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

Authors :
Zhang L
Zhang Q
Tang Y
Cong P
Ye Y
Chen S
Zhang X
Chen Y
Zhu B
Cai W
Chen S
Cai R
Guo X
Zhang C
Zhou Y
Zou J
Liu Y
Chen B
Yan S
Chen Y
Zhou Y
Ding H
Li X
Chen D
Zhong J
Shang X
Liu X
Qi M
Xu X
Source :
Human mutation [Hum Mutat] 2019 Dec; Vol. 40 (12), pp. 2221-2229. Date of Electronic Publication: 2019 Sep 11.
Publication Year :
2019

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.<br /> (© 2019 The Authors. Human Mutation Published by Wiley Periodicals, Inc.)

Details

Language :
English
ISSN :
1098-1004
Volume :
40
Issue :
12
Database :
MEDLINE
Journal :
Human mutation
Publication Type :
Academic Journal
Accession number :
31286593
Full Text :
https://doi.org/10.1002/humu.23863