Epidemiology of Surfactant Protein-B Deficiency

• Statistical association of rare, functionally disruptive genomic variant with RDS [ Time Frame: 4 weeks ] [ Designated as safety issue: No ]
  Using custom exon capture, next generation sequencing, and in silico prediction of function, discover statistical associations between gene loci with excess, rare, functionally disruptive variants and risk of neonatal respiratory distress syndrome.
  
  

• Statistical associations between risk of neonatal respiratory distress syndrome and excess, rare functional variants in gene pathways [ Time Frame: 4 weeks ] [ Designated as safety issue: No ]
  Using custom exon capture, next generation sequencing, in silico prediction of functional variants, and Metacore for pathway construction, identify statistical associations between risk of neonatal respiratory distress syndrome and pathways with excess, rare functional variants
  
  

BACKGROUND:

Respiratory distress syndrome is the most frequent respiratory cause of death and morbidity in infants less than 1 year of age in the United States. Of approximately 28,500 infant deaths in 2006, 5,421 (19.7%) were diagnosed with respiratory distress as either the primary (1,011 - 3.7%) or secondary (4,410 - 16%) cause of death. Despite improvement in infant mortality rates over the last 20 years, survivors of respiratory distress syndrome with chronic respiratory disease consume twenty times more annualized dollars than unaffected children and 5.9% of all dollars spent on children from 0-18 years of age. More recent estimates including data from California and New York, the Institute of Medicine, and the 2001 Nationwide Inpatient Sample from the Healthcare Cost and Utilization Project suggest that the average cost of hospitalization for each of the 49,900 infants with a diagnosis of respiratory distress syndrome was $56,800 vs. $10,700 for a premature infant without respiratory distress syndrome. The recent increase in late preterm births has contributed to both the frequency of respiratory distress syndrome and its economic impact. These medical costs do not include the economic consequences of infant respiratory morbidity for families, e.g., absence from work, and early intervention costs to optimize outcome. In addition, despite 2-3 fold greater risk of infant mortality for African American infants than European American infants from all other causes, European American infants have greater risk of death from respiratory distress than African American infants, and this increased risk is not attributable to differences in surfactant phospholipid composition, birth weight, gestational age, or confounding socioeconomic factors. Understanding the genetic mechanisms that cause respiratory distress syndrome is critical for improving outcomes of children in the United States, reducing costs of their health care, and reducing racial disparity in infant mortality. Since the original description of deficiency of the pulmonary surfactant in premature newborn infants by Avery and Mead in 1959, respiratory distress syndrome has most commonly been attributed to developmental immaturity of pulmonary surfactant production. Despite improvement in neonatal survival associated with availability of surfactant replacement therapy for premature infants, gender and race based disparities in disease frequency, morbidity and mortality have persisted, an observation that suggests that genetic factors play an important role in disease pathogenesis. In addition, twin studies indicate high heritability (h2) of neonatal respiratory distress syndrome (0.2 and 0.8). Recent clinical reports of monogenic causes of neonatal respiratory distress syndrome, statistical association of candidate gene variants with increased disease risk, and studies of targeted gene ablation in murine lineages have also strongly suggested that genetic mechanisms contribute to risk of respiratory distress syndrome in newborn infants. When we examined genetic variants in large population-based and case-control cohorts, we found that the population-based frequencies of individual, disruptive mutations in 3 candidate genes (SFTPB, SFTPC, and ABCA3) (<2%) account for <0.1% of the population attributable risk in term or near term infants, and that individual, rare, disruptive mutations are not associated with disease in case-control cohorts. In addition, when we attempted to establish an association between an intermediate biochemical phenotype (surfactant protein-B peptide mobility on western blot) and SFTPB variants (assessed by complete resequencing) in term and near term infants with and without respiratory distress, we failed to identify a SFTPB variant or combination of variants associated with respiratory distress and altered surfactant protein-B structure. Finally, we have recently found that tagSNPs in genes from gene networks expressed in lung but not part of the pulmonary surfactant network (ion channel, lung remodeling, and unfolded protein response genes) confer race-specific risk of neonatal respiratory distress syndrome. These studies suggest that variation in SFTPB, SFTPC, and ABCA3 is under significant purifying selection pressure and that the genetic contribution to neonatal respiratory distress syndrome is based on contributions of rare, independent risk alleles in multiple genes and gene networks.

DESIGN NARRATIVE:

Rare mutations in the surfactant protein-B gene (SFTPB) and other genes in the pulmonary surfactant metabolic network cause lethal neonatal respiratory distress syndrome in human newborn infants by disrupting metabolism and function of the pulmonary surfactant. Mutation frequencies (<1-2%) in SFTPB and 2 other candidate genes in the pulmonary surfactant network (SFTPC and ABCA3) do not account for heritability of neonatal respiratory distress syndrome (h2~0.2-0.8) suggested by twin studies. To develop a comprehensive catalogue of genes and gene networks that account for the heritability of this complex disease, 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. Specifically, using an agnostic candidate gene identification algorithm and the Kyoto Encyclopedia of Genes and Genomes (KEGG) Pathway Database, we will select a comprehensive list of genes (~2,000) and their cognate gene networks expressed in human lung. Next, to identify a subgroup of genes (N=250) and gene networks with excess, rare, disruptive exonic SNPs associated with neonatal respiratory distress syndrome, we will use hybridization selection/exon capture, next-generation sequencing technology, and new statistical strategies (e.g., Combined Multivariate and Collapsing (CMC) method) in a case-control cohort (N=250 cases, 250 controls) sized to provide adequate statistical power (>0.8). Finally, to validate the highest risk genes and to optimize statistical power to search for epistatic and network x network interactions that confer disease risk, we will use CMC, Bayesian, and logic tree methods to analyze exonic SNPs in a second case-control cohort (N=100 cases, 100 controls) also sized to provide adequate statistical power (>0.8). Using next-generation sequencing technology and state of the art statistical methods to elucidate the genetic complexity of neonatal respiratory distress syndrome will permit the development of personalized diagnostic tools and preventive therapeutic strategies that target whole gene networks rather than individual genes.