Prasad, Sanjay K

Abstract Background and Aims Truncating variants in the TTN gene (TTNtv) are the most common genetic cause of dilated cardiomyopathy (DCM) but also occur as incidental findings in the general population. This study investigated factors associated with the clinical manifestation of TTNtv. Methods An international multicentre retrospective observational study was performed in families with TTNtv-related DCM. Shared frailty models were used to estimate associations of variant characteristics with lifetime risk of DCM, and logistic regression to estimate odds ratios (ORs) for individual-level clinical risk factor profiles (cardiac conditions, cardiovascular comorbidities, lifestyle) and DCM. Results A total of 3158 subjects in 1043 families with TTNtv-related DCM were studied. TTNtv-positive subjects were 21-fold more likely to develop DCM [OR, 21.21; 95% confidence interval (CI), 14.80–30.39]. Disease onset was earlier in males, but was similar for TTNtv of different types and locations. The presence of clinical risk factors was associated with earlier DCM onset (OR, 3.41; 95% CI, 2.06–5.64), with a prior history of atrial fibrillation having a two-fold increased odds of DCM (OR, 2.05; 95% CI, 1.27–3.32). The prevalence of clinical risk factors increased with age; however, the strength of the DCM association was greatest for young-onset (<30 years) disease (OR, 4.75; 95% CI, 2.35–9.60). Administration of beta-adrenergic receptor or renin-angiotensin system-blocking drugs prior to overt DCM was associated with 87% reduced odds of DCM (OR, .13; 95% CI, .08–.23). Conclusions Disease onset in TTNtv-associated familial DCM is dependent on individual patient context and is potentially modifiable by risk factor management and prophylactic therapeutic intervention.

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: Hypertrophic cardiomyopathy (HCM) is an important cause of sudden cardiac death associated with heterogeneous phenotypes, but there is no systematic framework for classifying morphology or assessing associated risks. Here, we quantitatively survey genotype-phenotype associations in HCM to derive a data-driven taxonomy of disease expression. METHODS: We enrolled 436 patients with HCM (median age, 60 years; 28.8% women) with clinical, genetic, and imaging data. An independent cohort of 60 patients with HCM from Singapore (median age, 59 years; 11% women) and a reference population from the UK Biobank (n=16 691; mean age, 55 years; 52.5% women) were also recruited. We used machine learning to analyze the 3-dimensional structure of the left ventricle from cardiac magnetic resonance imaging and build a tree-based classification of HCM phenotypes. Genotype and mortality risk distributions were projected on the tree. RESULTS: Carriers of pathogenic or likely pathogenic variants for HCM had lower left ventricular mass, but greater basal septal hypertrophy, with reduced life span (mean follow-up, 9.9 years) compared with genotype negative individuals (hazard ratio, 2.66 [95% CI, 1.42–4.96]; P <0.002). Four main phenotypic branches were identified using unsupervised learning of 3-dimensional shape: (1) nonsarcomeric hypertrophy with coexisting hypertension; (2) diffuse and basal asymmetrical hypertrophy associated with outflow tract obstruction; (3) isolated basal hypertrophy; and (4) milder nonobstructive hypertrophy enriched for familial sarcomeric HCM (odds ratio for pathogenic or likely pathogenic variants, 2.18 [95% CI, 1.93–2.28]; P =0.0001). Polygenic risk for HCM was also associated with different patterns and degrees of disease expression. The model was generalizable to an independent cohort (trustworthiness, M 1 : 0.86–0.88). CONCLUSIONS: We report a data-driven taxonomy of HCM for identifying groups of patients with similar morphology while preserving a continuum of disease severity, genetic risk, and outcomes. This approach will be of value in understanding the causes and consequences of disease diversity.