This administrative supplement application is under the parent grant entitled "Alpha-1 Antitrypsin Deficiency and Lung Cancer Risk, R01 CA 80127," ending in May 2011 after a no-cost one-year extension. The proposed project is built on an established rich resource of multiple case-control sets that consists of over 600 never smoker pairs, over 1000 heavy smoker pairs, and over 1000 unaffected full siblings of cases. The main goal of this supplemental proposal is to strengthen and expand the analytical capacity and scope to overarch multiple levels of complexity from a single candidate gene to a well-defined mechanistic pathway, to a few highly-related functional pathways, then to genome-wide patterns and peaks recognition, all synthesized to the central framework of gene-environment interaction coupled with host susceptibility of lung cancer development. Two specific aims are:  series of rapid validation of recently published results from genome-wide (GW) association studies (GWAS) and  to effectively integrate germline GW-SNP (single nucleotide polymorphism), GW-CNV (copy number variation), and GW-CpG (methylation of CpG island) profiling data. A secondary aim, that is critical to a breakthrough in understanding the human genome, is cross verification of DNA alterations (under Aim 2) with target tissue-based RNA and micro RNA patterns. Two strategies in achieving this challenging aim are:  to timely utilize state-of-the-art tools and technology that are available and  to develop needed customized analytic tools in order to keep disease etiology research in line with the cutting-edge direction of integrated genomics. Equally important in lung cancer etiology research, we will encompass environmental exposure history and prior medical history of lung disease, particularly chronic obstructive pulmonary diseases (COPD). Our proposal project will employ a specialized post-doctoral associate/fellow to conduct multi-level genomic analysis; the purpose is to accelerate the understanding of the biological mechanisms underlying lung cancer, which in turn will accelerate the pace of translating genomic knowledge into improved patient care. Specifically, this post-doctoral associate/fellow will have specialized training and experience in high-dimension bioinformatics, genetic epidemiology, and computational biology; the top preference will be citizens of United States.