Unbiased genome-wide association studies (GWAS) in chronic obstructive pulmonary disease (COPD) and asthma have identified many novel candidate genes that can pinpoint pathways and mechanisms not previously recognized in lung diseases. However, in-depth functional and mechanistic studies targeting GWAS candidate genes in the post-GWAS era have been relatively limited. A critical step is to integrate in vitro and in vivo animal models, as well as “omics” measures and systems biological analysis, to elucidate the underlying biology of these novel genes.
The research goals of our Functional Genomics Laboratory at the Channing Division of Network Medicine (CDNM) are to fill in such knowledge gaps between population genetics and the biology of lung disease. To address this, we will:
Fundamental improvements in our translating genetic research will provide targets for new drug development for COPD.
More than 50% of GWAS regions identified in complex traits are located in the non-coding regions of the human genome, indicating potential regulatory roles of these functional variants. However, linking these intergenic or intronic GWAS regions to the correct disease casual genes relies on deep understanding on the chromatin states and chromatin interaction map in relevant lung cell types.
We apply different types of "Cs" methods (including 3C and 4C, capture HiC, et al) in lung-derived epithelial and fibroblasts to assign correct genes into the COPD GWAS regions. We also assess genome-wide DNA accessibility by ATAC-Seq (transposase-accessible chromatin using sequencing) and DNase-Seq in important lung cell types, including epithelial and fibroblasts. We subsequently apply CRISPR/Cas9-based genome editing method to confirm impacts of these regulatory elements within GWAS regions on gene expression levels in human bronchial epithelial cells.
Achievements of the CDNM Functional Genomics Lab include:
We apply a semi-high throughput method to search for functional variants in the COPD GWAS locus. Through the massively parallel reporter assay (MPRA), we can simultaneously measure allelic specific enhancer activity for hundreds of SNPs in a human bronchial epithelial cell line. This is a sequencing-based assay where the enhancer activity is inferred by copy number of a sequencing barcode that is transcribed downstream to the luciferase gene driven by SNPs-containing enhancer-promoter. Similar screening methods will be applied to other GWAS regions for screening functional variants in a high-throughput way.
Though GWAS is powerful to pinpoint novel disease candidate genes, the importance of GWAS genes in vivo has been questionable. Our findings in Hhip +/- mouse line, a suitable model to recapitulate human subjects carrying the COPD risk allele at the HHIP (Hedgehog Interacting Protein) locus (which have similar levels of HHIP reduction), provided supporting evidence for the biological impacts of GWAS variants.
We have demonstrated association of the COPD risk allele with reduced HHIP expression through chromatin long-range interactions, and an ~32% reduction in HHIP mRNA expression in human COPD lung samples. Moreover, developmentally normal HHIP heterozygous mice (Hhip +/-) demonstrated a ~33% reduction of HHIP in lung tissues and demonstrated increased susceptibility to CS-induced emphysema, recapitulating human genetic discoveries at the HHIP locus. Hhip +/- mice developed increased susceptibility to age- and smoke-induced emphysema and lung functional decline, providing in vivo evidence that HHIP locus is associated with lung function in both COPD patients and general non-smoker populations. Furthermore, the Hhip +/- mouse model also provides a very strong translational potentiation for mechanistic studies that will lead to novel drugs that will be tested in this murine model and eventually to smokers carrying risk genetic factors for COPD at the HHIP locus.
Integrative analysis on multi-omics data sets could infer COPD and asthma shared networks,which could potentially identify authentic genetic determinants that predispose early childhood asthma patients to subsequent impaired lung function and COPD in later life.
Genes derived from networks generated by a state-of-the-art building method using various 'omics' data, including genetic, epigenetic, or genomic data from asthma and COPD subjects, will be tested in a cellular model to mimic asthma and COPD-related phenotypes, including epithelial injury and cytokines release after gene silencing targeting these overlapped disease causal genes.