Citations

Mutagenesis screening is a powerful forward genetic approach that has been successfully applied in lower-model organisms to discover genetic factors for biological processes. This phenotype-based approach has yet to be established in vertebrates for probing major human diseases, largely because of the complexity of colony management. Herein, we report a rapid strategy for identifying genetic modifiers of cardiomyopathy (CM). Based on the application of doxorubicin stress to zebrafish insertional cardiac (ZIC) mutants, we identified 4 candidate CM-modifying genes, of which 3 have been linked previously to CM. The long isoform of DnaJ (Hsp40) homolog, subfamily B, member 6b ( dnajb6b(L) ) was identified as a CM susceptibility gene, supported by identification of rare variants in its human ortholog DNAJB6 from CM patients. Mechanistic studies indicated that the deleterious, loss-of-function modifying effects of dnajb6b(L) can be ameliorated by inhibition of ER stress. In contrast, overexpression of dnajb6(L) exerts cardioprotective effects on both fish and mouse CM models. Together, our findings establish a mutagenesis screening strategy that is scalable for systematic identification of genetic modifiers of CM, feasible to suggest therapeutic targets, and expandable to other major human diseases.

Background— Congenital long QT syndrome (LQTS) is characterized by QT prolongation. However, the QT interval itself is insufficient for diagnosis, unless the corrected QT interval is repeatedly ≥500 ms without an acquired explanation. Further, the majority of LQTS patients have a corrected QT interval below this threshold, and a significant minority has normal resting corrected QT interval values. Here, we aimed to develop and validate a novel, quantitative T wave morphological analysis program to differentiate LQTS patients from healthy controls. Methods and Results— We analyzed a genotyped cohort of 420 patients (22±16 years, 43% male) with either LQT1 (61%) or LQT2 (39%). ECG analysis was conducted using a novel, proprietary T wave analysis program that quantitates subtle changes in T wave morphology. The top 3 discriminating features in each ECG lead were determined and the lead with the best discrimination selected. Classification was performed using a linear discriminant classifier and validated on an untouched cohort. The top 3 features were Tpeak–Tend interval, T wave left slope, and T wave center of gravity x axis (last 25% of the T wave). Lead V6 had the best discrimination. It could distinguish 86.8% of LQTS patients from healthy controls. Moreover, it distinguished 83.33% of patients with concealed LQTS from controls, despite having essentially identical resting corrected QT interval values. Conclusions— T wave quantitative analysis on the 12-lead surface ECG provides an effective, novel tool to distinguish patients with either LQT1/LQT2 from healthy matched controls. It can provide guidance while mutation-specific genetic testing is in motion for family members.

Objectives: There is no evidence regarding the effect of ondansetron on the QT interval in pediatric patients in the ICU. This study aimed to describe the effect of ondansetron on the corrected QT interval in patients cared for in the PICU. Design: Retrospective cohort, consecutive enrollment study. Setting: Single-center, tertiary-level, medical/surgical PICU. Patients: All patients less than 8 years old who received ondansetron over an 11-month period were included. Exclusion criteria were atrial arrhythmia, bundle-branch block, known congenital long QT syndrome, and concomitant administration of proarrhythmic antiarrhythmic agents. Interventions: None. Measurements and Main Results: Overall, 210 doses of ondansetron were administered to 107 patients, with a mean age 10.5 ± 4.8 years; 49% were men. Corrected QT interval increased to 460–500 ms in 29% and to more than 500 ms in 11% of events of ondansetron administration. The mean baseline corrected QT interval even before ondansetron administration was higher for these groups (460–500 and > 500 ms; 457 ± 33 and 469 ± 45, respectively; p ≤ 0.05). In multivariate analysis, both groups were associated significantly with underlying electrolyte abnormalities (odds ratio, 2.2; 95% CI, 1.1–4.4 and odds ratio, 5.1; 95% CI, 1.8–15.7, respectively); the group with corrected QT interval more than 500 ms was also significantly associated with organ dysfunction (odds ratio, 3.2; 95% CI, 1.1–9.4). As the numbers of risk factors increased from only ondansetron to three additional QT aggravating factors (electrolyte abnormalities, administration of other QT-prolonging drugs, and organ dysfunction), the likelihood of being associated with corrected QT interval more than 500 ms increased. Conclusions: Prolonged QT interval is observed commonly in PICUs following the administration of ondansetron. Underlying risk factors, such as electrolyte abnormalities and organ dysfunction, seem to pose the highest risk of prolongation of QT interval in these patients. The awareness of prevalent risk factors for increased corrected QT interval may help identify patients at high risk for arrhythmias.

Background— Targeted postmortem genetic testing of the 4 major channelopathy-susceptibility genes ( KCNQ1 , KCNH2 , SCN5A , and RYR2 ) have yielded putative pathogenic mutations in ≤30% of autopsy-negative sudden unexplained death in the young (SUDY) cases with highest yields derived from the subset of exertion-related SUDY. Here, we evaluate the role of whole-exome sequencing in exertion-related SUDY cases. Methods and Results— From 1998 to 2010, 32 cases of exertion-related SUDY were referred by Medical Examiners for a cardiac channel molecular autopsy. A mutational analysis of the major long-QT syndrome–susceptibility genes ( KCNQ1 , KCNH2 , and SCN5A ) and catecholaminergic polymorphic ventricular tachycardia–susceptibility gene ( RYR2 ) identified a putative pathogenic mutation in 11 cases. Whole-exome sequencing was performed on the remaining 21 targeted gene–negative SUDY cases. After whole-exome sequencing, a gene-specific surveillance of all genes (N=100) implicated in sudden death was performed to identify putative pathogenic mutation(s). Three of these 21 decedents had a clinically actionable, pathogenic mutation (CALM2-F90L, CALM2-N98S, and PKP2-N634fs). Of the 18 remaining cases, 7 hosted at least 1 variant of unknown significance with a minor allele frequency <1:20 000. The overall yield of pathogenic mutations was higher among decedents aged 1 to 10 years (10/11, 91%) than those aged 11 to 19 years (4/21, 19%, P =0.0001). Conclusions— Molecular screening in this clinical scenario is appropriate with a pathogenic mutation detection rate of 44% using direct DNA sequencing followed by whole-exome sequencing. Only 5 of the 100 interrogated sudden death genes hosted actionable pathogenic mutations for more than one third of these exertion-related, autopsy-negative SUDY cases.

ABSTRACTRare variants (RVs) have been shown to be significant contributors to complex disease risk. By definition, these variants have very low minor allele frequencies and traditional single‐marker methods for statistical analysis are underpowered for typical sequencing study sample sizes. Multimarker burden‐type approaches attempt to identify aggregation of RVs across case‐control status by analyzing relatively small partitions of the genome, such as genes. However, it is generally the case that the aggregative measure would be a mixture of causal and neutral variants, and these omnibus tests do not directly provide any indication of which RVs may be driving a given association. Recently, Bayesian variable selection approaches have been proposed to identify RV associations from a large set of RVs under consideration. Although these approaches have been shown to be powerful at detecting associations at the RV level, there are often computational limitations on the total quantity of RVs under consideration and compromises are necessary for large‐scale application. Here, we propose a computationally efficient alternative formulation of this method using a probit regression approach specifically capable of simultaneously analyzing hundreds to thousands of RVs. We evaluate our approach to detect causal variation on simulated data and examine sensitivity and specificity in instances of high RV dimensionality as well as apply it to pathway‐level RV analysis results from a prostate cancer (PC) risk case‐control sequencing study. Finally, we discuss potential extensions and future directions of this work.

Background— Although the vast majority of mitral valve prolapse (MVP) is benign, a small subset of patients, predominantly women, with bileaflet prolapse, complex ventricular ectopy (VE), and abnormal T waves comprise the recently described bileaflet MVP syndrome. We compared findings on electrophysiological study in bileaflet MVP syndrome patients with and without cardiac arrest to identify factors that may predispose to malignant ventricular arrhythmia. Methods and Results— Fourteen consecutive bileaflet MVP syndrome patients (n=13 women; median [limits], age at index ablation, 33.8 [21.0–58.7] years; ejection fraction, 60% [45%–67%]; all ≤ moderate mitral regurgitation; n=6 with previous cardiac arrest and implantable cardioverter defibrillator shocks for ventricular fibrillation; and n=8 without implantable cardioverter defibrillator although with symptomatic complex VE) were included. The 2 groups had similar baseline echocardiographic and electrocardiographic characteristics. All patients had at least 1 left ventricular papillary or fascicular VE focus. Purkinje origin VE was identified as the ventricular fibrillation trigger in 6 of 6 cardiac arrest patients (4 from papillary muscle) and Purkinje origin of dominant VE was seen in 5 of 8 (3 from papillary muscle) nonarrest patients. Acute success was seen in 17 of 19 procedures, and a ventricular fibrillation storm occurred within 24 hours of ablation in a single patient. Repeat ablation for recurrent symptomatic arrhythmia was performed in 6 patients. At 478 (39–2099) days of follow-up, 2 cardiac arrest patients received appropriate shocks. Symptoms from VE were reduced in 12 of 14. Conclusions— Bileaflet MVP syndrome is characterized by fascicular and papillary muscle VE that triggers ventricular fibrillation. Ablation of clinically dominant VE foci improves symptoms and reduces appropriate implantable cardioverter defibrillator shocks.