An Empirical Pipeline for Personalized Diagnosis of Lafora Disease Mutations

Authors

M. Kathryn Brewer, University of Kentucky
Maria Machio-Castello, Universidad Autónoma de Madrid, Spain
Rosa Viana, Consejo Superior de Investigaciones Científicas, Spain
Jeremiah L. Wayne, University of KentuckyFollow
Andrea Kuchtová, University of Kentucky
Zoe R. Simmons, University of KentuckyFollow
Sarah Sternbach, University of Kentucky
Sheng Li, University of California, San Diego
Maria Adelaida García-Gimeno, Polytechnic University of Valencia, Spain
Jose M. Serratosa, University of Kentucky
Pascual Sanz, University of Kentucky
Craig W. Vander Kooi, University of KentuckyFollow
Matthew S. Gentry, University of KentuckyFollow

Abstract

Lafora disease (LD) is a fatal childhood dementia characterized by progressive myoclonic epilepsy manifesting in the teenage years, rapid neurological decline, and death typically within ten years of onset. Mutations in either EPM2A, encoding the glycogen phosphatase laforin, or EPM2B, encoding the E3 ligase malin, cause LD. Whole exome sequencing has revealed many EPM2A variants associated with late-onset or slower disease progression. We established an empirical pipeline for characterizing the functional consequences of laforin missense mutations in vitro using complementary biochemical approaches. Analysis of 26 mutations revealed distinct functional classes associated with different outcomes that were supported by clinical cases. For example, F321C and G279C mutations have attenuated functional defects and are associated with slow progression. This pipeline enabled rapid characterization and classification of newly identified EPM2A mutations, providing clinicians and researchers genetic information to guide treatment of LD patients.

Document Type

Article

Publication Date

10-13-2021

Notes/Citation Information

Published in iScience, v. 24, issue 11, 103276.

© 2021 The Authors

This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Digital Object Identifier (DOI)

https://doi.org/10.1016/j.isci.2021.103276

Funding Information

This work was supported by the National Institutes of Health (P01 NS097197 to M.S.G., J.M.S. and P.S., R35 NS116824 to M.S.G., and F31 NS093892 to M.K.B), National Science Foundation (DBI2018007 and MCB1817414 to M.S.G.), and Epilepsy Foundation New Therapy Commercialization Grant to M.S.G. M.K.B. received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement (No. 754510M). This project also received funding from the Spanish Ministry of Science and Innovation (SAF2017-83151-R to P.S. and RTI2018-095784b-100SAF to J.M.S).

Related Content

All data reported in this paper will be shared by the lead contact upon request.

This paper does not report original code.

Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Repository Citation

Brewer, M. Kathryn; Machio-Castello, Maria; Viana, Rosa; Wayne, Jeremiah L.; Kuchtová, Andrea; Simmons, Zoe R.; Sternbach, Sarah; Li, Sheng; García-Gimeno, Maria Adelaida; Serratosa, Jose M.; Sanz, Pascual; Vander Kooi, Craig W.; and Gentry, Matthew S., "An Empirical Pipeline for Personalized Diagnosis of Lafora Disease Mutations" (2021). Molecular and Cellular Biochemistry Faculty Publications. 193.
https://uknowledge.uky.edu/biochem_facpub/193