The combination of a genome-wide association study of lymphocyte count and analysis of gene expression data reveals novel asthma candidate genes

Abstract

Recent genome-wide association studies (GWAS) have identified a number of novel genetic associations with complex human diseases. In spite of these successes, results from GWAS generally explain only a small proportion of disease heritability, an observation termed the 'missing heritability problem'. Several sources for the missing heritability have been proposed, including the contribution of many common variants with small individual effect sizes, which cannot be reliably found using the standard GWAS approach. The goal of our study was to explore a complimentary approach, which combines GWAS results with functional data in order to identify novel genetic associations with small effect sizes. To do so, we conducted a GWAS for lymphocyte count, a physiologic quantitative trait associated with asthma, in 462 Hutterites. In parallel, we performed a genome-wide gene expression study in lymphoblastoid cell lines from 96 Hutterites. We found significant support for genetic associations using the GWAS data when we considered variants near the 193 genes whose expression levels across individuals were most correlated with lymphocyte counts. Interestingly, these variants are also enriched with signatures of an association with asthma susceptibility, an observation we were able to replicate. The associated loci include genes previously implicated in asthma susceptibility as well as novel candidate genes enriched for functions related to T cell receptor signaling and adenosine triphosphate synthesis. Our results, therefore, establish a new set of asthma susceptibility candidate genes. More generally, our observations support the notion that many loci of small effects influence variation in lymphocyte count and asthma susceptibility.

Figure 1.

Study design. We performed a gene expression profiling study (1a) to identify differentially expressed genes between individuals with low and high lymphocyte counts, as well as a GWAS (1b) to identify loci associated with lymphocyte counts. We integrated data from the two studies (2) to identify candidate genes that would have been missed by the GWAS alone. Ultimately, we asked whether these candidate genes are also associated with asthma (3).

Figure 2.

GWAS for lymphocyte count. (A) Manhattan plot displaying the −log₁₀ (P-values) for a GWAS of lymphocyte counts in 462 Hutterites. The top two SNPs are circled. (B) Close-up of the region around the top SNP, rs2746347 (red point), which is located within the first intron of PRKAA2. The estimated recombination rate (based on HapMap data) in the region is also plotted. (C) Close-up of the region around the second most significant SNP, rs881827 (red point), located within an intron of S100B.

Figure 3.

Choice of samples for the gene expression profiling study. A histogram of the distribution of lymphocyte counts (x-axis; the transformed residuals after correcting for age) for all available samples (gray bars) and for the 96 individuals chosen for the gene expression profiling study (red bars).

Figure 4.

Integrating the GWAS and gene expression profiling studies. (A) The median lymphocyte count GWAS P-value (y-axis) for an expanding window of genes is plotted in red. Genes are ordered by the strength of evidence supporting differences in expression level between individuals with low and high lymphocyte counts. The blue curves indicate the confidence interval for median P-values for random sets of genes at each test set size (based on 10 000 permutations). (B) A box plot of the distribution of median lymphocyte count GWAS P-values for random sets of 193 genes (based on 10 000 permutations). The whiskers extend to the 5th and 95th percentile. Black points indicate the observed medians outside this range. The red ‘X’ indicates the median P-value observed for the top 193 differentially expressed genes.

Figure 5.

Integrating results with asthma meta-analyses. Box plots of the distribution of median GABRIEL meta-analysis P-values and median EVE meta-analysis P-value for random sets of 117 genes (based on 10 000 permutations). The whiskers extend to the 5th and 95th percentiles. Black points indicate the observed medians outside this range. For each box plot, the red ‘X’ indicates the median P-value observed for the 117 genes carried forward based on the analysis of association with lymphocyte counts.