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. 2019 Dec;40(12):2221-2229.
doi: 10.1002/humu.23863. Epub 2019 Sep 11.

LOVD-DASH: A comprehensive LOVD database coupled with diagnosis and an at-risk assessment system for hemoglobinopathies

Li Zhang  1   2   3 , Qianqian Zhang  1   2   3 , Yaohua Tang  4 , Peikuan Cong  5 , Yuhua Ye  1   2   3 , Shiping Chen  6 , Xinhua Zhang  7 , Yan Chen  8 , Baosheng Zhu  9 , Wangwei Cai  10 , Shaoke Chen  11 , Ren Cai  12 , Xiaoling Guo  13 , Chonglin Zhang  14 , Yuqiu Zhou  15 , Jie Zou  16 , Yanhui Liu  17 , Biyan Chen  18 , Shanhuo Yan  19 , Yajun Chen  20 , Yuehong Zhou  21 , Hongmei Ding  22 , Xiarong Li  23 , Dianyu Chen  24 , Jianmei Zhong  1   2   3 , Xuan Shang  1   2   3 , Xuanzhu Liu  23 , Ming Qi  24   25 , Xiangmin Xu  1   2   3
Affiliations

LOVD-DASH: A comprehensive LOVD database coupled with diagnosis and an at-risk assessment system for hemoglobinopathies

Li Zhang et al. Hum Mutat. 2019 Dec.

Abstract

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.

Keywords: DASH; LOVD; clinical genotyping; database; hemoglobinopathy; molecular screening.

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Conflict of interest statement

The authors declare that there are no conflict of interest.

Figures

Figure 1
Figure 1
Homepage of the HBB gene from our LOVD‐China database. LOVD, Leiden Open Variation Database
Figure 2
Figure 2
Workflow of DASH. Data resources including LOVD‐China, 22,309 phenotype‐genotype data set, and HbVar data set were mainly used for the clinical genotyping module and at‐risk assessment module. DASH, diagnosis and at‐risk assessment system for hemoglobinopathies; LOVD, Leiden Open Variation Database
See this image and copyright information in PMC

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