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 Use of Electronic Health Records, Disease Registries, and Health Insurance Databases in Ophthalmology
Published in Ching-Yu Cheng, Tien Yin Wong, Ophthalmic Epidemiology, 2022
Rachel Marjorie Wei Wen Tseng, Grace May Chuang, Zhi Da Soh, Yih-Chung Tham
Aside from replicating genetic findings, the integration of EHR and genomics also led to the development of a technique known as phenome-wide association study (PheWAS). Compared to GWAS, which consists solely of identifying the association between genetic variants and a phenotype, PheWAS simultaneously searches for associations between clinical phenotypes and a given genetic variant and can identify pleiotropy (22, 23). In addition, inputs other than SNPs are being explored. These include a set of SNPs, disease exposure, drug exposure, transcription factor-based motifs, or other functional annotation data, thereby expanding the functions of PheWAS in EHR-based research (24, 25). PheWAS is often used as an approach complementary to GWAS, and the integration of these two tools has been explored in EHR-related research to validate findings, replicate known associations, identify pleiotropy, and predict disease development (26).
Linking endotypes to omics profiles in difficult-to-control asthma using the diagnostic Chinese medicine syndrome differentiation algorithm
Published in Journal of Asthma, 2020
Wenping Song, Si Zheng, Meng Li, Xia Zhang, Rui Cao, Cheng Ye, Rongguang Shao, Guangxi Li, Jiao Li, Shigang Liu, Hui Li, Liang Li
Our study employed a highly similar idea to a recently developed approach, PheWAS (phenome-wide association study), an alternative methodology to understand etiologies of complex diseases and to compensate or provide solutions for a variety of limited factors in GWAS. PheWAS usually investigate associations of a genotype with a wide spectrum of human phenotypes, namely the phenome. With this phenotype-to-genotype approach, many phenotypes of previously unappreciated etiologies in comprehensive diseases have been linked to some genes/pathways [27]. Although some researchers have made progress in endotypic classification of patients with asthma, most studies have only focused on airway inflammation, thereby ignoring the holistic nature of the human body. In contrast, our CMSDA classification approach focuses not only on known symptoms, like allergy, inflammation, or other asthma-associated symptoms, but also on unknown systematic phenotypes [28,29]. Therefore, the CMSDA could help identify more phenotypes not yet shown to be associated with asthma-related genes or asthma in general. The combined examination of local airway response and systematic evaluation of the human body could be more intuitive and helpful in future PheWAS. Moreover, this approach might provide new insights regarding this disease, in order to develop methodologies that define diverse phenotypes and enhance PheWAS practicality [30–32]. Certainly, more precise PheWAS stratification would be obtained by this approach in the future, to define the phenome using electronic medical records for larger sample size.
Use of big data in drug development for precision medicine: an update
Published in Expert Review of Precision Medicine and Drug Development, 2019
Tongqi Qian, Shijia Zhu, Yujin Hoshida
Integration of EHRs of various disease types from different racial groups to the genomic information delivers a new perspective of precision medicine [42]. Under this circumstance, the phenome-wide association study (PheWAS), which incorporates the information of GWAS and EHRs from large cohort studies, has emerged as another novel and effective paradigm [43]. The PheWAS broadened the scale of genotype-phenotype relationship and enabled researchers to find new uses of old drugs. It is exemplified by the study which integrated the PheWAS and DrugBank [44] to screen possible drug repurposing candidates for both rare and common diseases treatment [45]. A total of 52,966 drug-disease pairs were discovered in that study, where about one-third of these pairs were validated by existing drug disease relationship, ongoing clinical trials and publications, while the remaining could be candidates for future drug repurposing studies [38].