A novel statistical method for interpreting the pathogenicity of rare variants

Abstract

Purpose

To achieve the ultimate goal of personalized treatment of patients, accurate molecular diagnosis and precise interpretation of the impact of genetic variants on gene function is essential. With sequencing cost becoming increasingly affordable, the accurate distinguishing of benign from pathogenic variants becomes the major bottleneck. Although large normal population sequence databases have become a key resource in filtering benign variants, they are not effective at filtering extremely rare variants.

Methods

To address this challenge, we developed a novel statistical test by combining sequencing data from a patient cohort with a normal control population database. By comparing the expected and observed allele frequency in the patient cohort, variants that are likely benign can be identified.

Results

The performance of this new method is evaluated on both simulated and real data sets coupled with experimental validation. As a result, we demonstrate this new test is well powered to identify benign variants, and is particularly effective for variants with low frequency in the normal population.

Conclusion

Overall, as a general test that can be applied to any type of variants in the context of all Mendelian diseases, our work provides a general framework for filtering benign variants with very low population allele frequency.

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Fig. 1: The simulation analysis of the test power.
Fig. 2: The simulation analysis of sampling bias.
Fig. 3: The distribution of population allele frequency (AF) of the Human Gene Mutation Database (HGMD) variants in three genes.
Fig. 4: The distribution of other variant prediction scores and ClinVar assignment for the Human Gene Mutation Database (HGMD) variants in ABCA4, LRP5, and USH2A.
Fig. 5: The luciferase reporter assay of LRP5 variants.

Code availability

Our code is available at https://github.com/fe4960/Binomial_test.

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Acknowledgements

We are grateful to the lab of David Moore at Baylor College of Medicine for providing L cells for the functional assays of LRP5 variants. We thank the computing cluster server in the Molecular and Human Genetics Department at Baylor College of Medicine for providing the computing resource. This work was supported by grants from the National Eye Institute (grant numbers R01EY022356, R01EY018571, EY002520 to R.C.); Retinal Research Foundation [to RC]; National Institutes of Health shared instrument grant (grant number S10OD023469 to R.C.); and the Competitive Renewal Grant of Knights Templar Eye Foundation (to J.W.).

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Correspondence to Rui Chen PhD.

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Wang, J., Liu, H., Bertrand, R.E. et al. A novel statistical method for interpreting the pathogenicity of rare variants. Genet Med (2020). https://doi.org/10.1038/s41436-020-00948-3

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Keywords

  • variant interpretation
  • allele frequency
  • Mendelian diseases
  • statistical test
  • clinical genomics

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