Long QT Syndrome-Associated Mutations in Intrauterine Fetal Death

Department of Molecular Medicine, University of Pavia, and Molecular Cardiology Laboratory, Fondazione IRRCCS Policlinico S Matteo, Pavia, Italy.
JAMA The Journal of the American Medical Association (Impact Factor: 35.29). 04/2013; 309(14):1473-82. DOI: 10.1001/jama.2013.3219
Source: PubMed


Intrauterine fetal death or stillbirth occurs in approximately 1 out of every 160 pregnancies and accounts for 50% of all perinatal deaths. Postmortem evaluation fails to elucidate an underlying cause in many cases. Long QT syndrome (LQTS) may contribute to this problem.
To determine the spectrum and prevalence of mutations in the 3 most common LQTS susceptible genes (KCNQ1, KCNH2, and SCN5A) for a cohort of unexplained cases.
In this case series, retrospective postmortem genetic testing was conducted on a convenience sample of 91 unexplained intrauterine fetal deaths (mean [SD] estimated gestational age at fetal death, 26.3 [8.7] weeks) that were collected from 2006-2012 by the Mayo Clinic, Rochester, Minnesota, or the Fondazione IRCCS Policlinico San Matteo, Pavia, Italy. More than 1300 ostensibly healthy individuals served as controls. In addition, publicly available exome databases were assessed for the general population frequency of identified genetic variants. MAIN OUTCOMES AND MEASURES: Comprehensive mutational analyses of KCNQ1 (KV7.1, LQTS type 1), KCNH2 (HERG/KV11.1, LQTS type 2), and SCN5A (NaV1.5, LQTS type 3) were performed using denaturing high-performance liquid chromatography and direct DNA sequencing on genomic DNA extracted from decedent tissue. Functional analyses of novel mutations were performed using heterologous expression and patch-clamp recording.
The 3 putative LQTS susceptibility missense mutations (KCNQ1, p.A283T; KCNQ1, p.R397W; and KCNH2 [1b], p.R25W), with a heterozygous frequency of less than 0.05% in more than 10 000 publicly available exomes and absent in more than 1000 ethnically similar control patients, were discovered in 3 intrauterine fetal deaths (3.3% [95% CI, 0.68%-9.3%]). Both KV7.1-A283T (16-week male) and KV7.1-R397W (16-week female) mutations were associated with marked KV7.1 loss-of-function consistent with in utero LQTS type 1, whereas the HERG1b-R25W mutation (33.2-week male) exhibited a loss of function consistent with in utero LQTS type 2. In addition, 5 intrauterine fetal deaths hosted SCN5A rare nonsynonymous genetic variants (p.T220I, p.R1193Q, involving 2 cases, and p.P2006A, involving 2 cases) that conferred in vitro electrophysiological characteristics consistent with potentially proarrhythmic phenotypes.
In this molecular genetic evaluation of 91 cases of intrauterine fetal death, missense mutations associated with LQTS susceptibility were discovered in 3 cases (3.3%) and overall, genetic variants leading to dysfunctional LQTS-associated ion channels in vitro were discovered in 8 cases (8.8%). These preliminary findings may provide insights into mechanisms of some cases of stillbirth.

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Available from: Daniel C Bartos, Feb 04, 2015
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    • "Genome sequencing will be integrated into clinical care in many ways. It is already demonstrating clinical utility for the diagnosis and treatment of certain cancers [5,19] and rare diseases [2,3,20-22] and shows promise for use in infectious disease outbreaks [23-25] and fetal diagnosis in prenatal medicine [7,26]. The design of the MedSeq Project models two archetypal scenarios for how WGS could be integrated into clinical care. "
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    • "Nowadays, next-generation sequencing (NGS) is increasingly being used in genetic diagnostics for studying congenital malformations, intellectual disability, and other heterogeneous disorders. Although mutations in genes are known to cause fetal death [38], a systematic genome-wide study has not been performed yet, leaving a large proportion of fetal demise unexplained. It is already demonstrated that NGS not only enables the detection of Single Nucleotide Variation but CNVs as well [39], thus very soon replacing genome wide array analysis in diagnostics. "
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    ABSTRACT: The aim of this study was to evaluate the best diagnostic approach for the genetic analysis of samples from first, second and third trimester intrauterine fetal deaths (IUFDs). We examined a total of 417 IUFD samples from fetuses with and without congenital anomalies. On 414 samples, karyotyping (N = 46) and/or rapid aneuploidy testing by QF-PCR (N = 371) was performed). One hundred sixty eight samples with a normal test result were subsequently tested by genome wide Single Nucleotide Polymorphism (SNP) array analysis. Three samples were only analyzed by array. In 50 (12.0%) samples an aneuploidy was detected by QF-PCR and/or karyotyping, representing 47.1% of first, 13.2% of second and 3.4% of third trimester pregnancies. Karyotyping and QF-PCR failed in 4 (8.7%) and 7 (1.9%) samples, respectively, concerning mostly contaminated amniotic fluid samples from third trimester pregnancies.Clinically relevant aberrations were identified in 4.2% (all fetuses with malformations) of the 168 samples tested by SNP array. Inherited copy number variants (CNVs) were detected in 5.4% and 8.9% showed CNVs of unknown clinical relevance as parental inheritance could not be studied yet. In a sample from a fetus suspect for Meckel-Gruber syndrome, the genotype information from the SNP array revealed various stretches of homozygosity, including one stretch encompassing the CEP290 gene. Subsequent CEP290 mutation analysis revealed a homozygous, pathogenic mutation in this gene. Based on our experience we recommend QF-PCR as the first-line test in IUFD samples of first and second trimester pregnancies to exclude aneuploidy before performing array analysis. The chance to detect aneuploidy in third trimester pregnancies is relatively low and therefore array analysis can be performed as a first-tier test. A tissue sample, instead of amniotic fluid, is preferred because of a higher success rate in testing.We emphasize the need for analysis of parental samples whenever a rare, unique CNV is detected to allow for better interpretation of such findings and to improve future pregnancy management. Furthermore, we illustrate the strength of SNP arrays for genotype analysis, even though we realize it is crucial to have detailed phenotypic information to make optimal use of the genotype data in finding candidate recessive genes that may be related to the fetal phenotype.
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