RT Journal Article SR Electronic T1 Methodology in phenome-wide association studies: a systematic review JF Journal of Medical Genetics JO J Med Genet FD BMJ Publishing Group Ltd SP 720 OP 728 DO 10.1136/jmedgenet-2021-107696 VO 58 IS 11 A1 Lijuan Wang A1 Xiaomeng Zhang A1 Xiangrui Meng A1 Fotios Koskeridis A1 Andrea Georgiou A1 Lili Yu A1 Harry Campbell A1 Evropi Theodoratou A1 Xue Li YR 2021 UL http://jmg.bmj.com/content/58/11/720.abstract AB Phenome-wide association study (PheWAS) has been increasingly used to identify novel genetic associations across a wide spectrum of phenotypes. This systematic review aims to summarise the PheWAS methodology, discuss the advantages and challenges of PheWAS, and provide potential implications for future PheWAS studies. Medical Literature Analysis and Retrieval System Online (MEDLINE) and Excerpta Medica Database (EMBASE) databases were searched to identify all published PheWAS studies up until 24 April 2021. The PheWAS methodology incorporating how to perform PheWAS analysis and which software/tool could be used, were summarised based on the extracted information. A total of 1035 studies were identified and 195 eligible articles were finally included. Among them, 137 (77.0%) contained 10 000 or more study participants, 164 (92.1%) defined the phenome based on electronic medical records data, 140 (78.7%) used genetic variants as predictors, and 73 (41.0%) conducted replication analysis to validate PheWAS findings and almost all of them (94.5%) received consistent results. The methodology applied in these PheWAS studies was dissected into several critical steps, including quality control of the phenome, selecting predictors, phenotyping, statistical analysis, interpretation and visualisation of PheWAS results, and the workflow for performing a PheWAS was established with detailed instructions on each step. This study provides a comprehensive overview of PheWAS methodology to help practitioners achieve a better understanding of the PheWAS design, to detect understudied or overstudied outcomes, and to direct their research by applying the most appropriate software and online tools for their study data structure.