Understanding the clinical characteristics of our population enables the optimal allocation of healthcare resources, ensuring that the greatest number of patients benefit from the available means according to their clinical impact. Hypertrophic cardiomyopathy (HCM) is a clear example of a disease that must be analyzed from the workup process to the therapeutic approach, both of which are expensive. This analysis should be conducted with the aim of predicting and preventing the most serious outcomes, such as sudden cardiac death and progression to heart failure, with the greatest possible specificity, while maintaining sensitivity
The study by Parodi JB et al. (1) is a highly relevant population-based analysis that aligns with previous studies that have attempted to predict which patients with HCM will have a pathogenic (P) or likely pathogenic (LP) variant in genetic testing, such as that of Bos JM et al. (2), which led to the development of the Mayo Clinic score in 2014. Both studies agree, even though they involve different populations, that the reverse septal curvature pattern is associated with a higher probability of a positive genetic test with P or LP variants.
Hypertrophic cardiomyopathy has traditionally been considered a monogenic disease caused by variants in sarcomeric genes. While this assessment is not false, it is incomplete. A detailed analysis of sarcomeric genes can identify the genetic cause in 30 to 60% of cases, according to the series reported. If we only consider this pathogenesis, we would be leaving 40-70% of diagnosed patients without a genetic explanation for their disease. The constant analysis of variants found necessitates periodic reviews of genetic tests to assess the potential reclassification of those previously designated as negative as positive. One such example is the p.Arg652Lys variant in MYH7 (3) in a region of Spain, which was previously considered a variant of uncertain significance (VUS) and is currently P. In this context, the recent identification of non-sarcomeric genes associated with HCM, such as FHOD3, (4) has expanded the genetic spectrum of the disease. An analysis of intermediateeffect variants (IEVs) has recently been published. While these variants do not reach the category of P or LP, they influence the development of the disease. According to García Hernández S et al.(5) these IEVs account for 4.8% of HCM cases and modulate both the phenotype and clinical events when found in combination with P or LP variants.
Given the aforementioned reasons, it is imperative to ascertain the population to which patients with HCM belong and, following the results of a genetic test, to carry out a detailed analysis of the variants found. This analysis should consider the possibility of finding VUS or IEVs as the ultimate causes of the disease. A thorough understanding of HCM genetics improves diagnostic accuracy, facilitates optimized risk stratification, and allows for personalized therapeutic decisions)
Ethical considerations
Not applicable.
Conflicts of interest
None declared. (See authors' conflict of interests forms on the web).
