<25% of fetal LQTS cases. Rather, the most common presentation of fetal LQTS is sinus bradycardia, a subtle rhythm disturbance that often is unappreciated to be abnormal. Consequently, the majority of LQTS cases are unsuspected and undiagnosed during fetal life, with dire consequences. For example, maternal medications commonly used during pregnancy can prolong the fetal QT interval and may provoke lethal fetal ventricular arrhythmias. But the most significant consequence is the missed opportunity for primary prevention of life threatening ventricular arrhythmias after birth because the infant is not suspected to have LQTS before birth. The over-arching goal of the study is to overcome the barriers to prenatal detection of LQTS. The investigators plan to do so by developing an algorithm using fetal heart rate (FHR) which will discriminate fetuses with or without LQTS. Immediate Goal: The investigators propose a multicenter pre-birth observational cohort study to develop a Fetal Heart Rate (FHR)/Gestational Age (GA) algorithm from a cohort of fetuses recruited from 13 national and international centers where one parent is known by prior genetic testing to have a mutation in one of the common LQTS genes: potassium voltage-gated channel subfamily Q member 1 (KCNQ1), potassium voltage-gated channel subfamily H member 2 (KCNH2), or sodium voltage-gated channel alpha subunit 5 (SCN5A). The investigators have chosen this population because 1) These mutations are the most common genetic causes of LQTS, and 2) Offspring will have high risk of LQTS as inheritance of these LQTS gene mutations is autosomal dominant. Thus, progeny of parents with a known mutation are at high (50%) risk of having the same parental LQTS mutation. The algorithm will be developed using FHR measured serially throughout pregnancy. All offspring will undergo postnatal genetic testing for the parental mutation as the gold standard for diagnosing the presence or absence of LQTS.

Ascertainment of LQTS, an inherited arrhythmia disorder in a group of conditions known as the channelopathies, is challenging before birth. Recently, in a retrospective study it was reported that a gestational age dependent bradycardia allows a much higher recognition of genotype positive LQTS than the standard obstetrical gestational age independent definition of bradycardia (Mitchell 2012). However, the fetal heart rate in pregnancies with maternal or paternal LQTS diagnosed prior to the pregnancy has not been evaluated prospectively from the first trimester to birth. Nor is it known if the fetal heart rate /gestational age profile might be mutation specific. In addition, the use of fetal heart rate to successfully distinguish between LQTS and normal fetuses of pregnancies in which a parent has a known mutation has not been tested. The investigators believe that fetuses with an LQTS mutation born to families in which the mother or father has an LQTS mutation will have slower heart compared to fetuses, shown after birth not to have the family mutation. If the investigators hypothesis is correct, these findings could be applied to the general population of pregnant women to prospectively identify fetuses with LQTS and without a known family history. Since a fetal proband has been led to the identification of unsuspecting family members, prospectively identifying affected fetuses would increase ascertainment of life-threatening mutations in all ages (Cuneo 2013).

Eligibility

Sex: ALLMin age: 18 YearsMax age: 45 Years

Medical Language ↔ Plain English

Inclusion Criteria: (Prospective arm) 1. 18-45 years of age 2. Pregnant women with a previously identified mutation in a known LQTS gene or pregnant women whose partner (and the father of the baby) has a previously identified mutation in a known LQTS gene will be invited to participate. If the pregnant partner of a man with a LQTS gene is enrolled, then the man/father of child will be enrolled as well. 3. Women at 7-30 weeks of gestation Exclusion Criteria: (Prospective arm) 1. Phenotype positive but genotype negative pregnant woman or father of the fetus, 2. Fetuses with congenital or chromosomal anomaly identified before or after birth 3. Pregnant women who present beyond 30 weeks of pregnancy. Inclusion Criteria (Retrospective arm) 1. 18-45 years of age 2. Women with a previous pregnancy and a known LQTS gene or where the father of the baby had a known LQTS gene 3. Women with a mutation in a known LQTS gene, or 4. Women whose partner/father of the baby has a mutation in a known LQTS gene (The father of the child will be enrolled if mother of child is enrolled) Exclusion Criteria (Retrospective arm) 1. Phenotype positive but genotype negative pregnant woman or father of the fetus, 2. Fetuses with congenital or chromosomal anomaly identified before or after birth 3. Fetal heart rate data unavailable prior to 30 weeks of pregnancy

Outcomes

Primary Outcomes

Effectiveness of an Fetal Heart Rate/Gestational Age, FHR/GA, Algorithm

The investigators hypothesize that from this fetal cohort, they can construct a FHR/GA algorithm that will discriminate fetuses who inherit the parental LQTS mutation from those who do not, with an area under the ROC ≥0.75.

Time frame: 5 years

Differences in the Receiver Operating Characteristic (ROC) of FHR/GA vs gold standard of genetic testing

The area under the ROC of the FHR/GA algorithm compared to a gold standard of genetic testing will remain ≥0.75 across mutation types and offspring sex. Based on power calculations using preliminary studies, the investigators estimate they can test this hypothesis by study of 200 fetal subjects.