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

José Santiago Ibáñez-Cabellos^1,2, Juan Sandoval³, Federico V Pallardó^4,5,6

¹Department of Physiology, Faculty of Pharmacy, University of Valencia, 46100 Burjassot, Spain.

International Journal of Molecular Sciences

|April 17, 2025

Summary

Researchers developed a cost-effective biological age test using eight DNA methylation sites in the ELOVL2 gene. This simplified method accurately predicts biological age, offering a practical tool for assessing chronic disease risk and personalized medicine.

Keywords:

DNA methylation aging biological age epigenetic clocks epigenetics

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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.