Role of TBX20 Truncating Variants in Dilated Cardiomyopathy and Left Ventricular Noncompaction.

BACKGROUND: Less than 40% of patients with dilated cardiomyopathy (DCM) have a pathogenic/likely pathogenic genetic variant identified. TBX20 has been linked to congenital heart defects; although an association with left ventricular noncompaction (LVNC) and DCM has been proposed, it is still considered a gene with limited evidence for these phenotypes. This study sought to investigate the association between the TBX20 truncating variant (TBX20tv) and DCM/LVNC. METHODS: TBX20 was sequenced by next-generation sequencing in 7463 unrelated probands with a diagnosis of DCM or LVNC, 22 773 probands of an internal comparison group (hypertrophic cardiomyopathy, channelopathies, or aortic diseases), and 124 098 external controls (individuals from the gnomAD database). Enrichment of TBX20tv in DCM/LVNC was calculated, cosegregation was determined in selected families, and clinical characteristics and outcomes were analyzed in carriers. RESULTS: TBX20tv was enriched in DCM/LVNC (24/7463; 0.32%) compared with internal (1/22 773; 0.004%) and external comparison groups (4/124 098; 0.003%), with odds ratios of 73.23 (95% CI, 9.90-541.45; P<0.0001) and 99.76 (95% CI, 34.60-287.62; P<0.0001), respectively. TBX20tv was cosegregated with DCM/LVNC phenotype in 21 families for a combined logarythm of the odds score of 4.53 (strong linkage). Among 57 individuals with TBX20tv (49.1% men; mean age, 35.9±20.8 years), 41 (71.9%) exhibited DCM/LVNC, of whom 14 (34.1%) had also congenital heart defects. After a median follow-up of 6.9 (95% CI, 25-75:3.6-14.5) years, 9.7% of patients with DCM/LVNC had end-stage heart failure events and 4.8% experienced malignant ventricular arrhythmias. CONCLUSIONS: TBX20tv is associated with DCM/LVNC; congenital heart defect is also present in around one-third of cases. TBX20tv-associated DCM/LVNC is characterized by a nonaggressive phenotype, with a low incidence of major cardiovascular events. TBX20 should be considered a definitive gene for DCM and LVNC and routinely included in genetic testing panels for these phenotypes.

Polymorphisms in ACE, ACE2, AGTR1 genes and severity of COVID-19 disease.

BACKGROUND: Infection by the SARS-Cov-2 virus produces in humans a disease of highly variable and unpredictable severity. The presence of frequent genetic single nucleotide polymorphisms (SNPs) in the population might lead to a greater susceptibility to infection or an exaggerated inflammatory response. SARS-CoV-2 requires the presence of the ACE2 protein to enter in the cell and ACE2 is a regulator of the renin-angiotensin system. Accordingly, we studied the associations between 8 SNPs from AGTR1, ACE2 and ACE genes and the severity of the disease produced by the SARS-Cov-2 virus. METHODS: 318 (aged 59.6±17.3 years, males 62.6%) COVID-19 patients were grouped based on the severity of symptoms: Outpatients (n = 104, 32.7%), hospitalized on the wards (n = 73, 23.0%), Intensive Care Unit (ICU) (n = 84, 26.4%) and deceased (n = 57, 17.9%). Comorbidity data (diabetes, hypertension, obesity, lung disease and cancer) were collected for adjustment. Genotype distribution of 8 selected SNPs among the severity groups was analyzed. RESULTS: Four SNPs in ACE2 were associated with the severity of disease. While rs2074192 andrs1978124showed a protector effectassuming an overdominant model of inheritance (G/A vs. GG-AA, OR = 0.32, 95%CI = 0.12-0.82; p = 0.016 and A/G vs. AA-GG, OR = 0.37, 95%CI: 0.14-0.96; p = 0.038, respectively); the SNPs rs2106809 and rs2285666were associated with an increased risk of being hospitalized and a severity course of the disease with recessive models of inheritance (C/C vs. T/C-T/T, OR = 11.41, 95% CI: 1.12-115.91; p = 0.012) and (A/A vs. GG-G/A, OR = 12.61, 95% CI: 1.26-125.87; p = 0.0081). As expected, an older age (OR = 1.47), male gender (OR = 1.98) and comorbidities (OR = 2.52) increased the risk of being admitted to ICU or death vs more benign outpatient course. Multivariable analysis demonstrated the role of the certain genotypes (ACE2) with the severity of COVID-19 (OR: 0.31, OR 0.37 for rs2074192 and rs1978124, and OR = 2.67, OR = 2.70 for rs2106809 and rs2285666, respectively). Hardy-Weinberg equilibrium in hospitalized group for I/D SNP in ACE was not showed (p<0.05), which might be due to the association with the disease. No association between COVID-19 disease and the different AGTR1 SNPs was evidenced on multivariable, nevertheless the A/A genotype for rs5183 showed an higher hospitalization risk in patients with comorbidities. CONCLUSIONS: Different genetic variants in ACE2 were associated with a severe clinical course and death groups of patients with COVID-19. ACE2 common SNPs in the population might modulate severity of COVID-19 infection independently of other known markers like gender, age and comorbidities.

Prediction of ventricular arrhythmia in phospholamban p.Arg14del mutation carriers-reaching the frontiers of individual risk prediction.

AIMS: This study aims to improve risk stratification for primary prevention implantable cardioverter defibrillator (ICD) implantation by developing a new mutation-specific prediction model for malignant ventricular arrhythmia (VA) in phospholamban (PLN) p.Arg14del mutation carriers. The proposed model is compared to an existing PLN risk model. METHODS AND RESULTS: Data were collected from PLN p.Arg14del mutation carriers with no history of malignant VA at baseline, identified between 2009 and 2020. Malignant VA was defined as sustained VA, appropriate ICD intervention, or (aborted) sudden cardiac death. A prediction model was developed using Cox regression. The study cohort consisted of 679 PLN p.Arg14del mutation carriers, with a minority of index patients (17%) and male sex (43%), and a median age of 42 years [interquartile range (IQR) 27-55]. During a median follow-up of 4.3 years (IQR 1.7-7.4), 72 (10.6%) carriers experienced malignant VA. Significant predictors were left ventricular ejection fraction, premature ventricular contraction count/24 h, amount of negative T waves, and presence of low-voltage electrocardiogram. The multivariable model had an excellent discriminative ability {C-statistic 0.83 [95% confidence interval (CI) 0.78-0.88]}. Applying the existing PLN risk model to the complete cohort yielded a C-statistic of 0.68 (95% CI 0.61-0.75). CONCLUSION: This new mutation-specific prediction model for individual VA risk in PLN p.Arg14del mutation carriers is superior to the existing PLN risk model, suggesting that risk prediction using mutation-specific phenotypic features can improve accuracy compared to a more generic approach.

Computer versus cardiologist: Is a machine learning algorithm able to outperform an expert in diagnosing a phospholamban p.Arg14del mutation on the electrocardiogram?

BACKGROUND: Phospholamban (PLN) p.Arg14del mutation carriers are known to develop dilated and/or arrhythmogenic cardiomyopathy, and typical electrocardiographic (ECG) features have been identified for diagnosis. Machine learning is a powerful tool used in ECG analysis and has shown to outperform cardiologists. OBJECTIVES: We aimed to develop machine learning and deep learning models to diagnose PLN p.Arg14del cardiomyopathy using ECGs and evaluate their accuracy compared to an expert cardiologist. METHODS: We included 155 adult PLN mutation carriers and 155 age- and sex-matched control subjects. Twenty-one PLN mutation carriers (13.4%) were classified as symptomatic (symptoms of heart failure or malignant ventricular arrhythmias). The data set was split into training and testing sets using 4-fold cross-validation. Multiple models were developed to discriminate between PLN mutation carriers and control subjects. For comparison, expert cardiologists classified the same data set. The best performing models were validated using an external PLN p.Arg14del mutation carrier data set from Murcia, Spain (n = 50). We applied occlusion maps to visualize the most contributing ECG regions. RESULTS: In terms of specificity, expert cardiologists (0.99) outperformed all models (range 0.53-0.81). In terms of accuracy and sensitivity, experts (0.28 and 0.64) were outperformed by all models (sensitivity range 0.65-0.81). T-wave morphology was most important for classification of PLN p.Arg14del carriers. External validation showed comparable results, with the best model outperforming experts. CONCLUSION: This study shows that machine learning can outperform experienced cardiologists in the diagnosis of PLN p.Arg14del cardiomyopathy and suggests that the shape of the T wave is of added importance to this diagnosis.

Comprehensive clinical evaluation of a large Spanish family with Anderson-Fabry disease, novel GLA mutation and severe cardiac phenotype.

BACKGROUND AND OBJECTIVE: Fabry disease is an X-linked multisystemic lysosomal-storage condition. We describe a large family with a novel GLA mutation: p.M187R/g7219 T>G. PATIENTS AND METHODS: Anamnesis/physical-exam, blood/urine analysis, α-Gal-A activity and/or genetic study of at-risk individuals and multidisciplinary evaluation in confirmed cases. RESULTS: 4 males and 13 heterozygous-females displayed the mutation. Cardiac/renal/neurological disease was diagnosed at a mean age of 41/29/39 years in males and 51/56/46 years in females. Onset mean age was 20 years versus 42 years. 9/15 had cardiomyopathy. Delta wave suggestive of accessory pathway was identified in 1 male and 2 females. 1 female had cardiac arrest (ventricular fibrillation, 61 years). 2 females and 1 male died suddenly (63, 64 and 57 years). Cardiac-subscore of Mainz Severity-Score-Index was severe for males and females over 40 years. 4/15(26%) developed early renal disease. 2 males needed dialysis. 1 male died at 69 years in spite of kidney-heart transplant. CONCLUSION: We describe the largest genetically confirmed Spanish family using multidisciplinary evaluation and MSSI calculation. The novel mutation p.M187R/g7219 T>G is associated with a particularly malignant cardiac phenotype in males and females over 40 years. Severity was higher than that of the largest Spanish FOS-cohort. Short-PR with delta is being reported for the first time.