Characterization of the genetic architecture of dilated cardiomyopathy using families and cohorts

Cardiomyopathies are the leading cause of heart transplantation in the developed world, and dilated cardiomyopathy accounts for an important proportion of all heart failure cases in large clinical trials. In spite of a strong genetic basis for dilated cardiomyopathy being demonstrated widely in the past two decades, 60% of familial cases remain unexplained. Dilated cardiomyopathy is characterized by marked genetic heterogeneity, with more than 60 individual genes reported to cause the disease, yet only one (TTN) explaining more than 10% of cases. Here, high-throughput sequencing data, advanced imaging techniques and bioinformatics analyses were used to dissect the genetic architecture of dilated cardiomyopathy, by measuring the contribution of single genes and multi-genic variation on disease risk and severity, and performing gene and variant discovery in affected families. Burden testing (using bespoke software developed in the R programming language for this study) and regression modelling were used to examine the genetic determinants of disease by comparing a cohort of disease cases (n=332) to ethnically matched, phenotypically characterised healthy controls (n=319). This produced a measure of the contribution of each gene to dilated cardiomyopathy, taking into account the background variation rate in the general population. Analyses of multi-genic interactions were also performed, and having detected the signature of additive effects of variation in multiple genes on both disease likelihood and severity, further analyses were performed to identify specific gene-gene interactions in causing dilated cardiomyopathy. Subsequently, variant prioritisation strategies were developed to identify, from whole-exome sequencing data, possible genetic causes of an unexplained and very severe form of early-onset dilated cardiomyopathy segregating in a family. This led to the identification of new candidate genes, which might contribute towards a genetic diagnosis in the analysed family and to new insights into the pathogenesis of dilated cardiomyopathy. Preparatory work in developing variant prioritisation pipelines from whole-exome sequencing data had been performed earlier, on families affected with various inherited arrhythmia syndromes.Open Acces

The use of functional tests and planned coronary angiography after percutaneous coronary revascularization in clinical practice. Results from the AFTER multicenter study

Background: The follow-up strategies after percutaneous coronary intervention (PCI) have relevant clinical and economic implications. The purpose of this prospective observational multicenter study was to evaluate the effect of clinical, procedural and organizational variables on the execution of functional testing (FT) and planned coronary angiography (CA) after PCI, and to assess the impact of American College of Cardiology (ACC)/American Heart Association (AHA) guidelines on clinical practice. Methods: Four hundred twenty consecutive patients undergoing PCI were categorized as class I, IIB and III indications for follow-up FT according to ACC/AHA guidelines recommendations. Furthermore, all patients were grouped according to the presence or absence of FT and/or planned CA over 12 months after PCI. Multivariable analysis was used to assess the potential predictors of test execution. Results: During the 12-month follow-up at least one test was performed in 72% of patients with class I indication, 63% of patients with class IIB indication and 75% of patients with class III indication (p=ns). A total of 283 patients (67%) underwent testing. The use of tests was associated with younger age (R. R. 0.94, C. I. 0.91 +/- 0.97, p<0.001), a lower number of diseased vessels (R.R. 0.60, C.I. 0.43 +/- 0.84, p=0.003), follow-up by the center performing PCI (R. R. 2.64, C. I. 1.43 +/- 4.86, p=0.002), and the specific center at which PCI was performed. Most asymptomatic patients completed their testing prematurely with respect to the risk period for restenosis. Conclusions: The use of FT and planned CA after PCI is unrelated to patient's symptom status, and depends on patient's age and logistics. ACC/AHA guidelines have no influence in clinical practice, and test timing is not tailored to the risk period for restenosis. (C) 2008 Elsevier Ireland Ltd. All rights reserved

A Therapeutic and Diagnostic Multidisciplinary Pathway for Merkel Cell Carcinoma Patients

Merkel Cell Carcinoma (MCC) is a highly aggressive neuroendocrine neoplasm of the skin. Due to its rarity, the management of MCC is not standardized across centers. In this article, we present the experience of the Veneto region in the North-East of Italy, where a committee of skin cancer experts has proposed a clinical pathway for the diagnosis and treatment of MCC. Putting together the evidence available in the international literature, we outlined the best approach to the management of patients affected with this malignancy step- by- step for each possible clinical situation. Crucial in this pathway is the role of the multidisciplinary team to deal with the lack of robust information on each aspect of the management of this disease

Stereotactic body radiotherapy vs conventionally fractionated chemoradiation in locally advanced pancreatic cancer: A multicenter case‐control study (PAULA‐1)

The aim of this study was to compare two cohorts of LAPC patients treated with SBRT ± CHT vs CRT ± CHT in terms of local control (LC), distant metastases- free survival (DMFS), progression-free survival (PFS), overall survival (OS), and toxicity. Eighty patients were included. Patients in the two cohorts were matched ac- cording to: age ≤/&gt;65 years, tumor diameter (two cut-offs

A machine learning-based risk stratification model for ventricular tachycardia and heart failure in hypertrophic cardiomyopathy

Background: Machine learning (ML) and artificial intelligence are emerging as important components of precision medicine that enhance diagnosis and risk stratification. Risk stratification tools for hypertrophic cardiomyopathy (HCM) exist, but they are based on traditional statistical methods. The aim was to develop a novel machine learning risk stratification tool for the prediction of 5-year risk in HCM. The goal was to determine if its predictive accuracy is higher than the accuracy of the state-of-the-art tools. Method: Data from a total of 2302 patients were used. The data were comprised of demographic characteristics, genetic data, clinical investigations, medications, and disease-related events. Four classification models were applied to model the risk level, and their decisions were explained using the SHAP (SHapley Additive exPlanations) method. Unwanted cardiac events were defined as sustained ventricular tachycardia occurrence (VT), heart failure (HF), ICD activation, sudden cardiac death (SCD), cardiac death, and all-cause death. Results: The proposed machine learning approach outperformed the similar existing risk-stratification models for SCD, cardiac death, and all-cause death risk-stratification: it achieved higher AUC by 17%, 9%, and 1%, respectively. The boosted trees achieved the best performing AUC of 0.82. The resulting model most accurately predicts VT, HF, and ICD with AUCs of 0.90, 0.88, and 0.87, respectively. Conclusions: The proposed risk-stratification model demonstrates high accuracy in predicting events in patients with hypertrophic cardiomyopathy. The use of a machine-learning risk stratification model may improve patient management, clinical practice, and outcomes in general

Computational prediction of protein subdomain stability in MYBPC3 enables clinical risk stratification in hypertrophic cardiomyopathy and enhances variant interpretation

PURPOSE: Variants in MYBPC3 causing loss of function are the most common cause of hypertrophic cardiomyopathy (HCM). However, a substantial number of patients carry missense variants of uncertain significance (VUS) in MYBPC3. We hypothesize that a structural-based algorithm, STRUM, which estimates the effect of missense variants on protein folding, will identify a subgroup of HCM patients with a MYBPC3 VUS associated with increased clinical risk. METHODS: Among 7,963 patients in the multicenter Sarcomeric Human Cardiomyopathy Registry (SHaRe), 120 unique missense VUS in MYBPC3 were identified. Variants were evaluated for their effect on subdomain folding and a stratified time-to-event analysis for an overall composite endpoint (first occurrence of ventricular arrhythmia, heart failure, all-cause mortality, atrial fibrillation, and stroke) was performed for patients with HCM and a MYBPC3 missense VUS. RESULTS: We demonstrated that patients carrying a MYBPC3 VUS predicted to cause subdomain misfolding (STRUM+, ΔΔG ≤ −1.2 kcal/mol) exhibited a higher rate of adverse events compared with those with a STRUM- VUS (hazard ratio = 2.29, P = 0.0282). In silico saturation mutagenesis of MYBPC3 identified 4,943/23,427 (21%) missense variants that were predicted to cause subdomain misfolding. CONCLUSION: STRUM identifies patients with HCM and a MYBPC3 VUS who may be at higher clinical risk and provides supportive evidence for pathogenicity

Spatial and Functional Distribution of MYBPC3 Pathogenic Variants and Clinical Outcomes in Patients with Hypertrophic Cardiomyopathy

Background - Pathogenic variants in MYBPC3, encoding cardiac MyBP-C, are the most common cause of familial hypertrophic cardiomyopathy. A large number of unique MYBPC3 variants and relatively small genotyped HCM cohorts have precluded detailed genotype-phenotype correlations. Methods - Patients with HCM and MYBPC3 variants were identified from the Sarcomeric Human Cardiomyopathy Registry (SHaRe). Variant types and locations were analyzed, morphologic severity was assessed, and time-event analysis was performed (composite clinical outcome of sudden death, class III/IV heart failure, LVAD/transplant, atrial fibrillation). For selected missense variants falling in enriched domains, myofilament localization and degradation rates were measured in vitro. Results - Among 4,756 genotyped HCM patients in SHaRe, 1,316 patients were identified with adjudicated pathogenic truncating (N=234 unique variants, 1047 patients) or non-truncating (N=22 unique variants, 191 patients) variants in MYBPC3. Truncating variants were evenly dispersed throughout the gene, and hypertrophy severity and outcomes were not associated with variant location (grouped by 5' - 3' quartiles or by founder variant subgroup). Non-truncating pathogenic variants clustered in the C3, C6, and C10 domains (18 of 22, 82%, p<0.001 vs. gnomAD common variants) and were associated with similar hypertrophy severity and adverse event rates as observed with truncating variants. MyBP-C with variants in the C3, C6, and C10 domains was expressed in rat ventricular myocytes. C10 mutant MyBP-C failed to incorporate into myofilaments and degradation rates were accelerated by ~90%, while C3 and C6 mutant MyBP-C incorporated normally with degradation rate similar to wild-type. Conclusions - Truncating variants account for 91% of MYBPC3 pathogenic variants and cause similar clinical severity and outcomes regardless of location, consistent with locus-independent loss-of-function. Non-truncating MYBPC3 pathogenic variants are regionally clustered, and a subset also cause loss-of-function through failure of myofilament incorporation and rapid degradation. Cardiac morphology and clinical outcomes are similar in patients with truncating vs. non-truncating variants

Quantifying evidence toward pathogenicity for rare phenotypes: The case of succinate dehydrogenase genes, SDHB and SDHD.

PURPOSE: The weight of the evidence to attach to observation of a novel rare missense variant in SDHB or SDHD in individuals with the rare neuroendocrine tumors, pheochromocytomas and paragangliomas (PCC/PGL), is uncertain. METHODS: We compared the frequency of SDHB and SDHD very rare missense variants (VRMVs) in 6328 and 5847 cases of PCC/PGL, respectively, with that of population controls to generate a pan-gene VRMV likelihood ratio (LR). Via windowing analysis, we measured regional enrichments of VRMVs to calculate the domain-specific VRMV-LR (DS-VRMV-LR). We also calculated subphenotypic LRs for variant pathogenicity for various clinical, histologic, and molecular features. RESULTS: We estimated the pan-gene VRMV-LR to be 76.2 (54.8-105.9) for SDHB and 14.8 (8.7-25.0) for SDHD. Clustering analysis revealed an SDHB enriched region (ɑɑ 177-260, P = .001) for which the DS-VRMV-LR was 127.2 (64.9-249.4) and an SDHD enriched region (ɑɑ 70-114, P = .000003) for which the DS-VRMV-LR was 33.9 (14.8-77.8). Subphenotypic LRs exceeded 6 for invasive disease (SDHB), head-and-neck disease (SDHD), multiple tumors (SDHD), family history of PCC/PGL, loss of SDHB staining on immunohistochemistry, and succinate-to-fumarate ratio >97 (SDHB, SDHD). CONCLUSION: Using methodology generalizable to other gene-phenotype dyads, the LRs relating to rarity and phenotypic specificity for a single observation in PCC/PGL of a SDHB/SDHD VRMV can afford substantial evidence toward pathogenicity