Key result
A predictive model containing five disulfidptosis-associated genes (GYS1, MYH10, PDMIL1, SLC3A2, CAPZB) accurately distinguished hypertrophic cardiomyopathy patients from controls with AUCs of 0.974 and 0.911 in validation datasets.
Why the study?
Hypertrophic cardiomyopathy lacks effective treatments due to complex pathogenesis, and the role of disulfidptosis in cardiovascular diseases has rarely been studied.
Effect estimate: AUC 0.974 and 0.911
A machine learning model identified five disulfidptosis-related genes as potential biomarkers for hypertrophic cardiomyopathy, which were validated in a mouse model.
Hypertrophic cardiomyopathy (HCM) is one of the most common cardiovascular diseases with no effective treatment due to its complex pathogenesis. A novel cell death, disulfidptosis, has been extensively studied in the cancer field but rarely in cardiovascular diseases. This study revealed the potential relationship between disulfidptosis and hypertrophic cardiomyopathy and put forward a predictive model containing disulfidptosis-associated genes (DRGs) of GYS1, MYH10, PDMIL1, SLC3A2, CAPZB, showing excellent performance by SVM machine learning model. The results were further validated by western blot, RNA sequencing and immunohistochemistry in a TAC mice model. In addition, resveratrol was selected as a therapeutic drug targeting core genes using the CTD database. In summary, this study provides new perspectives for exploring disulfidptosis-related biomarkers and potential therapeutic targets for hypertrophic cardiomyopathy.
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Fan et al. (2024) studied Hypertrophic cardiomyopathy (n=361). Disulfidptosis-related genes (GYS1, MYH10, PDMIL1, SLC3A2, CAPZB) vs. Healthy controls was evaluated on Diagnostic performance of the 5-gene SVM predictive model (AUC 0.974 and 0.911). A predictive model containing five disulfidptosis-associated genes (GYS1, MYH10, PDMIL1, SLC3A2, CAPZB) accurately distinguished hypertrophic cardiomyopathy patients from controls with AUCs of 0.974 and 0.911 in validation datasets.
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