Zhang Qian Qian, Zhang Li, Tang Yao Hua, Li Xia Rong, Xu Xiao Peng, Qi Ming, Xu Xiang Min
Department of Medical Genetics, Southern Medical University, Guangzhou 510800, China.
DIAN Diagnostics, Hangzhou 310000, China.
Yi Chuan. 2019 Aug 20;41(8):746-753. doi: 10.16288/j.yczz.19-136.
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.
个人基因组信息受益于积累的大数据,其应用不再局限于科学研究。目前,它正在向日常医疗实践转变。对疾病相关基因组信息进行系统整理、存档和合理利用是未来精准医学的重要基础。血红蛋白病在中国南方地区较为普遍,但其分子病理基础具有种族特异性。为便于中国南方地区血红蛋白病的临床诊断和基因筛查,我们建立了血红蛋白病变异和表型谱的LOVD基因数据管理系统。然后,我们设计了一个集成高效的在线辅助精准诊断和风险评估系统,以便基于特定血红蛋白病变异的云标准化注释库和诊断知识库,协助临床医生在短时间内进行综合诊断和遗传咨询。利用大数据和人工智能技术提高疾病临床决策效率的方法和经验,可作为其他疾病临床和预防应用的范例。