Investigating the structural impacts of a novel missense variant identified with whole exome sequencing in an Egyptian patient with propionic acidemia

• Main Authors: Ali Zaki Ibrahim, D. Thirumal Kumar, Taghreed Abunada, Salma Younes, C. George Priya Doss, Osama K. Zaki, Hatem Zayed
• Format: Article
• Language: English
• Published: Elsevier 2020-12-01
• Series: Molecular Genetics and Metabolism Reports
• Subjects: Propionic acidemia (PA); PCCA gene; Next-generation sequencing; Computational analysis; Genotype-phenotype correlation
• Online Access: http://www.sciencedirect.com/science/article/pii/S2214426920300914

Propionic Acidemia (PA) is an inborn error of metabolism caused by variants in the PCCA or PCCB genes, leading to mitochondrial accumulation of propionyl-CoA and its by-products. Here, we report a 2 year-old Egyptian boy with PA who was born to consanguineous parents. Biochemical analysis was performed using tandem mass spectrometry (MS/MS) on the patient's dried blood spots (DBS) followed by urine examination of amino acids using gas chromatography/mass spectrometry (GC/MS). Molecular genetic analysis was carried out using whole-exome sequencing (WES). The PCCA gene sequencing revealed a novel homozygous missense variant affecting the locus (chr13:100962160) of exon 16 of the PCCA gene, resulting in the substitution of the amino acid arginine with proline at site 476 (p.Arg476Pro). Computational analyses revealed that the novel variant might have a pathogenic effect that attributed to decreased protein stability, and also has an effect on the biotin carboxylase c-terminal domain of the propionyl carboxylase enzyme. The physicochemical properties analysis using NCBI amino acid explorer study revealed restrictions in the side chain and loss of hydrogen bonds due to the variant. On the structural level, the loss of beta-sheet was observed due to the variant proline, which has further led to the loss of surrounding interactions. This loss of beta-sheet and the surrounding interactions might serve the purpose of the structural stability changes. The current study demonstrates that the combination of whole-exome sequencing (WES) and computational analysis are potent tools for validation of diagnosis and classification of disease-causing variants.