A comprehensive repository of mutation data and a clinical assistant decision system for hemoglobinopathy in the Chinese population
Received date: 2019-05-13
Revised date: 2019-07-24
Online published: 2019-08-01
Supported by
Supported by the National Key Research and Development Program of China(2018YFA0507803);The National Natural Science Foundation of China(31871265)
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
Qianqian Zhang,Li Zhang,Yaohua Tang,Xiarong Li,Xiaopeng Xu,Ming Qi,Xiangmin Xu . A comprehensive repository of mutation data and a clinical assistant decision system for hemoglobinopathy in the Chinese population[J]. Hereditas(Beijing), 2019 , 41(8) : 746 -753 . DOI: 10.16288/j.yczz.19-136
| [1] | Amberger JS, Bocchini CA, Schiettecatte F, Scott AF, Hamosh A . OMIM.org: online mendelian inheritance in man (OMIM®), an online catalog of human genes and genetic disorders. Nucleic Acids Res, 2015,43:D789-D798. |
| [2] | Landrum MJ, Lee JM, Benson M, Brown G, Chao C, Chitipiralla S, Gu B, Hart J, Hoffman D, Hoover J, Jang W, Katz K, Ovetsky M, Riley G, Sethi A, Tully R, Villamarin- Salomon R, Rubinstein W, Maglott DR . ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res, 2016,44:D862-D868. |
| [3] | Shah N, Hou YC, Yu HC, Sainger R, Caskey CT, Venter JC, Telenti A . Identification of misclassified clinvar variants via disease population prevalence. Am J Hum Genet, 2018,102(4):609-619. |
| [4] | Burn J, Watson M . The human variome project. Hum Mutat, 2016,37:505-507. |
| [5] | Pan M, Cong P, Wang Y, Lin C, Yuan Y, Dong J, Banerjee S, Zhang T, Chen Y, Zhang T, Chen M, Hu P, Zheng S, Zhang J, Qi M . Novel LOVD databases for hereditary breast cancer and colorectal cancer genes in the Chinese population. Hum Mutat, 2011,32(12):1335-1340. |
| [6] | Zhang T, Moss A, Cong P, Pan M, Chang B, Zheng L, Fang Q, Zareba W, Robinson J, Lin C, Li Z, Wei J, Zeng Q , Long QT International Registry Investigators; HVP-China Investigators, Qi M. LQTS gene LOVD database. Hum Mutat, 2010,31:E1801-E1810. |
| [7] | Nathan DG . Hemoglobin disorders: a look to the future. Blood, 2013,122:859-860. |
| [8] | Kountouris P, Lederer CW, Fanis P, Feleki X, Old J, Kleanthous M . IthaGenes: an interactive database for haemoglobin variations and epidemiology. PLoS One, 2014,9:e103020. |
| [9] | Ware RE, de Montalembert M, Tshilolo L, Abboud MR . Sickle cell disease. LANCET . 2017,390(10091):311-323. |
| [10] | Shang X, Peng Z, Ye Y, Asan, Zhang X, Chen Y, Zhu B, Cai W, Chen S, Cai R, Guo X, Zhang C, Zhou Y, Huang S, Liu Y, Chen B, Yan S, Chen Y, Ding H, Yin X, Wu L, He J, Huang D, He S, Yan T, Fan X, Zhou Y, Wei X, Zhao S, Cai D, Guo F, Zhang Q, Li Y, Zhang X, Lu H, Huang H, Guo J, Zhu F, Yuan Y, Zhang L, Liu N, Li Z, Jiang H, Zhang Q, Zhang Y, Juhari WKW, Hanafi S, Zhou W, Xiong F, Yang H, Wang J, Zilfalil BA, Qi M, Yang Y, Yin Y, Mao M, Xu X . Rapid targeted Next-Generation sequencing platform for molecular screening and clinical genotyping in subjects with hemoglobinopathies. E Bio Medicine, 2017,23:150-159. |
| [11] | Taher AT, Weatherall DJ, Cappellini MD . Thalassaemia. Lancet, 2018,391(10116):155-167. |
| [12] | Liu D, Zhang X, Yu L, Cai R, Ma X, Zheng C, Zhou Y, Liu Q, Wei X, Lin L, Yan T, Huang J, Mohandas N, An X, Xu X . KLF1 mutations are relatively more common in a thalassemia endemic region and ameliorate the severity of β-thalassemia. Blood, 2014,124(5):803-811. |
| [13] |