Mapping the gap: curation of phenotype-driven gene discovery in congenital heart disease research

The goal of translational research is to improve public health by accelerating basic science discovery to human application and clinical practice. The NHLBI Bench-to-Bassinet (B2B) program promotes this goal through its translational research initiative. Together with other collaborators of the B2B program, the University of Pittsburgh mutagenesis screen strives to elucidate the underlying genetic and developmental processes of congenital heart disease (CHD), which is a significant source of morbidity and mortality in the population. The screen investigators have curated over 200 mouse models of CHD on the Jackson Laboratory (JAX) Mouse Genome Database (MGD) through a multi-tiered strategy of phenotypic and genetic analyses. Within the translational research paradigm, this screen has contributed to the improvement of public health and patient care by enabling the identification of 107 pathogenic mutations in 68 unique genes as well as providing 62 models of human disease for future research and development of therapies. Two mutant mouse lines, lines 1702 and 2407, will be thoroughly discussed with regard to their significance to research. However, analysis of the screen curation protocol demonstrated inefficiencies representative of problems across the entirety of the translational research continuum. Within this continuum, data must be translated and readily shared between databases in each domain. Research is currently scattered across disconnected, autonomous databases, which prevents data integration and comprehensive retrieval of information from a single platform. Moreover, data are represented as a combination of discordant ontologies and free-text annotations, which further impede cross-species or cross-domain comparisons and database integration. Although ontology mapping endeavors have achieved some success, the process is flawed with unequivocal alignments or inaccuracies and requires extensive manual validation. Harmonization of ontologies through, ideally, a standardized, relational framework, is necessary to improve the efficacy and utility of translational research. In summary, the future progress of translational research, as exemplified by the University of Pittsburgh B2B program, and its potential in improving public health depends on the acceleration of basic discovery to clinical application through a network of integrated databases supported by a unified ontological system.

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