REVEL Is Better at Predicting Pathogenicity of Loss-of-Function than Gain-of-Function Variants

Area of Science:

• Genetics
• Bioinformatics
• Computational Biology

Background:

• In silico tools aid variant pathogenicity assessment.
• REVEL is a popular metapredictor for missense variant pathogenicity.
• Previous studies have not evaluated REVEL performance based on variant mechanism (loss-of-function vs. gain-of-function).

Purpose of the Study:

• To assess if REVEL's performance differs for loss-of-function (LoF) and gain-of-function (GoF) missense variants.
• To evaluate the impact of variant mechanism on REVEL score interpretation within the American College of Medical Genetics and Genomics (ACMG) guidelines.

Main Methods:

• Utilized a curated dataset of 66 confirmed LoF and 65 confirmed GoF variants.
• Analyzed REVEL scores against established pathogenicity thresholds (0.5 and 0.75).
• Compared the proportion of LoF and GoF variants meeting the ACMG threshold (0.932) for strong evidence of pathogenicity.

Main Results:

• Nearly all LoF (98%) and GoF (100%) variants met the 0.5 REVEL pathogenicity threshold.
• High proportions of both LoF (89%) and GoF (88%) variants exceeded the 0.75 threshold.
• Significantly fewer GoF variants (35%) met the 0.932 threshold for strong evidence compared to LoF variants (55%) (P = 0.0352).

Conclusions:

• REVEL scores are generally high for both LoF and GoF variants.
• Gain-of-function variants are less likely to achieve the highest REVEL scores required for strong evidence under ACMG guidelines.
• This finding has implications for variant classification, potentially underestimating the pathogenicity of GoF variants.