Division of Medical Genetics and Genomic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
Am J Med Genet A. 2024 May;194(5):e63527. doi: 10.1002/ajmg.a.63527. Epub 2024 Jan 16.
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.
疾病特异性队列研究已经报道了影响女性的 X 连锁(XL)疾病的详细信息。我们调查了电子健康记录(EHR)中所见 XL 疾病的谱和外显率。我们在范德比尔特大学医学中心创建了一个诊断为 XL 疾病的个体队列,时间跨度为 20 年。我们的队列包括 477 名男性和 203 名女性,他们被诊断患有 108 种不同的 XL 遗传疾病。我们发现,无论其 OMIM 注释的遗传方式如何,各种 XL 疾病的女性/男性(F/M)比值之间存在很大差异。我们确定了以前仅在男性中描述的四种影响女性的 XL 隐性疾病。XL 疾病的生物标志物具有独特的性别特异性模式,与遗传方式不同。EHR 提供了大量的 XL 遗传疾病队列,与文献相比,提供了新的见解。观察到的 XL 疾病的 F/M 比值和生物标志物之间的差异可能是由于疾病特异性和性别依赖性外显率所致。我们得出结论,与特定 XL 疾病相关的观察到的性别比例可能比 OMIM 提供的孟德尔遗传学预测的更有用。我们对 XL 疾病的性别特异性外显率和严重程度的发现与孟德尔预测存在出人意料的差异。需要进一步的工作来在更大的 EHR 队列中验证我们的发现。