美国宾夕法尼亚大学Daniel J. Rader研究组近日取得一项新成果。他们利用电子健康记录（EHR）对稀有编码变体进行全基因组评估，可确定新的基因-表型关联。相关论文于2021年1月11日发表于《自然-医学》。
利用宾州医学生物库中与EHR数据关联的10,900个全外显子序列，他们评估了整个个体在整个外显子组范围内罕见的预测功能丧失变体对人类疾病的累积影响与人类疾病的关联性，并使用一组不同的EHR表型。在发现具有全外显子组显著表型关联（P genes <10-6）的97个基因后，他们在宾州医学生物库、其他三个医学生物库和基于人群的UK生物库中复制了其中的26个。
在这26个基因中，有5个具有先前报道的并代表阳性对照的关联，而21个具有先前未报道的表型关联，其中有与青光眼、主动脉扩张、糖尿病、肌营养不良和听力下降有关的基因。这些发现表明，将罕见的预测功能丧失变体整合到“基因负荷”中，对于在医疗生物库中使用EHR表型鉴定新的基因-疾病关联具有价值。他们建议将此方法应用于更多的个体，将提供发现稀有遗传变异与疾病表型之间未探明关系所需的统计能力。
据介绍，对于大多数基因来说，罕见的功能丧失型变体的临床影响尚待确定。将DNA测序数据与EHR集成在一起，可以增强人们对罕见遗传变异对人类疾病的贡献的了解。
附：英文原文
Title: Exome-wide evaluation of rare coding variants using electronic health records identifies new gene–phenotype associations
Author: Joseph Park, Anastasia M. Lucas, Xinyuan Zhang, Kumardeep Chaudhary, Judy H. Cho, Girish Nadkarni, Amanda Dobbyn, Geetha Chittoor, Navya S. Josyula, Nathan Katz, Joseph H. Breeyear, Shadi Ahmadmehrabi, Theodore G. Drivas, Venkata R. M. Chavali, Maria Fasolino, Hisashi Sawada, Alan Daugherty, Yanming Li, Chen Zhang, Yuki Bradford, JoEllen Weaver, Anurag Verma, Renae L. Judy, Rachel L. Kember, John D. Overton, Jeffrey G. Reid, Manuel A. R. Ferreira, Alexander H. Li, Aris Baras, Scott A. LeMaire, Ying H. Shen, Ali Naji, Klaus H. Kaestner, Golnaz Vahedi, Todd L. Edwards, Jinbo Chen, Scott M. Damrauer, Anne E. Justice, Ron Do, Marylyn D. Ritchie, Daniel J. Rader
Issue&Volume: 2021-01-11
Abstract: The clinical impact of rare loss-of-function variants has yet to be determined for most genes. Integration of DNA sequencing data with electronic health records (EHRs) could enhance our understanding of the contribution of rare genetic variation to human disease1. By leveraging 10,900 whole-exome sequences linked to EHR data in the Penn Medicine Biobank, we addressed the association of the cumulative effects of rare predicted loss-of-function variants for each individual gene on human disease on an exome-wide scale, as assessed using a set of diverse EHR phenotypes. After discovering 97 genes with exome-by-phenome-wide significant phenotype associations (P<106), we replicated 26 of these in the Penn Medicine Biobank, as well as in three other medical biobanks and the population-based UK Biobank. Of these 26 genes, five had associations that have been previously reported and represented positive controls, whereas 21 had phenotype associations not previously reported, among which were genes implicated in glaucoma, aortic ectasia, diabetes mellitus, muscular dystrophy and hearing loss. These findings show the value of aggregating rare predicted loss-of-function variants into ‘gene burdens’ for identifying new gene–disease associations using EHR phenotypes in a medical biobank. We suggest that application of this approach to even larger numbers of individuals will provide the statistical power required to uncover unexplored relationships between rare genetic variation and disease phenotypes.
DOI: 10.1038/s41591-020-1133-8
Source: https://www.nature.com/articles/s41591-020-1133-8
Nature Medicine：《自然—医学》，创刊于1995年。隶属于施普林格·自然出版集团，最新IF：87.241
官方网址：https://www.nature.com/nm/
投稿链接：https://mts-nmed.nature.com/cgi-bin/main.plex
本期文章：《自然—医学》：Online/在线发表
