Methodology in phenome-wide association studies: a systematic review

Abstract

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.

Association of Pathogenic Variants in Hereditary Cancer Genes With Multiple Diseases

“…The validity of this EHR-based PheWAS approach has been demonstrated in previous studies. 35,[37][38][39][40][41][42][43] In the UKB, we extracted ICD-9 and ICD-10 data from the harmonized health outcome data derived from cancer and death registries, inpatient medical records, and self-reported health outcomes. 23 Details on the clinical data linkage and standardized questionnaires and interviews have been described previously.…”

Genetically predicted sex hormone levels and health outcomes: phenome-wide Mendelian randomization investigation

“…Phenome-wide Mendelian randomization (MR) analysis has been proposed as a hypothesis-searching approach to comprehensively examine causality between exposure and a wide range of disease outcomes. 13 The method can minimize residual confounding and diminish reverse causality. Previous phenome-wide MR and two-sample MR studies have explored the associations of SHBG and testosterone, 14 , 15 including associations of SHBG with lipid metabolism, 15 cardiovascular disease, 16 kidney function 17 and endometrial cancer, 18 and associations of testosterone with lipid metabolism 14 and cardiovascular disease.…”

Health effects of high serum calcium levels: Updated phenome-wide Mendelian randomisation investigation and review of Mendelian randomisation studies

“…A phenome-wide Mendelian Randomisation analysis (MR-PheWAS) has been proposed as a hypothesis-searching method to comprehensively examine the causality between an exposure and a broad range of outcomes. 13 The approach can minimize confounding and diminish reverse causality by using genetic variants as instrumental variables for an exposure (e.g., serum calcium). 14 A previous MR-PheWAS in the UK Biobank including 337,535 individuals found that genetically predicted serum calcium levels were associated with risk of urinary stones, allergy/adverse effect of penicillin, osteoarthrosis, and myocardial infarction.…”