The utility of the Mayo Score for predicting the yield of genetic testing in patients with hypertrophic cardiomyopathy

Relationship Between Genotype Status and Clinical Outcome in Hypertrophic Cardiomyopathy

BACKGROUND

The genetic basis of hypertrophic cardiomyopathy (HCM) is complex, and the relationship between genotype status and clinical outcome is incompletely resolved.

METHODS AND RESULTS

We assessed a large international HCM cohort to define in contemporary terms natural history and clinical consequences of genotype. Consecutive patients (n=1468) with established HCM diagnosis underwent genetic testing. Patients with pathogenic (or likely pathogenic) variants were considered genotype positive (G+; n=312; 21%); those without definite disease-causing mutations (n=651; 44%) or variants of uncertain significance (n=505; 35%) were considered genotype negative (G-). Patients were followed up for a median of 7.8 years (interquartile range, 3.5-13.4 years); HCM end points were examined by cumulative event incidence. Over follow-up, 135 (9%) patients died, 33 from a variety of HCM-related causes. After adjusting for age, all-cause and HCM-related mortality did not differ between G- versus G+ patients (hazard ratio [HR], 0.78 [95% CI, 0.46-1.31]; P=0.37; HR, 0.93 [95% CI, 0.38-2.30]; P=0.87, respectively). Adverse event rates, including heart failure progression to class III/IV, heart transplant, or heart failure death, did not differ (G- versus G+) when adjusted for age (HR, 1.20 [95% CI, 0.63-2.26]; P=0.58), nor was genotype independently associated with sudden death event risk (HR, 1.39 [95% CI, 0.88-2.21]; P=0.16). In multivariable analysis, age was the only independent predictor of all-cause and HCM-related mortality, heart failure progression, and sudden death events.

CONCLUSIONS

In this large consecutive cohort of patients with HCM, genotype (G+ or G-) was not a predictor of clinical course, including all-cause and HCM-related mortality and risk for heart failure progression or sudden death. G+ status should not be used to dictate clinical management or predict outcome in HCM.

Meta-Analysis of Penetrance and Systematic Review on Transition to Disease in Genetic Hypertrophic Cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is characterized by unexplained left ventricular hypertrophy and is classically caused by pathogenic or likely pathogenic variants (P/LP) in genes encoding sarcomere proteins. Not all subclinical variant carriers will manifest clinically overt disease because penetrance (proportion of sarcomere or sarcomere-related P/LP variant carriers who develop disease) is variable, age dependent, and not reliably predicted.

METHODS

A systematic search of the literature was performed. We used random-effects generalized linear mixed model meta-analyses to contrast the cross-sectional prevalence and penetrance of sarcomere or sarcomere-related genes in 2 different contexts: clinically-based studies on patients and families with HCM versus population or community-based studies. Longitudinal family/clinical studies were additionally analyzed to investigate the rate of phenotypic conversion from subclinical to overt HCM during follow-up.

RESULTS

In total, 455 full-text manuscripts and articles were assessed. In family/clinical studies, the prevalence of sarcomere variants in patients diagnosed with HCM was 34%. The penetrance across all genes in nonproband relatives carrying P/LP variants identified during cascade screening was 57% (95% CI, 52%-63%), and the mean age at HCM diagnosis was 38 years (95% CI, 36%-40%). Penetrance varied from ≈32% for MYL3 (myosin light chain 3) to ≈55% for MYBPC3 (myosin-binding protein C3), ≈60% for TNNT2 (troponin T2) and TNNI3 (troponin I3), and ≈65% for MYH7 (myosin heavy chain 7). Population-based genetic studies demonstrate that P/LP sarcomere variants are present in the background population but at a low prevalence of <1%. The penetrance of HCM in incidentally identified P/LP variant carriers was also substantially lower at ≈11%, ranging from 0% in Atherosclerosis Risk in Communities to 18% in UK Biobank. In longitudinal family studies, the pooled phenotypic conversion across all genes was 15% over an average of ≈8 years of follow-up, starting from a mean of ≈16 years of age. However, short-term gene-specific phenotypic conversion varied between ≈12% for MYBPC3 and ≈23% for MYH7.

CONCLUSIONS

The penetrance of P/LP variants is highly variable and influenced by currently undefined and context-dependent genetic and environmental factors. Additional longitudinal studies are needed to improve our understanding of true lifetime penetrance in families and in the community and to identify drivers of the transition from subclinical to overt HCM.

Gene-echocardiography: refining genotype-phenotype correlations in hypertrophic cardiomyopathy

AIMS

This study aims to clarify the association between hypertrophic patterns and genetic variants in hypertrophic cardiomyopathy (HCM) patients, contributing to the advancement of personalized management strategies for HCM.

METHODS AND RESULTS

A comprehensive evaluation of genetic mutations was conducted in 392 HCM-affected families using Whole Exome Sequencing. Concurrently, relevant echocardiographic data from these individuals were collected. Our study revealed an increased susceptibility to enhanced septal and interventricular septal thickness in HCM patients harbouring gene mutations compared with those without. Mid-septal hypertrophy was found to be associated predominantly with myosin binding protein C3 (MYBPC3) variants, while a higher septum-to-posterior wall ratio correlated with myosin heavy chain 7 (MYH7) variants. Mutations in MYH7, MYBPC3, and other sarcomeric or myofilament genes (troponin I3 [TNNI3], tropomyosin 1 [TPM1], and troponin T2 [TNNT2]) showed a relationship with increased hypertrophy in the anterior wall, interventricular septum, and lateral wall of the left ventricle. In contrast, alpha kinase 3 (ALPK3)-associated hypertrophy chiefly presented in the apical region, while hypertrophy related to titin (TTN) and obscurin (OBSCN) mutations exhibited a uniform distribution across the myocardium. Hypertrophic patterns varied with the type and category of gene mutations, offering valuable diagnostic insights.

CONCLUSION

Our findings underscore a strong link between hypertrophic patterns and genetic variants in HCM, providing a foundation for more accurate genetic testing and personalized management of HCM patients. The novel concept of 'gene-echocardiography' may enhance the precision and efficiency of genetic counselling and testing in HCM.

Deep learning-derived 12-lead electrocardiogram-based genotype prediction for hypertrophic cardiomyopathy: a pilot study

Objective: Given the psychosocial and ethical burden, patients with hypertrophic cardiomyopathy (HCMs) could benefit from the establishment of genetic probability prior to the test. This study aimed to develop a simple tool to provide genotype prediction for HCMs.Methods: A convolutional neural network (CNN) was built with the 12-lead electrocardiogram (ECG) of 124 HCMs who underwent genetic testing (GT), externally tested by predicting the genotype on another HCMs cohort (n = 54), and compared with the conventional methods (the Mayo and Toronto score). Using a third cohort of HCMs (n = 76), the role of the network in risk stratification was explored by calculating the sudden cardiac death (SCD) risk scorers (HCM risk-SCD) across the predicted genotypes. Score-CAM was employed to provide a visual explanation of the network.Results: Overall, 80 of 178 HCMs (45%) were genotype-positive. Using the 12-lead ECG as input, the network showed an area under the curve (AUC) of 0.89 (95% CI, 0.83-0.96) on the test set, outperforming the Mayo score (0.69 [95% CI, 0.65-0.78], p < 0.001) and the Toronto score (0.69 [95% CI, 0.64-0.75], p < 0.001). The network classified the third cohort into two groups (predicted genotype-negative vs. predicted genotype-positive). Compared with the former, patients predicted genotype-positive had a significantly higher HCM risk-SCD (0.04 ± 0.03 vs. 0.03 ± 0.02, p <0.01). Visualization indicated that the prediction was heavily influenced by the limb lead.Conclusions: The network demonstrated a promising ability in genotype prediction and risk assessment in HCM.

Predictors of the utility of clinical exome sequencing as a first-tier genetic test in patients with Mendelian phenotypes: results from a referral center study on 603 consecutive cases

BACKGROUND

Clinical exome sequencing (CES) provides a comprehensive and effective analysis of relevant disease-associated genes in a cost-effective manner compared to whole exome sequencing. Although several studies have focused on the diagnostic yield of CES, no study has assessed predictors of CES utility among patients with various Mendelian phenotypes. We assessed the effectiveness of CES as a first-level genetic test for molecular diagnosis in patients with a Mendelian phenotype and explored independent predictors of the clinical utility of CES.

RESULTS

Between January 2016 and December 2019, 603 patients (426 probands and 177 siblings) underwent CES at the Department of Molecular Medicine of the University Hospital of Nancy. The median age of the probands was 34 years (IQR, 12-48), and the proportion of males was 46.9% (200/426). Adults and children represented 64.8% (276/426) and 35.2% (150/426), respectively. The median test-to-report time was 5.6 months (IQR, 4.1-7.2). CES revealed 203 pathogenic or likely pathogenic variants in 160 patients, corresponding to a diagnostic yield of 37.6% (160/426). Independent predictors of CES utility were criteria strongly suggestive of an extreme phenotype, including pediatric presentation and patient phenotypes associated with an increased risk of a priori probability of a monogenic disorder, the inclusion of at least one family member in addition to the proband, and a CES prescription performed by an expert in the field of rare genetic disorders.

CONCLUSIONS

Based on a large dataset of consecutive patients with various Mendelian phenotypes referred for CES as a first-tier genetic test, we report a diagnostic yield of ~ 40% and several independent predictors of CES utility that might improve CES diagnostic efficiency.

The Genetic Architecture of Hypertrophic Cardiomyopathy in Hungary: Analysis of 242 Patients with a Panel of 98 Genes

Hypertrophic cardiomyopathy (HCM) is a primary disease of the myocardium most commonly caused by mutations in sarcomeric genes. We aimed to perform a nationwide large-scale genetic analysis of a previously unreported, representative HCM cohort in Hungary. A total of 242 consecutive HCM index patients (127 men, 44 ± 11 years) were studied with next generation sequencing using a custom-designed gene-panel comprising 98 cardiomyopathy-related genes. A total of 90 patients (37%) carried pathogenic/likely pathogenic (P/LP) variants. The percentage of patients with P/LP variants in genes with definitive evidence for HCM association was 93%. Most of the patients with P/LP variants had mutations in MYBPC3 (55 pts, 61%) and in MYH7 (21 pts, 23%). Double P/LP variants were present in four patients (1.7%). P/LP variants in other genes could be detected in ≤3% of patients. Of the patients without P/LP variants, 46 patients (19%) carried a variant of unknown significance. Non-HCM P/LP variants were identified in six patients (2.5%), with two in RAF1 (p.Leu633Val, p.Ser257Leu) and one in DES (p.Arg406Trp), FHL1 (p.Glu96Ter), TTN (p.Lys23480fs), and in the mitochondrial genome (m.3243A>G). Frameshift, nonsense, and splice-variants made up 82% of all P/LP MYBPC3 variants. In all the other genes, missense mutations were the dominant form of variants. The MYBPC3 p.Gln1233Ter, the MYBPC3 p.Pro955ArgfsTer95, and the MYBPC3 p.Ser593ProfsTer11 variants were identified in 12, 7, and 13 patients, respectively. These three variants made up 36% of all patients with identified P/LP variants, raising the possibility of a possible founder effect for these mutations. Similar to other HCM populations, the MYBPC3 and the MYH7 genes seemed to be the most frequently affected genes in Hungarian HCM patients. The high prevalence of three MYBPC3 mutations raises the possibility of a founder effect in our HCM cohort.

It Is Not Carved in Stone—The Need for a Genetic Reevaluation of Variants in Pediatric Cardiomyopathies

(1) Background: In cardiomyopathies, identification of genetic variants is important for the correct diagnosis and impacts family cascade screening. A classification system was published by the American College of Medical Genetics and Genomics (ACMG) in 2015 to standardize variants’ classification. The aim of the study was to determine the rate of reclassification of previously identified variants in patients with childhood-onset cardiomyopathies. (2) Methods: Medical records of patients and their relatives were screened for clinical and genetic information at the Department of Congenital Heart Defects and Pediatric Cardiology, German Heart Center Munich. Patients without an identified genetic variant were excluded from further analyses. Previously reported variants were reevaluated by the ACMG criteria in November 2021. (3) Results: Data from 167 patients or relatives of patients with childhood-onset cardiomyopathy from 137 families were analyzed. In total, 45 different genetic variants were identified in 71 individuals. Classification changed in 29% (13/45) with the greatest shift in “variants of unknown significance” to “(likely) benign” (9/13). (4) Conclusions: In patients with childhood-onset cardiomyopathies, nearly a third of reported genetic variants change mostly to more benign classes upon reclassification. Given the impact on patient management and cascade screening, this finding underlines the importance of continuous genetic counseling and variant.

Genetic Testing in Patients with Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a common inherited heart disease with an estimated prevalence of up to 1 in 200 individuals. In the majority of cases, HCM is considered a Mendelian disease, with mainly autosomal dominant inheritance. Most pathogenic variants are usually detected in genes for sarcomeric proteins. Nowadays, the genetic basis of HCM is believed to be rather complex. Thousands of mutations in more than 60 genes have been described in association with HCM. Nevertheless, screening large numbers of genes results in the identification of many genetic variants of uncertain significance and makes the interpretation of the results difficult. Patients lacking a pathogenic variant are now believed to have non-Mendelian HCM and probably have a better prognosis than patients with sarcomeric pathogenic mutations. Identifying the genetic basis of HCM creates remarkable opportunities to understand how the disease develops, and by extension, how to disrupt the disease progression in the future. The aim of this review is to discuss the brief history and recent advances in the genetics of HCM and the application of molecular genetic testing into common clinical practice.

Deep Learning Analysis of Echocardiographic Images to Predict Positive Genotype in Patients With Hypertrophic Cardiomyopathy

Genetic testing provides valuable insights into family screening strategies, diagnosis, and prognosis in patients with hypertrophic cardiomyopathy (HCM). On the other hand, genetic testing carries socio-economical and psychological burdens. It is therefore important to identify patients with HCM who are more likely to have positive genotype. However, conventional prediction models based on clinical and echocardiographic parameters offer only modest accuracy and are subject to intra- and inter-observer variability. We therefore hypothesized that deep convolutional neural network (DCNN, a type of deep learning) analysis of echocardiographic images improves the predictive accuracy of positive genotype in patients with HCM. In each case, we obtained parasternal short- and long-axis as well as apical 2-, 3-, 4-, and 5-chamber views. We employed DCNN algorithm to predict positive genotype based on the input echocardiographic images. We performed 5-fold cross-validations. We used 2 reference models—the Mayo HCM Genotype Predictor score (Mayo score) and the Toronto HCM Genotype score (Toronto score). We compared the area under the receiver-operating-characteristic curve (AUC) between a combined model using the reference model plus DCNN-derived probability and the reference model. We calculated the p-value by performing 1,000 bootstrapping. We calculated sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). In addition, we examined the net reclassification improvement. We included 99 adults with HCM who underwent genetic testing. Overall, 45 patients (45%) had positive genotype. The new model combining Mayo score and DCNN-derived probability significantly outperformed Mayo score (AUC 0.86 [95% CI 0.79–0.93] vs. 0.72 [0.61–0.82]; p < 0.001). Similarly, the new model combining Toronto score and DCNN-derived probability exhibited a higher AUC compared to Toronto score alone (AUC 0.84 [0.76–0.92] vs. 0.75 [0.65–0.85]; p = 0.03). An improvement in the sensitivity, specificity, PPV, and NPV was also achieved, along with significant net reclassification improvement. In conclusion, compared to the conventional models, our new model combining the conventional and DCNN-derived models demonstrated superior accuracy to predict positive genotype in patients with HCM.

Clinical prediction of genotypes in hypertrophic cardiomyopathy: A systematic review

INTRODUCTION

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiac condition and the most common cause of sudden cardiac death (SCD) in patients below the age of 35. Genetic testing is a vital part of HCM diagnostics, yet correlation with clinical phenotypes remains complex. Identifying clinical predictors of informative genetic testing may prevent unnecessary investigations and improve cost-effectiveness of services. This article reviews the current literature pertinent to identifying such predictors.

METHODS

Five literature databases were screened using a suitably designed search strategy. Studies investigating the correlation between having a positive genetic test for HCM and a range of clinical and radiological parameters were included in the systematic review.

RESULTS

Twenty-nine observational studies of a total of 9,486 patients were included. The main predictors of informative genetic testing were younger age, higher septal thickness, reverse septal curvature, family history of HCM and SCD and the absence of hypertension. Two externally validated scoring systems have also been developed: the Mayo and Toronto scores. Novel imaging markers and complex algorithmic models are emerging predictors.

CONCLUSION

Using clinical predictors to decide whom to test is a feasible alternative to investigating all comers. Nonetheless, currently there is not enough evidence to unequivocally recommend for or against this strategy. Further validation of current predictors and identification of new ones remain open research avenues.

Prediction of Genotype Positivity in Patients With Hypertrophic Cardiomyopathy Using Machine Learning

BACKGROUND

Genetic testing can determine family screening strategies and has prognostic and diagnostic value in hypertrophic cardiomyopathy (HCM). However, it can also pose a significant psychosocial burden. Conventional scoring systems offer modest ability to predict genotype positivity. The aim of our study was to develop a novel prediction model for genotype positivity in patients with HCM by applying machine learning (ML) algorithms.

METHODS

We constructed 3 ML models using readily available clinical and cardiac imaging data of 102 patients from Columbia University with HCM who had undergone genetic testing (the training set). We validated model performance on 76 patients with HCM from Massachusetts General Hospital (the test set). Within the test set, we compared the area under the receiver operating characteristic curves (AUROCs) for the ML models against the AUROCs generated by the Toronto HCM Genotype Score (the Toronto score) and Mayo HCM Genotype Predictor (the Mayo score) using the Delong test and net reclassification improvement.

RESULTS

Overall, 63 of the 178 patients (35%) were genotype positive. The random forest ML model developed in the training set demonstrated an AUROC of 0.92 (95% CI, 0.85-0.99) in predicting genotype positivity in the test set, significantly outperforming the Toronto score (AUROC, 0.77 [95% CI, 0.65-0.90], P=0.004, net reclassification improvement: P<0.001) and the Mayo score (AUROC, 0.79 [95% CI, 0.67-0.92], P=0.01, net reclassification improvement: P=0.001). The gradient boosted decision tree ML model also achieved significant net reclassification improvement over the Toronto score (P<0.001) and the Mayo score (P=0.03), with an AUROC of 0.87 (95% CI, 0.75-0.99). Compared with the Toronto and Mayo scores, all 3 ML models had higher sensitivity, positive predictive value, and negative predictive value.

CONCLUSIONS

Our ML models demonstrated a superior ability to predict genotype positivity in patients with HCM compared with conventional scoring systems in an external validation test set.

Long-term outcomes and left ventricular diastolic function of sarcomere mutation-positive and mutation-negative patients with hypertrophic cardiomyopathy: a prospective cohort study

AIMS

Hypertrophic cardiomyopathy (HCM) is an inheritable disease that leads to sudden cardiac death and heart failure (HF). Sarcomere mutations (SMs) have been associated with HF. However, the differences in ventricular function between SM-positive and SM-negative HCM patients are poorly characterized.

METHODS AND RESULTS

Of the prospectively enrolled 374 unrelated HCM patients in Taiwan, 115 patients underwent both 91 cardiomyopathy-related gene screening and cardiovascular magnetic resonance (45.6 ± 10.6 years old, 76.5% were male). Forty pathogenic/likely pathogenic mutations were identified in 52 patients by next-generation sequencing. The SM-positive group were younger at first cardiovascular event (P = 0.04) and progression to diastolic HF (P = 0.02) with higher N-terminal pro-brain natriuretic peptide (NT-proBNP) [New York Heart Association (NYHA) Class III/IV symptoms with left ventricular ejection fraction > 55%] than the SM-negative group (P < 0.001). SM-positive patients had a greater extent of late gadolinium enhancement (P = 0.01), larger left atrial diameter (P = 0.03), higher normalized peak filling rate (PFR) and PFR ratio, and a greater reduction in global longitudinal strain than SM-negative patients (all P ≤ 0.01). During mean lifelong follow-up time (49.2 ± 15.6 years), SM-positive was a predictor of earlier HF (NYHA Class III/IV symptoms) after multivariate adjustment (hazard ratio 3.5; 95% confidence interval 1.3-9.7; P = 0.015).

CONCLUSION

SM-positive HCM patients had a higher extent of myocardial fibrosis and more severe ventricular diastolic dysfunction than those without, which may contribute to earlier onset of advanced HF, suggesting the importance of close surveillance and early treatment throughout life.

Clinical Utility of a Phenotype-Enhanced MYH7 -Specific Variant Classification Framework in Hypertrophic Cardiomyopathy Genetic Testing

Background:

Missense variants in the MYH7 -encoded MYH7 (beta myosin heavy chain 7) represent a leading cause of hypertrophic cardiomyopathy (HCM). MYH7 -specific American College of Medical Genetics and Genomics (ACMG) variant classification guidelines were released recently but have yet to be assessed independently. We set out to assess the performance of the MYH7 -specific ACMG guidelines and determine if the addition of phenotype-enhanced criteria (PE-ACMG) using the HCM Genotype Predictor Score can further reduce the burden of variants of uncertain significance (VUS).

Methods:

Re-assessment was performed on 70 MYH7 -variants in 121 unique patients from Mayo Clinic, and an independent cohort of 54 variants in 70 patients from Royal Prince Alfred Hospital (Australia). Qualifying variants were re-adjudicated using both standard ACMG and MYH7 -ACMG guidelines, and HCM Genotype Predictor Score was used to provide a validated measure of strength of clinical phenotype to be incorporated into the MYH7 -ACMG framework.

Results:

Among Mayo Clinic identified variants, 11/70 (16%) were classified as pathogenic (P), 10/70 (14%) as likely pathogenic, and 49/70 (70%) as a VUS. A similar distribution was seen in the Australian patients (12/54 [22%] P, 12/54 [22%] likely pathogenic, and 30/54 [56%] VUS; P =not significant). Application of the MYH7 -ACMG resulted in a nonsignificant reduction of the VUS burden in both cohorts from 49/70 to 39/70 (56%; P =0.1; Mayo Clinic) and from 30/54 to 20/54 (37%; P =0.1; Australia). Using the combined PE-MYH7-ACMG framework, the VUS decreased significantly from 49 to 27 ( P <0.001, Mayo Clinic) and from 30 to 16 ( P <0.001; Australia).

Conclusions:

Use of the MYH7 -specific guidelines alone failed to significantly decrease VUS burden in 2 independent cohorts. However, a significant reduction in VUS burden was observed after the addition of phenotypic criteria. Using a patient’s strength of sarcomeric HCM phenotype for variant adjudication can increase significantly the clinical utility of genetic testing for patients with HCM.

Patients with hypertrophic obstructive cardiomyopathy after alcohol septal ablation have favorable long-term outcome irrespective of their genetic background

Background

The genetic background of patients with hypertrophic cardiomyopathy (HCM) treated with alcohol septal ablation (ASA) and its relationship to the outcomes are not known. We aimed to investigate whether the outcome of genotype positive (G+) patients differs from genotype negative (G-) patients treated with ASA.

Methods

We included 129 HCM patients (mean age 54±13 years) treated with ASA in a tertiary cardiovascular center and performed next generation sequencing (NGS) based genomic testing. All patients were followed-up three months after the procedure and yearly thereafter.

Results

A total of 30 (23%) HCM patients were G+ patients. At the 3-months follow-up, both groups of patients had similar left ventricular outflow tract PG (16.9±15.7 mmHg in G+ vs. 16.3±18.8 mmHg in G-, P=0.73) and symptoms (follow-up NYHA class 1.40±0.62 vs. 1.37±0.53, P=0.99, follow-up CCS class 0.23±0.52 vs. 0.36±0.65, P=0.36). The independent predictors of all-cause mortality were baseline interventricular septum (IVS) thickness (HR 1.12, 95% CI: 1.00-1.26, P=0.049) and age at the time of ASA (HR 1.11, 95% CI: 1.06-1.17, P<0.01). The adjusted all-cause mortality rate did not differ significantly between G+ and G- patients (P=0.52). The adjusted combined mortality event rate did not differ between both groups (P=0.78).

Conclusions

Despite more severe phenotype in G+ HCM patients, ASA is an equally effective treatment for LVOTO in G+ patients as it is for treating LVOTO in G- patients. The long-term outcome after ASA is similar in G+ and G- patients.

Head-Up Tilt Test in Risk Stratification of Patients with Hypertrophic Cardiomyopathy

Conflicting results have been published considering the role of head-up tilt test (HUTT) positivity as a prognostic factor in patients with hypertrophic cardiomyopathy (HCM). The relationship between HCM patients' genotype and their HUTT results has not been previously reported. The aim of this study was to evaluate patients with HCM and their HUTT results in regard to its value for outcome prediction and to investigate the relation of patients' genotype and their HUTT results. Seventy-four (51 ± 15 years; 42% women; median follow-up 72 months) HCM patients were divided into two groups based on their HUTT results and were retrospectively analyzed. In 67 (90.5%) subjects included in the analysis, next-generation sequencing-based genomic testing was performed. A composite end point of unexplained syncope, heart failure hospitalization, and death was defined. A total of 14 patients (18.9%) had positive HUTT (HUTT+), whereas 60 (81.1%) had negative HUTT (HUTT-). Except for the New York Heart Association functional class ( p  = 0.01), both groups had similar characteristics. Positive genotype was evenly distributed between the two groups. Composite end point occurred in 5 patients (35.7%) in HUTT+ group versus 14 (23.3%) patients in HUTT- group ( p  = 0.33). We did not find a relationship between HUTT results and long-term outcome. We found no association between HUTT results and genotype.