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Integration of Mouse and Human Genome-Wide Association Data Identifies KCNIP4 as an Asthma Gene

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 and Scott T Weiss

PLOS ONE, 2013, vol. 8, issue 2, 1-11

Abstract: 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

Date: 2013
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0056179

DOI: 10.1371/journal.pone.0056179

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