A Sex-Specific Minimal CpG-Based Model for Biological Aging Using ELOVL2 Methylation Analysis

Area of Science:

• Epigenetics and Aging
• Molecular Biology
• Biomarker Discovery

Background:

• Discrepancies between chronological and biological age are linked to chronic disease risk.
• Current DNA methylation-based aging clocks are accurate but face clinical adoption barriers like cost and complexity.
• There is a need for simplified, cost-effective biological age determination tools.

Purpose of the Study:

• To develop a simplified, cost-effective method for biological age prediction.
• To validate a multivariate linear model based on a minimal set of CpG sites.
• To explore sex-specific differences in DNA methylation patterns related to aging.

Main Methods:

• Developed a multivariate linear model analyzing eight CpGs in the promoter region of the ELOVL2 gene.
• Validated the model's predictive accuracy for biological age.
• Investigated sex-specific methylation patterns and their impact on age prediction.

Main Results:

• The developed ELOVL2-based clock achieved a mean absolute error (MAE) of 5.04 years for overall biological age prediction.
• Sex-specific clocks demonstrated improved accuracy, with MAEs of 4.37 for males and 5.38 for females.
• The study identified significant sex-related molecular differences in ELOVL2 gene methylation during aging.

Conclusions:

• A minimal CpG-based clock using ELOVL2 methylation offers a simplified and cost-effective alternative for biological age estimation.
• The findings highlight the potential for practical clinical applications in assessing age-related disease risks.
• The identified sex-specific clocks pave the way for more personalized healthcare interventions.