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Variability in pathogenicity prediction programs: impact on clinical diagnostics.

Lauren C Walters-Sen1, Sayaka Hashimoto2, Devon Lamb Thrush3

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Summary
This summary is machine-generated.

Clinical labs use online tools to predict variant pathogenicity, but accuracy varies. MutPred performed best, yet no single tool or combination reliably predicted all variants, highlighting the need for caution.

Keywords:
Diagnosticspathogenicitypredictionsequencingvariants

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Area of Science:

  • Genetics
  • Bioinformatics
  • Computational Biology

Background:

  • Clinical diagnostic laboratories rely on online prediction programs to assess novel genetic variants.
  • Existing pathogenicity prediction tools exhibit significant variability in accuracy and methodology.
  • Accurate variant interpretation is crucial for diagnosing genetic disorders like RASopathies and limb-girdle muscular dystrophy.

Purpose of the Study:

  • To evaluate the performance of 17 publicly available pathogenicity prediction programs.
  • To compare the accuracy of these programs for loss-of-function and gain-of-function variants.
  • To identify the most reliable prediction tool for clinical genetic variant interpretation.

Main Methods:

  • Assayed 17 pathogenicity prediction programs using a dataset of 122 known pathogenic and benign variants.
  • Focused on variants within genes associated with RASopathy and limb-girdle muscular dystrophy.
  • Compared performance metrics, including accuracy for different variant mechanisms.

Main Results:

  • No single program achieved perfect accuracy across all tested variants.
  • MutPred demonstrated the highest weighted accuracy at 82.6% on the full dataset.
  • Combining top-performing programs did not improve predictive ability over the best single program.

Conclusions:

  • Online pathogenicity prediction programs show limitations and variable performance.
  • Extreme caution is advised when reporting variant pathogenicity based solely on these statistical tools.
  • Functional studies remain essential for definitive variant interpretation in clinical diagnostics.