遗传 ›› 2019, Vol. 41 ›› Issue (8): 746-753.doi: 10.16288/j.yczz.19-136

• 资源与平台 • 上一篇    下一篇

中国人血红蛋白病突变数据集和临床辅助决策管理系统

张倩倩1,张立1,唐耀华2,李厦戎3,徐晓鹏3,祁鸣2,4,5(),徐湘民1()   

  1. 1. 南方医科大学基础医学院医学遗传学教研室,广州 510800
    2. 迪安医学检验中心,杭州 310012
    3. 聚道科技,北京 100000
    4. 浙江大学医学院细胞生物学与医学遗传学系,杭州 310000
    5. 浙江大学医学院附属邵逸夫医院妇产科,杭州 310000
  • 收稿日期:2019-05-13 修回日期:2019-07-24 出版日期:2019-08-20 发布日期:2019-08-01
  • 通讯作者: 祁鸣,徐湘民 E-mail:qiming_14618@yahoo.com;xixm@smu.edu.cn
  • 作者简介:张倩倩,博士研究生,专业方向:遗传学。E-mail: zqq.smu@foxmail.com
  • 基金资助:
    国家重点研发计划项目(2018YFA0507803);国家自然科学基金项目资助(31871265)

A comprehensive repository of mutation data and a clinical assistant decision system for hemoglobinopathy in the Chinese population

Zhang Qianqian1,Zhang Li1,Tang Yaohua2,Li Xiarong3,Xu Xiaopeng3,Qi Ming2,4,5(),Xu Xiangmin1()   

  1. 1. Department of Medical Genetics, Southern Medical University, Guangzhou 510800, China
    2. DIAN Diagnostics, Hangzhou 310000, China
    3. GeneDock, Beijing 100000, China
    4. Department of Cell Biology and Medical Genetics, School of Medicine, Zhejiang University, Hangzhou 310058, China
    5. Department of Obstetrics and Gynecology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou 310016, China
  • Received:2019-05-13 Revised:2019-07-24 Online:2019-08-20 Published:2019-08-01
  • Contact: Qi Ming,Xu Xiangmin E-mail:qiming_14618@yahoo.com;xixm@smu.edu.cn
  • Supported by:
    Supported by the National Key Research and Development Program of China(2018YFA0507803);The National Natural Science Foundation of China(31871265)

摘要:

个体基因组信息得益于大数据的积累,其应用不再局限于科学研究,正在经历逐步走向日常医疗实践的过程中。对疾病关联基因组信息的系统整理、归档及合理应用配置是未来精准医学的重要基础。血红蛋白病在我国南方发病率高,其分子病理学基础有明显的种族特异性。为助力我国南方血红蛋白病的临床诊断和遗传筛查的应用,本项目团队建立了中国人群血红蛋白病变异谱及表型谱LOVD基因变异数据管理系统,并通过设计全面整合和高效分析的在线辅助精确诊断及风险评估系统,展示了基于云端标准化的特定血红蛋白病变异注释库和诊断知识库辅助医生快速做出综合、全面的诊断和遗传咨询的操作。通过数据整合和人工智能技术的结合提高疾病临床决策效率的方法和经验,可为其他疾病的临床和预防应用起示范作用。

关键词: LOVD, 血红蛋白病, 变异谱, 临床辅助决策

Abstract:

Personal genomic information benefits from accumulated big data and its application is no longer limited to scientific research. Presently, it is undergoing the transformation to daily medical practice. Systematic arrangement, archiving and rational utilization of disease-related genomic information is an important foundation of future precision medicine. Hemoglobinopathy is prevalent in southern China, but its molecular pathological basis has racial specificity. To facilitate clinical diagnosis and genetic screening of hemoglobinopathy in southern China, we established the LOVD gene data management system for the variation and phenotype spectrum of hemoglobinopathy. Then we designed an integrated and efficient on-line auxiliary accurate diagnosis and risk assessment system in order to assist clinicians to make comprehensive diagnosis and genetic counseling in a short time based on cloud standardized annotated library of specific hemoglobinopathy variants and diagnostic repository. The methodology and experience of improving the clinical decision-making efficiency of diseases with big data and artificial intelligence technology can be used as an example in the clinical and preventive application of other diseases.

Key words: LOVD, hemoglobinopathy, mutation spectrum, clinical assist decision