Compilation of genotype and phenotype data in GCDH-LOVD for variant classification and further application
Glutaric aciduria type 1 (GA-1) is a rare but treatable autosomal-recessive neurometabolic disorder of lysin metabolism caused by biallelic pathogenic variants in glutaryl-CoA dehydrogenase gene (GCDH) that lead to deficiency of GCDH protein. Without treatment, this enzyme defect causes a neurologic...
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| Main Authors: | , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
14 December 2023
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| In: |
Genes
Year: 2023, Volume: 14, Issue: 12, Pages: 1-17 |
| ISSN: | 2073-4425 |
| DOI: | 10.3390/genes14122218 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.3390/genes14122218 Verlag, lizenzpflichtig, Volltext: https://www.mdpi.com/2073-4425/14/12/2218 
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| Author Notes: | Alexandra Tibelius, Christina Evers, Sabrina Oeser, Isabelle Rinke, Anna Jauch and Katrin Hinderhofer |
| Summary: | Glutaric aciduria type 1 (GA-1) is a rare but treatable autosomal-recessive neurometabolic disorder of lysin metabolism caused by biallelic pathogenic variants in glutaryl-CoA dehydrogenase gene (GCDH) that lead to deficiency of GCDH protein. Without treatment, this enzyme defect causes a neurological phenotype characterized by movement disorder and cognitive impairment. Based on a comprehensive literature search, we established a large dataset of GCDH variants using the Leiden Open Variation Database (LOVD) to summarize the known genotypes and the clinical and biochemical phenotypes associated with GA-1. With these data, we developed a GCDH-specific variation classification framework based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines. We used this framework to reclassify published variants and to describe their geographic distribution, both of which have practical implications for the molecular genetic diagnosis of GA-1. The freely available GCDH-specific LOVD dataset provides a basis for diagnostic laboratories and researchers to further optimize their knowledge and molecular diagnosis of this rare disease. |
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| Item Description: | Gesehen am 21.02.2024 |
| Physical Description: | Online Resource |
| ISSN: | 2073-4425 |
| DOI: | 10.3390/genes14122218 |