Evidence map›Paper›PMID 40910438›Full record

ArticleJournal of neuromuscular diseases2026

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

Martin Krenn, Axel Schmidt, Matias Wagner, Margot Ernst, Elisabeth Graf, Gudrun Zulehner, Hakan Cetin, Fritz Zimprich, Jakob Rath

Abstract read
In one paragraph

Article in Journal of neuromuscular diseases, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Correlations ofAlzheimer's & dementia (New York, N. Y.)
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Martin KrennDepartment of Neurology, Medical University of Vienna, Vienna, Austria.ORCID 0000-0003-3026-3082
Axel SchmidtInstitute of Human Genetics, University of Bonn, Medical Faculty and University Hospital Bonn, Bonn, Germany.
Matias WagnerInstitute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.ORCID 0000-0002-4454-8823
Margot ErnstDepartment of Pathobiology of the Nervous System, Center for Brain Research, Medical University of Vienna, Vienna, Austria.
Elisabeth GrafInstitute of Human Genetics, Klinikum rechts der Isar, School of Medicine, Technical University of Munich, Munich, Germany.
Gudrun ZulehnerDepartment of Neurology, Medical University of Vienna, Vienna, Austria.ORCID 0000-0003-4151-684X
Hakan CetinDepartment of Neurology, Medical University of Vienna, Vienna, Austria.
Fritz ZimprichDepartment of Neurology, Medical University of Vienna, Vienna, Austria.
Jakob RathDepartment of Neurology, Medical University of Vienna, Vienna, Austria.ORCID 0000-0001-6581-4572

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Machine LearningMutation, MissenseNeuromuscular DiseasesHigh-Throughput Nucleotide SequencingHumansAlphaMissensemissense variantsneuromuscular disordernext-generation sequencing

Identifiers

PMID40910438
PMCPMC13434959

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.