A Sex-Specific Minimal CpG-Based Model for Biological Aging Using <i>ELOVL2</i> Methylation Analysis.

ABSTRACT: Significant deviations between chronological and biological age can signal the early risk of chronic diseases, driving the need for tools that accurately determine biological age. While DNA methylation-based clocks have demonstrated strong predictive power for biological aging determination, their clinical application is limited by several barriers including high costs, the need to analyze hundreds of methylation sites using sophisticated platforms and the lack of standardized measurement tools and protocols. In this study, we developed a multivariate linear model using the analysis of eight CpGs within the promoter region of the very long chain fatty acid elongase 2 gene (ELOVL2). The model generated predicts biological age with a mean absolute error (MAE) of 5.04, providing a simp

SUBMITTER: Ibanez-Cabellos JS 

PROVIDER: S-EPMC11989821 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature