Neonatal respiratory distress syndrome due to pulmonary surfactant deficiency is the most frequent respiratory cause of morbidity and mortality among infants <1 year of age in the United States. Although disease pathogenesis has been attributed to developmental delay in pulmonary surfactant production, studies of gender, race, and twins demonstrate significant disease heritability (h2~0.2-0.8). Low frequencies of functional variants, allelic heterogeneity, low linkage disequilibrium in pulmonary surfactant metabolic network genes (SFTPB, SFTPC, and ABCA3), and natural selection against variants that disrupt neonatal lung function suggest that rare, high penetrance alleles of independent origin in multiple candidate genes and gene pathways account for missing disease heritability. Using race-specific, discovery and replication case-control cohorts, next generation sequencing platforms, and Combined Multivariate and Collapsing (CMC) statistical methods, we propose to test the hypothesis that excess, rare, functionally disruptive single nucleotide polymorphisms (SNPs) characterize genes and gene networks associated with increased risk of neonatal respiratory distress syndrome. First, to select a comprehensive, hierarchical list of candidate genes (~1,300) and their cognate gene networks expressed in human lung, we will use a candidate gene identification algorithm and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database. Secondly, to rank gene loci by race-specific disease risk, we will use exonic sequencing, in silico evaluation of exonic SNP function, CMC statistical methods, and separate European American and African American case- control cohorts sized to provide adequate statistical power (>0.8). Thirdly, to validate the ranking of gene loci by race-specific disease risk and to search for epistatic and gene x environment interactions that confer disease risk, we will use exonic sequencing and CMC, Bayesian, and logic tree statistical methods in replication and merged case-control cohorts. The overall impact on child health of unraveling the genetic basis of neonatal respiratory distress syndrome includes reduction in neonatal morbidity and mortality through development of clinically useful diagnostic tools and identification of novel therapeutic targets to prevent genetic disruption of pulmonary surfactant metabolism.
Using state of the art, inexpensive, rapid methods for evaluating genetic code in multiple genes and gene networks and state of the art statistical methods, we will develop preventive and personalized diagnostic and therapeutic strategies to reduce genetic risk of neonatal respiratory distress syndrome, the most common cause of respiratory morbidity and mortality in infants <1 year of age in the United States.
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