Title: Novel Methods for Analysis of Genetic and Epigenetic Studies of Childhood Asthma Candidate: Dr. Qi Yan is a junior biostatistician and statistical geneticist. He obtained his Ph.D. degree at the University of Alabama at Birmingham (2014). His main scientific interests lie in development and application of statistical and computational methods for analysis of high-throughput genetic and epigenetic data. He is author and co-author of 15 manuscripts, 11 of which are in the field of statistical genetics. Environment: Children's Hospital of Pittsburgh (CHP) of UPMC, affiliated with the University of Pittsburgh, School of Medicine, is a leading pediatric center for clinical care, research, and education excellence. Dr. Yan works in the new Rangos Research Center, comprised of 10 floors of state-of-the-art laboratories, offices, and conference facilities. In addition to superb mentoring by Dr. Daniel E. Weeks, Dr. Juan C. Celedn and Dr. Wei Chen, institutional commitment includes dedicated office space and resource allocation; shared personnel including clinicians and biologists, database manager, and laboratory staff; and guaranteed salary support until June 2017. Research: SIGNIFICANCE: The proposed project will develop novel statistical approaches for genetic and epigenetic analysis and the developed approaches should identify novel susceptibility genes and help researchers better understand the pathogenesis of childhood asthma in Puerto Ricans (PRs). The developed methods can be widely applied to other complex diseases with similar datasets. INNOVATION: The novel statistical approaches will be developed for integrative analysis of genetic and epigenetic data.
AIMS : The goal of this proposal is to develop and apply sophisticated statistical approaches to identify genetic and epigenetic effects on childhood asthma in an integrative manner. APPROACH:
In Aim1, we will develop novel statistical approaches for testing overall genetic and epigenetic effects on childhood asthma related phenotypes in PRs.
In Aim2, we will develop novel statistical approaches for testing mediated genetic and epigenetic effects on childhood asthma related phenotypes in PRs.
In Aim3, We will develop novel statistical methods for considering tissue or/and familial correlations when applying integrative analyses to PR childhood asthma samples.
Public Health Relevance Statement: Childhood asthma is a serious public health problem. This proposal aims to develop novel statistical approaches for integrative analysis of genetic and epigenetic data and apply them to identify susceptibility genes that influence asthma in Puerto Rican children. Such results are expected to have a positive impact because the identified susceptibility genes should help our understanding of the pathogenesis of asthma and the developed statistical methods can be applied to study asthma and other complex diseases.
