Integrating electrocardiogram into the Mayo score enhances genotype prediction in hypertrophic cardiomyopathy

Abstract Introduction Hypertrophic cardiomyopathy (HCM) is a common inherited cardiovascular disease, typically transmitted in an autosomal dominant manner. Although pathogenic variants in sarcomere-encoding genes are key determinants of disease onset and progression, genetic testing has faced hurdles in terms of human and financial resources, necessitating efficient prioritization. The Mayo HCM Genotype Predictor Score (Mayo score) and the Toronto HCM Genotype Score (Toronto score), both derived from clinical and echocardiographic variables, have showed acceptable performance estimating the pre-test probability of genotype positivity. While electrocardiogram (ECG) is a low-cost and minimally invasive modality and pathogenic variants are associated with electrophysiological abnormalities, ECG parameters were not incorporated into these models. Purpose This study aimed to develop an improved predictive model for genotype positivity in HCM by integrating ECG parameters. Methods We retrospectively analysed 507 unrelated HCM patients from a Japanese multicentre cohort. Genotype positivity was defined as the presence of pathogenic or likely pathogenic (P/LP) variants in definitive sarcomeric genes. Candidate ECG variables were selected via univariate analysis and stepwise selection based on Akaike’s information criterion in a multivariable logistic regression model. A novel point-based Mayo-ECG score was developed and internally validated using bootstrap resampling. Predictive performance was assessed by the area under the receiver operating characteristic curve (AUROC) and net reclassification improvement (NRI). Results Overall, 162 (32.0%) were genotype positive. P/LP variants were most frequently identified in MYBPC3 (n = 74), followed by MYH7 (n = 62), and the other genes. Genotype-positive patients had a higher prevalence of atrial fibrillation, intraventricular conduction disturbance (QRS duration ≥ 120 msec or bundle branch block), prolonged QT interval, left axis deviation, lower Sokolow-Lyon index and less frequent T-wave inversion in the precordial leads compared to genotype-negative patients. The Mayo-ECG score (Figure 1) stratified genotype positivity from 7.6% (score ≤ -1) to 90.9% (score ≥ 4) (Figure 2A). Bootstrap resampling demonstrated the Mayo-ECG score (AUROC, 0.81 [95% CI, 0.77-0.85]) outperformed the Mayo score (AUROC, 0.76 [95% CI, 0.72-0.81]; p < 0.001, NRI: 0.21 [95% CI, 0.13-0.29]; p = 0.007) and the Toronto score (AUROC, 0.75 [95% CI, 0.70-0.79]; p = 0.009, NRI: 0.17 [95% CI, 0.06-0.27]; p < 0.001) (Figure 2B), with good calibration (Brier score: 0.156, max calibration error: 0.024). Conclusions Genotype-positive and genotype-negative HCM patients exhibited distinct ECG characteristics. The Mayo-ECG score significantly enhances genotype prediction in HCM by incorporating ECG parameters, outperforming conventional models. Its simplicity and improved accuracy support its use for optimizing genetic screening in HCM.Novel Mayo-ECG score Performance of Mayo-ECG score

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