Phenotype-Driven Virtual Panel Is an Effective Method to Analyze WES Data of Neurological Disease

Area of Science:

• Genomics
• Rare Diseases
• Bioinformatics

Background:

• Whole Exome Sequencing (WES) is crucial for diagnosing rare diseases but presents analysis challenges.
• Efficient annotation and single-case analysis of WES data remain difficult.

Purpose of the Study:

• To introduce and evaluate a phenotype-driven "virtual panel" method for simplifying WES analysis.
• To assess the diagnostic rate improvement offered by this novel approach.

Main Methods:

• WES was performed on 30 rare disease patients.
• Core phenotypes were used with the "Mingjian" software to generate a phenotype-driven virtual gene panel.
• Candidate mutations were filtered, annotated, and confirmed via Sanger sequencing and co-segregation analysis.

Main Results:

• The method successfully identified PMM2 mutations in a patient with ataxia, seizures, and developmental delay.
• Applied to 29 other neurological rare disease cases, the virtual panel achieved a 65.52% diagnostic rate, a significant increase.

Conclusions:

• Phenotype-driven virtual panels offer a cost-effective, individualized approach to WES analysis.
• This method reduces annotation time and enhances diagnostic efficiency and success rates for rare diseases.