Development of Risk Scores and Prediction Models of Childhood Asthma and Allergic Diseases Based on Genetic and Clinical Data by Using Bioinformatic Methods

Current genome-wide association studies (GWAS) have discovered novel genetic variants associated with risk and development of asthma and allergy in Western countries, and findings were mostly based on Caucasian populations. Ethnic-specific genetic risk factors of asthma and other allergic diseases identified for Asian populations using the GWAS approach are still limited. In addition to common genetic variants, rare coding variants can have large effects on disease-associated phenotypes and help pinpoint which genes are causal within GWAS loci. In this study, we propose to (1) identify common variant loci associated with asthma, allergic diseases and related phenotypes using the GWAS approach; (2) explore the effects of low-frequency and rare variants on these outcomes; (3) use the gene set enrichment analysis to identify potential genes and pathways associated with the phenotypes; (4) construct prediction models for disease risk, disease progression and personal trajectory and disease persistence or whether an individual remits by incorporating genetic risk scores, individual characteristics and possible clinical predictors. Using well-defined clinical phenotypes and genetic genotypes data in a population-based Taiwanese children cohort of more than 1300 subjects, we anticipate to understand the genetic basis of asthma and allergic diseases in Taiwan and to establish personalized disease profiling of each individual in our cohort as a step closer to personalized healthcare.

Project ID:PC10508-0346
External Project ID:MOST105-2314-B182-052