来自电子医疗记录的数据扩大了我们对X链接遗传疾病的理解
Rory J Tinker1, Lisa Bastarache2, Kimberly Ezell1
1Division of Medical Genetics and Genomic Medicine, Vanderbilt University Medical Center, Nashville, Tennessee, USA.
American journal of medical genetics. Part A
|January 16, 2024
概括
电子健康记录揭示了女性的X链接 (XL) 遗传疾病,挑战了孟德尔的预测. 在XL疾病中的性别特异性模式突显了疾病中性别依赖性透的重要性.
科学领域:
- 遗传学 是一个遗传学.
- 医疗信息学 医疗信息学
- 人口健康 人口健康
背景情况:
- 传统上,X链接 (XL) 遗传疾病主要集中在男性人群中.
- 关于女性XL疾病的频谱和透度的数据有限.
- 电子健康记录 (EHR) 为研究罕见疾病提供了大量数据集.
研究的目的:
- 通过使用EHR数据,在大型队列中调查X链接遗传疾病的频谱和透率.
- 与现有文献和孟德尔预测相比,确定XL疾病的性别特异性模式和差异.
- 探索EHR在揭示XL遗传疾病的新见解方面的实用性.
主要方法:
- 在20年间,从范德比尔特大学医学中心的EHR中生成了一组被诊断患有XL疾病的个人.
- 分析了性别分布 (女性/男性比例),并确定了特定的XL疾病.
- 检查了性别特定的生物标志物模式,并将结果与OMIM (人类在线孟德尔遗传) 数据进行了比较.
主要成果:
- 确定了一个由477名男性和203名女性组成的队列,他们有108种不同的XL疾病.
- 在不同的XL疾病中,无论OMIM遗传模式如何,都观察到女性/男性比例的显著变化.
- 在女性中发现了四种XL衰退性疾病,以前只在男性中描述. 发现了独特的性别特异性生物标志物模式.
- 关于XL疾病的EHR衍生见解与既定文献有所不同,表明性别依赖的透性.
结论:
- 电子健康记录数据为XL遗传疾病提供了有价值的见解,揭示了传统研究中没有明显的模式.
- 观察到的性别比率和生物标志物模式表明,XL疾病的性别依赖性透率显著.
- 这些发现挑战了孟德尔的预测,表明在特定的XL疾病中观察到的性别比率可能比OMIM数据更有信息. 需要在更大的队列中进一步验证.
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