The development of massively parallel sequencing technologies may hold the key to personalized medicine as it allows for the identification of functional genetic variants that rende a person susceptible to disease. For this to become reality, disease-causing genes must be identified. This proposal concentrates on non-syndromic congenital heart defects (CHDs). Representing the most common type of birth defect, CHDs affect not only children but also a growing population of adult survivors. Epidemiologic studies have demonstrated genetic contributors, but few etiologic genes have been identified. Until this knowledge gap is overcome, the underlying molecular cause will remain hidden and hinder the development of new therapies and potentially prediction of long-term complications. Our long-term goal is to identify the underlying genetic causes and elucidate the molecular mechanisms leading to CHDs. The overall objective of this application is to discover the genetic variation that results in CHDs. Th central hypothesis is that CHD-causing genes can be identified by a genome-wide sequencing approach, using families exhibiting Mendelian inheritance patterns. The rationale for the proposed research is that the discovery of genetic causes of CHDs has the potential to provide better risk counseling and result in novel therapies for malformations that contribute to mortality from infancy to adulthood. Guided by recent literature supporting this premise and possession of a unique cohort of families, the central hypothesis will be tested by pursuing two Specific Aims: 1) Expand our current cohort of multiplex families and sporadic cases of CHDs;2) Identify disease-causing genes in families exhibiting Mendelian segregation for CHDs and in trios via transmission disequilibrium tests by exome and whole genome sequencing. Methods will be developed specifically to test for rare variant associations in trio data, which aggregate over variants within a gene region and weight these variants based upon frequency and functionality. These methods will also allow for the joint analysis of unrelated individuals with a family history of CHD and trio data. The putative causal variants functional effects will be investigated by in vitro and in vivo Xenopus assays. A larger cohort with CHD will then be screened for mutations in identified genes. Our approach is innovative not only because it employs new technologies but also adds the power of Mendelian genetics through the use of families to tackle the genetic basis of a complex disease. This application focuses on part of the NHLBI Strategic Plan goals and challenges to identify key genetic variants in the human population that are associated with specific diseases. Success of this proposal will create a paradigm shift in the approach for human disease gene identification. The proposed research is significant because it is expected to vertically advance the fields of human genetics, developmental biology and cardiovascular medicine by identifying causal genes for CHDs. In the current era of fetal diagnosis and intervention, this knowledge will be used to improve prevention measures, in utero diagnosis, genetic counseling and therapy.

Public Health Relevance

Project Narrative. The proposed study is relevant to public health as it address a significant cause of morbidity and mortality in infancy. This planned research has the potential to increase the fundamental understanding of disease pathogenesis, and identify at risk individuals early for possible interventions. Thus, the proposed research is relevant to Goal 1 of the NHLBI Strategic Plan, to increase understanding of the molecular and physiological basis of health and disease, by determining key genetic variants that account for susceptibility to specific disease, and to the NICHD's scientific goals of understanding genetics of disease susceptibility and normal and abnormal development by genetic studies of birth defects.

Agency
National Institute of Health (NIH)
Institute
National Heart, Lung, and Blood Institute (NHLBI)
Type
Research Project (R01)
Project #
1R01HL109758-01A1
Application #
8297881
Study Section
Genetics of Health and Disease Study Section (GHD)
Program Officer
Kaltman, Jonathan R
Project Start
2012-09-24
Project End
2016-07-31
Budget Start
2012-09-24
Budget End
2013-07-31
Support Year
1
Fiscal Year
2012
Total Cost
$695,636
Indirect Cost
$177,981
Name
Nationwide Children's Hospital
Department
Type
DUNS #
147212963
City
Columbus
State
OH
Country
United States
Zip Code
43205
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Fitzgerald-Butt, S M; Bodine, A; Fry, K M et al. (2016) Measuring genetic knowledge: a brief survey instrument for adolescents and adults. Clin Genet 89:235-43
Prakash, Siddharth; Kuang, Shao-Qing; GenTAC Registry Investigators et al. (2016) Recurrent Rare Genomic Copy Number Variants and Bicuspid Aortic Valve Are Enriched in Early Onset Thoracic Aortic Aneurysms and Dissections. PLoS One 11:e0153543
Hanchard, Neil A; Swaminathan, Shanker; Bucasas, Kristine et al. (2016) A genome-wide association study of congenital cardiovascular left-sided lesions shows association with a locus on chromosome 20. Hum Mol Genet 25:2331-2341
LaHaye, Stephanie; Corsmeier, Don; Basu, Madhumita et al. (2016) Utilization of Whole Exome Sequencing to Identify Causative Mutations in Familial Congenital Heart Disease. Circ Cardiovasc Genet 9:320-9
Fry, Kevin M; Gerhardt, Cynthia A; Ash, Jerry et al. (2015) Lifetime prevalence of sexual intercourse and contraception use at last sex among adolescents and young adults with congenital heart disease. J Adolesc Health 56:396-401
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Cheng, Jeeyun; Koenig, Sara N; Kuivaniemi, Helena S et al. (2014) Pharmacological inhibitor of notch signaling stabilizes the progression of small abdominal aortic aneurysm in a mouse model. J Am Heart Assoc 3:e001064
Bonachea, Elizabeth M; Zender, Gloria; White, Peter et al. (2014) Use of a targeted, combinatorial next-generation sequencing approach for the study of bicuspid aortic valve. BMC Med Genomics 7:56
Brownstein, Catherine A; Beggs, Alan H; Homer, Nils et al. (2014) An international effort towards developing standards for best practices in analysis, interpretation and reporting of clinical genome sequencing results in the CLARITY Challenge. Genome Biol 15:R53

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