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Updated: May 8, 2026

Sample Preparation to Bioinformatics Analysis of DNA Methylation: Association Strategy for Obesity and Related Trait Studies
Published on: May 6, 2022
Age-varying DNA methylation patterns associated with blood pressure in mid-to-late adulthood
Gang Xu1, Xiaowei Zhuang2,3, Amei Amei4
1Laboratory of Neurogenetics and Precision Medicine, College of Sciences, University of Nevada Las Vegas, Las Vegas, NV, USA. gang.xu@unlv.edu.
DNA methylation patterns in blood dynamically change with age, influencing blood pressure. These age-dependent epigenetic changes, particularly in mid-to-late adulthood, may indicate vascular aging and inform cardiovascular risk biomarkers.
Area of Science:
- Epigenetics and Cardiovascular Health
- Genomics and Aging Research
Background:
- Epigenome-wide association studies (EWAS) link DNA methylation to blood pressure.
- Existing studies often use single time-point data, limiting understanding of age-related changes.
Purpose of the Study:
- To investigate age-dependent associations between DNA methylation and blood pressure traits using longitudinal data.
- To identify specific CpG sites and biological pathways involved in age-related blood pressure regulation.
Main Methods:
- Longitudinal epigenome-wide association study (EWAS) of 1945 blood samples from 976 participants.
- Employed spline-based varying-coefficient models to detect age-dependent methylation-blood pressure associations.
- Replicated findings in the Framingham Heart Study and adjusted for covariates like sex, ancestry, and leukocyte composition.
Main Results:
- Identified six CpG sites with significant age-dependent associations with systolic or pulse pressure.
- Observed reversals in methylation-blood pressure effect direction with age, particularly for STIP1 and CSRP1 loci.
- Pathway analysis implicated focal adhesion, actin remodeling, and Wnt/β-catenin signaling in vascular aging.
Conclusions:
- Blood DNA methylation exhibits dynamic, age-related associations with blood pressure, especially in mid-to-late adulthood.
- These patterns likely reflect systemic or vascular aging, not just direct cellular effects.
- Longitudinal EWAS can uncover temporal epigenetic variations crucial for identifying age-related cardiovascular risk biomarkers.
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