Abstract
Murine studies have linked TGF-β signaling to emphysema, and human genome-wide association studies (GWAS) studies of lung function and COPD have identified associated regions near genes in the TGF-β superfamily. However, the functional regulatory mechanisms at these loci have not been identified. We performed the largest GWAS of emphysema patterns to date, identifying 10 GWAS loci including an association peak spanning a 200 kb region downstream from TGFB2. Integrative analysis of publicly available eQTL, DNaseI, and chromatin conformation data identified a putative functional variant, rs1690789, that may regulate TGFB2 expression in human fibroblasts. Using chromatin conformation capture, we confirmed that the region containing rs1690789 contacts the TGFB2 promoter in fibroblasts, and CRISPR/Cas-9 targeted deletion of a ~ 100 bp region containing rs1690789 resulted in decreased TGFB2 expression in primary human lung fibroblasts. These data provide novel mechanistic evidence linking genetic variation affecting the TGF-β pathway to emphysema in humans.
Highlights
Emphysema, that is pathologic destruction of lung parenchyma resulting in airspace enlargement, is one of the major manifestations of chronic obstructive pulmonary disease (COPD)
These local histogram emphysema (LHE) measures are more predictive of clinical outcomes than standard computed tomography (CT) emphysema quantifications (Castaldi et al, 2013), and in a previous genome-wide association study (GWAS) we identified genome-wide significant
In subjects from the COPDGene Study, we have previously demonstrated that LHE measures are associated with COPD-related phenotypes (Castaldi et al, 2013) and with common genetic variants at genome-wide significance (Castaldi et al, 2014)
Summary
That is pathologic destruction of lung parenchyma resulting in airspace enlargement, is one of the major manifestations of chronic obstructive pulmonary disease (COPD). Emphysema occurs in distinct pathologic patterns, but these patterns are not captured by traditional quantitative measures of emphysema from lung computed tomography (CT). In order to have more detailed radiographic measures of emphysema, we developed novel image extraction techniques to quantify the distinct patterns of emphysema based on the analysis of local lung density histograms (Mendoza, 2012). These local histogram emphysema (LHE) measures are more predictive of clinical outcomes than standard CT emphysema quantifications (Castaldi et al, 2013), and in a previous genome-wide association study (GWAS) we identified genome-wide significant
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