ArticleGenetics in medicine : official journal of the American College of Medical Genetics2023
Phenotypic presentation of Mendelian disease across the diagnostic trajectory in electronic health records.
Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 7 citations in OpenAlex.
- Decoding Genetic Disease Through the Skin: Lessons From the UDN.International journal of dermatology · 2026Article
- Drivers of Diagnostic Delay in Mitochondrial Disease: Missed Recognition of Canonical Features.JIMD reports · 2026Article
- Sex-Based Disparities in Fabry Disease Cause Challenges in Newborn Screening.Public health genomics · 2026Article
- Information content as a health system screening tool for rare diseases.NPJ digital medicine · 2025Article
- Data from electronic healthcare records expand our understanding of X-linked genetic diseases.American journal of medical genetics. Part A · 2024Article
- Diagnostic delay in monogenic disease: A scoping review.Genetics in medicine : official journal of the American College of Medical Genetics · 2024Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
Abstract
purposeTo investigate the phenotypic presentation of Mendelian disease across the diagnostic trajectory in the electronic health record (EHR).
methodsWe applied a conceptual model to delineate the diagnostic trajectory of Mendelian disease to the EHRs of patients affected by 1 of 9 Mendelian diseases. We assessed data availability and phenotype ascertainment across the diagnostic trajectory using phenotype risk scores and validated our findings via chart review of patients with hereditary connective tissue disorders.
resultsWe identified 896 individuals with genetically confirmed diagnoses, 216 (24%) of whom had fully ascertained diagnostic trajectories. Phenotype risk scores increased following clinical suspicion and diagnosis (P < 1 × 10
conclusionUsing a novel conceptual model to study the diagnostic trajectory of genetic disease in the EHR, we demonstrated that phenotype ascertainment is, in large part, driven by the clinical examinations and studies prompted by clinical suspicion of a genetic disease, a process we term diagnostic convergence. Algorithms designed to detect undiagnosed genetic disease should consider censoring EHR data at the first date of clinical suspicion to avoid data leakage.
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Registered trials
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