ABSTRACT
Bidirectional ventricular tachycardia is a unique arrhythmia that can herald lethal arrhythmia syndromes. Using cases based on real patient stories, this article examines 3 different presentations to help clinicians learn the differential diagnosis associated with this condition. Each associated genetic disorder will be briefly discussed, and valuable tips for distinguishing them from each other will be provided.
Subject(s)
Tachycardia, Ventricular , Child , Humans , Male , Arrhythmias, Cardiac/genetics , Arrhythmias, Cardiac/diagnosis , Arrhythmias, Cardiac/physiopathology , Diagnosis, Differential , Electrocardiography , Long QT Syndrome/genetics , Long QT Syndrome/diagnosis , Long QT Syndrome/physiopathology , Tachycardia, Ventricular/diagnosis , Tachycardia, Ventricular/genetics , Tachycardia, Ventricular/physiopathology , AdolescentABSTRACT
While genome sequencing has transformed medicine by elucidating the genetic underpinnings of both rare and common complex disorders, its utility to predict clinical outcomes remains understudied. Here, we used artificial intelligence (AI) technologies to explore the predictive value of genome sequencing in forecasting clinical outcomes following surgery for congenital heart defects (CHD). We report results for a cohort of 2,253 CHD patients from the Pediatric Cardiac Genomics Consortium with a broad range of complex heart defects, pre- and post-operative clinical variables and exome sequencing. Damaging genotypes in chromatin-modifying and cilia-related genes were associated with an elevated risk of adverse post-operative outcomes, including mortality, cardiac arrest and prolonged mechanical ventilation. The impact of damaging genotypes was further amplified in the context of specific CHD phenotypes, surgical complexity and extra-cardiac anomalies. The absence of a damaging genotype in chromatin-modifying and cilia-related genes was also informative, reducing the risk for adverse postoperative outcomes. Thus, genome sequencing enriches the ability to forecast outcomes following congenital cardiac surgery.
ABSTRACT
The case series reviews differential diagnosis of a genetic arrhythmia syndrome when evaluating a patient with prolonged QTc. Making the correct diagnosis requires: detailed patient history, family history, and careful review of the electrocardiogram (ECG). Signs and symptoms and ECG characteristics can often help clinicians make the diagnosis before genetic testing results return. These skills can help clinicians make an accurate and timely diagnosis and prevent life-threatening events.
Subject(s)
Arrhythmias, Cardiac , Electrocardiography , Long QT Syndrome , Humans , Diagnosis, Differential , Arrhythmias, Cardiac/diagnosis , Arrhythmias, Cardiac/genetics , Arrhythmias, Cardiac/physiopathology , Long QT Syndrome/diagnosis , Long QT Syndrome/genetics , Long QT Syndrome/physiopathology , Child , Male , Female , Adolescent , Genetic TestingABSTRACT
Pediatric ECG standards have been defined without echocardiographic confirmation of normal anatomy. The Pediatric Heart Network Normal Echocardiogram Z-score Project provides a racially diverse group of healthy children with normal echocardiograms. We hypothesized that ECG and echocardiographic measures of left ventricular (LV) dimensions are sufficiently correlated in healthy children to imply a clinically meaningful relationship. This was a secondary analysis of a previously described cohort including 2170 digital ECGs. The relationship between 6 ECG measures associated with LV size were analyzed with LV Mass (LVMass-z) and left ventricular end-diastolic volume (LVEDV-z) along with 11 additional parameters. Pearson or Spearman correlations were calculated for the 78 ECG-echocardiographic pairs with regression analyses assessing the variance in ECG measures explained by variation in LV dimensions and demographic variables. ECG/echocardiographic measurement correlations were significant and concordant in 41/78 (53%), though many were significant and discordant (13/78). Of the 6 ECG parameters, 5 correlated in the clinically predicted direction for LV Mass-z and LVEDV-z. Even when statistically significant, correlations were weak (0.05-0.24). R2 was higher for demographic variables than for echocardiographic measures or body surface area in all pairs, but remained weak (R2 ≤ 0.17). In a large cohort of healthy children, there was a positive association between echocardiographic measures of LV size and ECG measures of LVH. These correlations were weak and dependent on factors other than echocardiographic or patient derived variables. Thus, our data support deemphasizing the use of solitary, traditional measurement-based ECG markers traditionally thought to be characteristic of LVH as standalone indications for further cardiac evaluation of LVH in children and adolescents.
Subject(s)
Echocardiography , Electrocardiography , Heart Ventricles , Humans , Child , Female , Male , Heart Ventricles/diagnostic imaging , Echocardiography/methods , Child, Preschool , Adolescent , Reference Values , Infant , Stroke Volume/physiology , Organ SizeABSTRACT
BACKGROUND: Sudden unexpected death in children is a tragic event. Understanding the genetics of sudden death in the young (SDY) enables family counseling and cascade screening. The objective of this study was to characterize genetic variation in an SDY cohort using whole genome sequencing. METHODS: The SDY Case Registry is a National Institutes of Health/Centers for Disease Control and Prevention surveillance effort to discern the prevalence, causes, and risk factors for SDY. The SDY Case Registry prospectively collected clinical data and DNA biospecimens from SDY cases < 20 years of age. SDY cases were collected from medical examiner and coroner offices spanning 13 US jurisdictions from 2015 to 2019. The cohort included 211 children (median age 0.33 year; range 0-20 years), determined to have died suddenly and unexpectedly and from whom DNA biospecimens for DNA extractions and next-of-kin consent were ascertained. A control cohort consisted of 211 randomly sampled, sex- and ancestry-matched individuals from the 1000 Genomes Project. Genetic variation was evaluated in epilepsy, cardiomyopathy, and arrhythmia genes in the SDY and control cohorts. American College of Medical Genetics/Genomics guidelines were used to classify variants as pathogenic or likely pathogenic. Additionally, pathogenic and likely pathogenic genetic variation was identified using a Bayesian-based artificial intelligence (AI) tool. RESULTS: The SDY cohort was 43% European, 29% African, 3% Asian, 16% Hispanic, and 9% with mixed ancestries and 39% female. Six percent of the cohort was found to harbor a pathogenic or likely pathogenic genetic variant in an epilepsy, cardiomyopathy, or arrhythmia gene. The genomes of SDY cases, but not controls, were enriched for rare, potentially damaging variants in epilepsy, cardiomyopathy, and arrhythmia-related genes. A greater number of rare epilepsy genetic variants correlated with younger age at death. CONCLUSIONS: While damaging cardiomyopathy and arrhythmia genes are recognized contributors to SDY, we also observed an enrichment in epilepsy-related genes in the SDY cohort and a correlation between rare epilepsy variation and younger age at death. These findings emphasize the importance of considering epilepsy genes when evaluating SDY.
Subject(s)
Cardiomyopathies , Epilepsy , Child , Humans , Female , Infant , Male , Death, Sudden, Cardiac/etiology , Artificial Intelligence , Bayes Theorem , Arrhythmias, Cardiac/complications , Arrhythmias, Cardiac/genetics , Cardiomyopathies/genetics , Cardiomyopathies/complications , Epilepsy/genetics , DNA , Genetic TestingABSTRACT
BACKGROUND: Sudden death is the leading cause of mortality in medically refractory epilepsy. Middle-aged persons with epilepsy (PWE) are under investigated regarding their mortality risk and burden of cardiovascular disease (CVD). METHODS: Using UK Biobank, we identified 7786 (1.6%) participants with diagnoses of epilepsy and 6,171,803 person-years of follow-up (mean 12.30 years, standard deviation 1.74); 566 patients with previous histories of stroke were excluded. The 7220 PWE comprised the study cohort with the remaining 494,676 without epilepsy as the comparator group. Prevalence of CVD was determined using validated diagnostic codes. Cox proportional hazards regression was used to assess all-cause mortality and sudden death risk. RESULTS: Hypertension, coronary artery disease, heart failure, valvular heart disease, and congenital heart disease were more prevalent in PWE. Arrhythmias including atrial fibrillation/flutter (12.2% vs 6.9%; P < 0.01), bradyarrhythmias (7.7% vs 3.5%; P < 0.01), conduction defects (6.1% vs 2.6%; P < 0.01), and ventricular arrhythmias (2.3% vs 1.0%; P < 0.01), as well as cardiac implantable electric devices (4.6% vs 2.0%; P < 0.01) were more prevalent in PWE. PWE had higher adjusted all-cause mortality (hazard ratio [HR], 3.9; 95% confidence interval [CI], 3.01-3.39), and sudden death-specific mortality (HR, 6.65; 95% CI, 4.53-9.77); and were almost 2 years younger at death (68.1 vs 69.8; P < 0.001). CONCLUSIONS: Middle-aged PWE have increased all-cause and sudden death-specific mortality and higher burden of CVD including arrhythmias and heart failure. Further work is required to elucidate mechanisms underlying all-cause mortality and sudden death risk in PWE of middle age, to identify prognostic biomarkers and develop preventative therapies in PWE.
Subject(s)
Cardiovascular Diseases , Epilepsy , Heart Failure , Middle Aged , Humans , Cardiovascular Diseases/epidemiology , UK Biobank , Biological Specimen Banks , Risk Factors , Epilepsy/complications , Epilepsy/epidemiology , Death, Sudden/epidemiology , Death, Sudden/etiology , Death, Sudden, Cardiac/epidemiology , Death, Sudden, Cardiac/etiologyABSTRACT
BACKGROUND: Recent large-scale sequencing efforts have shed light on the genetic contribution to the etiology of congenital heart defects (CHD); however, the relative impact of genetics on clinical outcomes remains less understood. Outcomes analyses using genetics are complicated by the intrinsic severity of the CHD lesion and interactions with conditionally dependent clinical variables. METHODS: Bayesian Networks were applied to describe the intertwined relationships between clinical variables, demography, and genetics in a cohort of children with single ventricle CHD. RESULTS: As isolated variables, a damaging genetic variant in a gene related to abnormal heart morphology and prolonged ventilator support following stage I palliative surgery increase the probability of having a low Mental Developmental Index (MDI) score at 14 months of age by 1.9- and 5.8-fold, respectively. However, in combination, these variables act synergistically to further increase the probability of a low MDI score by 10-fold. The absence of a damaging variant in a known syndromic CHD gene and a shorter post-operative ventilator support increase the probability of a normal MDI score 1.7- and 2.4-fold, respectively, but in combination increase the probability of a good outcome by 59-fold. CONCLUSIONS: Our analyses suggest a modest genetic contribution to neurodevelopmental outcomes as isolated variables, similar to known clinical predictors. By contrast, genetic, demographic, and clinical variables interact synergistically to markedly impact clinical outcomes. These findings underscore the importance of capturing and quantifying the impact of damaging genomic variants in the context of multiple, conditionally dependent variables, such as pre- and post-operative factors, and demography.
Single ventricle congenital heart disease is a birth defect. In these children, the heart has only one effective blood-pumping chamber instead of two. Surgery can reroute the blood to use only one chamber, but multiple risk factors influence how well a child develops afterwards. Studying these risk factors can be challenging because they are interconnected, i.e. children with a genetic birth defect may be more likely to have a lower birthweight, and hence more likely to spend longer in hospital after surgery. Here, we used a statistical approach not commonly applied to study congenital heart disease and describe that whether a genetic variant (a small difference in a child's DNA) is important for how a child with single ventricle heart disease develops and grows after surgery depends on the presence of other risk factors.
ABSTRACT
BACKGROUND: Thoracic aortic disease and bicuspid aortic valve (BAV) likely have a heritable component, but large population-based studies are lacking. This study characterizes familial associations of thoracic aortic disease and BAV, as well as cardiovascular and aortic-specific mortality, among relatives of these individuals in a large-population database. METHODS: In this observational case-control study of the Utah Population Database, we identified probands with a diagnosis of BAV, thoracic aortic aneurysm, or thoracic aortic dissection. Age- and sex-matched controls (10:1 ratio) were identified for each proband. First-degree relatives, second-degree relatives, and first cousins of probands and controls were identified through linked genealogical information. Cox proportional hazard models were used to quantify the familial associations for each diagnosis. We used a competing-risk model to determine the risk of cardiovascular-specific and aortic-specific mortality for relatives of probands. RESULTS: The study population included 3 812 588 unique individuals. Familial hazard risk of a concordant diagnosis was elevated in the following populations compared with controls: first-degree relatives of patients with BAV (hazard ratio [HR], 6.88 [95% CI, 5.62-8.43]); first-degree relatives of patients with thoracic aortic aneurysm (HR, 5.09 [95% CI, 3.80-6.82]); and first-degree relatives of patients with thoracic aortic dissection (HR, 4.15 [95% CI, 3.25-5.31]). In addition, the risk of aortic dissection was higher in first-degree relatives of patients with BAV (HR, 3.63 [95% CI, 2.68-4.91]) and in first-degree relatives of patients with thoracic aneurysm (HR, 3.89 [95% CI, 2.93-5.18]) compared with controls. Dissection risk was highest in first-degree relatives of patients who carried a diagnosis of both BAV and aneurysm (HR, 6.13 [95% CI, 2.82-13.33]). First-degree relatives of patients with BAV, thoracic aneurysm, or aortic dissection had a higher risk of aortic-specific mortality (HR, 2.83 [95% CI, 2.44-3.29]) compared with controls. CONCLUSIONS: Our results indicate that BAV and thoracic aortic disease carry a significant familial association for concordant disease and aortic dissection. The pattern of familiality is consistent with a genetic cause of disease. Furthermore, we observed higher risk of aortic-specific mortality in relatives of individuals with these diagnoses. This study provides supportive evidence for screening in relatives of patients with BAV, thoracic aneurysm, or dissection.
Subject(s)
Aortic Aneurysm, Thoracic , Aortic Diseases , Aortic Dissection , Bicuspid Aortic Valve Disease , Heart Valve Diseases , Humans , Aortic Valve , Heart Valve Diseases/diagnosis , Case-Control Studies , Prevalence , Cause of Death , Aortic Aneurysm, Thoracic/genetics , Aortic Dissection/geneticsABSTRACT
The field of pediatric skeletal muscle channelopathies has seen major new advances in terms of a wider understanding of clinical presentations and new phenotypes. Skeletal muscle channelopathies cause significant disability and even death in some of the newly described phenotypes. Despite this, there are virtually no data on the epidemiology and longitudinal natural history of these conditions or randomized controlled trial evidence of efficacy or tolerability of any treatment in children, and thus best practice care recommendations do not exist. Clinical history, and to a lesser extent examination, is key to eliciting symptoms and signs that indicate a differential diagnosis of muscle channelopathy. Normal routine investigations should not deter one from the diagnosis. Specialist neurophysiologic investigations have an additional role, but their availability should not delay genetic testing. New phenotypes are increasingly likely to be identified by next-generation sequencing panels. Many treatments or interventions for symptomatic patients are available, with anecdotal data to support their benefit, but we lack trial data on efficacy, safety, or superiority. This lack of trial data in turn can lead to hesitancy in prescribing among doctors or in accepting medication by parents. Holistic management addressing work, education, activity, and additional symptoms of pain and fatigue provides significant benefit. Preventable morbidity and sometimes mortality occurs if the diagnosis and therefore treatment is delayed. Advances in genetic sequencing technology and greater access to testing may help to refine recently identified phenotypes, including histology, as more cases are described. Randomized controlled treatment trials are required to inform best practice care recommendations. A holistic approach to management is essential and should not be overlooked. Good quality data on prevalence, health burden, and optimal treatment are urgently needed.
Subject(s)
Channelopathies , Child , Humans , Channelopathies/diagnosis , Channelopathies/genetics , Channelopathies/therapy , Muscle, Skeletal/pathology , Genetic Testing , Randomized Controlled Trials as TopicABSTRACT
BACKGROUND: Known genetic causes of congenital heart disease (CHD) explain <40% of CHD cases, and interpreting the clinical significance of variants with uncertain functional impact remains challenging. We aim to improve diagnostic classification of variants in patients with CHD by assessing the impact of noncanonical splice region variants on RNA splicing. METHODS: We tested de novo variants from trio studies of 2649 CHD probands and their parents, as well as rare (allele frequency, <2×10-6) variants from 4472 CHD probands in the Pediatric Cardiac Genetics Consortium through a combined computational and in vitro approach. RESULTS: We identified 53 de novo and 74 rare variants in CHD cases that alter splicing and thus are loss of function. Of these, 77 variants are in known dominant, recessive, and candidate CHD genes, including KMT2D and RBFOX2. In 1 case, we confirmed the variant's predicted impact on RNA splicing in RNA transcripts from the proband's cardiac tissue. Two probands were found to have 2 loss-of-function variants for recessive CHD genes HECTD1 and DYNC2H1. In addition, SpliceAI-a predictive algorithm for altered RNA splicing-has a positive predictive value of ≈93% in our cohort. CONCLUSIONS: Through assessment of RNA splicing, we identified a new loss-of-function variant within a CHD gene in 78 probands, of whom 69 (1.5%; n=4472) did not have a previously established genetic explanation for CHD. Identification of splice-altering variants improves diagnostic classification and genetic diagnoses for CHD. REGISTRATION: URL: https://clinicaltrials.gov; Unique identifier: NCT01196182.
Subject(s)
Heart Defects, Congenital , RNA , Child , Humans , Heart Defects, Congenital/diagnosis , Heart Defects, Congenital/genetics , Mutation , RNA Splicing , Gene Frequency , RNA Splicing Factors/genetics , Repressor Proteins/geneticsABSTRACT
Background: Sudden unexpected death in children is a tragic event. Understanding the genetics of sudden death in the young (SDY) enables family counseling and cascade screening. The objective of this study was to characterize genetic variation in an SDY cohort using whole genome sequencing. Methods: The SDY Case Registry is a National Institutes of Health/Centers for Disease Control surveillance effort to discern the prevalence, causes, and risk factors for SDY. The SDY Case Registry prospectively collected clinical data and DNA biospecimens from SDY cases <20 years of age. SDY cases were collected from medical examiner and coroner offices spanning 13 US jurisdictions from 2015-2019. The cohort included 211 children (mean age 1 year; range 0-20 years), determined to have died suddenly and unexpectedly and in whom DNA biospecimens and next-of-kin consent were ascertained. A control cohort consisted of 211 randomly sampled, sex-and ancestry-matched individuals from the 1000 Genomes Project. Genetic variation was evaluated in epilepsy, cardiomyopathy and arrhythmia genes in the SDY and control cohorts. American College of Medical Genetics/Genomics guidelines were used to classify variants as pathogenic or likely pathogenic. Additionally, genetic variation predicted to be damaging was identified using a Bayesian-based artificial intelligence (AI) tool. Results: The SDY cohort was 42% European, 30% African, 17% Hispanic, and 11% with mixed ancestries, and 39% female. Six percent of the cohort was found to harbor a pathogenic or likely pathogenic genetic variant in an epilepsy, cardiomyopathy or arrhythmia gene. The genomes of SDY cases, but not controls, were enriched for rare, damaging variants in epilepsy, cardiomyopathy and arrhythmia-related genes. A greater number of rare epilepsy genetic variants correlated with younger age at death. Conclusions: While damaging cardiomyopathy and arrhythmia genes are recognized contributors to SDY, we also observed an enrichment in epilepsy-related genes in the SDY cohort, and a correlation between rare epilepsy variation and younger age at death. These findings emphasize the importance of considering epilepsy genes when evaluating SDY.
ABSTRACT
BACKGROUND: Congenital heart disease (CHD) is highly heritable, but the power to identify inherited risk has been limited to analyses of common variants in small cohorts. METHODS: We performed reimputation of 4 CHD cohorts (n=55 342) to the TOPMed reference panel (freeze 5), permitting meta-analysis of 14 784 017 variants including 6 035 962 rare variants of high imputation quality as validated by whole genome sequencing. RESULTS: Meta-analysis identified 16 novel loci, including 12 rare variants, which displayed moderate or large effect sizes (median odds ratio, 3.02) for 4 separate CHD categories. Analyses of chromatin structure link 13 of the genome-wide significant loci to key genes in cardiac development; rs373447426 (minor allele frequency, 0.003 [odds ratio, 3.37 for Conotruncal heart disease]; P=1.49×10-8) is predicted to disrupt chromatin structure for 2 nearby genes BDH1 and DLG1 involved in Conotruncal development. A lead variant rs189203952 (minor allele frequency, 0.01 [odds ratio, 2.4 for left ventricular outflow tract obstruction]; P=1.46×10-8) is predicted to disrupt the binding sites of 4 transcription factors known to participate in cardiac development in the promoter of SPAG9. A tissue-specific model of chromatin conformation suggests that common variant rs78256848 (minor allele frequency, 0.11 [odds ratio, 1.4 for Conotruncal heart disease]; P=2.6×10-8) physically interacts with NCAM1 (PFDR=1.86×10-27), a neural adhesion molecule acting in cardiac development. Importantly, while each individual malformation displayed substantial heritability (observed h2 ranging from 0.26 for complex malformations to 0.37 for left ventricular outflow tract obstructive disease) the risk for different CHD malformations appeared to be separate, without genetic correlation measured by linkage disequilibrium score regression or regional colocalization. CONCLUSIONS: We describe a set of rare noncoding variants conferring significant risk for individual heart malformations which are linked to genes governing cardiac development. These results illustrate that the oligogenic basis of CHD and significant heritability may be linked to rare variants outside protein-coding regions conferring substantial risk for individual categories of cardiac malformation.
Subject(s)
Heart Defects, Congenital , Humans , Heart Defects, Congenital/diagnosis , Heart Defects, Congenital/genetics , Phenotype , Gene Frequency , Whole Genome Sequencing , Chromatin , Adaptor Proteins, Signal Transducing/geneticsABSTRACT
The American Heart Association's Strategically Focused Children's Research Network started in July 2017 with 4 unique programs at Children's National Hospital in Washington, DC; Duke University in Durham, North Carolina; University of Utah in Salt Lake City, Utah; and Lurie Children's Hospital/Northwestern University in Chicago, Illinois. The overarching goal of the Children's National center was to develop evidence-based strategies to strengthen the health system response to rheumatic heart disease through synergistic basic, clinical, and population science research. The overall goals of the Duke center were to determine risk factors for obesity and response to treatment including those that might work on a larger scale in communities across the country. The integrating theme of the Utah center focused on leveraging big data-science approaches to improve the quality of care and outcomes for children with congenital heart defects, within the context of the patient and their family. The overarching hypothesis of the Northwestern center is that the early course of change in cardiovascular health, from birth onward, reflects factors that result in either subsequent development of cardiovascular risk or preservation of lifetime favorable cardiovascular health. All 4 centers exceeded the original goals of research productivity, fellow training, and collaboration. This article describes details of these accomplishments and highlights challenges, especially around the COVID-19 pandemic.
Subject(s)
COVID-19 , Heart Defects, Congenital , Humans , Child , United States/epidemiology , American Heart Association , Pandemics , UtahABSTRACT
Calcium entering mitochondria potently stimulates ATP synthesis. Increases in calcium preserve energy synthesis in cardiomyopathies caused by mitochondrial dysfunction, and occur due to enhanced activity of the mitochondrial calcium uniporter channel. The signaling mechanism that mediates this compensatory increase remains unknown. Here, we find that increases in the uniporter are due to impairment in Complex I of the electron transport chain. In normal physiology, Complex I promotes uniporter degradation via an interaction with the uniporter pore-forming subunit, a process we term Complex I-induced protein turnover. When Complex I dysfunction ensues, contact with the uniporter is inhibited, preventing degradation, and leading to a build-up in functional channels. Preventing uniporter activity leads to early demise in Complex I-deficient animals. Conversely, enhancing uniporter stability rescues survival and function in Complex I deficiency. Taken together, our data identify a fundamental pathway producing compensatory increases in calcium influx during Complex I impairment.
Subject(s)
Calcium Channels , Calcium , Animals , Calcium/metabolism , Calcium Channels/metabolism , Homeostasis , Mitochondria/metabolismABSTRACT
Understanding the conditionally-dependent clinical variables that drive cardiovascular health outcomes is a major challenge for precision medicine. Here, we deploy a recently developed massively scalable comorbidity discovery method called Poisson Binomial based Comorbidity discovery (PBC), to analyze Electronic Health Records (EHRs) from the University of Utah and Primary Children's Hospital (over 1.6 million patients and 77 million visits) for comorbid diagnoses, procedures, and medications. Using explainable Artificial Intelligence (AI) methodologies, we then tease apart the intertwined, conditionally-dependent impacts of comorbid conditions and demography upon cardiovascular health, focusing on the key areas of heart transplant, sinoatrial node dysfunction and various forms of congenital heart disease. The resulting multimorbidity networks make possible wide-ranging explorations of the comorbid and demographic landscapes surrounding these cardiovascular outcomes, and can be distributed as web-based tools for further community-based outcomes research. The ability to transform enormous collections of EHRs into compact, portable tools devoid of Protected Health Information solves many of the legal, technological, and data-scientific challenges associated with large-scale EHR analyses.
ABSTRACT
The well-established manifestation of mitochondrial mutations in functional cardiac disease (e.g., mitochondrial cardiomyopathy) prompted the hypothesis that mitochondrial DNA (mtDNA) sequence and/or copy number (mtDNAcn) variation contribute to cardiac defects in congenital heart disease (CHD). MtDNAcns were calculated and rare, non-synonymous mtDNA mutations were identified in 1,837 CHD-affected proband-parent trios, 116 CHD-affected singletons, and 114 paired cardiovascular tissue/blood samples. The variant allele fraction (VAF) of heteroplasmic variants in mitochondrial RNA from 257 CHD cardiovascular tissue samples was also calculated. On average, mtDNA from blood had 0.14 rare variants and 52.9 mtDNA copies per nuclear genome per proband. No variation with parental age at proband birth or CHD-affected proband age was seen. mtDNAcns in valve/vessel tissue (320 ± 70) were lower than in atrial tissue (1,080 ± 320, p = 6.8E-21), which were lower than in ventricle tissue (1,340 ± 280, p = 1.4E-4). The frequency of rare variants in CHD-affected individual DNA was indistinguishable from the frequency in an unaffected cohort, and proband mtDNAcns did not vary from those of CHD cohort parents. In both the CHD and the comparison cohorts, mtDNAcns were significantly correlated between mother-child, father-child, and mother-father. mtDNAcns among people with European (mean = 52.0), African (53.0), and Asian haplogroups (53.5) were calculated and were significantly different for European and Asian haplogroups (p = 2.6E-3). Variant heteroplasmic fraction (HF) in blood correlated well with paired cardiovascular tissue HF (r = 0.975) and RNA VAF (r = 0.953), which suggests blood HF is a reasonable proxy for HF in heart tissue. We conclude that mtDNA mutations and mtDNAcns are unlikely to contribute significantly to CHD risk.
Subject(s)
DNA, Mitochondrial , Heart Defects, Congenital , DNA Copy Number Variations/genetics , DNA, Mitochondrial/genetics , Heart Defects, Congenital/genetics , Humans , Mitochondria/genetics , Mutation/geneticsABSTRACT
In a US population-based registry of sudden death in the young, this study performed familial evaluation of surviving relatives.
Subject(s)
Death, Sudden, Cardiac , Research , Child , Death, Sudden, Cardiac/epidemiology , Death, Sudden, Cardiac/etiology , Death, Sudden, Cardiac/prevention & control , Family , Genetic Testing , Humans , Retrospective StudiesABSTRACT
BACKGROUND: Congenital heart disease (CHD) is the most common anomaly at birth, with a prevalence of ≈1%. While infants born to mothers with diabetes or obesity have a 2- to 3-fold increased incidence of CHD, the cause of the increase is unknown. Damaging de novo variants (DNV) in coding regions are more common among patients with CHD, but genome-wide rates of coding and noncoding DNVs associated with these prenatal exposures have not been studied in patients with CHD. METHODS: DNV frequencies were determined for 1812 patients with CHD who had whole-genome sequencing and prenatal history data available from the Pediatric Cardiac Genomics Consortium's CHD GENES study (Genetic Network). The frequency of DNVs was compared between subgroups using t test or linear model. RESULTS: Among 1812 patients with CHD, the number of DNVs per patient was higher with maternal diabetes (76.5 versus 72.1, t test P=3.03×10-11), but the difference was no longer significant after including parental ages in a linear model (paternal and maternal correction P=0.42). No interaction was observed between diabetes risk and parental age (paternal and maternal interaction P=0.80 and 0.68, respectively). No difference was seen in DNV count per patient based on maternal obesity (72.0 versus 72.2 for maternal body mass index <25 versus maternal body mass index >30, t test P=0.86). CONCLUSIONS: After accounting for parental age, the offspring of diabetic or obese mothers have no increase in DNVs compared with other children with CHD. These results emphasize the role for other mechanisms in the cause of CHD associated with these prenatal exposures. REGISTRATION: URL: https://clinicaltrials.gov; NCT01196182.