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Assessment of predicted enzymatic activity of α‐ N ‐acetylglucosaminidase variants of unknown significance for CAGI 2016
Author(s) -
Clark Wyatt T.,
Kasak Laura,
Bakolitsa Constantina,
Hu Zhiqiang,
Andreoletti Gaia,
Babbi Giulia,
Bromberg Yana,
Casadio Rita,
Dunbrack Roland,
Folkman Lukas,
Ford Colby T.,
Jones David,
Katsonis Panagiotis,
Kundu Kunal,
Lichtarge Olivier,
Martelli Pier L.,
Mooney Sean D.,
Nodzak Conor,
Pal Lipika R.,
Radivojac Predrag,
Savojardo Castrense,
Shi Xinghua,
Zhou Yaoqi,
Uppal Aneeta,
Xu Qifang,
Yin Yizhou,
Pejaver Vikas,
Wang Meng,
Wei Liping,
Moult John,
Yu Guoying Karen,
Brenner Steven E.,
LeBowitz Jonathan H.
Publication year - 2019
Publication title -
human mutation
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.981
H-Index - 162
eISSN - 1098-1004
pISSN - 1059-7794
DOI - 10.1002/humu.23875
Subject(s) - library science , biology , computer science
The NAGLU challenge of the fourth edition of the Critical Assessment of Genome Interpretation experiment (CAGI4) in 2016, invited participants to predict the impact of variants of unknown significance (VUS) on the enzymatic activity of the lysosomal hydrolase α‐ N ‐acetylglucosaminidase (NAGLU). Deficiencies in NAGLU activity lead to a rare, monogenic, recessive lysosomal storage disorder, Sanfilippo syndrome type B (MPS type IIIB). This challenge attracted 17 submissions from 10 groups. We observed that top models were able to predict the impact of missense mutations on enzymatic activity with Pearson's correlation coefficients of up to .61. We also observed that top methods were significantly more correlated with each other than they were with observed enzymatic activity values, which we believe speaks to the importance of sequence conservation across the different methods. Improved functional predictions on the VUS will help population‐scale analysis of disease epidemiology and rare variant association analysis.