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Methodology in phenome-wide association studies: a systematic review.
Wang, Lijuan; Zhang, Xiaomeng; Meng, Xiangrui; Koskeridis, Fotios; Georgiou, Andrea; Yu, Lili; Campbell, Harry; Theodoratou, Evropi; Li, Xue.
Afiliação
  • Wang L; School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Zhang X; Centre for Global Health, The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK.
  • Meng X; Vanke School of Public Health, Tsinghua University, Beijing, China.
  • Koskeridis F; Department of Hygiene and Epidemiology, University of Ioannina, Ioannina, Epirus, Greece.
  • Georgiou A; Department of Hygiene and Epidemiology, University of Ioannina, Ioannina, Epirus, Greece.
  • Yu L; School of Public Health and the Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang, China.
  • Campbell H; Centre for Global Health, The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK.
  • Theodoratou E; Centre for Global Health, The University of Edinburgh Usher Institute of Population Health Sciences and Informatics, Edinburgh, UK.
  • Li X; Cancer Research UK Edinburgh Centre, The University of Edinburgh MRC Institute of Genetics and Molecular Medicine, Edinburgh, UK.
J Med Genet ; 58(11): 720-728, 2021 11.
Article em En | MEDLINE | ID: mdl-34272311
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.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fenótipo / Estudo de Associação Genômica Ampla Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Fenótipo / Estudo de Associação Genômica Ampla Idioma: En Ano de publicação: 2021 Tipo de documento: Article