Richer Models of Asthma Risk: Bridging the Environment-Genetics Divide. This is an application for a Mentored Quantitative Research Development Award (K25) for Dr. Noah Zaitlen, an Assistant Professor in the UC San Francisco Department of Medicine, Lung Biology Center. Dr. Zaitlen has established himself as a successful young investigator in the fields of bioinformatics and computational genetics. He has recently accepted at faculty position at UCSF with the aim of establishing an independent laboratory dedicated to the study of the genetic and environmental basis of pulmonary disease with a focus on Latino and African American populations. The proposed K25 award would provide Dr. Zaitlen with support and protected time to accomplish the following goals: (1) develop via course-work and guided mentorship a sufficient background in pulmonary medicine to construct asthma risk models over genetic and environmental variables;(2) develop an expertise in immunology and environmental health, especially as they relate to pulmonary phenotypes;(3) conduct research into the relationship between genetic, environmental, and ethnic variation in asthma;(4) foster skills to form large-scale interdisciplinary collaborations; with an ultimate goal of (5) developing an independent research career. Dr. Zaitlen has assembled a mentoring team comprised of a primary mentor, Dr. Esteban Gonzalez Burchard, Director of the Asthma Genetics Laboratory at UCSF, co-mentors Dr. John Balmes who studies environmental health, and Dr. Prescott Woodruff who studies asthma subphenotypes, and advisors Drs. Neal Risch, Saunak Sen, and John Witte who all successfully transitioned from quantitative backgrounds into biomedical research. Asthma is a common and complex disease with significant morbidity, often striking early in life. Family and twin studies clearly point to genetic susceptibility, but the epidemiology also strongly indicates important environmental risk factors. There are substantial ethnic differences that are not yet explained - and not entirely consistent with a simple genetic or environmental explanation (i.e. the two Latino groups, Mexicans and Puerto Ricans have the most disparate rates). To better understand the pathogenesis of asthma therefore requires a multi-pronged approach, bringing together basic understanding of immunology, lung biology and environmental health as well as genetic susceptibility. While Dr. Zaitlen is well versed in statistical genetics, he is much less so in the other important disciplines named above. Dr. Burchard's mentorship and access to his studies of asthma in Latino populations offer a unique opportunity for Dr. Zaitlen to develop his research plans. The detailed clinical, genetic and environmental information on these subjects will not only provide a rich resource for simultaneously modeling genetic and environmental risk factors, but will require Dr. Zaitlen, with the help of Dr. Balmes, to learn the fundamentals of environmental epidemiology. Furthermore, the specimens from these subjects along with those from Dr. Woodruff's cohorts will be used for relevant immunological and genomic assays that more directly address the pathways to disease. This experimental component, conducted under the mentorship of Dr. Woodruff, provide Dr. Zaitlen with training in immunology as well as significantly broadening the scope of his future research projects. Future assays may include immunologic function, host response to environmental exposures as manifest through epigenetic and expression level studies, and other direct assays of cellular response to antigenic agents. To date, on the genetic side, genome-wide association studies of asthma have only been partially enlightening. They have indicated some important candidate genes, but at the same time reflect the general observation that the mechanism of how variants contribute to disease risk is unknown. Because pathogenesis depends on an interaction between genetic susceptibility and environmental exposure, complex systems biologic models ultimately are required to fully understand these relationships. Such models are greatly enhanced by the inclusion of measured 'intermediate'phenotypes that are more directly causally related to the underlying genes and environmental agents than frank disease. These approaches will capitalize on Dr. Zaitlen's strong computational background, but also need to be well informed by a basic understanding of immunology, lung biology and host responses to environmental exposures. With the protected time afforded by this award, the models Dr. Zaitlen ends up creating will not be better simply because of his statistical acumen. He will have the required understanding of the underlying biology as well the technical training in designing assays to direct a comprehensive asthma research program spanning experimental and computational work.

Public Health Relevance

This study will improve the understanding of the relationship between genetics, environment, and population/ethnicity in asthma risk. Given the public health consequences of the growing asthma epidemic, and the current divide between environmental and genetic studies of asthma, establishing a connection between the two fields is of critical public health importance. Developing richer models asthma will lead to identification of novel genetic risk loci, more accurate risk prediction, and improved treatment options.

National Institute of Health (NIH)
Mentored Quantitative Research Career Development Award (K25)
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Study Section
Special Emphasis Panel (ZHL1)
Program Officer
Tigno, Xenia
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University of California San Francisco
Internal Medicine/Medicine
Schools of Medicine
San Francisco
United States
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Balliu, Brunilda; Zaitlen, Noah (2016) A Novel Test for Detecting SNP-SNP Interactions in Case-Only Trio Studies. Genetics 202:1289-97
Brown, Brielin C; Price, Alkes L; Patsopoulos, Nikolaos A et al. (2016) Local Joint Testing Improves Power and Identifies Hidden Heritability in Association Studies. Genetics 203:1105-16
Biton, Anne; Torgerson, Dara; Letonqueze, Olivier et al. (2016) Massively Parallel Identification of Regulatory Variants in Asthma. Ann Am Thorac Soc 13 Suppl 1:S104
Brown, Brielin C; Asian Genetic Epidemiology Network Type 2 Diabetes Consortium; Ye, Chun Jimmie et al. (2016) Transethnic Genetic-Correlation Estimates from Summary Statistics. Am J Hum Genet 99:76-88
Uricchio, Lawrence H; Zaitlen, Noah A; Ye, Chun Jimmie et al. (2016) Selection and explosive growth alter genetic architecture and hamper the detection of causal rare variants. Genome Res 26:863-73
Watkin, Levi B; Jessen, Birthe; Wiszniewski, Wojciech et al. (2015) COPA mutations impair ER-Golgi transport and cause hereditary autoimmune-mediated lung disease and arthritis. Nat Genet 47:654-60
Cornelis, Marilyn C; Zaitlen, Noah; Hu, Frank B et al. (2015) Genetic and environmental components of family history in type 2 diabetes. Hum Genet 134:259-67
Hayeck, Tristan J; Zaitlen, Noah A; Loh, Po-Ru et al. (2015) Mixed model with correction for case-control ascertainment increases association power. Am J Hum Genet 96:720-30
Vilhjálmsson, Bjarni J; Yang, Jian; Finucane, Hilary K et al. (2015) Modeling Linkage Disequilibrium Increases Accuracy of Polygenic Risk Scores. Am J Hum Genet 97:576-92
Caswell, Jennifer L; Camarda, Roman; Zhou, Alicia Y et al. (2015) Multiple breast cancer risk variants are associated with differential transcript isoform expression in tumors. Hum Mol Genet 24:7421-31

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