Methylation array signals are predictive of chronological age without bisulfite conversion

Area of Science:

• Genomics
• Epigenetics
• Aging Research

Background:

• Epigenetic clocks use DNA methylation data to estimate chronological and biological age.
• Current models primarily rely on bisulfite sequencing for methylation state determination.

Purpose of the Study:

• To investigate non-methylation factors that may influence epigenetic clock accuracy.
• To identify novel age-predictive signals beyond traditional methylation markers.

Main Methods:

• Analysis of DNA methylation data and associated non-methylation factors.
• Evaluation of age prediction accuracy using different genomic data types.
• Examination of genomic regions with sequence variant-dependent methylation.

Main Results:

• Identified "pseudomethylation" signals arising from non-methylation factors.
• These pseudomethylation signals confound epigenetic clocks but are uniquely age-predictive.
• Human genotyping arrays were ineffective for age prediction in this context.

Conclusions:

• Non-methylation factors significantly impact epigenetic clock performance.
• Quantifying pseudomethylation and sequence variant effects is crucial for developing robust aging clocks.
• Future aging studies require careful consideration of these covariates for accurate epigenetic age assessment.