Non-invasive prediction of genotype positive-phenotype negative in hypertrophic cardiomyopathy by 3D modern shape analysis

Genotype-Phenotype Taxonomy of Hypertrophic Cardiomyopathy

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, M1: 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.

Correcting bias in cardiac geometries derived from multimodal images using spatiotemporal mapping

Cardiovascular imaging studies provide a multitude of structural and functional data to better understand disease mechanisms. While pooling data across studies enables more powerful and broader applications, performing quantitative comparisons across datasets with varying acquisition or analysis methods is problematic due to inherent measurement biases specific to each protocol. We show how dynamic time warping and partial least squares regression can be applied to effectively map between left ventricular geometries derived from different imaging modalities and analysis protocols to account for such differences. To demonstrate this method, paired real-time 3D echocardiography (3DE) and cardiac magnetic resonance (CMR) sequences from 138 subjects were used to construct a mapping function between the two modalities to correct for biases in left ventricular clinical cardiac indices, as well as regional shape. Leave-one-out cross-validation revealed a significant reduction in mean bias, narrower limits of agreement, and higher intraclass correlation coefficients for all functional indices between CMR and 3DE geometries after spatiotemporal mapping. Meanwhile, average root mean squared errors between surface coordinates of 3DE and CMR geometries across the cardiac cycle decreased from 7 ± 1 to 4 ± 1 mm for the total study population. Our generalised method for mapping between time-varying cardiac geometries obtained using different acquisition and analysis protocols enables the pooling of data between modalities and the potential for smaller studies to leverage large population databases for quantitative comparisons.

Time course of ischemic and bleeding burden in consecutive patients undergoing transcatheter aortic valve replacement (FOCUS-ONE registry)

BACKGROUND AND AIMS

Ischemic or bleeding events might occur after transcatheter aortic valve replacement (TAVR), with the potential to hamper clinical outcomes. This study aimed to characterize the average daily ischemic risks (ADIRs) and the average daily bleeding risks (ADBRs) over 1-year in all consecutive patients undergoing TAVR.

METHODS

ADBR included all bleeding events according to VARC-2 definition, and ADIR included cardiovascular deaths, myocardial infarction and ischemic stroke. ADIRs and ADBRs were assessed within different timeframes post TAVR: acute (0-30 days), late (31-180 days), and very late (>181 days). Generalized estimating equations were used to test the least squares mean differences for the pairwise comparison of ADIRs and ADBRs. Our analysis was performed in the overall cohort and according to antithrombotic strategy (LT-OAC vs No LT-OAC).

RESULTS

Ischemic burden was higher than bleeding burden, independently from the indication to LT-OAC, and in all timeframes examined. In the overall population, ADIRs were three-fold ADBRs (0.0467 [95% CI, 0.0431-0.0506] vs 0.0179 [95% CI, 0.0174-0.0185]; p < 0.001*). While ADIR was significantly higher in the acute phase, ADBR was relatively stable in all timeframes analysed. Of note, in LT-OAC population, OAC + SAPT group showed lower ischemic risk and higher bleeding events compared with OAC alone (ADIR: 0.0447 [95% CI: 0.0417-0.0477] vs 0.0642 [95% CI: 0.0557-0.0728]; p < 0.001*, ADBR 0.0395 [95% CI: 0.0381-0.0409] vs 0.0147 [95% CI: 0.0138-0.0156]; p < 0.001*).

CONCLUSIONS

In patients undergoing TAVR Average daily risk fluctuates over time. However, ADIRs overcome ADBRs in all timeframes, especially in the acute phase and regardless of antithrombotic strategy adopted.

Geometry Does Impact on the Plane Strain Directions of the Human Left Ventricle, Irrespective of Disease

The directions of primary strain lines of local deformation in Epicardial and Endocardial layers have been the subject of debate in recent years. Different methods led to different conclusions and a complete assessment of strain direction patterns in large and variable (in terms of pathology) cohorts of healthy and diseased patients is still lacking. Here, we use local deformation tensors in order to evaluate the angle of strain lines with respect to the horizontal circumferential direction in both Epi- and Endo-layers. We evaluated this on a large group of 193 subjects including 82 healthy control and 111 patients belonging to a great variety of pathological conditions. We found that Epicardial strain lines obliquely directed while those of Endocardium are almost circumferential. This result occurs irrespective of pathological condition. We propose that the geometric vinculum characterizing Endocardium and Epicardium in terms of different lever arm length and orientation of muscular fibers during contraction inescapably requires Endocardial strain lines to be circumferentially oriented and this is corroborated by experimental results. Further investigations on transmural structure of myocytes could couple results presented here in order to furnish additional experimental explanations.