DESCRIPTION (provided by applicant): Candidate: The candidate is an Assistant Professor of Pediatrics in the Divisions of Asthma Research at Cincinnati Children's Medical Center and the University of Cincinnati. Upon completion of his quantitative genetics training, the candidate pursed statistical and human genetics fellowship programs at the University of Alabama Section on Statistical Genetics and the Human Genetics Center of Medical College of Wisconsin. These projects have been published in peer-review journals. Dr. Baye's overall research interest includes the use of quantitative and statistical genetics methods to dissect complex diseases particularly asthma and asthma-related allergy disorders. The long-term goals are to reduce childhood morbidity and mortality associated with asthma. Environment: At the Cincinnati Children's Hospital Medical center, the applicant will work with a highly collaborative multidisciplinary research team and will be fostered in an excellent academic environment offering outstanding educational programs for junior faculty members. The institution, through the Divisions of Asthma Research, Asthma Center, Biostatistics and Epidemiology, Biomedical Informatics and the Genetic Variation and Gene Discovery Core, provides all resources and facilities that are needed for the applicant's proposed research and is providing full access to all necessary resources to the applicant. The applicant will be provided 90% protected time to conduct the research proposed in this application. Research: This project aims to develop a program of study that would lead to an in depth understanding of the genome of African American (AA) admixed populations and develop procedures and methods for utilizing this information and SNP markers for linkage disequilibrium admixture mapping to localize asthma liability genes. The burden of asthma is disproportionately high among individuals of African descent. Due to recent admixture, AAs have a mixed parental genome contribution, with an average ratio of 80:20 for the proportion from African descent and European descent. This generates linkage disequilibrium (LD) among alleles on all chromosomes, which is detectable even at substantial distances (20-30 cM) using Ancestry Informative Markers (AIMs). We plan to develop methods to exploit this LD that span along the genomes of AAs with asthma, in search for specific regions of unusually high African or European ancestry, thereby identifying the chromosomal segments that are likely to contain genes that are related to the disease liability. To achieve these goals, the following specific aims are proposed: 1) Investigate the genome of African American admixed population using our recently developed ancestry informative markers (Baye et al., 2009); 2) Estimate admixture proportions and evaluate differences between asthma cases and controls; 3) Apply these procedures to investigate whether genetic ancestral background at the 5q31 region is associated with asthma outcome measures. Hence, genotypic data from HapMap, Perlegen datasets and Greater Cincinnati Pediatric Clinic Cohort will be used to test the approach and enhance our ability to map asthma liability genes. Implications: This career development plan will foster Dr. Baye's development into an established independent expertise in complex disease and asthma genetics. The research will improve mapping of loci affecting complex traits in admixed populations, ultimately improving elucidation of the genetic architecture of complex human diseases.

The burden of asthma is disproportionately high among individuals of ethnic minorities. This project aims to develop procedures and methods for utilize the genome of admixed African American populations to localize asthma liability genes by modeling individual estimates of genetic admixture and socioeconomic status on measures of asthma. By gaining a better understanding of asthma risk factors in admixed minority populations, this proposal is consistent with the goals established by Healthy People 2010, which are to eliminate health disparities among different segments of the population. (End of Abstract)