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Open Access 01-12-2023 | Neonatal Screening | Review

Chinese genetic variation database of inborn errors of metabolism: a systematic review of published variants in 13 genes

Authors: Yongchao Guo, Jianhui Jiang, Zhongyao Xu

Published in: Orphanet Journal of Rare Diseases | Issue 1/2023

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Abstract

Background

Population-specific variation database of inborn errors of metabolism (IEMs) is essential for precise genetic diagnosis and disease prevention. Here we presented a systematic review of clinically relevant variants of 13 IEMs genes reported among Chinese patients.

Methods

A systematic search of the following electronic databases for 13 IEMs genes was conducted: PubMed-NCBI, China national knowledge infrastructure and Wanfang databases. Patient data was extracted from articles eligible for inclusion and recorded in Excel electronic form using a case-by-case approach.

Results

A total of 218 articles, 93 published in English and 125 in Chinese, were retrieved. After variant annotation and deduplication, 575 unique patients (241 from articles published in Chinese) were included in the population-specific variation database. Patients identified by newborn screening and symptomatic presentation were 231 (40.17%) and 344 (59.83%), respectively. Biallelic variants were observed in 525/575 (91.3%). Among the 581 unique variants identified, 83 (14.28%) were described ≥ 3 times and 97 (16.69%) were not recorded in Clinvar or HGMD. Four variants were reclassified as benign and dozens of confusing variants deserved further research.

Conclusion

This review provides a unique resource of the well-characterized diseases and causative variants that have accumulated in Chinese population and is a preliminary attempt to build the Chinese genetic variation database of IEMs.
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Literature
Metadata
Title
Chinese genetic variation database of inborn errors of metabolism: a systematic review of published variants in 13 genes
Authors
Yongchao Guo
Jianhui Jiang
Zhongyao Xu
Publication date
01-12-2023
Publisher
BioMed Central
Published in
Orphanet Journal of Rare Diseases / Issue 1/2023
Electronic ISSN: 1750-1172
DOI
https://doi.org/10.1186/s13023-023-02726-1

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