Genome-wide association study of Idiopathic Pulmonary Fibrosis susceptibility using clinically-curated European-ancestry datasets

Abstract

Background: Idiopathic pulmonary fibrosis (IPF) is a rare, incurable lung disease with a median survival of 3-5 years after diagnosis. Treatment options are limited. Genetic association studies can identify new genes involved in disease that might represent potential new drug targets, and it has been shown that drug targets with support from genetic studies are more likely to be successful in clinical development. Previous genome-wide association studies (GWAS) of IPF susceptibility have identified more than 20 signals implicating genes involved in multiple mechanisms, including telomere dysfunction, cell-cell adhesion, host defence immunity, various signalling pathways and, more recently, mitotic spindle assembly complex.

Aim: To leverage new datasets and genotype imputation to discover further genes involved in development of IPF that could yield new pathobiological avenues for exploration and to guide future drug target discovery.

Methods: We conducted a GWAS of IPF susceptibility including seven IPF case-control studies comprising 5,159 IPF cases and 27,459 controls of European ancestry, where IPF diagnosis was made by a respiratory clinician according to international guidelines. Genotypes were obtained from Whole Genome Sequencing (WGS) or from array-based imputation to the TOPMed WGS reference panel. New signals were replicated in independent biobanks with IPF defined using Electronic Healthcare Records. Bayesian fine-mapping was performed to identify the most likely causal variant(s) and bioinformatic investigation undertaken to map associated variants to putative causal genes.

Results: We identified three novel genetic signals of association with IPF susceptibility. Genes prioritised by functional evidence at these signals included MUC1, which encodes a large transmembrane glycoprotein and known biomarker of lung fibrosis, and NTN4 encoding Netrin-4 whose known roles include angiogenesis. The third signal may map to SLC6A6, a taurine and beta-alanine transporter gene, previously implicated in retinal, cardiac and kidney dysfunction.

Conclusion: Our study has identified new associations not previously identified by previous large biobank-based studies thereby highlighting the value of utilising clinically-curated IPF case-control studies, and new genotype imputation. We present new evidence for disease-driving roles of MUC1 and of endothelial cell and vascular changes in IPF.

Figure 1.. Study overview.

SNPs: Single Nucleotide Polymorphisms. WGS: Whole-genome sequencing data.

Figure 2.. Manhattan plot of meta-analysis results.

The y-axis shows the transformed p-values (−log10[p-value]) while the x-axis represents chromosome positions. The horizontal red line corresponds to the genome-wide threshold (p=5.0×10⁻⁸) and the blue line shows the suggestive significance threshold (p=5.0×10⁻⁵). The genomic inflation factor of the meta-analysis results did not show major deviations from the null hypothesis of no association. Newly discovered annotated genes are highlighted in red and bold. The plot has been truncated at p=1×10⁻³⁵. The most significant previously reported MUC5B signal (rs357058950) has a p<5.00×10⁻¹²¹.

Figure 3.. Region plots and forest plots of the three signals of interest:

a) 1q22 region; b) 3p25.1 region; and c) 12q23.1 region. In region plots, the y-axis shows the transformed p-values (−log10[p-value]), while the x-axis represents chromosomal positions (GRCh38). The genome-wide significance threshold (p =5.0×10⁻⁸) is indicated by the horizontal dashed line. Linkage disequilibrium values (r2) are presented according to the LD colour scheme of the upper left legend. Plots were generated using LocusZoom (http://locuszoom.org/).