Key result
Automated patch clamp and MAVE functional assays align on ~79% of KCNH2 variants.
Why the study?
Many individuals with long QT syndrome carry KCNH2 missense variants of uncertain significance, and functional evidence requires validation for clinical interpretation.
Does likelihood ratio calibration align automated patch-clamp functional evidence with MAVE data for classifying KCNH2 variants in long QT syndrome?
Does likelihood ratio calibration align automated patch-clamp functional evidence with MAVE data for classifying KCNH2 variants in long QT syndrome?
Calibrating automated patch-clamp and MAVE data using likelihood ratios harmonizes functional evidence, significantly improving the clinical interpretation and classification of KCNH2 variants in long QT syndrome.
Answers are grounded in this paper and cite their sources.
Supports calibrated functional assays for KCNH2 reclassification; leaves open prospective validation before clinical adoption.
BACKGROUND Many people with long QT syndrome carry missense variants that are classified as variants of uncertain significance. Functional evidence from laboratory experiments can help improve genetic diagnosis, but it requires proper validation before use in a clinical interpretation framework. OBJECTIVE To compare two functional datasets for KCNH2 variants: a high-throughput assay that measures how much KV11.1 channel reaches the cell surface, and automated patch clamp, which measures the level of potassium current in HEK293 cells. METHODS Automated patch clamp results were converted into likelihood ratios using reference sets of pathogenic and benign KCNH2 variants. These values were then mapped to ACMG/AMP functional evidence categories and compared with previously calibrated MAVE evidence for 495 single-nucleotide KCNH2 variants found in individuals with long QT syndrome. RESULTS Overall, 392 of 495 variants (79%) had concordant interpretations between MAVE and automated patch clamp. The remaining 103 variants differed between assays: 49 shifted between normal and abnormal functional evidence, and 54 shifted between a functional evidence category and an indeterminate result. Among variants assigned strong abnormal evidence by both assays, 54 were absent from ClinVar. Of 111 unresolved or conflicting ClinVar variants, 92 would meet evidence combinations sufficient for likely pathogenic classification when strong functional evidence was combined with supporting computational and population-frequency evidence. CONCLUSION Likelihood ratio calibration allows MAVE and automated patch clamp data to be compared within the same clinical interpretation framework. Together, these functional datasets can support more transparent interpretation of KCNH2 variants in long QT syndrome.
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Shen et al. (2026) studied long QT syndrome (n=495). Automated patch clamp vs. MAVE (Multiplexed Assays of Variant Effect) was evaluated on Concordance between MAVE and automated patch clamp interpretations. Automated patch clamp and MAVE functional evidence were concordant for 79% (392 of 495) of KCNH2 variants in long QT syndrome.
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