A novel tool for arrhythmic risk stratification in desmoplakin gene variant carriers
Authors: Carrick Richard T , Gasperetti Alessio , Protonotarios Alexandros , Murray Brittney , Laredo Mikael , van der Schaaf Iris , Dooijes Dennis , Syrris Petros , Cannie Douglas , Tichnell Crystal , Gilotra Nisha A , Cappelletto Chiara , Medo Kristen , Saguner Ardan M , Duru Firat , Hylind Robyn J , Abrams Dominic J , Lakdawala Neal K , Cadrin-Tourigny Julia , Targetti Mattia , Olivotto Iacopo , Graziosi Maddalena , Cox Moniek , Biagini Elena , Charron Philippe , Compagnucci Paolo , Casella Michela , Conte Giulio , Tondo Claudio , Yazdani Momina , Ware James S , Prasad Sanjay K , Calò Leonardo , Smith Eric D , Helms Adam S , Hespe Sophie , Ingles Jodie , Tandri Harikrishna , Ader Flavie , Peretto Giovanni , Peters Stacey , Horton Ari , Yao Jessica , Schulze-Bahr Eric , Dittman Sven , Carruth Eric D , Young Katelyn , Qureshi Maria , Haggerty Chris , Parikh Victoria N , Taylor Matthew , Mestroni Luisa , Wilde Arthur , Sinagra Gianfranco , Merlo Marco , Gandjbakhch Estelle , van Tintelen J Peter , te Riele Anneline S J M , Elliott Perry , Calkins Hugh , Wu Katherine C , James Cynthia A 
Published: July 2024

Background and Aims

Pathogenic desmoplakin (DSP) gene variants are associated with the development of a distinct form of arrhythmogenic cardiomyopathy known as DSP cardiomyopathy. Patients harbouring these variants are at high risk for sustained ventricular arrhythmia (VA), but existing tools for individualized arrhythmic risk assessment have proven unreliable in this population.

Methods

Patients from the multi-national DSP-ERADOS (Desmoplakin SPecific Effort for a RAre Disease Outcome Study) Network patient registry who had pathogenic or likely pathogenic DSP variants and no sustained VA prior to enrolment were followed longitudinally for the development of first sustained VA event. Clinically guided, step-wise Cox regression analysis was used to develop a novel clinical tool predicting the development of incident VA. Model performance was assessed by c-statistic in both the model development cohort (n = 385) and in an external validation cohort (n = 86).

Results

In total, 471 DSP patients [mean age 37.8 years, 65.6% women, 38.6% probands, 26% with left ventricular ejection fraction (LVEF) &lt; 50%] were followed for a median of 4.0 (interquartile range: 1.6–7.3) years; 71 experienced first sustained VA events {2.6% [95% confidence interval (CI): 2.0, 3.5] events/year}. Within the development cohort, five readily available clinical parameters were identified as independent predictors of VA and included in a novel DSP risk score: female sex [hazard ratio (HR) 1.9 (95% CI: 1.1–3.4)], history of non-sustained ventricular tachycardia [HR 1.7 (95% CI: 1.1–2.8)], natural logarithm of 24-h premature ventricular contraction burden [HR 1.3 (95% CI: 1.1–1.4)], LVEF &lt; 50% [HR 1.5 (95% CI: .95–2.5)], and presence of moderate to severe right ventricular systolic dysfunction [HR 6.0 (95% CI: 2.9–12.5)]. The model demonstrated good risk discrimination within both the development [c-statistic .782 (95% CI: .77–.80)] and external validation [c-statistic .791 (95% CI: .75–.83)] cohorts. The negative predictive value for DSP patients in the external validation cohort deemed to be at low risk for VA (&lt;5% at 5 years; n = 26) was 100%.

Conclusions

The DSP risk score is a novel model that leverages readily available clinical parameters to provide individualized VA risk assessment for DSP patients. This tool may help guide decision-making for primary prevention implantable cardioverter-defibrillator placement in this high-risk population and supports a gene-first risk stratification approach.