Dabbagh, Ghaith Sharaf

Abstract Dilated cardiomyopathy (DCM) is a clinical diagnosis characterized by the presence of left ventricular dilatation and systolic dysfunction unexplained by abnormal loading conditions or coronary artery disease. However, a broad range of phenotypic manifestations, encompassing isolated scar, DCM with preserved ejection fraction, and overt DCM, should be regarded as a diagnostic classification representing a broad spectrum of underlying aetiologies, including both inherited and acquired heart muscle disorders. A multimodal non-invasive imaging approach is essential for accurate morpho-functional assessment of cardiac chambers and is key to establish the cardiac phenotype and to rule out an underlying ischaemic aetiology. Furthermore, advanced imaging techniques enable deep cardiovascular phenotyping and non-invasive tissue characterization. The aim of this review is to propose a systematic approach to the diagnosis of DCM, emphasizing the importance of genetics and clinical findings for a precise and practical clinical approach. Also, we strive to qualify the role of cardiac imaging in the diagnosis of DCM, particularly on the relevance of novel techniques and clinical utility of actionable parameters to improve current diagnostic schemes and risk stratification algorithms. We further elaborate on the role of cardiac imaging to deliver optimal guidance to aetiology-based therapeutic approaches, verification of treatment response and disease progression monitoring.

Background: Mitral valve prolapse (MVP) is a common valvular abnormality. Observational studies demonstrate an association between MVP and increased risk of sudden cardiac death from ventricular arrhythmias, coined arrhythmogenic MVP. A genetic component has been postulated but remains under-investigated. Hypothesis: Predicted deleterious variants in Mendelian cardiomyopathy and arrhythmia genes are more frequent in arrhythmogenic MVP (aMVP) compared to non-arrhythmogenic MVP. Aims: To comprehensively phenotype and genotype a single-center aMVP cohort and compare to non-aMVP from two large population-based cohorts and investigate their clinical outcomes. Methods: The aMVP cohort included 46 prospectively enrolled patients from a regional referral center for inherited cardiovascular disease and had undergone multi-modality imaging and clinical gene panel testing. The non-aMVP comparator cohorts included 453 participants from the UK Biobank (UKBB), a prospective cohort of 500,000 UK residents, and 1,418 participants from the National Institutes of Health (NIH) All of Us (AoU), a prospective cohort of 450,000 USA participants. Gene variants were annotated in ANNOVAR. Participants with and without pathogenic/likely pathogenic (P/LP) variants reported on ClinVar with ≥2-star level of evidence were considered genotype positive (G+) and negative (G-) respectively. Results: The demographics for aMVP (age 61.2 ± 12.8 years, 56.5% female) and non-aMVP (UKBB: age 59.8 ± 7.3 years, 50.7% female and AoU: age 65.3 ± 13.4 years, 76.2% female) were comparable. G+ participants were more prevalent in the aMVP cohort 10/46 (21.7%) versus non-aMVP in the UKBB 8/453 (1.8%) and in the AoU 21/1418 (1.5%); p<0.001. The most frequently implicated gene in aMVP was TTN . Of 46 in aMVP cohort, 33 (71%) underwent CMR. G+ participants had a higher frequency of late gadolinium enhancement [6/6 (100%) vs. 14/27 (51.8%), p<0.001] and wall motion abnormalities [3/6 (50%) vs. 1/27 (3.7%), p<0.001] compared to G- participants. The aMVP cohort had significantly more implantable cardioverter defibrillator (ICD) implants compared to non-aMVP cohort [5/46 (10.9%) vs. 1/453 in UKBB (0.2%), p<0.001]. G+ aMVP cohort showed a trend for developing heart failure and ICD implants compared to G- aMVP . Conclusion: P/LP variants in cardiomyopathy and arrhythmia genes are more prevalent in aMVP participants compared to non-aMVP participants. This could be a hitherto unrecognized effect modifier predicting aMVP .

Precision medicine, which among other aspects includes an individual's genomic data in diagnosis and management, has become the standard‐of‐care for Mendelian cardiovascular disease (CVD). However, early identification and management of asymptomatic patients with potentially lethal and manageable Mendelian CVD through screening, which is the promise of precision health, remains an unsolved challenge. The reduced costs of genomic sequencing have enabled the creation of biobanks containing in‐depth genetic and health information, which have facilitated the understanding of genetic variation, penetrance, and expressivity, moving us closer to the genotype‐first screening of asymptomatic individuals for Mendelian CVD. This approach could transform health care by diagnostic refinement and facilitating prevention or therapeutic interventions. Yet, potential benefits must be weighed against the potential risks, which include evolving variant pathogenicity assertion or identification of variants with low disease penetrance; costly, stressful, and inappropriate diagnostic evaluations; negative psychological impact; disqualification for employment or of competitive sports; and denial of insurance. Furthermore, the natural history of Mendelian CVD is often unpredictable, making identification of those who will benefit from preventive measures a priority. Currently, there is insufficient evidence that population‐based genetic screening for Mendelian CVD can reduce adverse outcomes at a reasonable cost to an extent that outweighs the harms of true‐positive and false‐positive results. Besides technical, clinical, and financial burdens, ethical and legal aspects pose unprecedented challenges. This review highlights key developments in the field of genotype‐first approaches to Mendelian CVD and summarizes challenges with potential solutions that can pave the way for implementing this approach for clinical care.

Abstract Cardiac disease affects the heart non-uniformly. Examples include focal septal or apical hypertrophy with reduced strain in hypertrophic cardiomyopathy, replacement fibrosis with akinesia in an infarct-related coronary artery territory, and a pattern of scarring in dilated cardiomyopathy. The detail and versatility of cardiovascular magnetic resonance (CMR) imaging mean it contains a wealth of information imperceptible to the naked eye and not captured by standard global measures. CMR-derived heterogeneity biomarkers could facilitate early diagnosis, better risk stratification, and a more comprehensive prediction of treatment response. Small cohort and case–control studies demonstrate the feasibility of proof-of-concept structural and functional heterogeneity measures. Detailed radiomic analyses of different CMR sequences using open-source software delineate unique voxel patterns as hallmarks of histopathological changes. Meanwhile, measures of dispersion applied to emerging CMR strain sequences describe variable longitudinal, circumferential, and radial function across the myocardium. Two of the most promising heterogeneity measures are the mean absolute deviation of regional standard deviations on native T1 and T2 and the standard deviation of time to maximum regional radial wall motion, termed the tissue synchronization index in a 16-segment left ventricle model. Real-world limitations include the non-standardization of CMR imaging protocols across different centres and the testing of large numbers of radiomic features in small, inadequately powered patient samples. We, therefore, propose a three-step roadmap to benchmark novel heterogeneity biomarkers, including defining normal reference ranges, statistical modelling against diagnosis and outcomes in large epidemiological studies, and finally, comprehensive internal and external validations.

Background: There is a paucity of data regarding the phenotype of dilated cardiomyopathy (DCM) gene variants in the general population. We aimed to determine the frequency and penetrance of DCM-associated putative pathogenic gene variants in a general adult population, with a focus on the expression of clinical and subclinical phenotype, including structural, functional, and arrhythmic disease features. Methods: UK Biobank participants who had undergone whole exome sequencing, ECG, and cardiovascular magnetic resonance imaging were selected for study. Three variant-calling strategies (1 primary and 2 secondary) were used to identify participants with putative pathogenic variants in 44 DCM genes. The observed phenotype was graded DCM (clinical or cardiovascular magnetic resonance diagnosis); early DCM features, including arrhythmia or conduction disease, isolated ventricular dilation, and hypokinetic nondilated cardiomyopathy; or phenotype-negative. Results: Among 18 665 individuals included in the study, 1463 (7.8%) possessed ≥1 putative pathogenic variant in 44 DCM genes by the main variant calling strategy. A clinical diagnosis of DCM was present in 0.34% and early DCM features in 5.7% of individuals with putative pathogenic variants. ECG and cardiovascular magnetic resonance analysis revealed evidence of subclinical DCM in an additional 1.6% and early DCM features in an additional 15.9% of individuals with putative pathogenic variants. Arrhythmias or conduction disease (15.2%) were the most common early DCM features, followed by hypokinetic nondilated cardiomyopathy (4%). The combined clinical/subclinical penetrance was ≤30% with all 3 variant filtering strategies. Clinical DCM was slightly more prevalent among participants with putative pathogenic variants in definitive/strong evidence genes as compared with those with variants in moderate/limited evidence genes. Conclusions: In the UK Biobank, ≈1 of 6 of adults with putative pathogenic variants in DCM genes exhibited early DCM features potentially associated with DCM genotype, most commonly manifesting with arrhythmias in the absence of substantial ventricular dilation or dysfunction.

AbstractIntroductionVentricular tachycardia (VT) in structurally normal hearts or nonischemic cardiomyopathy can originate from the aortic sinuses of Valsalva (SoV). It is unknown whether VT can originate from the SoVs in patients with prior myocardial infarction (MI).ObjectiveTo evaluate the prevalence, arrhythmogenic substrate, and ablation outcomes of postinfarction VT originating from the SoVs.MethodsAmong 217 consecutive patients with postinfarction VT undergoing ablation, we identified 13 (6%) patients who had ≥1 VT mapped in a SoV. Control groups of 13 patients with idiopathic SoV VT and 13 postinfarction patients without SoV VT were included.ResultsIn the study group, 17 VTs were mapped in a SoV (right n = 5, left‐right commissure n = 6, left n = 6). SoV VT target sites had low bipolar voltage during sinus rhythm [median 0.42 (IQR: 0.16–0.53) mV] which was significantly lower than target sites in patients with idiopathic SoV VTs [median 1.02 (IQR: 0.89–1.52) mV; p < .001]. An area of endocardial low voltage was found below the aortic valve in all patients with postinfarction SoV VTs compared to 9 (69%) of the patients in the postinfarction control group without SoV VT (p = .02). Morphology characteristics of postinfarction SoV VTs differed from idiopathic SoV VTs. None of the postinfarction SoV VTs were inducible after ablation and none recurred after a median follow‐up of 14 months.ConclusionIn patients with prior MI, VT can be targeted in an aortic SoV. The SoVs should be routinely investigated in postinfarction patients with inferior axis VT and an area of low voltage below the aortic valve.