Department of Medical Genetics, Southern Medical University, Guangzhou, Guangdong, China.
Guangdong Technology and Engineering Research Center for Molecular Diagnostics of Human Genetic Diseases, Guangzhou, Guangdong, China.
Hum Mutat. 2019 Dec;40(12):2221-2229. doi: 10.1002/humu.23863. Epub 2019 Sep 11.
Hemoglobinopathies are the most common monogenic disorders worldwide. Substantial effort has been made to establish databases to record complete mutation spectra causing or modifying this group of diseases. We present a variant database which couples an online auxiliary diagnosis and at-risk assessment system for hemoglobinopathies (DASH). The database was integrated into the Leiden Open Variation Database (LOVD), in which we included all reported variants focusing on a Chinese population by literature peer review-curation and existing databases, such as HbVar and IthaGenes. In addition, comprehensive mutation data generated by high-throughput sequencing of 2,087 hemoglobinopathy patients and 20,222 general individuals from southern China were also incorporated into the database. These sequencing data enabled us to observe disease-causing and modifier variants responsible for hemoglobinopathies in bulk. Currently, 371 unique variants have been recorded; 265 of 371 were described as disease-causing variants, whereas 106 were defined as modifier variants, including 34 functional variants identified by a quantitative trait association study of this high-throughput sequencing data. Due to the availability of a comprehensive phenotype-genotype data set, DASH has been established to automatically provide accurate suggestions on diagnosis and genetic counseling of hemoglobinopathies. LOVD-DASH will inspire us to deal with clinical genotyping and molecular screening for other Mendelian disorders.
血红蛋白病是全球最常见的单基因疾病。人们已经做出了大量努力来建立数据库,以记录导致或改变这组疾病的完整突变谱。我们提出了一个变体数据库,该数据库将在线辅助诊断和血红蛋白病的风险评估系统(DASH)结合在一起。该数据库已集成到莱顿开放变异数据库(LOVD)中,我们通过文献同行评议策展和现有的数据库,如 HbVar 和 IthaGenes,包括所有报告的变体,重点关注中国人群。此外,我们还将通过对来自中国南方的 2,087 名血红蛋白病患者和 20,222 名普通个体进行高通量测序产生的综合突变数据也纳入了该数据库。这些测序数据使我们能够大规模观察导致血红蛋白病的致病和修饰变体。目前,已记录了 371 个独特的变体;371 个变体中有 265 个被描述为致病变体,而 106 个被定义为修饰变体,其中 34 个功能变体是通过对高通量测序数据的定量性状关联研究确定的。由于有了全面的表型-基因型数据集,因此建立了 DASH 来自动提供血红蛋白病的准确诊断和遗传咨询建议。LOVD-DASH 将激励我们处理其他孟德尔疾病的临床基因分型和分子筛查。