Using DNA Methylation Profiling to Evaluate Biological Age and Longevity Interventions

Petkovich, Daniel A.; Podolskiy, Dmitriy I.; Lobanov, Alexei V.; Lee, Sang Goo; Miller, Richard A.; Gladyshev, Vadim N.

doi:10.1016/j.cmet.2017.03.016

Cited by 323 publications

(498 citation statements)

References 40 publications

(49 reference statements)

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“…We assessed age‐related changes in DNA methylation based on reduced representation bisulfite sequencing (RRBS) of blood of 141 C57BL/6 male mice representing 16 age groups (Petkovich et al., 2017; Table S3). The youngest mice were 3 months old (young adults), and the oldest 35 months old (corresponding to the survival of the remaining 10% animals).…”

Section: Resultsmentioning

confidence: 99%

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Global remodeling of the mouse DNA methylome during aging and in response to calorie restriction

2018

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SummaryAging is characterized by numerous molecular changes, such as accumulation of molecular damage and altered gene expression, many of which are linked to DNA methylation. Here, we characterize the blood DNA methylome across 16 age groups of mice and report numerous global, region‐ and site‐specific features, as well as the associated dynamics of methylation changes. Transition of the methylome throughout lifespan was not uniform, with many sites showing accelerated changes in late life. The associated genes and promoters were enriched for aging‐related pathways, pointing to a fundamental link between DNA methylation and control of the aging process. Calorie restriction both shifted the overall methylation pattern and was accompanied by its gradual age‐related remodeling, the latter contributing to the lifespan‐extending effect. With age, both highly and poorly methylated sites trended toward intermediate levels, and aging was accompanied by an accelerated increase in entropy, consistent with damage accumulation. However, the entropy effects differed for the sites that increased, decreased and did not change methylation with age. Many sites trailed behind, whereas some followed or even exceeded the entropy trajectory and altered the developmental DNA methylation pattern. The patterns we observed in certain genomic regions were conserved between humans and mice, suggesting common principles of functional DNA methylome remodeling and its critical role in aging. The highly resolved DNA methylome remodeling provides an excellent model for understanding systemic changes that characterize the aging process.

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Section: Resultsmentioning

confidence: 99%

“…Reduced representation bisulfite sequencing was performed using blood from the inferior vena cavae, and details can be found in Supplementary Experimental Procedures. The original data (Petkovich et al., 2017) were deposited to GEO under accession number GEO: GSE80672.…”

Section: Methodsmentioning

confidence: 99%

Global remodeling of the mouse DNA methylome during aging and in response to calorie restriction

2018

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“…Thus, the field has moved toward identifying specific genomic sites and regions with differential methylation in animal models (Maegawa et al 2010) and humans (Rakyan et al 2010). A number of recent reports have provided the first comprehensive analyses of altered DNA methylation with aging in a range of mouse tissues (Cole et al 2017;Hahn et al 2017;Masser et al 2017b;Petkovich et al 2017;Stubbs et al 2017). Human studies have also advanced by examining age-affected tissues (e.g., Zykovich et al 2014) and through the development of a variety of chronological aging Bclocks^ (Hannum et al 2013;Horvath 2013;Weidner et al 2014;Chen et al 2016).…”

Section: Dna Modifications and Agingmentioning

confidence: 99%

“…Therefore, averages over regions that are 1-10 kb wide provide limited insight into the true pattern of methylation. Furthermore, a number of reports have described basespecific changes in methylation with aging (Maegawa et al 2010;Mangold et al 2017a;Petkovich et al 2017;Stubbs et al 2017). Moreover, given the growing importance of examining methylation at both CG and CH sites, site-specific quantitation is required to differentiate between these two.…”

Section: Base-specificity Of Dna Modificationsmentioning

confidence: 99%

“…We have previously demonstrated in the mouse hippocampus, for example, the majority of changes in methylation with aging are in the CH context, which cannot be differentiated from CG by meDIPSeq and MBD-Seq techniques outlined above (Masser et al 2017a). Lastly, absolute quantitation in a basespecific manner allows data from multiple studies to be combined to increase power, test reproducibility, identify biomarkers, and compare between species (Horvath 2013;Masser et al 2017a;Petkovich et al 2017;Stubbs et al 2017). Taken together, these points provide strong justification that to fully understand differences in DNA modifications with aging, basespecific resolution is required.…”

Section: Base-specificity Of Dna Modificationsmentioning

confidence: 99%

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Analysis of DNA modifications in aging research

et al. 2018

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As geroscience research extends into the role of epigenetics in aging and age-related disease, researchers are being confronted with unfamiliar molecular techniques and data analysis methods that can be difficult to integrate into their work. In this review, we focus on the analysis of DNA modifications, namely cytosine methylation and hydroxymethylation, through nextgeneration sequencing methods. While older techniques for modification analysis performed relative quantitation across regions of the genome or examined average genome levels, these analyses lack the desired specificity, rigor, and genomic coverage to firmly establish the nature of genomic methylation patterns and their response to aging. With recent methodological advances, such as whole genome bisulfite sequencing (WGBS), bisulfite oligonucleotide capture sequencing (BOCS), and bisulfite amplicon sequencing (BSAS), cytosine modifications can now be readily analyzed with base-specific, absolute quantitation at both cytosine-guanine dinucleotide (CG) and non-CG sites throughout the genome or within specific regions of interest by next-generation sequencing. Additional advances, such as oxidative bisulfite conversion to differentiate methylation from hydroxymethylation and analysis of limited input/single-cells, have great promise for continuing to expand epigenomic capabilities. This review provides a background on DNA modifications, the current state-of-theart for sequencing methods, bioinformatics tools for converting these large data sets into biological insights, and perspectives on future directions for the field.

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Metabolic reprogramming: a bridge between aging and tumorigenesis

2022

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Aging is the most robust risk factor for cancer development, with more than 60% of cancers occurring in those aged 60 and above. However, how aging and tumorigenesis are intertwined is poorly understood and a matter of significant debate. Metabolic changes are hallmarks of both aging and tumorigenesis. The deleterious consequences of aging include dysfunctional cellular processes, the build-up of metabolic byproducts and waste molecules in circulation and within tissues, and stiffer connective tissues that impede blood flow and oxygenation. Collectively, these age-driven changes lead to metabolic reprogramming in different cell types of a given tissue that significantly affects their cellular functions. Here, we put forward the idea that metabolic changes that happen during aging help create a favorable environment for tumorigenesis. We review parallels in metabolic changes that happen during aging and how these changes function both as adaptive mechanisms that enable the development of malignant phenotypes in a cell-autonomous manner and as mechanisms that suppress immune surveillance, collectively creating the perfect environment for cancers to thrive. Hence, antiaging therapeutic strategies that target the metabolic reprogramming that occurs as we age might provide new opportunities to prevent cancer initiation and/or improve responses to standard-of-care anticancer therapies.

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Using DNA Methylation Profiling to Evaluate Biological Age and Longevity Interventions

Cited by 323 publications

References 40 publications

Global remodeling of the mouse DNA methylome during aging and in response to calorie restriction

Global remodeling of the mouse DNA methylome during aging and in response to calorie restriction

Analysis of DNA modifications in aging research

Metabolic reprogramming: a bridge between aging and tumorigenesis

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