Genome-wide interrogation of longitudinal FEV1in children with asthma

Kehua Wu, Eric R. Gamazon, Hae Kyung Im, Paul Geeleher, Steven R. White, Julian Solway, George L. Clemmer, Scott T. Weiss, Kelan G. Tantisira, Nancy J. Cox, Mark J. Ratain, R. Stephanie Huang

Research output: Contribution to journalArticlepeer-review

12 Scopus citations

Abstract

Rationale: Mostgenomic studies of lung function have used phenotypic data derived from a single time-point (e.g., presence/absence of disease) without considering the dynamic progression of a chronic disease. Objectives: To characterize lung function change over time in subjects with asthma and identify genetic contributors to a longitudinal phenotype. Methods: Wepresent a method that models longitudinal FEV1 data, collected from 1,041 children with asthma who participated in the Childhood Asthma Management Program. This longitudinal progression model was built using population-based nonlinear mixed-effects modeling with an exponential structure and the determinants of age and height. Measurements and Main Results: We found ethnicity was a key covariate for FEV1 level. Budesonide-treated children with asthma had a slight but significant effect on FEV1 when compared with those treated with placebo or nedocromil (P < 0.001). A genome-wide association study identified seven single-nucleotide polymorphisms nominally associated with longitudinal lung function phenotypes in 581 white Childhood Asthma Management Program subjects (P < 10-4 in the placebo ["discovery"] and P < 0.05 in the nedocromil treatment ["replication"] group). Using ChIP-seq and RNA-seq data, we found that some of the associated variants were in strong enhancer regions in human lung fibroblasts andmay affect gene expression in human lung tissue. Genetic mapping restricted to genome-wide enhancer single-nucleotide polymorphisms in lung fibroblasts revealed a highly significant variant (rs6763931; P = 4 × 10-6; false discovery rate < 0.05). Conclusions: This study offers a strategy to explore the genetic determinants of longitudinal phenotypes, provide a comprehensive picture of disease pathophysiology, and suggest potential treatment targets.

Original languageEnglish (US)
Pages (from-to)619-627
Number of pages9
JournalAmerican journal of respiratory and critical care medicine
Volume190
Issue number6
DOIs
StatePublished - Sep 15 2014

Keywords

  • Asthma
  • FEV
  • Longitudinal model
  • NONMEM

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