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LOVD-DASH: A comprehensive LOVD database coupled with diagnosis and an at-risk assessment system for
Li Zhang1,2,3, Qianqian Zhang1,2,3, Yaohua Tang4
1Department of Medical Genetics, Southern Medical University, Guangzhou, Guangdong, China.
Insights
A new database, DASH, integrates variant information for hemoglobinopathies in China, aiding diagnosis and genetic counseling. This resource includes comprehensive mutation data, improving understanding of these common genetic blood disorders.
Area of Science:
- Genetics
- Bioinformatics
- Hematology
Background:
- Hemoglobinopathies represent the most prevalent monogenic disorders globally.
- Existing efforts focus on cataloging mutation spectra for these diseases.
- A comprehensive variant database is crucial for diagnosis and management.
Purpose of the Study:
- To develop and present a variant database coupled with an auxiliary diagnosis and at-risk assessment system for hemoglobinopathies (DASH).
- To integrate curated variant data from literature and existing databases, focusing on the Chinese population.
- To incorporate high-throughput sequencing data for a deeper understanding of disease-causing and modifier variants.
Main Methods:
- Literature peer-review curation and integration of existing databases (HbVar, IthaGenes).
- High-throughput sequencing of 2,087 hemoglobinopathy patients and 20,222 general individuals from southern China.
- Development of the DASH system integrated into the Leiden Open Variation Database (LOVD).
Main Results:
- The LOVD-DASH database currently records 371 unique variants.
- Of these, 265 are disease-causing and 106 are modifier variants, including 34 identified through quantitative trait association.
- The DASH system provides automated suggestions for diagnosis and genetic counseling.
Conclusions:
- The LOVD-DASH database offers a valuable resource for hemoglobinopathy research and clinical application in China.
- The integrated phenotype-genotype data facilitates accurate diagnosis and genetic counseling.
- This approach can serve as a model for managing other Mendelian disorders.
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.
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