African American individuals are more likely to develop asthma and are nearly three times as likely to experience serious asthma complications when compared with European American individuals. Genome wide association studies have identified a number of genetic risk markers for asthma, but many of the associations observed in European and European American patients have not replicated in African American individuals. This may be the result of allele frequencies, linkage disequilibria, or disease-related genes which differ by ancestry. Detailed characterization of the transcriptome can aid in the identification of asthma-related genes by circumventing some of the aforementioned problems associated with genotype association alone. Therefore, this proposal seeks to combine transcriptomics and genomics to identify asthma-related genes and the expression quantitative trait loci (eQTL) which appear to regulate these genes. We propose using RNA sequencing (RNA-seq) to characterize the transcriptome of African American individuals with and without asthma. RNA-seq is superior to traditional microarrays at quantifying transcript abundance, but this method has not been widely used in U.S. minority populations to date. The Study of Asthma Phenotypes and Pharmacogenomic Interactions by Race-ethnicity (SAPPHIRE) cohort is an ideal group in which combine these analytic approaches. In addition to being one of largest and best characterized asthma cohorts in the U.S., genome wide genotype data and banked whole blood RNA already exist for a large number of SAPPHIRE participants.
In Specific Aim 1, we will use RNA-seq to identify expression differences in previously identified asthma-related genes among African American individuals by asthma status. Pre-existing genotype data will then be used to identify eQTL for these differentially expressed, asthma-associated genes.
In Specific Aim 2, we will use admixture mapping to identify chromosomal regions where ancestry is associated with asthma. The genes in these regions will be interrogated for differential expression by asthma status. The resulting potentially novel, ancestry-specific asthma genes will also be assessed for eQTL. As a subset of African American SAPPHIRE participants have RNA collected at both their initial evaluation and the time of an asthma exacerbation, in Specific Aim 3 we will assess whether the genes identified in the preceding aims are also associated with asthma exacerbations. Lastly, Specific Aim 4 will attempt to replicate our findings in a separate group of African American participants with and without asthma. In summary, asthma is a complex disease with potentially distinct genetic predictors by ancestry. Persisting inequities in asthma complications by race-ethnicity underscore the need for improved disease biomarkers and therapeutic targets. As a step in this direction, we proffer an integrative approach with greater statistical power to identify asthma-related genes and their regulatory elements.
Although African Americans are more likely to be affected by asthma and its complications, less is known about the genetics of asthma in this group as compared with European Americans. This project will identify new asthma-related genes by using the genetic diversity of African Americans and recent advances in measuring gene expression. Through this combined approach we anticipate finding new targets to better diagnose and manage asthma.
|Sherenian, M G; Cho, S H; Levin, A et al. (2017) PAI-1 gain-of-function genotype, factors increasing PAI-1 levels, and airway obstruction: The GALA II Cohort. Clin Exp Allergy 47:1150-1158|
|Yang, James J; Williams, L Keoki; Buu, Anne (2017) Identifying pleiotropic genes in genome-wide association studies from related subjects using the linear mixed model and Fisher combination function. BMC Bioinformatics 18:376|
|Johnston, Henry Richard; Hu, Yi-Juan; Gao, Jingjing et al. (2017) Identifying tagging SNPs for African specific genetic variation from the African Diaspora Genome. Sci Rep 7:46398|
|Cajigal, Sonia; Wells, Karen E; Peterson, Edward L et al. (2017) Predictive Properties of the Asthma Control Test and Its Component Questions for Severe Asthma Exacerbations. J Allergy Clin Immunol Pract 5:121-127.e2|
|Lanfear, David E; Gibbs, Joseph J; Li, Jia et al. (2017) Targeted Metabolomic Profiling of Plasma and Survival in Heart Failure Patients. JACC Heart Fail 5:823-832|
|Mathias, Rasika Ann; Taub, Margaret A; Gignoux, Christopher R et al. (2016) A continuum of admixture in the Western Hemisphere revealed by the African Diaspora genome. Nat Commun 7:12522|
|Zhou, Kaixin; Yee, Sook Wah; Seiser, Eric L et al. (2016) Variation in the glucose transporter gene SLC2A2 is associated with glycemic response to metformin. Nat Genet 48:1055-1059|
|Yang, James J; Li, Jia; Williams, L Keoki et al. (2016) An efficient genome-wide association test for multivariate phenotypes based on the Fisher combination function. BMC Bioinformatics 17:19|
|Ahmedani, Brian K; Peterson, Edward L; Wells, Karen E et al. (2016) Long-term Management of Low Back Pain with Opioids and Non-steroidal Anti-inflammatory Drugs in a Health System. Am J Prev Med 50:e191-e193|
|Wells, Karen E; Cajigal, Sonia; Peterson, Edward L et al. (2016) Assessing differences in inhaled corticosteroid response by self-reported race-ethnicity and genetic ancestry among asthmatic subjects. J Allergy Clin Immunol 137:1364-1369.e2|
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