Literature DB >> 28855307

Testing Two Evolutionary Theories of Human Aging with DNA Methylation Data.

Chloe Robins1,2, Allan F McRae3,4, Joseph E Powell3,4, Howard W Wiener5, Stella Aslibekyan5, Elizabeth M Kennedy6, Devin M Absher7, Donna K Arnett8, Grant W Montgomery3, Peter M Visscher3,4, David J Cutler6, Karen N Conneely6.   

Abstract

The evolutionary theories of mutation accumulation (MA) and disposable soma (DS) provide possible explanations for the existence of human aging. To better understand the relative importance of these theories, we devised a test to identify MA- and DS-consistent sites across the genome using familial DNA methylation data. Two key characteristics of DNA methylation allowed us to do so. First, DNA methylation exhibits distinct and widespread changes with age, with numerous age-differentially-methylated sites observed across the genome. Second, many sites show heritable DNA methylation patterns within families. We extended heritability predictions of MA and DS to DNA methylation, predicting that MA-consistent age-differentially-methylated sites will show increasing heritability with age, while DS-consistent sites will show the opposite. Variance components models were used to test for changing heritability of methylation with age at 48,601 age-differentially-methylated sites across the genome in 610 individuals from 176 families. Of these, 102 sites showed significant MA-consistent increases in heritability with age, while 2266 showed significant DS-consistent decreases in heritability. These results suggest that both MA and DS play a role in explaining aging and aging-related changes, and that while the majority of DNA methylation changes observed in aging are consistent with epigenetic drift, targeted changes exist and may mediate effects of aging-related genes.
Copyright © 2017 by the Genetics Society of America.

Entities:  

Keywords:  DNA methylation; aging; disposable soma; evolution; mutation accumulation

Mesh:

Year:  2017        PMID: 28855307      PMCID: PMC5714465          DOI: 10.1534/genetics.117.300217

Source DB:  PubMed          Journal:  Genetics        ISSN: 0016-6731            Impact factor:   4.562


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