Article Text

Download PDFPDF
Methodology in phenome-wide association studies: a systematic review
  1. Lijuan Wang1,
  2. Xiaomeng Zhang2,
  3. Xiangrui Meng3,
  4. Fotios Koskeridis4,
  5. Andrea Georgiou4,
  6. Lili Yu1,
  7. Harry Campbell2,
  8. Evropi Theodoratou2,5,
  9. Xue Li1
  1. 1 School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China
  2. 2 Centre for Global Health, The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK
  3. 3 Vanke School of Public Health, Tsinghua University, Beijing, China
  4. 4 Department of Hygiene and Epidemiology, University of Ioannina, Ioannina, Epirus, Greece
  5. 5 Cancer Research UK Edinburgh Centre, The University of Edinburgh MRC Institute of Genetics and Molecular Medicine, Edinburgh, UK
  1. Correspondence to Dr Xue Li, School of Public Health and the Second affiliated hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China; xueli157{at}


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.

  • genetic association studies
  • molecular epidemiology
  • public health

Statistics from

Request Permissions

If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.


  • Contributors LW: conceptualisation, literature review, data extraction, writing original draft. XZ, XM and HC: conceptualisation, writing review and editing. FK and AG: literature review, data extraction, writing review and editing. LY: data extraction. ET and XL: conceptualisation, supervision, writing review and editing. ET and XL are joint last authors.

  • Funding This work was supported by funding for the infrastructure and staffing of the Edinburgh CRUK Cancer Research Centre. ET is supported by a CRUK Career Development Fellowship (C31250/A22804).

  • Competing interests None declared.

  • Provenance and peer review Not commissioned; externally peer reviewed.

  • Supplemental material This content has been supplied by the author(s). It has not been vetted by BMJ Publishing Group Limited (BMJ) and may not have been peer-reviewed. Any opinions or recommendations discussed are solely those of the author(s) and are not endorsed by BMJ. BMJ disclaims all liability and responsibility arising from any reliance placed on the content. Where the content includes any translated material, BMJ does not warrant the accuracy and reliability of the translations (including but not limited to local regulations, clinical guidelines, terminology, drug names and drug dosages), and is not responsible for any error and/or omissions arising from translation and adaptation or otherwise.