Blanca E. Himes, Keith Sheppard, Annerose Berndt, Adriana S. Leme, Rachel A. Myers, Christopher R. Gignoux, Albert M. Levin, W. James Gauderman, James J. Yang, Rasika A. Mathias, Isabelle Romieu, Dara G. Torgerson, Lindsey A. Roth, Scott Huntsman, Celeste Eng, Barbara Klanderman, John Ziniti, Jody Senter-Sylvia, Stanley J. Szefler, Robert F. Lemanske, Robert S. Zeiger, Robert C. Strunk, Fernando D. Martinez, Homer Boushey, Vernon M. Chinchilli, Elliot Israel, David Mauger, Gerard H. Koppelman, Dirkje S. Postma, Maartje A. E. Nieuwenhuis, Judith M. Vonk, John J. Lima, Charles G. Irvin, Stephen P. Peters, Michiaki Kubo, Mayumi Tamari, Yusuke Nakamura, Augusto A. Litonjua, Kelan G. Tantisira, Benjamin A. Raby, Eugene R. Bleecker, Deborah A. Meyers, Stephanie J. London, Kathleen C. Barnes, Frank D. Gilliland, L. Keoki Williams, Esteban G. Burchard, Dan L. Nicolae, Carole Ober, Dawn L. DeMeo, Edwin K. Silverman, Beverly Paigen, Gary Churchill, Steve D. Shapiro, Scott T. Weiss

Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR). The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify asthma-related genes by integrating AHR associations in mouse with human genome-wide association study (GWAS) data. We used Efficient Mixed Model Association (EMMA) analysis to conduct a GWAS of baseline AHR measures from males and females of 31 mouse strains. Genes near or containing SNPs with EMMA p-values <0.001 were selected for further study in human GWAS. The results of the previously reported EVE consortium asthma GWAS meta-analysis consisting of 12,958 diverse North American subjects from 9 study centers were used to select a subset of homologous genes with evidence of association with asthma in humans. Following validation attempts in three human asthma GWAS (i.e., Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG) and two human AHR GWAS (i.e., SHARP, DAG), the Kv channel interacting protein 4 (KCNIP4) gene was identified as nominally associated with both asthma and AHR at a gene- and SNP-level. In EVE, the smallest KCNIP4 association was at rs6833065 (P-value 2.9e-04), while the strongest associations for Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG were 1.5e-03, 1.0e-03, 3.1e-03 at rs7664617, rs4697177, rs4696975, respectively. At a SNP level, the strongest association across all asthma GWAS was at rs4697177 (P-value 1.1e-04). The smallest P-values for association with AHR were 2.3e-03 at rs11947661 in SHARP and 2.1e-03 at rs402802 in DAG. Functional studies are required to validate the potential involvement of KCNIP4 in modulating asthma susceptibility and/or AHR. Our results suggest that a useful approach to identify genes associated with human asthma is to leverage mouse AHR association data.