Differential DNA methylation and lymphocyte proportions in a Costa Rican high longevity region

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Abstract

Background

The Nicoya Peninsula in Costa Rica has one of the highest old-age life expectancies in the world, but the underlying biological mechanisms of this longevity are not well understood. As DNA methylation is hypothesized to be a component of biological aging, we focused on this malleable epigenetic mark to determine its association with current residence in Nicoya versus elsewhere in Costa Rica. Examining a population’s unique DNA methylation pattern allows us to differentiate hallmarks of longevity from individual stochastic variation. These differences may be characteristic of a combination of social, biological, and environmental contexts.

Methods

In a cross-sectional subsample of the Costa Rican Longevity and Healthy Aging Study, we compared whole blood DNA methylation profiles of residents from Nicoya ( n = 48) and non-Nicoya (other Costa Rican regions, n = 47) using the Infinium HumanMethylation450 microarray.

Results

We observed a number of differences that may be markers of delayed aging, such as bioinformatically derived differential CD8+ T cell proportions. Additionally, both site- and region-specific analyses revealed DNA methylation patterns unique to Nicoyans. We also observed lower overall variability in DNA methylation in the Nicoyan population, another hallmark of younger biological age.

Conclusions

Nicoyans represent an interesting group of individuals who may possess unique immune cell proportions as well as distinct differences in their epigenome, at the level of DNA methylation.

Electronic supplementary material

The online version of this article (doi:10.1186/s13072-017-0128-2) contains supplementary material, which is available to authorized users.

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Most cited references 23

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DNA methylation age of blood predicts all-cause mortality in later life

Riccardo E Marioni, Sonia Shah, Allan McRae … (2015)

Background DNA methylation levels change with age. Recent studies have identified biomarkers of chronological age based on DNA methylation levels. It is not yet known whether DNA methylation age captures aspects of biological age. Results Here we test whether differences between people’s chronological ages and estimated ages, DNA methylation age, predict all-cause mortality in later life. The difference between DNA methylation age and chronological age (Δage) was calculated in four longitudinal cohorts of older people. Meta-analysis of proportional hazards models from the four cohorts was used to determine the association between Δage and mortality. A 5-year higher Δage is associated with a 21% higher mortality risk, adjusting for age and sex. After further adjustments for childhood IQ, education, social class, hypertension, diabetes, cardiovascular disease, and APOE e4 status, there is a 16% increased mortality risk for those with a 5-year higher Δage. A pedigree-based heritability analysis of Δage was conducted in a separate cohort. The heritability of Δage was 0.43. Conclusions DNA methylation-derived measures of accelerated aging are heritable traits that predict mortality independently of health status, lifestyle factors, and known genetic factors. Electronic supplementary material The online version of this article (doi:10.1186/s13059-015-0584-6) contains supplementary material, which is available to authorized users.

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Aging of blood can be tracked by DNA methylation changes at just three CpG sites

Carola Weidner, Qiong Lin, Carmen Koch … (2014)

Background Human aging is associated with DNA methylation changes at specific sites in the genome. These epigenetic modifications may be used to track donor age for forensic analysis or to estimate biological age. Results We perform a comprehensive analysis of methylation profiles to narrow down 102 age-related CpG sites in blood. We demonstrate that most of these age-associated methylation changes are reversed in induced pluripotent stem cells (iPSCs). Methylation levels at three age-related CpGs - located in the genes ITGA2B, ASPA and PDE4C - were subsequently analyzed by bisulfite pyrosequencing of 151 blood samples. This epigenetic aging signature facilitates age predictions with a mean absolute deviation from chronological age of less than 5 years. This precision is higher than age predictions based on telomere length. Variation of age predictions correlates moderately with clinical and lifestyle parameters supporting the notion that age-associated methylation changes are associated more with biological age than with chronological age. Furthermore, patients with acquired aplastic anemia or dyskeratosis congenita - two diseases associated with progressive bone marrow failure and severe telomere attrition - are predicted to be prematurely aged. Conclusions Our epigenetic aging signature provides a simple biomarker to estimate the state of aging in blood. Age-associated DNA methylation changes are counteracted in iPSCs. On the other hand, over-estimation of chronological age in bone marrow failure syndromes is indicative for exhaustion of the hematopoietic cell pool. Thus, epigenetic changes upon aging seem to reflect biological aging of blood.

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DNA methylation and healthy human aging

Meaghan Jones, Sarah J Goodman, Michael S. Kobor (2015)

Summary The process of aging results in a host of changes at the cellular and molecular levels, which include senescence, telomere shortening, and changes in gene expression. Epigenetic patterns also change over the lifespan, suggesting that epigenetic changes may constitute an important component of the aging process. The epigenetic mark that has been most highly studied is DNA methylation, the presence of methyl groups at CpG dinucleotides. These dinucleotides are often located near gene promoters and associate with gene expression levels. Early studies indicated that global levels of DNA methylation increase over the first few years of life and then decrease beginning in late adulthood. Recently, with the advent of microarray and next‐generation sequencing technologies, increases in variability of DNA methylation with age have been observed, and a number of site‐specific patterns have been identified. It has also been shown that certain CpG sites are highly associated with age, to the extent that prediction models using a small number of these sites can accurately predict the chronological age of the donor. Together, these observations point to the existence of two phenomena that both contribute to age‐related DNA methylation changes: epigenetic drift and the epigenetic clock. In this review, we focus on healthy human aging throughout the lifetime and discuss the dynamics of DNA methylation as well as how interactions between the genome, environment, and the epigenome influence aging rates. We also discuss the impact of determining ‘epigenetic age’ for human health and outline some important caveats to existing and future studies.

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Author and article information

Contributors

Lisa M. McEwen:

ORCID: http://orcid.org/0000-0002-0500-9173

lmcewen@cmmt.ubc.ca

Alexander M. Morin: amorin@cmmt.ubc.ca

Rachel D. Edgar: redgar@cmmt.ubc.ca

Julia L. MacIsaac: jmacisaac@cmmt.ubc.ca

Meaghan J. Jones: mjones@cmmt.ubc.ca

William H. Dow: wdow@berkeley.edu

Luis Rosero-Bixby: lrosero@mac.com

Michael S. Kobor: msk@cmmt.ubc.ca

David H. Rehkopf: 650-725-0356 , drehkopf@stanford.edu

Journal

Journal ID (nlm-ta): Epigenetics Chromatin

Journal ID (iso-abbrev): Epigenetics Chromatin

Title: Epigenetics & Chromatin

Publisher: BioMed Central (London )

ISSN (Electronic): 1756-8935

Publication date (Electronic): 27 April 2017

Publication date PMC-release: 27 April 2017

Publication date Collection: 2017

Volume: 10

Electronic Location Identifier: 21

Affiliations

[1 ]ISNI 0000 0001 2288 9830, GRID grid.17091.3e, Department of Medical Genetics, Centre for Molecular Medicine and Therapeutics, , BC Children’s Hospital Research Institute, University of British Columbia, ; 950 West 28th Ave, Vancouver, Canada

[2 ]ISNI 0000 0001 2181 7878, GRID grid.47840.3f, School of Public Health, , University of California, Berkeley, ; Berkeley, CA USA

[3 ]ISNI 0000 0004 1937 0706, GRID grid.412889.e, Centro Centroamericano de Población, , Universidad de Costa Rica, ; San José, Costa Rica

[4 ]ISNI 0000000419368956, GRID grid.168010.e, Division of General Medical Disciplines, Department of Medicine, School of Medicine, , Stanford University, ; 1070 Arastradero Road, Suite 300, Palo Alto, CA 94304 USA

Author information

Lisa M. McEwen http://orcid.org/0000-0002-0500-9173

Article

Publisher ID: 128

DOI: 10.1186/s13072-017-0128-2

PMC ID: 5408416

PubMed ID: 28465725

SO-VID: 0556eba4-e81e-46d9-8234-1b7f86c96fd5

License:

Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

History

Date received : 10 January 2017

Date accepted : 13 April 2017

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100000024, Canadian Institutes of Health Research;

Award ID: F16-00910

Award ID: F15-04283

Award Recipient : Lisa M. McEwen Michael S. Kobor

Funded by: FundRef http://dx.doi.org/10.13039/100004440, Wellcome Trust;

Award ID: 072406

Award Recipient : Luis Rosero-Bixby

Funded by: FundRef http://dx.doi.org/10.13039/100006978, University of California Berkeley;

Award ID: P30AG012839

Award Recipient : William H. Dow

Funded by: R. Howard Webster Foundation

Award ID: F13-00031

Award Recipient : Rachel D. Edgar

Funded by: FundRef http://dx.doi.org/10.13039/100000049, National Institute on Aging;

Award ID: K01 AG047280

Award Recipient : David H. Rehkopf

Custom metadata

ScienceOpen disciplines: Genetics

Keywords: dna methylation,epigenetics,immune aging,longevity,biodemography,epigenetic age

Data availability:

ScienceOpen disciplines: Genetics

Keywords: dna methylation, epigenetics, immune aging, longevity, biodemography, epigenetic age

Differential DNA methylation and lymphocyte proportions in a Costa Rican high longevity region

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Abstract

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Genomic Prediction

Most cited references 23

DNA methylation age of blood predicts all-cause mortality in later life

Aging of blood can be tracked by DNA methylation changes at just three CpG sites

DNA methylation and healthy human aging

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