Value of Electrocardiography to Distinguish Fabry Disease from Sarcomeric Hypertrophic Cardiomyopathy

Fabry disease caused by the GLA p.Gly183Asp (p.G183D) variant: Clinical profile of a serious phenotype

Background

The detailed clinical phenotype of patients carrying the α-galactosidase gene (GLA) c.548 G > A/p.Gly183Asp (p.G183D) variant in Fabry disease (FD) has not been thoroughly documented in the existing literature.

Methods

This paper offers a meticulous overview of the clinical phenotype and relevant auxiliary examination results of nine confirmed FD patients with the p.G183D gene variant from two families. Pedigree analysis was conducted on two male patients with the gene variant, followed by biochemical and genetic screening of all high-risk relatives. Subsequently, evaluation of multiple organ systems and comprehensive instrument assessment were performed on heterozygotes of the p.G183D gene variant.

Results

The study revealed that all patients exhibited varying degrees of cardiac involvement, with two demonstrating left ventricular wall thickness exceeding 15 mm on echocardiography, and the remaining six exceeding 11 mm. Impaired renal function was evident in all six patients with available blood test data, two of whom underwent kidney transplantation. Eight cases reported neuropathic pain, and five experienced varying degrees of stroke or transient ischemic attack (TIA).

Conclusion

This study indicates that the GLA p.G183D gene variant can induce premature organ damage, particularly affecting the heart, kidneys, and nervous system.

Cardiovascular Involvement in Fabry's Disease: New Advances in Diagnostic Strategies, Outcome Prediction and Management

Cardiovascular involvement is common in Fabry's disease and is the leading cause of morbidity and mortality. The research is focused on identifying diagnostic clues suggestive of cardiovascular involvement in the preclinical stage of the disease through clinical and imaging markers. Different pathophysiologically driven therapies are currently or will soon be available for the treatment of Fabry's disease, with the most significant benefit observed in the early stages of the disease. Thus, early diagnosis and risk stratification for adverse outcomes are crucial to determine when to start an aetiological treatment. This review describes the cardiovascular involvement in Fabry's disease, focusing on the advances in diagnostic strategies, outcome prediction and disease management.

The Establishment of Hypertrophic Cardiomyopathy Diagnosis Model via Artificial Neural Network and Random Decision Forest Method

Hypertrophic cardiomyopathy is a hereditary disease characterized by asymmetric ventricular hypertrophy as the key anatomical feature. Currently, there exists no effective method for the early diagnosis of hypertrophic cardiomyopathy. In this analysis, we incorporated multiple GEO datasets containing RNA profiles of hypertrophic cardiomyopathic patient tissues, identified 642 differentially expressed genes, and performed GO and KEGG analyses. Furthermore, we narrowed down 46 characteristic genes from these differentially expressed genes using random decision forests and conducted transcription factor regulation analysis on them. Using 40 genes that showed overlap between the training set and the verification set, the artificial neural network was trained, and the final MPS scoring model was constructed, and a receiver-operating characteristic (ROC) curve was drawn. We used the MPS model to predict the verification dataset and drew the ROC curve, which demonstrated the good prediction performance of the model. In conclusion, this study combines a random decision forest and artificial neural network to build a diagnostic model for hypertrophic cardiomyopathy to predict the disease, aiming at early detection and treatment, prolonging the survival time, and improving the quality of life of patients.