ArticleAmerican journal of medical genetics. Part A2024
Data from electronic healthcare records expand our understanding of X-linked genetic diseases.
Article in American journal of medical genetics. Part A, 2024. 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.
- Evaluating pregnancy and neonatal outcomes in mothers with genetic disease using electronic health care records.Genetics in medicine : official journal of the American College of Medical Genetics · 2026Article
- Sex-Specific Diagnostic Inequality in Fabry Disease: Lessons Learned from Analysis of Newborn Screening and Cascade Testing in Tennessee from 2017 to 2024.Public health genomics · 2026Article
- Sex-Based Disparities in Fabry Disease Cause Challenges in Newborn Screening.Public health genomics · 2026Article
- The Undiagnosed Diseases Network (UDN) Solves Ocular Syndromic Diagnostic Dilemmas.American journal of ophthalmology · 2025Article
- Prevalence of Individuals With Multiple Diagnosed Genetic Diseases in the Undiagnosed Diseases Network.American journal of medical genetics. Part A · 2025Article
- The Clinical Spectrum of Mosaic Genetic Disease.Genes · 2024Review
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Disease specific cohort studies have reported details on X linked (XL) disorders affecting females. We investigated the spectrum and penetrance of XL disorders seen in electronic health records (EHR). We generated a cohort of individuals diagnosed with XL disorders at Vanderbilt University Medical Center over 20 years. Our cohort included 477 males and 203 females diagnosed with 108 different XL genetic disorders. We found large differences between the female/male (F/M) ratios for various XL disorders regardless of their OMIM annotated mode of inheritance. We identified four XL recessive disorders affecting women previously only described in men. Biomarkers for XL disease had unique gender-specific patterns differing between modes of inheritance. EHRs provide large cohorts of XL genetic disorders that give new insights compared to the literature. Differences in the F/M ratios and biomarkers of XL disorders observed likely result from disease specific and sex dependent penetrance. We conclude that observed gender ratios associated with specific XL disorders may be more useful than those predicted by Mendelian genetics provided by OMIM. Our findings of a gender specific penetrance and severity for XL disorders show unexpected differences from Mendelian predictions. Further work is required to validate our findings in larger combined EHR cohorts.
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