RESUMO
Chronic respiratory diseases are a major cause of worldwide mortality and morbidity. Although hereditary severe deficiency of α1 antitrypsin (A1AD) has been established to cause emphysema, A1AD accounts for only â¼ 1% of Chronic Obstructive Pulmonary Disease (COPD) cases. Genome-wide association studies (GWAS) have been successful at detecting multiple loci harboring variants predicting the variation in lung function measures and risk of COPD. However, GWAS are incapable of distinguishing causal from noncausal variants. Several approaches can be used for functional translation of genetic findings. These approaches have the scope to identify underlying alleles and pathways that are important in lung function and COPD. Computational methods aim at effective functional variant prediction by combining experimentally generated regulatory information with associated region of the human genome. Classically, GWAS association follow-up concentrated on manipulation of a single gene. However association data has identified genetic variants in >50 loci predicting disease risk or lung function. Therefore there is a clear precedent for experiments that interrogate multiple candidate genes in parallel, which is now possible with genome editing technology. Gene expression profiling can be used for effective discovery of biological pathways underpinning gene function. This information may be used for informed decisions about cellular assays post genetic manipulation. Investigating respiratory phenotypes in human lung tissue and specific gene knockout mice is a valuable in vivo approach that can complement in vitro work. Herein, we review state-of-the-art in silico, in vivo, and in vitro approaches that may be used to accelerate functional translation of genetic findings.
