VariantMatcher: Phenotypic and Genomic Data Sharing to Facilitate Variant Classification and Disease Gene Discovery

Area of Science:

• Genomics
• Clinical Genetics
• Bioinformatics

Background:

• Variant classification is crucial for genetic testing interpretation.
• Variants of uncertain significance (VUS) pose challenges in clinical decision-making.
• Genomic data sharing platforms can aid variant interpretation.

Purpose of the Study:

• To evaluate the utility of the VariantMatcher platform for enhancing variant classification in a clinical setting.
• To assess the impact of data sharing on reclassifying VUS.
• To improve diagnostic accuracy and clinical decision-making.

Main Methods:

• Retrospective analysis of 3025 molecular genetic test results.
• Identification and selection of VUS not present in gnomAD.
• Investigation of VUS presence and phenotypic overlap in VariantMatcher.
• Reclassification of variants based on further phenotypic investigation.

Main Results:

• 1679 out of 2302 reported variants were classified as VUS.
• 80 of 542 selected VUS were found in VariantMatcher.
• 63 variants showed phenotypic overlap.
• 20 VUS (32%) were reclassified, primarily ruling out causality for early-onset dominant diseases.

Conclusions:

• VariantMatcher facilitates improved variant classification accuracy in clinical laboratories.
• Data sharing through platforms like VariantMatcher enhances the interpretation of VUS.
• Accurate variant classification leads to more precise clinical decision-making and genetic counseling.