Which Is the Best In Silico Program for the Missense Variations in IDUA Gene? A Comparison of 33 Programs Plus a Conservation Score and Evaluation of 586 Missense Variants
التفاصيل البيبلوغرافية
العنوان:
Which Is the Best In Silico Program for the Missense Variations in IDUA Gene? A Comparison of 33 Programs Plus a Conservation Score and Evaluation of 586 Missense Variants
Mucopolysaccharidosis type I (MPS I) is an autosomal recessive disease characterized by the deficiency of alpha-L-iduronidase (IDUA), an enzyme involved in glycosaminoglycan degradation. More than 200 disease-causing variants have been reported and characterized in the IDUA gene. It also has several variants of unknown significance (VUS) and literature conflicting interpretations of pathogenicity. This study evaluated 586 variants obtained from the literature review, five population databases, in addition to dbSNP, Human Genome Mutation Database (HGMD), and ClinVar. For the variants described in the literature, two datasets were created based on the strength of the criteria. The stricter criteria subset had 108 variants with expression study, analysis of healthy controls, and/or complete gene sequence. The less stringent criteria subset had additional 52 variants found in the literature review, HGMD or ClinVar, and dbSNP with an allele frequency higher than 0.001. The other 426 variants were considered VUS. The two strength criteria datasets were used to evaluate 33 programs plus a conservation score. BayesDel (addAF and noAF), PON-P2 (genome and protein), and ClinPred algorithms showed the best sensitivity, specificity, accuracy, and kappa value for both criteria subsets. The VUS were evaluated with these five algorithms. Based on the results, 122 variants had total consensus among the five predictors, with 57 classified as predicted deleterious and 65 as predicted neutral. For variants not included in PON-P2, 88 variants were considered deleterious and 92 neutral by all other predictors. The remaining 124 did not obtain a consensus among predictors.
Full Text Finder