Reclassifying variations of unknown significance in diseases affecting Saudi Arabia’s population reveal new associations

Mariam M. Al Eissa, Raniah S. Alotibi, Bader Alhaddad, Taghrid Aloraini, Manar S. Samman, Abdulrahman AlAsiri, Mohamed Abouelhoda, Amerh S. AlQahtani*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

Introduction: Physicians face diagnostic dilemmas upon reports indicating disease variants of unknown significance (VUS). The most puzzling cases are patients with rare diseases, where finding another matched genotype and phenotype to associate their results is challenging. This study aims to prove the value of updating patient files with new classifications, potentially leading to better assessment and prevention. Methodology: We recruited retrospective phenotypic and genotypic data from King Saud Medical City, Riyadh, Kingdom of Saudi Arabia. Between September 2020 and December 2021, 1,080 patients’ genetic profiles were tested in a College of American Pathologists accredited laboratory. We excluded all confirmed pathogenic variants, likely pathogenic variants and copy number variations. Finally, we further reclassified 194 VUS using different local and global databases, employing in silico prediction to justify the phenotype–genotype association. Results: Of the 194 VUS, 90 remained VUS, and the other 104 were reclassified as follows: 16 pathogenic, 49 likely pathogenic, nine benign, and 30 likely benign. Moreover, most of these variants had never been observed in other local or international databases. Conclusion: Reclassifying the VUS adds value to understanding the causality of the phenotype if it has been reported in another family or population. The healthcare system should establish guidelines for re-evaluating VUS, and upgrading VUS should reflect on individual/family risks and management strategies.

Original languageEnglish
Article number1250317
JournalFrontiers in Genetics
Volume14
DOIs
Publication statusPublished - 2023

Keywords

  • disease-related
  • exome sequencing
  • next-generation sequencing
  • novel variation
  • single nucleotide variation
  • variants of unknown significance

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