scholarly journals Molecular Genetics and Complex Inheritance of Congenital Heart Disease

Genes ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 1020
Author(s):  
Nicholas S. Diab ◽  
Syndi Barish ◽  
Weilai Dong ◽  
Shujuan Zhao ◽  
Garrett Allington ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
High Throughput ◽  
Congenital Heart ◽  
High Throughput Sequencing ◽  
De Novo ◽  
Copy Number Variations ◽  
De Novo Mutations ◽  
Genomic Technologies ◽  
Chd Risk

Congenital heart disease (CHD) is the most common congenital malformation and the leading cause of mortality therein. Genetic etiologies contribute to an estimated 90% of CHD cases, but so far, a molecular diagnosis remains unsolved in up to 55% of patients. Copy number variations and aneuploidy account for ~23% of cases overall, and high-throughput genomic technologies have revealed additional types of genetic variation in CHD. The first CHD risk genotypes identified through high-throughput sequencing were de novo mutations, many of which occur in chromatin modifying genes. Murine models of cardiogenesis further support the damaging nature of chromatin modifying CHD mutations. Transmitted mutations have also been identified through sequencing of population scale CHD cohorts, and many transmitted mutations are enriched in cilia genes and Notch or VEGF pathway genes. While we have come a long way in identifying the causes of CHD, more work is required to end the diagnostic odyssey for all CHD families. Complex genetic explanations of CHD are emerging but will require increasingly sophisticated analysis strategies applied to very large CHD cohorts before they can come to fruition in providing molecular diagnoses to genetically unsolved patients. In this review, we discuss the genetic architecture of CHD and biological pathways involved in its pathogenesis.

scholarly journals High throughput in vivo functional validation of candidate congenital heart disease genes in Drosophila

eLife ◽  
2017 ◽  
Vol 6 ◽  
Author(s):  
Jun-yi Zhu ◽  
Yulong Fu ◽  
Margaret Nettleton ◽  
Adam Richman ◽  
Zhe Han
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
High Throughput ◽  
Congenital Heart ◽  
De Novo ◽  
Disease Risk ◽  
In Vivo Model ◽  
Disease Genes ◽  
Specific Patient

Genomic sequencing has implicated large numbers of genes and de novo mutations as potential disease risk factors. A high throughput in vivo model system is needed to validate gene associations with pathology. We developed a Drosophila-based functional system to screen candidate disease genes identified from Congenital Heart Disease (CHD) patients. 134 genes were tested in the Drosophila heart using RNAi-based gene silencing. Quantitative analyses of multiple cardiac phenotypes demonstrated essential structural, functional, and developmental roles for more than 70 genes, including a subgroup encoding histone H3K4 modifying proteins. We also demonstrated the use of Drosophila to evaluate cardiac phenotypes resulting from specific, patient-derived alleles of candidate disease genes. We describe the first high throughput in vivo validation system to screen candidate disease genes identified from patients. This approach has the potential to facilitate development of precision medicine approaches for CHD and other diseases associated with genetic factors.

scholarly journals De novo mutations in histone-modifying genes in congenital heart disease

Nature ◽  
2013 ◽  
Vol 498 (7453) ◽  
pp. 220-223 ◽  
Author(s):  
Samir Zaidi ◽  
Murim Choi ◽  
Hiroko Wakimoto ◽  
Lijiang Ma ◽  
Jianming Jiang ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Congenital Heart ◽  
De Novo ◽  
De Novo Mutations ◽  
Modifying Genes

scholarly journals De novo mutations in congenital heart disease with neurodevelopmental and other congenital anomalies

Science ◽  
2015 ◽  
Vol 350 (6265) ◽  
pp. 1262-1266 ◽  
Author(s):  
J. Homsy ◽  
S. Zaidi ◽  
Y. Shen ◽  
J. S. Ware ◽  
K. E. Samocha ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Congenital Anomalies ◽  
Congenital Heart ◽  
De Novo ◽  
De Novo Mutations

scholarly journals Model system identification of novel congenital heart disease gene candidates: focus on RPL13

2019 ◽  
Vol 28 (23) ◽  
pp. 3954-3969 ◽  
Author(s):  
Analyne M Schroeder ◽  
Massoud Allahyari ◽  
Georg Vogler ◽  
Maria A Missinato ◽  
Tanja Nielsen ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
High Throughput ◽  
Heart Development ◽  
Congenital Heart ◽  
De Novo ◽  
Model Systems ◽  
New Genes ◽  
Cardiac Model

Abstract Genetics is a significant factor contributing to congenital heart disease (CHD), but our understanding of the genetic players and networks involved in CHD pathogenesis is limited. Here, we searched for de novo copy number variations (CNVs) in a cohort of 167 CHD patients to identify DNA segments containing potential pathogenic genes. Our search focused on new candidate disease genes within 19 deleted de novo CNVs, which did not cover known CHD genes. For this study, we developed an integrated high-throughput phenotypical platform to probe for defects in cardiogenesis and cardiac output in human induced pluripotent stem cell (iPSC)-derived multipotent cardiac progenitor (MCPs) cells and, in parallel, in the Drosophila in vivo heart model. Notably, knockdown (KD) in MCPs of RPL13, a ribosomal gene and SON, an RNA splicing cofactor, reduced proliferation and differentiation of cardiomyocytes, while increasing fibroblasts. In the fly, heart-specific RpL13 KD, predominantly at embryonic stages, resulted in a striking ‘no heart’ phenotype. KD of Son and Pdss2, among others, caused structural and functional defects, including reduced or abolished contractility, respectively. In summary, using a combination of human genetics and cardiac model systems, we identified new genes as candidates for causing human CHD, with particular emphasis on ribosomal genes, such as RPL13. This powerful, novel approach of combining cardiac phenotyping in human MCPs and in the in vivo Drosophila heart at high throughput will allow for testing large numbers of CHD candidates, based on patient genomic data, and for building upon existing genetic networks involved in heart development and disease.

scholarly journals Case report: adult onset diabetes with partial pancreatic agenesis and congenital heart disease due to a de novo GATA6 mutation

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Begona Sanchez-Lechuga ◽  
Muhammad Saqlain ◽  
Nicholas Ng ◽  
Kevin Colclough ◽  
Conor Woods ◽  
...  
Keyword(s):  
Congenital Heart Disease ◽  
Heart Disease ◽  
Case Report ◽  
Congenital Heart ◽  
De Novo ◽  
Adult Onset ◽  
Onset Diabetes ◽  
Adult Onset Diabetes ◽  
Pancreatic Agenesis

scholarly journals Neighbourhood maternal socioeconomic status indicators and risk of congenital heart disease

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Qun Miao ◽  
Sandra Dunn ◽  
Shi Wu Wen ◽  
Jane Lougheed ◽  
Jessica Reszel ◽  
...  
Keyword(s):  
Socioeconomic Status ◽  
Congenital Heart Disease ◽  
Heart Disease ◽  
Household Income ◽  
Congenital Heart ◽  
Population Based ◽  
Income Poverty ◽  
Lower Odds ◽  
Logistic Regression Models ◽  
Chd Risk

Abstract Background This study aimed to examine the relationships between various maternal socioeconomic status (SES) indicators and the risk of congenital heart disease (CHD). Methods This was a population-based retrospective cohort study, including all singleton stillbirths and live births in Ontario hospitals from April 1, 2012 to March 31, 2018. Multivariable logistic regression models were performed to examine the relationships between maternal neighbourhood household income, poverty, education level, employment and unemployment status, immigration and minority status, and population density and the risk of CHD. All SES variables were estimated at a dissemination area level and categorized into quintiles. Adjustments were made for maternal age at birth, assisted reproductive technology, obesity, pre-existing maternal health conditions, substance use during pregnancy, rural or urban residence, and infant’s sex. Results Of 804,292 singletons, 9731 (1.21%) infants with CHD were identified. Compared to infants whose mothers lived in the highest income neighbourhoods, infants whose mothers lived in the lowest income neighbourhoods had higher likelihood of developing CHD (adjusted OR: 1.29, 95% CI: 1.20–1.38). Compared to infants whose mothers lived in the neighbourhoods with the highest percentage of people with a university or higher degree, infants whose mothers lived in the neighbourhoods with the lowest percentage of people with university or higher degree had higher chance of CHD (adjusted OR: 1.34, 95% CI: 1.24–1.44). Compared to infants whose mothers lived in the neighbourhoods with the highest employment rate, the odds of infants whose mothers resided in areas with the lowest employment having CHD was 18% higher (adjusted OR: 1.18, 95% CI: 1.10–1.26). Compared to infants whose mothers lived in the neighbourhoods with the lowest proportion of immigrants or minorities, infants whose mothers resided in areas with the highest proportions of immigrants or minorities had 18% lower odds (adjusted OR: 0.82, 95% CI: 0.77–0.88) and 16% lower odds (adjusted OR: 0.84, 95% CI: 0.78–0.91) of CHD, respectively. Conclusion Lower maternal neighbourhood household income, poverty, lower educational level and unemployment status had positive associations with CHD, highlighting a significant social inequity in Ontario. The findings of lower CHD risk in immigrant and minority neighbourhoods require further investigation.

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