Article (Périodiques scientifiques)
Machine learning-based identification and characterization of 15 novel pathogenic SUOX missense mutations
Kaczmarek, Alexander Tobias; Bahlmann, Nike; Thaqi, Besarta et al.
2021In Molecular Genetics and Metabolism
Peer reviewed
 

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Mots-clés :
Isolated sulfite oxidase deficiency; Molybdenum cofactor; Machine learning; Random forest classification; Sulfite oxidase; SUOX
Résumé :
[en] Isolated sulfite oxidase deficiency (ISOD) is a rare hereditary metabolic disease caused by absence of functional sulfite oxidase (SO) due to mutations of the SUOX gene. SO oxidizes toxic sulfite and sulfite accumulation is associated with neurological disorders, progressive brain atrophy and early death. Similarities of these neurological symptoms to abundant diseases like neonatal encephalopathy underlines the raising need to increase the awareness for ISOD. Here we report an interdisciplinary approach utilizing exome/genome data derived from gnomAD database as well as published variants to predict the pathogenic outcome of 303 naturally occurring SO missense variants and combining these with activity determination. We identified 15 novel ISOD-causing SO variants and generated a databank of pathogenic SO missense variants to support future diagnosis of ISOD patients. We found six inactive variants (W101G, H118Y, E197K, R217W, S427W, D512Y, Q518R) and seven (D110H, P119S, G121E, G130R, Y140C, R269H, Q396P, R459Q) with severe reduction in activity. Based on the Hardy-Weinberg-equilibrium and the combination of our results with published SO missense and protein truncating variants, we calculated the first comprehensive incidence rate for ISOD of 1 in 1,377,341 births and provide a pathogenicity score to 303 naturally occurring SO missense variants.
Centre de recherche :
- Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
Disciplines :
Génétique & processus génétiques
Biochimie, biophysique & biologie moléculaire
Auteur, co-auteur :
Kaczmarek, Alexander Tobias
Bahlmann, Nike
Thaqi, Besarta
MAY, Patrick  ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core
Schwarz, Guenter
Co-auteurs externes :
yes
Langue du document :
Anglais
Titre :
Machine learning-based identification and characterization of 15 novel pathogenic SUOX missense mutations
Date de publication/diffusion :
08 août 2021
Titre du périodique :
Molecular Genetics and Metabolism
ISSN :
1096-7192
Peer reviewed :
Peer reviewed
Focus Area :
Systems Biomedicine
Projet FnR :
FNR11583046 - Epileptogenesis Of Genetic Epilepsies, 2017 (01/04/2018-30/06/2021) - Roland Krause
Intitulé du projet de recherche :
National Centre for Excellence Missing in Research on Parkinson‟s disease (NCER-PD), BMBF Treat-ION grant (01GM1907).
Disponible sur ORBilu :
depuis le 12 août 2021

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