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DNA methylation variation across the human life course

University of British Columbia

Aging is a multifaceted process occurring in all living organisms, and it involves the breakdown of biological robustness. Although much research has revealed fascinating features of cellular mechanisms related to aging and lifespan, we have yet to understand the underpinnings driving this inevitable progression. Epigenetics is one area of aging research that has developed significant interest as certain modifications, such as DNA methylation, have been proposed to mediate the relationship between the environment and gene expression as well as have age-associated patterns. Interestingly, predictors of age based on DNA methylation of <400 CpG sites, have been created to estimate age with impressive accuracy; however, these tools are less characterized in pediatric populations. To further characterize DNA, I used the Illumina 450K and EPIC microarrays to assess genome-wide over 2,500 profiles from varying cohorts across the human life course. Specifically, I examined the relationship between buccal DNA methylation and age from pediatric samples, creating an accurate multivariate age-predictor with DNA methylation at 94 CpG site. Furthermore, I observed unique DNA methylation patterns in a long-lived population from Nicoya, Costa Rica; specifically, 20 differentially methylated regions as compared to non-Nicoyans as well as a lower overall variability of the measured sites. Additionally, I tested whether physical activity was associated with methylation changes by examining peripheral mononuclear blood cells before and after a six-month intervention, finding no apparent alterations, although, interestingly, I observed potential associations between the change in DNA methylation at 12 CpG sites with percent weight loss. Lastly, I investigated potential technical factors that may contribute to variance when estimating age with the most popular predictor based on DNA methylation. I observed moderate variability in the estimated DNA methylation age across three common preprocessing methods and provided evidence that the latest microarray technology, the EPIC, may still provide accurate measures despite missing predictor sites. In summary, I have contributed to the characterization of the human DNA methylome across the human life course, ranging from age-associated patterns in the pediatric life stage, variation related to a middle-aged lifestyle intervention, to DNA methylation signatures in a long-lived population.

Text

2018-10-11

Attribution-NonCommercial-NoDerivatives 4.0 International

http://hdl.handle.net/2429/67476

Medical Genetics

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nc-nd/4.0/