From the first genome-wide association study (GWAS) on macular degeneration in 2005 (1) to the present, thousands of GWASs have been conducted to explore diverse quantitative traits and complex diseases, identifying numerous significant associations between genotypes and phenotypes. In particular, with the introduction of methodologies such as imputation (2), meta-analysis (3) and multi-trait test (4), and emergence of projects with a large sample size such as the UK Biobank (UKBB) (5), the number of identified significant trait/disease-associated loci is rapidly accumulating, covering most regions of the human genome. Because there are many restrictions on accessing the genotype and phenotype data of individuals, publicly available GWAS summary statistics together with derived statistical methods are of a great value to GWAS downstream studies and for applications such as potential causal variant fine-mapping and validation, causal relationship inference among traits, polygenic risk prediction, as well as drug target discovery (6,7).
