Article (Scientific journals)
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
 

Files


Full Text
1-s2.0-S1096719221007617-main.pdf
Author postprint (1.5 MB)
Request a copy

All documents in ORBilu are protected by a user license.

Send to



Details



Keywords :
Isolated sulfite oxidase deficiency; Molybdenum cofactor; Machine learning; Random forest classification; Sulfite oxidase; SUOX
Abstract :
[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.
Research center :
- Luxembourg Centre for Systems Biomedicine (LCSB): Bioinformatics Core (R. Schneider Group)
Disciplines :
Genetics & genetic processes
Biochemistry, biophysics & molecular biology
Author, co-author :
Kaczmarek, Alexander Tobias
Bahlmann, Nike
Thaqi, Besarta
May, Patrick  ;  University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > Bioinformatics Core
Schwarz, Guenter
External co-authors :
yes
Language :
English
Title :
Machine learning-based identification and characterization of 15 novel pathogenic SUOX missense mutations
Publication date :
08 August 2021
Journal title :
Molecular Genetics and Metabolism
ISSN :
1096-7192
Peer reviewed :
Peer reviewed
Focus Area :
Systems Biomedicine
FnR Project :
FNR11583046 - Epileptogenesis Of Genetic Epilepsies, 2017 (01/04/2018-30/06/2021) - Roland Krause
Name of the research project :
National Centre for Excellence Missing in Research on Parkinson‟s disease (NCER-PD), BMBF Treat-ION grant (01GM1907).
Available on ORBilu :
since 12 August 2021

Statistics


Number of views
91 (8 by Unilu)
Number of downloads
2 (2 by Unilu)

Scopus citations®
 
8
Scopus citations®
without self-citations
4
OpenCitations
 
3
WoS citations
 
7

Bibliography


Similar publications



Contact ORBilu