Dutch genome diagnostic laboratories accelerated and improved variant interpretation and increased accuracy by...

Area of Science:

• Genetics
• Bioinformatics
• Medical Diagnostics

Background:

• Diagnostic laboratories profile thousands of individuals annually for heritable diseases using next-generation sequencing (NGS).
• Pathogenicity classification of millions of DNA variants is required, posing challenges in data interpretation, quality, and reliability.

Purpose of the Study:

• To improve the efficiency and reliability of DNA variant classification in heritable disease diagnostics.
• To establish a collaborative framework for sharing variant classifications among Dutch diagnostic laboratories.

Main Methods:

• Nine Dutch laboratories established a centralized MOLGENIS database to catalog and compare variant classifications for nearly 100,000 unique variants.
• Classifications were labeled as "consensus" (agreed), "conflicting" (opposed), or "no consensus".
• InterVar software was used to compare classifications against ACMG 2015 guidelines.

Main Results:

• Achieved 99.7% overall consistency with ACMG 2015 guidelines, with only 0.3% discrepancies.
• Identified classification differences primarily in genes with low penetrance or late-onset disorders, highlighting limitations of the 5-tier system.
• Data sharing demonstrably boosted the quality of DNA diagnostics within Dutch laboratories.

Conclusions:

• Collaborative data sharing significantly enhances the quality and reliability of DNA variant classification in heritable disease diagnostics.
• The initiative provides a model for international cooperation in genetic variant interpretation.
• Improved classification led to more definitive disease diagnoses, as evidenced by a recent case match.