Automated patch clamp data improve variant classification and penetrance stratification for SCN5A-Brugada syndrome

Area of Science:

• Cardiovascular genetics
• Molecular cardiology
• Genetic testing and precision medicine

Background:

• Brugada syndrome (BrS) is an inherited arrhythmia disorder linked to SCN5A gene variants, increasing sudden cardiac death risk.
• Genetic diagnosis of BrS is challenging due to variants of uncertain significance (VUS) and incomplete penetrance.
• SCN5A encodes the cardiac sodium channel NaV1.5, crucial for heart rhythm regulation.

Purpose of the Study:

• To deploy a high-throughput functional assay for SCN5A variants in Brugada syndrome patients.
• To facilitate genetic diagnosis and precision medicine implementation for BrS.
• To reclassify SCN5A variants of uncertain significance (VUS) using functional data.

Main Methods:

• Analyzed 252 SCN5A missense and in-frame insertion/deletion variants from 3335 BrS cases using automated patch-clamp (APC) assay.
• Assigned variant functional Z-scores with evidence levels (BS3_moderate to PS3_strong) per ACMG criteria.
• Integrated functional data with population frequency, hotspot analysis, case counts, protein changes, and in silico predictions for variant classification.

Main Results:

• 146 of 252 variants showed abnormal function (Z ≤ -2), with 100 exhibiting severe loss-of-function (Z ≤ -4).
• Functional evidence enabled reclassification of 110 of 225 VUS (104 to likely pathogenic, 6 to likely benign).
• Loss-of-function variants were primarily in transmembrane domains; penetrance correlated with severity (Z ≤ -6 variants had 24.5% penetrance, OR 501).

Conclusions:

• The cohort-scale APC dataset stratifies SCN5A variants into low-risk 'bystander' and high-risk loss-of-function types.
• Functional data integration aids VUS reclassification, improving diagnostic accuracy for BrS.
• This study clarifies the SCN5A-BrS relationship, enhancing diagnosis and clinical management for BrS families.