ArticleScientific reports2018
Using whole genome scores to compare three clinical phenotyping methods in complex diseases.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- A multi-site randomized trial of a clinical decision support intervention to improve problem list completeness.Journal of the American Medical Informatics Association : JAMIA · 2023Trial
- Multi-domain rule-based phenotyping algorithms enable improved GWAS signal.NPJ digital medicine · 2025Article
- A genome-wide Association study of the Count of Codeine prescriptions.Scientific reports · 2024Article
- First-line genome sequencing is here to stay, but how crucial is clinical phenotyping going to be?BMJ case reports · 2022Article
- Electronic Medical Record-Based Case Phenotyping for the Charlson Conditions: Scoping Review.JMIR medical informatics · 2021Article
- How to Better Understand the Influence of Host Genetics on Developing an Effective Immune Response to Thoracic Cancers.Frontiers in oncology · 2021Review
- Genetic Epidemiology of Complex Phenotypes.Methods in molecular biology (Clifton, N.J.) · 2021Review
- Genome-wide association analysis of insomnia using data from Partners Biobank.Scientific reports · 2020Article
- Improving the phenotype risk score as a scalable approach to identifying patients with Mendelian disease.Journal of the American Medical Informatics Association : JAMIA · 2019Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
Genome-wide association studies depend on accurate ascertainment of patient phenotype. However, phenotyping is difficult, and it is often treated as an afterthought in these studies because of the expense involved. Electronic health records (EHRs) may provide higher fidelity phenotypes for genomic research than other sources such as administrative data. We used whole genome association models to evaluate different EHR and administrative data-based phenotyping methods in a cohort of 16,858 Caucasian subjects for type 1 diabetes mellitus, type 2 diabetes mellitus, coronary artery disease and breast cancer. For each disease, we trained and evaluated polygenic models using three different phenotype definitions: phenotypes derived from billing data, the clinical problem list, or a curated phenotyping algorithm. We observed that for these diseases, the curated phenotype outperformed the problem list, and the problem list outperformed administrative billing data. This suggests that using advanced EHR-derived phenotypes can further increase the power of genome-wide association studies.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.