Review of genome-wide association study

Common diseases are caused by the combined effects of genetic and environmental factors with obvious genetic heterogeneity and phenotypic complexity. These diseases have a high incidence and seriously affect the physical and mental health of patients. With the consecutive completions of the Human Genome Project (HGP), the International HapMap Project and the 1000 Genomes Project, the detailed map of human genomic variations has been gradually decoded. Along with the rapid development of the technology and the rapid reduction of the cost of genotyping, genome wide association studies (GWAS) have become the most efficient and popular method to identify the susceptibility genes of common diseases and traits. Based on the principle of "common disease, common variation", GWAS can explore the differences in allele frequencies between different groups using association analysis at the whole genome level. Following the first successful application of GWAS on age-related macular degeneration in 2005, a large number of susceptibility genes have been identified for common diseases and traits. In China, there are 179 GWAS on 127 kinds of common human diseases, and traits have been determined in a total sample size of 300000 cases and 400000 controls. These studies have identified a large number of susceptibility genes and revealed plentiful potential biological pathways that have tremendously expanded the mechanism of these common diseases and traits. To expand the application fields, several novel technologies based on the results or principle have been performed to further identify the genetic pathogenesis of common diseases, including high-throughput sequencing, epigenomic study, imputation analysis, expression quantitative trait loci (eQTL) analysis and pharmacogenomic study. To adequately utilize the massive genome data acquired from GWAS, many downstream analyses have also been performed with these vast databases. First, to better understand the exact mechanism of a susceptibility gene in the pathogenesis of a disease, functional studies at different levels have been widely performed. In addition, new analysis methods were also developed to further elucidate the underlying results of these data, including meta-analyses with data from different platforms, different sample cohorts or different ethnic groups, gene-based analysis and pathway analysis. Another research field is how to translate these findings to clinical applications. To date, several explorations have been performed using the GWAS principle and data in predictions of disease risk and drug effects, while various susceptibility genes have been proven to be the targets of several biological agents. With the fast development of this technology, GWAS have provided novel ideas and methods to explore the genetic pathogenesis of common diseases, which revealed the basis of the occurrence, development and treatment of these diseases and laid a solid foundation for precision medicine. This paper reviews the rise, development, expansion, clinical transformation and future of GWAS.