Machine learning and experimental validation of novel biomarkers for hypertrophic cardiomyopathy and cancers.

ABSTRACT: Hypertrophic cardiomyopathy (HCM) is a hereditary cardiac disorder marked by anomalous thickening of the myocardium, representing a significant contributor to mortality. While the involvement of immune inflammation in the development of cardiac ailments is well-documented, its specific impact on HCM pathogenesis remains uncertain. Five distinct machine learning algorithms, namely LASSO, SVM, RF, Boruta and XGBoost, were utilized to discover new biomarkers associated with HCM. A unique nomogram was developed using two newly identified biomarkers and subsequently validated. Furthermore, samples of HCM and normal heart tissues were gathered from our institution to confirm the variance in expression levels and prognostic significance of GATM and MGST1. Five novel biomarkers (DARS2, GATM, MGST1

SUBMITTER: Dai H 

PROVIDER: S-EPMC11333198 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature