AlphaMissense prediction for the evaluation of missense variants in the diagnostic setting of neuromuscular disorders.

Journal: Journal of neuromuscular diseases
Published Date: Sep 5, 2025

Abstract

Next-generation sequencing has improved diagnostic outcomes for neuromuscular disorders, but interpreting rare missense variants remains challenging. We evaluated AlphaMissense, a recently developed machine learning tool, for predicting missense variant pathogenicity, using 45 (likely) pathogenic variants and 21 variants of uncertain significance from 58 deeply phenotyped patients. AlphaMissense predicted 69% of pathogenic variants correctly, but also classified 62% of variants of uncertain significance as pathogenic. Median AlphaMissense scores were not significantly different between pathogenic and uncertain variants. Overall, AlphaMissense accurately predicted the pathogenicity of most missense variants, but may be limited in certain functional contexts, highlighting the need for disease-specific interpretation approaches.

Authors

  • Martin Krenn
    Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Axel Schmidt
    Institute of Human Genetics, University of Bonn, Medical Faculty & University Hospital Bonn, Bonn, Germany.
  • Matias Wagner
    Institute of Human Genetics, School of Medicine, Technical University Munich, Munich, Germany.
  • Margot Ernst
    Department of Pathobiology of the Nervous System, Center for Brain Research, Medical University of Vienna, Vienna, Austria.
  • Elisabeth Graf
    Institute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
  • Gudrun Zulehner
    Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Hakan Cetin
    Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Fritz Zimprich
    Department of Neurology, Medical University of Vienna, Vienna, Austria.
  • Jakob Rath
    Department of Neurology, Medical University of Vienna, Vienna, Austria.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals