Non-compaction cardiomyopathy: genetic and clinical features, 5-years outcomes
Authors: Vaikhanskaya T , Sivitskaya L.N , Liaudanski A.D , Danilenko N.G , Davydenko O.G 
Published: November 2020

Presence of morphological sign as a left ventricular non-compaction (LVNC) only, without supporting clinical criteria, does not determine diagnosis of non-compaction cardiomyopathy (NCCM).

Objective

To study of the spectrum of NCCM-associated genes, analysis of phenotype-genotype correlations and predictors of life-threatening ventricular tachyarrhythmia (ltVTA), myocardial fibrosis, and adverse outcome.

Methods

Of 93 pts with identified (Echo/MRI) morphological criteria for LVNC (follow-up median 5,1 years), 60 unrelated pts were included in the study (aged 38.5±13.8 years; 33/55% male; LVEF 42.1±12.9%) with clinical confirmed NCCM (presence any one obligate criteria): family history, neuromuscular disorder, abnormal 12-lead ECG, arrhythmia, HF or thromboembolism (Figure). Genetic testing by NGS (174 genes) was performed; all variants considered as pathogenic (PV) and likely pathogenic (LPV) were confirmed by a Sanger sequencing. Baseline and follow-up data (ECG, HM, Echo, MRI, device interrogation) were collected. Combined adverse outcomes (HF death; SCD; LVAD; HTx; and ltVTA: VT/VF, successful resuscitation, ICD shock) were accepted as composite endpoint.

Results

PV and LPV were detected in 33 (55%) pts. The most common variants were identified in sarcomere genes – TTNtv, MYBPC3, and MYH7 (47.4%); ion channel genes – 18.2%; digenic mutations were found in 21.6% pts. Gene positivity was associated with systolic dysfunction (LVEF≤49%); the highest risk of low LVEF revealed for digenic carriers (OR 38; 95% CI 4.74–305; p=0.0001). According to CATREG analysis, predictive model was built (R=0,80; R2=0,65; F=10,1; p=0,0001); the presence of disease-causing PV/LPV (β=0.46; F=15.2; p=0,0001) along with low LVEF (β=−0.28; F= 5.96; p=0,018), fibrosis (β=0.21; F= 3.05; p=0,037), wide QRS (β=0.22; F= 4.11; p=0,011) were identified as independent predictors of adverse outcomes.

As a result of ROC analysis, independent predictors of ltVTA were determined: fibrosis (nLGE≥2: AUC 0.824; 95% CI: 0.716–0.931; p=0.0001; sen 69%, spe 79%), systolic dysfunction (LVEF≤39%: AUC 0.832; 95% CI: 0.720–0.943; p=0.0001; sen 85%, spe 70%) and nsVT (HR≥150 bmp: AUC 0.829; 95% CI: 0.719–0.940; p=0.0001; sen 76%, spe 83%). According to ROC curves analysis, independent markers of myocardial fibrosis (LGE) were found: nsVT (HR≥150 bpm: AUC 0.766; 95% CI: 0.635–0.897; sen 80%, spe 77%); QRS fragmentation (nQRSfr≥4 leads ECG: AUC 0.822; 95% CI: 0.706–0.938; sen 76%, spe 92%); QTc duration (QTc≥450 ms: AUC 0.828; 95% CI: 0.722–0.935; sen 80%, spe 72%) and native MRI T1-relaxation (T1≥1086 ms: AUC 0.752; 95% CI: 0.626–0.879; sen 70%, spe 70%).

Conclusion

This results show a basically genetic causing NCCM with predominant mutations in sarcomere genes. As per predictive model, the strongest predictor of poor outcome was gene positivity. Identifying the genetic cause allows risk stratification and management optimization with counseling NCCM pts and their relatives.

Study design

Funding Acknowledgement

Type of funding source: None