ACMG/AMP variant classification framework in arginase 1 deficiency: Implications for birth prevalence estimates and...

Area of Science:

• Genetics
• Biochemistry
• Medical Research

Background:

• Arginase 1 (ARG1) deficiency causes hyperargininemia and neurological issues.
• Current ARG1 variant frequency estimates lack precision in distinguishing benign from pathogenic variants.
• Accurate ARG1 variant classification is crucial for reproductive carrier screening.

Purpose of the Study:

• To apply updated variant classification guidelines for ARG1.
• To estimate the global birth prevalence of ARG1 deficiency more accurately.
• To improve understanding of ARG1 variant pathogenicity.

Main Methods:

• Interrogation of Genome Aggregation Database and PubMed for published and unpublished ARG1 variants.
• Classification of variants using American College of Medical Genetics and Genomics/Association for Molecular Pathology guidelines.
• In silico predictions and AI-powered platform (Franklin Genoox) combined with manual review.

Main Results:

• Analysis of 73 published and 302 unpublished ARG1 variants.
• Classification revealed varying degrees of pathogenicity, with many variants of uncertain significance.
• Mutant allele frequencies ranged from 17 to 266 per 100,000, impacting birth prevalence estimates.

Conclusions:

• A significant number of ARG1 variants lack sufficient evidence of pathogenicity.
• Functional studies and clinical data are essential for accurate variant classification.
• Improved understanding of ARG1 variant pathogenicity is key to refining birth prevalence estimates.