CYSMA

CYSMA predicts the impact of missense variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene to support interpretation of exome sequencing findings and assessment of variant pathogenicity.

Key Features:

• Comprehensive Data Integration: Consolidates evolutionary conservation metrics and functional insights derived from three-dimensional structural analyses of CFTR.
• Allelic Frequencies and Clinical Observations: Provides available allelic frequencies, clinical observations, and references for functional studies for each variant.
• Evolutionary and Structural Analysis: Combines conservation data with three-dimensional protein structure–based functional observations to generate nuanced impact predictions.
• Benchmarking Performance: In comparative evaluations against classical analysis software on a dataset of 141 well-characterized missense variants, demonstrated 85% specificity and 89% sensitivity for distinguishing benign from pathogenic variants.

Scientific Applications:

• Molecular diagnosis of cystic fibrosis: Supports interpretation of CFTR missense variants in clinical and research settings where exome sequencing yields variants of uncertain significance.
• Variant interpretation when databases are insufficient: Provides predictive evidence for at least ~40% of CFTR missense variants that remain uncharacterized and complements patient databases such as CFTR-France, CFTR1, and CFTR2.

Methodology:

Integrates evolutionary conservation metrics and functional observations derived from three-dimensional CFTR protein structures; comparative benchmarking against classical analysis software was performed on a dataset of 141 well-characterized missense variants yielding reported specificity and sensitivity values.