Exploring genotype–phenotype correlations in glutaric aciduria type 1

表型 错义突变 基因型-表型区分 遗传学 基因 基因型 生物 生物信息学
作者
Imke M. E. Schuurmans,Bianca Dimitrov,Julian Schröter,Antònia Ribes,Rubén Pérez de la Fuente,Berta Zamora,Clara D.M. van Karnebeek,Stefan Kölker,Alejandro Garanto
出处
期刊:Journal of Inherited Metabolic Disease [Wiley]
卷期号:46 (3): 371-390 被引量:16
标识
DOI:10.1002/jimd.12608
摘要

Abstract Glutaric aciduria type 1 (GA1) is a rare neurometabolic disease caused by pathogenic variants in the gene encoding the enzyme glutaryl‐CoA dehydrogenase (GCDH). We performed an extensive literature search to collect data on GA1 patients, together with unpublished cases, to provide an up‐to‐date genetic landscape of GCDH pathogenic variants and to investigate potential genotype‐phenotype correlation, as this is still poorly understood. From this search, 421 different GCDH pathogenic variants have been identified, including four novel variants; c.179T>C (p.Leu60Pro), c.214C>T (p.Arg72Cys), c.309G>C (p.Leu103Phe), and c.665T>C (p.Phe222Ser).The variants are mostly distributed across the entire gene; although variant frequency in GA1 patients is relatively high in the regions encoding for active domains of GCDH . To investigate potential genotype‐phenotype correlations, phenotypic descriptions of 532 patients have been combined and evaluated using novel combinatorial analyses. To do so, various clinical phenotypes were determined for each pathogenic variant by combining the information of all GA1 patients reported with this pathogenic variant, and subsequently mapped onto the 2D and 3D GCDH protein structure. In addition, the predicted pathogenicity of missense variants was analyzed using different in silico prediction score models. Both analyses showed an almost similar distribution of the highly pathogenic variants across the GCDH protein, although some hotspots, including the active domain, were observed. Moreover, it was demonstrated that highly pathogenic variants are significantly correlated with lower residual enzyme activity and the most accurate estimation was achieved by the REVEL score. A clear correlation of the genotype and the clinical phenotype however is still lacking.
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