Genome-wide interrogation of longitudinal FEV1 in children with asthma

Abstract

Rationale: Most genomic 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: We present 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 and may 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.

Keywords: FEV1; NONMEM; asthma; longitudinal model.

Figure 1.

Goodness of fit of final model. (A) Relationship between observed FEV₁ and population typical FEV₁ predictions. (B) Relationship between observed FEV₁ and individual FEV₁ predictions. (C) Conditional weighted residuals (WRES) versus age. Most conditional WRES evenly distributed around 0. The solid lines are diagonal lines of identity in A and B.

Figure 2.

Visual predictive check of the final model. The median, the 5th, and 95th percent prediction intervals from visual predictive check simulation were superimposed with the observations. (A) Placebo and nedocromil treatment groups. (B) Budesonide treatment group. The medians of model simulations are shown by solid lines and 95% prediction intervals are encompassed by the broken lines. The gray circles refer to the observed FEV₁.

Figure 3.

Regulatory function of rs6763931. The single-nucleotide polymorphism rs6763931 (located in an intron of ZBTB38, black arrow) overlaps a strong enhancer in normal human lung fibroblast (NHLF) and in a lymphoblastoid cell line (GM12878).

Figure 4.

Quantile–quantile plot for the single-nucleotide polymorphisms (SNPs) overlapping strong enhancers. A highly significant association (rs6763931, FDR < 0.05) was identified using SNPs in regulatory regions in human lung fibroblast. The P values obtained from associations of the enhancer SNPs with theta₃ are shown as circles. The horizontal line at 0.05/N (significance level after Bonferroni correction) is also shown. FDR = false discovery rate.