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Assessment of predicted enzymatic activity of α-N-acetylglucosaminidase variants of unknown significance for CAGI 2016

  • Wyatt T. Clark
  • , Laura Kasak
  • , Constantina Bakolitsa
  • , Zhiqiang Hu
  • , Gaia Andreoletti
  • , Giulia Babbi
  • , Yana Bromberg
  • , Rita Casadio
  • , Roland Dunbrack
  • , Lukas Folkman
  • , Colby T. Ford
  • , David Jones
  • , Panagiotis Katsonis
  • , Kunal Kundu
  • , Olivier Lichtarge
  • , Pier L. Martelli
  • , Sean D. Mooney
  • , Conor Nodzak
  • , Lipika R. Pal
  • , Predrag Radivojac
  • Castrense Savojardo, Xinghua Shi, Yaoqi Zhou, Aneeta Uppal, Qifang Xu, Yizhou Yin, Vikas Pejaver, Meng Wang, Liping Wei, John Moult, Guoying Karen Yu, Steven E. Brenner, Jonathan H. LeBowitz
  • BioMarin Pharmaceutical Inc.
  • University of California at Berkeley
  • University of Tartu
  • University of Bologna
  • Rutgers - The State University of New Jersey, New Brunswick
  • Swiss Federal Institute of Technology Zurich
  • University of North Carolina at Charlotte
  • University College London
  • Baylor College of Medicine
  • University of Maryland
  • University of Maryland, College Park
  • Buck Institute for Age Research
  • Indiana University Bloomington
  • Fox Chase Cancer Center
  • Peking University

Research output: Contribution to journalArticlepeer-review

16 Scopus citations

Abstract

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.

Original languageEnglish
Pages (from-to)1519-1529
Number of pages11
JournalHuman Mutation
Volume40
Issue number9
DOIs
StatePublished - Sep 1 2019

Keywords

  • Acetylglucosaminidase/genetics
  • Computational Biology/methods
  • Humans
  • Models, Genetic
  • Mutation, Missense
  • Regression Analysis

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