Risk Stratification of Arrhythmogenic Consequences of Andersen-Tawil Syndrome Affecting Kir2.1-PIP2 Interactions
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Background
Andersen-Tawil syndrome type 1 (ATS1) is caused by loss-of-function mutations in KCNJ2 , which encodes the inward rectifier K + channel Kir2.1, a key determinant of I K1 . Impaired Kir2.1 destabilizes membrane excitability and predisposes to ventricular arrhythmias. Most ATS1 variants disrupt channel regulation by phosphatidylinositol 4,5-bisphosphate (PIP2), but whether specific mutations confer differential arrhythmic risk remains unclear.
Objective
To determine whether ATS1 variants disrupting Kir2.1–PIP2 interactions define distinct arrhythmic risk profiles and establish a mechanistically informed framework for risk stratification.
Methods
We performed a pooled patient-level analysis of 225 ATS1 patients carrying KCNJ2 variants impairing Kir2.1-PIP2 interaction. Inclusion of 22 clinical and electrocardiographic variables were used to identify mutation-specific risk profiles and predictors for arrhythmia risk. The approach was validated in a multicenter cohort of 20 ATS1 patients. Functional validation was performed using patient-derived iPSC-CMs, cardiac-targeted mouse models, and structural in silico analyses.
Results
ATS1 variants segregated into three discrete clusters corresponding to high-, intermediate-, and low-risk arrhythmic phenotypes, establishing a mutation-dependent hierarchy of arrhythmic risk. Regression analyses identified six variables independently associated with severe arrhythmic outcomes. In patient-derived Patient-derived iPSC-CM demonstrated graded impairment of electrical propagation and arrhythmia susceptibility, with a hierarchy in CV (Control > R82W > R218W > G215D). ATS1 mouse models reproduced the clinical risk stratification. Structural modeling showed that high-risk variants localize near the channel pore and disrupt Kir2.1–PIP2 interactions through mutation-specific mechanisms.
Conclusions
ATS1 caused by Kir2.1–PIP2–disrupting variants is not a uniform disorder but comprises biologically distinct subgroups with predictable differences in arrhythmic severity. Integrating genetics, functional phenotyping, and structural modeling provides a mechanistically grounded framework for ATS1 risk stratification and precision therapy development.
