Vascular Ehlers-Danlos Syndrome: A Comprehensive Natural History Study in a Dutch National Cohort of 142 Patients.

BACKGROUND: Vascular Ehlers-Danlos syndrome (vEDS) is a rare connective tissue disorder with a high risk for arterial, bowel, and uterine rupture, caused by heterozygous pathogenic variants in COL3A1. The aim of this cohort study is to provide further insights into the natural history of vEDS and describe genotype-phenotype correlations in a Dutch multicenter cohort to optimize patient care and increase awareness of the disease. METHODS: Individuals with vEDS throughout the Netherlands were included. The phenotype was charted by retrospective analysis of molecular and clinical data, combined with a one-time physical examination. RESULTS: A total of 142 individuals (50% female) participated the study, including 46 index patients (32%). The overall median age at genetic diagnosis was 41.0 years. More than half of the index patients (54.3%) and relatives (53.1%) had a physical appearance highly suggestive of vEDS. In these individuals, major events were not more frequent (P=0.90), but occurred at a younger age (P=0.01). A major event occurred more often and at a younger age in men compared with women (P<0.001 and P=0.004, respectively). Aortic aneurysms (P=0.003) and pneumothoraces (P=0.029) were more frequent in men. Aortic dissection was more frequent in individuals with a COL3A1 variant in the first quarter of the collagen helical domain (P=0.03). CONCLUSIONS: Male sex, type and location of the COL3A1 variant, and physical appearance highly suggestive of vEDS are risk factors for the occurrence and/or early age of onset of major events. This national multicenter cohort study of Dutch individuals with vEDS provides a valuable basis for improving guidelines for the diagnosing, follow-up, and treatment of individuals with vEDS.

Penetrance and Prognosis of MYH7 Variant-Associated Cardiomyopathies: Results From a Dutch Multicenter Cohort Study.

BACKGROUND: MYH7 variants cause hypertrophic cardiomyopathy (HCM), noncompaction cardiomyopathy (NCCM), and dilated cardiomyopathy (DCM). Screening of relatives of patients with genetic cardiomyopathy is recommended from 10 to 12 years of age onward, irrespective of the affected gene. OBJECTIVES: This study sought to study the penetrance and prognosis of MYH7 variant-associated cardiomyopathies. METHODS: In this multicenter cohort study, penetrance and major cardiomyopathy-related events (MCEs) were assessed in carriers of (likely) pathogenic MYH7 variants by using Kaplan-Meier curves and log-rank tests. Prognostic factors were evaluated using Cox regression with time-dependent coefficients. RESULTS: In total, 581 subjects (30.1% index patients, 48.4% male, median age 37.0 years [IQR: 19.5-50.2 years]) were included. HCM was diagnosed in 226 subjects, NCCM in 70, and DCM in 55. Early penetrance and MCEs (age <12 years) were common among NCCM-associated variant carriers (21.2% and 12.0%, respectively) and DCM-associated variant carriers (15.3% and 10.0%, respectively), compared with HCM-associated variant carriers (2.9% and 2.1%, respectively). Penetrance was significantly increased in carriers of converter region variants (adjusted HR: 1.87; 95% CI: 1.15-3.04; P = 0.012) and at age ≤1 year in NCCM-associated or DCM-associated variant carriers (adjusted HR: 21.17; 95% CI: 4.81-93.20; P < 0.001) and subjects with a family history of early MCEs (adjusted HR: 2.45; 95% CI: 1.09-5.50; P = 0.030). The risk of MCE was increased in subjects with a family history of early MCEs (adjusted HR: 1.82; 95% CI: 1.15-2.87; P = 0.010) and at age ≤5 years in NCCM-associated or DCM-associated variant carriers (adjusted HR: 38.82; 95% CI: 5.16-291.88; P < 0.001). CONCLUSIONS: MYH7 variants can cause cardiomyopathies and MCEs at a young age. Screening at younger ages may be warranted, particularly in carriers of NCCM- or DCM-associated variants and/or with a family history of MCEs at <12 years.

The genetic basis of apparently idiopathic ventricular fibrillation: a retrospective overview.

AIMS: During the diagnostic work-up of patients with idiopathic ventricular fibrillation (VF), next-generation sequencing panels can be considered to identify genotypes associated with arrhythmias. However, consensus for gene panel testing is still lacking, and variants of uncertain significance (VUS) are often identified. The aim of this study was to evaluate genetic testing and its results in idiopathic VF patients. METHODS AND RESULTS: We investigated 419 patients with available medical records from the Dutch Idiopathic VF Registry. Genetic testing was performed in 379 (91%) patients [median age at event 39 years (27-51), 60% male]. Single-gene testing was performed in 87 patients (23%) and was initiated more often in patients with idiopathic VF before 2010. Panel testing was performed in 292 patients (77%). The majority of causal (likely) pathogenic variants (LP/P, n = 56, 15%) entailed the DPP6 risk haplotype (n = 39, 70%). Moreover, 10 LP/P variants were found in cardiomyopathy genes (FLNC, MYL2, MYH7, PLN (two), TTN (four), RBM20), and 7 LP/P variants were identified in genes associated with cardiac arrhythmias (KCNQ1, SCN5A (2), RYR2 (four)). For eight patients (2%), identification of an LP/P variant resulted in a change of diagnosis. In 113 patients (30%), a VUS was identified. Broad panel testing resulted in a higher incidence of VUS in comparison to single-gene testing (38% vs. 3%, P < 0.001). CONCLUSION: Almost all patients from the registry underwent, albeit not broad, genetic testing. The genetic yield of causal LP/P variants in idiopathic VF patients is 5%, increasing to 15% when including DPP6. In specific cases, the LP/P variant is the underlying diagnosis. A gene panel specifically for idiopathic VF patients is proposed.

Phenotypic variability of filamin C-related cardiomyopathy: Insights from a novel Dutch founder variant.

BACKGROUND: Dilated cardiomyopathy (DCM) can be caused by truncating variants in the filamin C gene (FLNC). A new pathogenic FLNC variant, c.6864_6867dup, p.(Val2290Argfs∗23), was recently identified in Dutch patients with DCM. OBJECTIVES: The report aimed to evaluate the phenotype of FLNC variant carriers and to determine whether this variant is a founder variant. METHODS: Clinical and genetic data were retrospectively collected from variant carriers. Cardiovascular magnetic resonance studies were reassessed. Haplotypes were reconstructed to determine a founder effect. The geographical distribution and age of the variant were determined. RESULTS: Thirty-three individuals (of whom 23 [70%] were female) from 9 families were identified. Sudden cardiac death was the first presentation in a carrier at the age of 28 years. The median age at diagnosis was 41 years (range 19-67 years). The phenotype was heterogeneous. DCM with left ventricular dilation and reduced ejection fraction (<45%) was present in 11 (33%) individuals, 3 (9%) of whom underwent heart transplantation. Cardiovascular magnetic resonance showed late gadolinium enhancement in 13 (65%) of the assessed individuals, primarily in a ringlike distribution. Nonsustained ventricular arrhythmias were detected in 6 (18%), and 5 (15%) individuals received an implantable cardioverter-defibrillator. A shared haplotype spanning 2.1 Mb was found in all haplotyped individuals. The variant originated between 275 and 650 years ago. CONCLUSION: The pathogenic FLNC variant c.6864_6867dup, p.(Val2290Argfs∗23) is a founder variant originating from the south of the Netherlands. Carriers are susceptible to developing heart failure and ventricular arrhythmias. The cardiac phenotype is characterized by ringlike late gadolinium enhancement, even in individuals without significantly reduced left ventricular function.

Individualized Family Screening for Arrhythmogenic Right Ventricular Cardiomyopathy.

BACKGROUND: Clinical guidelines recommend regular screening for arrhythmogenic right ventricular cardiomyopathy (ARVC) to monitor at-risk relatives, resulting in a significant burden on clinical resources. Prioritizing relatives on their probability of developing definite ARVC may provide more efficient patient care. OBJECTIVES: The aim of this study was to determine the predictors and probability of ARVC development over time among at-risk relatives. METHODS: A total of 136 relatives (46% men, median age 25.5 years [IQR: 15.8-44.4 years]) from the Netherlands Arrhythmogenic Cardiomyopathy Registry without definite ARVC by 2010 task force criteria were included. Phenotype was ascertained using electrocardiography, Holter monitoring, and cardiac imaging. Subjects were divided into groups with "possible ARVC" (only genetic or familial predisposition) and "borderline ARVC" (1 minor task force criterion plus genetic or familial predisposition). Cox regression was performed to determine predictors and multistate modeling to assess the probability of ARVC development. Results were replicated in an unrelated Italian cohort (57% men, median age 37.0 years [IQR: 25.4-50.4 years]). RESULTS: At baseline, 93 subjects (68%) had possible ARVC, and 43 (32%) had borderline ARVC. Follow-up was available for 123 relatives (90%). After 8.1 years (IQR: 4.2-11.4 years), 41 (33%) had developed definite ARVC. Independent of baseline phenotype, symptomatic subjects (P = 0.014) and those 20 to 30 years of age (P = 0.002) had a higher hazard of developing definite ARVC. Furthermore, patients with borderline ARVC had a higher probability of developing definite ARVC compared with those with possible ARVC (1-year probability 13% vs 0.6%, 3-year probability 35% vs 5%; P < 0.01). External replication showed comparable results (P > 0.05). CONCLUSIONS: Symptomatic relatives, those 20 to 30 years of age, and those with borderline ARVC have a higher probability of developing definite ARVC. These patients may benefit from more frequent follow-up, while others may be monitored less often.

Untargeted Metabolomics Identifies Potential Hypertrophic Cardiomyopathy Biomarkers in Carriers of MYBPC3 Founder Variants.

Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease, commonly caused by pathogenic MYBPC3 variants, and a significant cause of sudden cardiac death. Severity is highly variable, with incomplete penetrance among genotype-positive family members. Previous studies demonstrated metabolic changes in HCM. We aimed to identify metabolite profiles associated with disease severity in carriers of MYBPC3 founder variants using direct-infusion high-resolution mass spectrometry in plasma of 30 carriers with a severe phenotype (maximum wall thickness ≥20 mm, septal reduction therapy, congestive heart failure, left ventricular ejection fraction <50%, or malignant ventricular arrhythmia) and 30 age- and sex-matched carriers with no or a mild phenotype. Of the top 25 mass spectrometry peaks selected by sparse partial least squares discriminant analysis, XGBoost gradient boosted trees, and Lasso logistic regression (42 total), 36 associated with severe HCM at a p < 0.05, 20 at p < 0.01, and 3 at p < 0.001. These peaks could be clustered to several metabolic pathways, including acylcarnitine, histidine, lysine, purine and steroid hormone metabolism, and proteolysis. In conclusion, this exploratory case-control study identified metabolites associated with severe phenotypes in MYBPC3 founder variant carriers. Future studies should assess whether these biomarkers contribute to HCM pathogenesis and evaluate their contribution to risk stratification.

Prevalence and Disease Expression of Pathogenic and Likely Pathogenic Variants Associated With Inherited Cardiomyopathies in the General Population.

BACKGROUND: Pathogenic and likely pathogenic variants associated with arrhythmogenic right ventricular cardiomyopathy (ARVC), dilated cardiomyopathy (DCM), and hypertrophic cardiomyopathy (HCM) are recommended to be reported as secondary findings in genome sequencing studies. This provides opportunities for early diagnosis, but also fuels uncertainty in variant carriers (G+), since disease penetrance is incomplete. We assessed the prevalence and disease expression of G+ in the general population. METHODS: We identified pathogenic and likely pathogenic variants associated with ARVC, DCM and/or HCM in 200 643 UK Biobank individuals, who underwent whole exome sequencing. We calculated the prevalence of G+ and analyzed the frequency of cardiomyopathy/heart failure diagnosis. In undiagnosed individuals, we analyzed early signs of disease expression using available electrocardiography and cardiac magnetic resonance imaging data. RESULTS: We found a prevalence of 1:578, 1:251, and 1:149 for pathogenic and likely pathogenic variants associated with ARVC, DCM and HCM respectively. Compared with controls, cardiovascular mortality was higher in DCM G+ (odds ratio 1.67 [95% CI 1.04; 2.59], P=0.030), but similar in ARVC and HCM G+ (P≥0.100). Cardiomyopathy or heart failure diagnosis were more frequent in DCM G+ (odds ratio 3.66 [95% CI 2.24; 5.81], P=4.9×10-7) and HCM G+ (odds ratio 3.03 [95% CI 1.98; 4.56], P=5.8×10-7), but comparable in ARVC G+ (P=0.172). In contrast, ARVC G+ had more ventricular arrhythmias (P=3.3×10-4). In undiagnosed individuals, left ventricular ejection fraction was reduced in DCM G+ (P=0.009). CONCLUSIONS: In the general population, pathogenic and likely pathogenic variants associated with ARVC, DCM, or HCM are not uncommon. Although G+ have increased mortality and morbidity, disease penetrance in these carriers from the general population remains low (1.2-3.1%). Follow-up decisions in case of incidental findings should not be based solely on a variant, but on multiple factors, including family history and disease expression.

Genetic Evaluation of A Nation-Wide Dutch Pediatric DCM Cohort: The Use of Genetic Testing in Risk Stratification.

BACKGROUND: This study aimed to describe the current practice and results of genetic evaluation in Dutch children with dilated cardiomyopathy and to evaluate genotype-phenotype correlations that may guide prognosis. METHODS: We performed a multicenter observational study in children diagnosed with dilated cardiomyopathy, from 2010 to 2017. RESULTS: One hundred forty-four children were included. Initial diagnostic categories were idiopathic dilated cardiomyopathy in 67 children (47%), myocarditis in 23 (16%), neuromuscular in 7 (5%), familial in 18 (13%), inborn error of metabolism in 4 (3%), malformation syndrome in 2 (1%), and "other" in 23 (16%). Median follow-up time was 2.1 years [IQR 1.0-4.3]. Hundred-seven patients (74%) underwent genetic testing. We found a likely pathogenic or pathogenic variant in 38 children (36%), most often in MYH7 (n = 8). In 1 patient initially diagnosed with myocarditis, a pathogenic LMNA variant was found. During the study, 39 patients (27%) reached study endpoint (SE: all-cause death or heart transplantation). Patients with a likely pathogenic or pathogenic variant were more likely to reach SE compared with those without (hazard ratio 2.8; 95% CI 1.3-5.8, P = 0.007), while transplant-free survival was significantly lower (P = 0.006). Clinical characteristics at diagnosis did not differ between the 2 groups. CONCLUSIONS: Genetic testing is a valuable tool for predicting prognosis in children with dilated cardiomyopathy, with carriers of a likely pathogenic or pathogenic variant having a worse prognosis overall. Genetic testing should be incorporated in clinical work-up of all children with dilated cardiomyopathy regardless of presumed disease pathogenesis.

Evaluation of the cardiac amyloidosis clinical pathway implementation: a real-world experience.

Aims: The aim of this study is to evaluate the implementation of the cardiac amyloidosis (CA) clinical pathway on awareness among referring cardiologists, diagnostic delay, and severity of CA at diagnosis. Methods and results: Patients with CA were retrospectively included in this study and divided into two periods: pre-implementation of the CA clinical pathway (2007-18; T1) and post-implementation (2019-20; T2). Patients' and disease characteristics were extracted from electronic health records and compared. In total, 113 patients (mean age 67.8 ± 8.5 years, 26% female) were diagnosed with CA [T1 (2007-18): 56; T2 (2019-20): 57]. The number of CA diagnoses per year has increased over time. Reasons for referral changed over time, with increased awareness of right ventricular hypertrophy (9% in T1 vs. 36% in T2) and unexplained heart failure with preserved ejection fraction (22% in T1 vs. 38% in T2). Comparing T1 with T2, the diagnostic delay also improved (14 vs. 8 months, P < 0.01), New York Heart Association Class III (45% vs. 23%, P = 0.03), and advanced CA stage (MAYO/Gillmore Stage III/IV; 61% vs. 33%, P ≤ 0.01) at time of diagnosis decreased. Conclusion: After implementation of the CA clinical pathway, the awareness among referring cardiologists improved, diagnostic delay was decreased, and patients had less severe CA at diagnosis. Further studies are warranted to assess the prognostic impact of CA clinical pathway implementation.

Surveillance and monitoring in vascular Ehlers-Danlos syndrome in European Reference Network For Rare Vascular Diseases (VASCERN).

Vascular Ehlers-Danlos syndrome (vEDS) is a rare genetic disorder clinically characterized by vascular, intestinal and uterine fragility and caused by heterozygous pathogenic variants in the COL3A1 gene. Management of patients with vEDS is difficult due to the unpredictability of the events and clear recommendations on the care of adults and children with vEDS are lacking. Therefore, we aimed to collect data on the current strategy of surveillance and monitoring of vEDS patients by expert centers in continental Europe and Great Britain, as a first step towards a consensus statement. A survey on the clinical management of vEDS was sent to all members of the Medium Sized Artery (MSA) Working Group of the European Reference Network for Rare Vascular Diseases (VASCERN) and other expert centers. All experts endorse the importance of monitoring patients with vEDS. Despite the absence of evidence based guidelines monitoring is considered in almost all countries, but screening intervals and modalities used for monitoring may differ among centers. There is a need for more prospective multicenter studies to define proper guidelines.

Blood-based biomarkers for the prediction of hypertrophic cardiomyopathy prognosis: a systematic review and meta-analysis.

AIMS: Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease. HCM is an important cause of sudden cardiac death and may also lead to outflow tract obstruction and heart failure. Disease severity is highly variable and risk stratification remains limited. Therefore, we aimed to review current knowledge of prognostic blood-based biomarkers in HCM. METHODS AND RESULTS: A systematic literature search was performed on PubMed, Embase, and the Cochrane library to identify studies assessing plasma or serum biomarkers for outcomes involving malignant ventricular arrhythmia, outflow tract obstruction, and heart failure. Risk of bias was assessed using the QUIPS tool. Meta-analyses were performed using the random effects method. A total of 26 unique cohort studies assessing 42 biomarkers were identified. Overall risk of bias was moderate. Thirty-two biomarkers were significantly associated to an HCM outcome in at least one study (nine biomarkers in at least two studies). In pooled analyses, cardiovascular mortality was predicted by N-terminal prohormone of brain natriuretic peptide (hazard ratio [HR] 5.38 per log[pg/mL], 95% confidence interval [CI] 2.07-14.03, P < 0.001, I2  = 0%) and high-sensitivity C-reactive protein (HR 1.30 per µg/mL, 95% CI 1.00-1.68, P = 0.05, I2  = 78%), all-cause mortality by low-density lipoprotein cholesterol (HR 0.63 per µmol/mL, 95% CI 0.49-0.80, P < 0.001, I2  = 0%), and a combined congestive heart failure, malignant ventricular arrhythmia, and stroke outcome by high-sensitivity cardiac troponin T (pooled HR 4.19 for ≥0.014 ng/mL, 95% CI 2.22-7.88, P < 0.001, I2  = 0%). Quality of evidence was low-moderate. CONCLUSIONS: Several blood-based biomarkers were identified as predictors of HCM outcomes. Additional studies are required to validate their prognostic utility within current risk stratification models.

Automatic Identification of Patients With Unexplained Left Ventricular Hypertrophy in Electronic Health Record Data to Improve Targeted Treatment and Family Screening.

Background: Unexplained Left Ventricular Hypertrophy (ULVH) may be caused by genetic and non-genetic etiologies (e.g., sarcomere variants, cardiac amyloid, or Anderson-Fabry's disease). Identification of ULVH patients allows for early targeted treatment and family screening. Aim: To automatically identify patients with ULVH in electronic health record (EHR) data using two computer methods: text-mining and machine learning (ML). Methods: Adults with echocardiographic measurement of interventricular septum thickness (IVSt) were included. A text-mining algorithm was developed to identify patients with ULVH. An ML algorithm including a variety of clinical, ECG and echocardiographic data was trained and tested in an 80/20% split. Clinical diagnosis of ULVH was considered the gold standard. Misclassifications were reviewed by an experienced cardiologist. Sensitivity, specificity, positive, and negative likelihood ratios (LHR+ and LHR-) of both text-mining and ML were reported. Results: In total, 26,954 subjects (median age 61 years, 55% male) were included. ULVH was diagnosed in 204/26,954 (0.8%) patients, of which 56 had amyloidosis and two Anderson-Fabry Disease. Text-mining flagged 8,192 patients with possible ULVH, of whom 159 were true positives (sensitivity, specificity, LHR+, and LHR- of 0.78, 0.67, 2.36, and 0.33). Machine learning resulted in a sensitivity, specificity, LHR+, and LHR- of 0.32, 0.99, 32, and 0.68, respectively. Pivotal variables included IVSt, systolic blood pressure, and age. Conclusions: Automatic identification of patients with ULVH is possible with both Text-mining and ML. Text-mining may be a comprehensive scaffold but can be less specific than machine learning. Deployment of either method depends on existing infrastructures and clinical applications.

A tailored approach to informing relatives at risk of inherited cardiac conditions: results of a randomised controlled trial.

If undetected, inherited cardiac conditions can lead to sudden cardiac death, while treatment options are available. Predictive DNA testing is therefore advised for at-risk relatives, and probands are currently asked to inform relatives about this. However, fewer than half of relatives attend genetic counselling. In this trial, we compared a tailored approach to informing relatives, in which probands were asked whether they preferred relatives to be informed by themselves or by the genetic counsellor, with current practice. Our primary outcome was uptake of genetic counselling in relatives in the first year after test result disclosure. Secondary outcomes were evaluation of the approach and impact on psychological/family functioning measured 3 (T1) and 9 (T2) months post-disclosure via telephone interviews and questionnaires. We included 96 probands; 482 relatives were eligible for counselling and genetic testing. We observed no significant difference in uptake of genetic counselling between the control (38%) and the intervention (37%) group (p = 0.973). Nor were there significant differences between groups in impact on family/psychological functioning. Significantly more probands in the tailored group were satisfied (p = 0.001) and felt supported (p = 0.003) by the approach, although they also felt somewhat coerced to inform relatives (p < 0.001) and perceived room for improvement (p < 0.001). To conclude, we observed no differences in uptake and impact on family/psychological functioning between the current and tailored approach, but probands in the tailored group more often felt satisfied. Further research on barriers to relatives attending genetic counselling and on how to optimize the provision of a tailored approach is needed.

Distinct Metabolomic Signatures in Preclinical and Obstructive Hypertrophic Cardiomyopathy.

Hypertrophic Cardiomyopathy (HCM) is a common inherited heart disease with poor risk prediction due to incomplete penetrance and a lack of clear genotype-phenotype correlations. Advanced imaging techniques have shown altered myocardial energetics already in preclinical gene variant carriers. To determine whether disturbed myocardial energetics with the potential to serve as biomarkers are also reflected in the serum metabolome, we analyzed the serum metabolome of asymptomatic carriers in comparison to healthy controls and obstructive HCM patients (HOCM). We performed non-quantitative direct-infusion high-resolution mass spectrometry-based untargeted metabolomics on serum from fasted asymptomatic gene variant carriers, symptomatic HOCM patients and healthy controls (n = 31, 14 and 9, respectively). Biomarker panels that discriminated the groups were identified by performing multivariate modeling with gradient-boosting classifiers. For all three group-wise comparisons we identified a panel of 30 serum metabolites that best discriminated the groups. These metabolite panels performed equally well as advanced cardiac imaging modalities in distinguishing the groups. Seven metabolites were found to be predictive in two different comparisons and may play an important role in defining the disease stage. This study reveals unique metabolic signatures in serum of preclinical carriers and HOCM patients that may potentially be used for HCM risk stratification and precision therapeutics.

A novel risk model for predicting potentially life-threatening arrhythmias in non-ischemic dilated cardiomyopathy (DCM-SVA risk).

BACKGROUND: Non-ischemic dilated cardiomyopathy (DCM) can be complicated by sustained ventricular arrhythmias (SVA) and sudden cardiac death (SCD). By now, left-ventricular ejection fraction (LV-EF) is the main guideline criterion for primary prophylactic ICD implantation, potentially leading either to overtreatment or failed detection of patients at risk without severely impaired LV-EF. The aim of the European multi-center study DETECTIN-HF was to establish a clinical risk calculator for individualized risk stratification of DCM patients. METHODS: 1393 patients (68% male, mean age 50.7 ± 14.3y) from four European countries were included. The outcome was occurrence of first potentially life-threatening ventricular arrhythmia. The model was developed using Cox proportional hazards, and internally validated using cross validation. The model included seven independent and easily accessible clinical parameters sex, history of non-sustained ventricular tachycardia, history of syncope, family history of cardiomyopathy, QRS duration, LV-EF, and history of atrial fibrillation. The model was also expanded to account for presence of LGE as the eight8h parameter for cases with available cMRI and scar information. RESULTS: During a mean follow-up period of 57.0 months, 193 (13.8%) patients experienced an arrhythmic event. The calibration slope of the developed model was 00.97 (95% CI 0.90-1.03) and the C-index was 0.72 (95% CI 0.71-0.73). Compared to current guidelines, the model was able to protect the same number of patients (5-year risk ≥8.5%) with 15% fewer ICD implantations. CONCLUSIONS: This DCM-SVA risk model could improve decision making in primary prevention of SCD in non-ischemic DCM using easily accessible clinical information and will likely reduce overtreatment.

Early Lethal Noncompaction Cardiomyopathy in Siblings With Compound Heterozygous RYR2 Variant.

Two siblings presented with early lethal noncompaction cardiomyopathy (NCCM). Both carry compound heterozygous variants in the ryanodine receptor gene (RYR2). Evolving animal and human data have begun to implicate a role for RYR2 dysfunction in the development of NCCM. The identified RYR2 variants are therefore likely causative for this early lethal NCCM phenotype. Further research is needed to understand the role of RYR2 in the heart compaction process.

Genotype-phenotype correlation in pseudoxanthoma elasticum.

BACKGROUND AND AIMS: Pseudoxanthoma elasticum (PXE) is caused by variants in the ABCC6 gene. It results in calcification in the skin, peripheral arteries and the eyes, but has considerable phenotypic variability. We investigated the association between the ABCC6 genotype and calcification and clinical phenotypes in these different organs. METHODS: ABCC6 sequencing was performed in 289 PXE patients. Genotypes were grouped as two truncating, mixed, or two non-truncating variants. Arterial calcification mass was quantified on whole body, low dose CT scans; and peripheral arterial disease was measured with the ankle brachial index after treadmill test. The presence of pseudoxanthoma in the skin was systematically scored. Ophthalmological phenotypes were the length of angioid streaks as a measure of Bruchs membrane calcification, the presence of choroidal neovascularizations, severity of macular atrophy and visual acuity. Regression models were built to test the age and sex adjusted genotype-phenotype association. RESULTS: 158 patients (median age 51 years) had two truncating variants, 96 (median age 54 years) a mixed genotype, 18 (median age 47 years) had two non-truncating variants. The mixed genotype was associated with lower peripheral (ß: 0.39, 95%CI:-0.62;-0.17) and total (ß: 0.28, 95%CI:-0.47;-0.10) arterial calcification mass scores, and lower prevalence of choroidal neovascularizations (OR: 0.41 95%CI:0.20; 0.83) compared to two truncating variants. No association with pseudoxanthomas was found. CONCLUSIONS: PXE patients with a mixed genotype have less severe arterial and ophthalmological phenotypes than patients with two truncating variants in the ABCC6 gene. Research into environmental and genetic modifiers might provide further insights into the unexplained phenotypic variability.

Diagnosis and Risk Prediction of Dilated Cardiomyopathy in the Era of Big Data and Genomics.

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and life-threatening ventricular arrhythmias (LTVA). Work-up and risk stratification of DCM is clinically challenging, as there is great heterogeneity in phenotype and genotype. Throughout the last decade, improved genetic testing of patients has identified genotype-phenotype associations and enhanced evaluation of at-risk relatives leading to better patient prognosis. The field is now ripe to explore opportunities to improve personalised risk assessments. Multivariable risk models presented as "risk calculators" can incorporate a multitude of clinical variables and predict outcome (such as heart failure hospitalisations or LTVA). In addition, genetic risk scores derived from genome/exome-wide association studies can estimate an individual's lifetime genetic risk of developing DCM. The use of clinically granular investigations, such as late gadolinium enhancement on cardiac magnetic resonance imaging, is warranted in order to increase predictive performance. To this end, constructing big data infrastructures improves accessibility of data by using electronic health records, existing research databases, and disease registries. By applying methods such as machine and deep learning, we can model complex interactions, identify new phenotype clusters, and perform prognostic modelling. This review aims to provide an overview of the evolution of DCM definitions as well as its clinical work-up and considerations in the era of genomics. In addition, we present exciting examples in the field of big data infrastructures, personalised prognostic assessment, and artificial intelligence.

Automatic multilabel detection of ICD10 codes in Dutch cardiology discharge letters using neural networks.

Standard reference terminology of diagnoses and risk factors is crucial for billing, epidemiological studies, and inter/intranational comparisons of diseases. The International Classification of Disease (ICD) is a standardized and widely used method, but the manual classification is an enormously time-consuming endeavor. Natural language processing together with machine learning allows automated structuring of diagnoses using ICD-10 codes, but the limited performance of machine learning models, the necessity of gigantic datasets, and poor reliability of terminal parts of these codes restricted clinical usability. We aimed to create a high performing pipeline for automated classification of reliable ICD-10 codes in the free medical text in cardiology. We focussed on frequently used and well-defined three- and four-digit ICD-10 codes that still have enough granularity to be clinically relevant such as atrial fibrillation (I48), acute myocardial infarction (I21), or dilated cardiomyopathy (I42.0). Our pipeline uses a deep neural network known as a Bidirectional Gated Recurrent Unit Neural Network and was trained and tested with 5548 discharge letters and validated in 5089 discharge and procedural letters. As in clinical practice discharge letters may be labeled with more than one code, we assessed the single- and multilabel performance of main diagnoses and cardiovascular risk factors. We investigated using both the entire body of text and only the summary paragraph, supplemented by age and sex. Given the privacy-sensitive information included in discharge letters, we added a de-identification step. The performance was high, with F1 scores of 0.76-0.99 for three-character and 0.87-0.98 for four-character ICD-10 codes, and was best when using complete discharge letters. Adding variables age/sex did not affect results. For model interpretability, word coefficients were provided and qualitative assessment of classification was manually performed. Because of its high performance, this pipeline can be useful to decrease the administrative burden of classifying discharge diagnoses and may serve as a scaffold for reimbursement and research applications.

Mechanisms of calcification in Fahr disease and exposure of potential therapeutic targets.

PURPOSE OF REVIEW: There is growing interest in disorders involved in ectopic mineralization. Fahr disease or idiopathic basal ganglia calcification can serve as a model for ectopic mineralization in the basal ganglia, which is fairly common in the general population. In this review, we will focus on causative gene mutations and corresponding pathophysiologic pathways in Fahr disease. RECENT FINDINGS: Patients with Fahr disease have a variability of symptoms, such as movement disorders, psychiatric signs, and cognitive impairment, but can also be asymptomatic. Fahr disease is mostly autosomal dominant inherited, and there are mutations found in 4 causative genes. Mutations in SLC20A2 and XPR1 lead to a disrupted phosphate metabolism involving brain-specific inorganic phosphate transporters. Mutations in PDGFB and PDGFRB are associated with disrupted blood-brain barrier integrity and dysfunctional pericyte maintenance. In addition, the MYORG gene has recently been discovered to be involved in the autosomal recessive inheritance of Fahr. SUMMARY: Knowledge about the mutations and corresponding pathways may expose therapeutic opportunities for patients with Fahr disease and vascular calcifications in the brain in general.