Integration of Genetics and Cell-type Specific Gene Expression in COPD

Abstract Background: Genome-wide association studies (GWAS) have identified multiple genomic loci associated with COPD susceptibility. Genetic variants that influence gene expression are termed expression quantitative trait loci (eQTL). Integration of COPD GWAS results and lung tissue eQTLs using statistical colocalization methods have been successful in identifying shared causal variants to implicate particular genes in COPD, though these findings have lacked cell-type specific context. In this study, we sought to identify lung cell-type specific eQTLs to uncover the cell-type specific signal traditionally buried in the noise during bioinformatic analyses of homogenized lung tissue. Methods: Using bulk lung tissue RNA-sequencing (RNA-seq) data from the Lung Tissue Research Consortium TOPMed study, we estimated cell-type proportions and cell-type specific gene expression profiles (GEPs) using the computational deconvolution method CIBERSORTx with published lung single cell RNA-seq reference data. Single nucleotide polymorphism (SNP) data were extracted from whole-genome sequencing. We performed eQTL analyses by testing associations between SNP genotypes and the GEP for each cell type in the deconvolution output, using regression models in the R package limma. We integrated the association profiles from eQTLs and prior COPD GWAS within COPD-associated genomic loci using the colocalization method in the R package coloc. Results: We selected 715 subjects with complete RNA-seq, genetic and phenotypic data, including 420 COPD cases and 295 control subjects. Based on previous colocalization studies in lung tissue bulk expression data and studies that identified a functional variant (rs7962469) for ACVR1B in emphysema, we investigated the genomic region near the gene ACVR1B. Associations between rs7962469 genotype and estimated GEPs were tested in epithelial type 2 (ATII), goblet and mesothelial cells; three cell types with non-zero expression of ACVR1B. Significant associations (p-value < 0.05) were observed for ATII and mesothelial cells, though the ATII association was more robust (p-value < 0.0001). The results from coloc for the ACVR1B genomic region suggest colocalization for ATII cells (probability of shared causal variant = 0.482). Conclusions: We sought to identify cell-type specific eQTLs, leveraging computational deconvolution methods and single-cell RNA-seq reference data. We hypothesized this would reveal cell-type dependent genetic control of gene regulation in COPD-relevant loci. We observed colocalization in the ACVR1B locus, providing additional context to previous eQTL and functional studies. We believe these findings provide insight for future functional studies.

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