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Genotype–phenotype correlation of 33 patients with maple syrup urine disease
Author(s) -
Khalifa Ola A.,
Imtiaz Faiqa,
Ramzan Khushnooda,
Zaki Osama,
Gamal Radwa,
Elbaik Lina,
Rihan Shaimaa,
Salam Ehab,
AbdulMawgoud Rehab,
Hassan Magdy,
Hassan Nahla,
Saleh Eman,
Seoudi Dina,
Moustafa Amr S.
Publication year - 2020
Publication title -
american journal of medical genetics part a
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.064
H-Index - 112
eISSN - 1552-4833
pISSN - 1552-4825
DOI - 10.1002/ajmg.a.61806
Subject(s) - maple syrup urine disease , missense mutation , genetics , in silico , biology , phenotype , genotype , frameshift mutation , genetic heterogeneity , gene , amino acid , leucine
Maple syrup urine disease (MSUD) is a rare autosomal recessive inherited disorder due to defects in the branched‐chain α‐ketoacid dehydrogenase complex (BCKDC). MSUD varies in severity and its clinical spectrum is quite broad, ranging from mild to severe phenotypes. Thirty‐three MSUD patients were recruited into this study for molecular genetic variant profiling and genotype–phenotype correlation. Except for one patient, all other patients presented with the classic neonatal form of the disease. Seventeen different variants were detected where nine were novel. The detected variants spanned across the entire BCKDHA , BCKDHB and DBT genes. All variants were in homozygous forms. The commonest alterations were nonsense and frameshift variants, followed by missense variants. For the prediction of variant's pathogenicity, we used molecular modeling and several in silico tools including SIFT, Polyphen2, Condel, and Provean. In addition, six other tools were used for the prediction of the conservation of the variants' sites including Eigen‐PC, GERP++, SiPhy, PhastCons vertebrates and primates, and PhyloP100 rank scores. Herein, we presented a comprehensive characterization of a large cohort of patients with MSUD. The clinical severity of the variants' phenotypes was well correlated with the genotypes. The study underscores the importance of the use of in silico analysis of MSUD genotypes for the prediction of the clinical outcomes in patients with MSUD.