ArticleBMC medical genomics2014
Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve.
Article in BMC medical genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01192048 (Genetic Testing of Individuals and Families With Congenital Heart Disease), which is not on this map. Cited by 34 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Genetic Testing of Individuals and Families With Congenital Heart Disease
Who cites it
34 citing papers in PubMed, 60 citations in OpenAlex.
- Bicuspid Aortic Valve: Old and Novel Gene Contribution to Disease Onset and Complications.Diagnostics (Basel, Switzerland) · 2025Article
- Bicuspid Aortic Valve and Sudden Cardiac Death.Life (Basel, Switzerland) · 2025Review
- Spatial transcriptomics reveals novel genes during the remodelling of the embryonic human arterial valves.PLoS genetics · 2023Article
- A Comprehensive Review of Management Strategies for Bicuspid Aortic Valve (BAV): Exploring Epidemiology, Aetiology, Aortopathy, and Interventions in Light of Recent Guidelines.Journal of cardiovascular development and disease · 2023Review
- Isolated Absent Aortic Valves: A Unique Fetal Case With Echocardiographic, Pathologic, and Genetic Correlation.JACC. Case reports · 2023Article
- Combinatorial batching of DNA for ultralow-cost detection of pathogenic variants.Genome medicine · 2023Article
- Capturing heart valve development with Gene Ontology.Frontiers in genetics · 2023Article
- Neutrophil and T Cell Functions in Patients with Congenital Heart Diseases: A Review.Pediatric cardiology · 2021Review
- Aortic root aortopathy in bicuspid aortic valve associated with high genetic risk.BMC cardiovascular disorders · 2021Article
- ADAMTSL2 gene variant in patients with features of autosomal dominant connective tissue disorders.American journal of medical genetics. Part A · 2021Article
- Genetic Etiology of Left-Sided Obstructive Heart Lesions: A Story in Development.Journal of the American Heart Association · 2021Review
- Article
- Analysis of the contribution of 129 candidate genes to thoracic aortic aneurysm or dissection of a mixed cohort of sporadic and familial cases in South China.American journal of translational research · 2021Article
- Development of the Human Arterial Valves: Understanding Bicuspid Aortic Valve.Frontiers in cardiovascular medicine · 2021Review
- [Gene mutation analysis of 19 Uighur families with aortic disease in Kashgar, China].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2020Article
- New Concepts in the Development and Malformation of the Arterial Valves.Journal of cardiovascular development and disease · 2020Review
- Article
- Genetics of Congenital Heart Disease.Biomolecules · 2019Review
- The role of ESCO2, SALL4 and TBX5 genes in the susceptibility to thalidomide teratogenesis.Scientific reports · 2019Article
- Endocardial Coronary Artery: A Rare Congenital Coronary Anomaly.Pediatric cardiology · 2019Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundBicuspid aortic valve (BAV) is the most common type of congenital heart disease with a population prevalence of 1-2%. While BAV is known to be highly heritable, mutations in single genes (such as GATA5 and NOTCH1) have been reported in few human BAV cases. Traditional gene sequencing methods are time and labor intensive, while next-generation high throughput sequencing remains costly for large patient cohorts and requires extensive bioinformatics processing. Here we describe an approach to targeted multi-gene sequencing with combinatorial pooling of samples from BAV patients.
methodsWe studied a previously described cohort of 78 unrelated subjects with echocardiogram-identified BAV. Subjects were identified as having isolated BAV or BAV associated with coarctation of aorta (BAV-CoA). BAV cusp fusion morphology was defined as right-left cusp fusion, right non-coronary cusp fusion, or left non-coronary cusp fusion. Samples were combined into 19 pools using a uniquely overlapping combinatorial design; a given mutation could be attributed to a single individual on the basis of which pools contained the mutation. A custom gene capture of 97 candidate genes was sequenced on the Illumina HiSeq 2000. Multistep bioinformatics processing was performed for base calling, variant identification, and in-silico analysis of putative disease-causing variants.
resultsTargeted capture identified 42 rare, non-synonymous, exonic variants involving 35 of the 97 candidate genes. Among these variants, in-silico analysis classified 33 of these variants as putative disease-causing changes. Sanger sequencing confirmed thirty-one of these variants, found among 16 individuals. There were no significant differences in variant burden among BAV fusion phenotypes or isolated BAV versus BAV-CoA. Pathway analysis suggests a role for the WNT signaling pathway in human BAV.
conclusionWe successfully developed a pooling and targeted capture strategy that enabled rapid and cost effective next generation sequencing of target genes in a large patient cohort. This approach identified a large number of putative disease-causing variants in a cohort of patients with BAV, including variants in 26 genes not previously associated with human BAV. The data suggest that BAV heritability is complex and polygenic. Our pooling approach saved over $39,350 compared to an unpooled, targeted capture sequencing strategy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.