Pediatric conditions, such as birth defects and pediatric cancers, if not fatal, have profound, lifelong effects on patients and their families with society as a whole ultimately bearing the socioeconomic costs. Annually, almost five percent of all live births in the United States (more than 180,000 babies) involve babies born with birth defects when broadly defined to include both structural and functional/metabolic abnormalities. Next to accidents, birth defects are the leading cause of death in children; they account for half of all pediatric hospitalizations. In addition, cancer remains the leading cause of childhood disease-related mortality beyond the first year of life.
The genomics revolution holds promise for enabling the discovery of effective and targeted therapies based on the underlying genetic classification of conditions – the ideal of precision medicine. Developmental biology has revealed the underlying genetic networks common to organ system development, and the combined efforts of basic scientists studying these genetic networks and physician scientists sequencing patient cohorts together place the field of structural birth defects research on the verge of major advances. Likewise, major advances have been made in understanding the genetics and genomics of childhood cancers, particularly in the past decade through the work of large projects such as the NCI Childhood Cancer TARGET Initiative, the St. Jude Children’s Research Hospital – Washington University Pediatric Cancer Genome Project, and other research efforts throughout the world. Within both research communities, understanding the etiology and mechanisms and ultimately formulating treatments and prevention strategies are more than ever a possibility for these pediatric conditions.
Heterogeneous genetic etiology is an issue for both the structural birth defects and the pediatric cancer fields. It is clear that recent advances in sequencing technology have led to greater insights. For example, our understanding of congenital heart defects has benefited with sequencing implicating de novo point mutations in several hundreds of genes that collectively contribute to approximately 10% of severe congenital heart disease cases. Importantly, a lesson from these and other studies is that large sample sizes are required to fully understand the heterogeneous genetic etiology. Studies have suggested that there may be genetic overlap between different, currently felt to be unrelated, birth defects. A lesson from these studies is that integrating genotype datasets from disparate diseases may increase the power for gene discovery and open up avenues of novel exploration. While these intellectual insights can be applied within the fields of structural birth defects research or childhood cancer research, it is equally true that genetic pathways common to both conditions will continue to be revealed by efforts that integrate genomic data.
In response to The Gabriella Miller Kids First Act, NIH has established the Gabriella Miller Kids First Pediatric Research Program (Kids First). The Kids First Program’s long term goal is to develop an integrated pediatric research data resource by obtaining and aggregating genome sequence and phenotype data for as many relevant structural birth defects and pediatric cancer cohorts as possible. It is anticipated that these genomic and phenotypic data will be of high value for the pediatric research community. During fiscal years 2015-2018, the intent is to augment the whole genome sequence data available to the research community by sequencing relevant cohorts through other funding opportunities (e.g., PAR-15-259; PAR-16-150) and to establish a Kids First Sequencing Center(s) (RFA-RM-16-001). The Data Resource is expected to be funded in fiscal year 2017 and will coordinate access to Kids First data stored in NIH’s dbGaP and the NCI’s Genomic Data Commons (GDC). All told, the Kids First Program is expected to be a ten-year effort that will continue building an integrated data resource and expanding the capacity to effectively mine data across diverse conditions to uncover shared developmental pathways. The overall goal is to help researchers understand the underlying mechanisms of childhood diseases, leading to more refined diagnostic capabilities and ultimately more targeted therapies or interventions.
The purpose of this FOA is to support meritorious small research projects that involve analyses of genomic and phenotypic datasets that are part of the Kids First Data Resource or that could be added to the Data Resource. Investigators who have had samples sequenced through the Kids First program may apply to analyze these datasets. Applicants whose analyses focus on their own whole genome sequence data must be willing and able to deposit their datasets into the Kids First Data Resource if funded, so that these data are available to the pediatric research community.
The data analyses proposed should utilize the Kids First sequence and phenotype data currently available through the NIH’s dbGaP or the NCI’s GDC and eventually though the Kids First Data Resource. If the applicant already has other whole genome sequence data relevant to the Kids First program and is willing and able to submit it to the Kids First Data Resource, then they may also apply to this FOA for data analyses funds. Both primary and secondary analyses of Kids First data may be proposed in order to develop hypotheses or investigate research questions related to structural birth defects and/or pediatric cancers. Studies proposed may combine data within cohorts or across phenotypically different cohorts to more powerfully address the research questions. While combining Kids First data and other genomic data in the analyses is permissible under this FOA, it is expected that the Kids First data will be the major focus of the project. The intent is to catalyze the discovery of new variants underlying these pediatric conditions, to reveal unrealized common genetic pathways shared by related conditions, and to provide a means to generate preliminary data supporting larger projects focused on functional studies. Potential types of analyses that would be supported by this FOA could include, but are not limited to, variant annotation, de novo annotation, de novo structural variant and SNP detection, rare variant analyses through burden testing, or candidate gene analyses. Development of statistical methodology appropriate for analyzing genome-wide data relevant to childhood cancer and/or structural birth defects may also be proposed.
Deadlines: standard dates apply
Filed Under: Funding Opportunities