CoChat
Sign Up
Cited by 1,012Epigenetics and DNA MethylationTelomeres, Telomerase, and SenescenceGenetic Syndromes and Imprinting

The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.

Epigenetic Predictor of Age

Open access
Bocklandt, Sven, Lin, Wen, Sehl, Mary E., Sánchez, Francisco J., Sinsheimer, Janet S., Horvath, Steve, Vilain, Eric·2011·PLoS ONE
DOI 10.1371/journal.pone.0014821PMC PMC3120753
Open this paper in CoChat — free accountOpen PDF

Abstract

From the moment of conception, we begin to age. A decay of cellular structures, gene regulation, and DNA sequence ages cells and organisms. DNA methylation patterns change with increasing age and contribute to age related disease. Here we identify 88 sites in or near 80 genes for which the degree of cytosine methylation is significantly correlated with age in saliva of 34 male identical twin pairs between 21 and 55 years of age. Furthermore, we validated sites in the promoters of three genes and replicated our results in a general population sample of 31 males and 29 females between 18 and 70 years of age. The methylation of three sites--in the promoters of the EDARADD, TOM1L1, and NPTX2 genes--is linear with age over a range of five decades. Using just two cytosines from these loci, we built a regression model that explained 73% of the variance in age, and is able to predict the age of an individual with an average accuracy of 5.2 years. In forensic science, such a model could estimate the age of a person, based on a biological sample alone. Furthermore, a measurement of relevant sites in the genome could be a tool in routine medical screening to predict the risk of age-related diseases and to tailor interventions based on the epigenetic bio-age instead of the chronological age.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0014821

Cites

22 of 22 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Detection of gene co-methylation modules in human saliva in twins. (a) Branches of the hierarchical cluster tree define five co-methylation modules which are assigned a color as can be seen from the first color band underneath the tree. Probes that could not be clustered into one of these modules were coded grey. Every probe represents a line in the hierarchical cluster tree. Distance between two probes is shown as height on the y-axis. The second color band encodes the age relationships of each gene. Genes with positive age correlations are colored in blue. (b) Barplots showing age relationships of modules. Specifically, the y-axis shows the mean Student T-statistic testing whether the methylation status of a probe is correlated with age. Note that the green module is enriched for probes that have a significant positive correlation with age. A t-statistic value of 2 or higher indicates a significant correlation (p<0.05).
Figure 1 Detection of gene co-methylation modules in human saliva in twins. (a) Branches of the hierarchical cluster tree define five co-methylation modules which are assigned a color as can be seen from the first color band underneath the tree. Probes that could not be clustered into one of these modules were coded grey. Every probe represents a line in the hierarchical cluster tree. Distance between two probes is shown as height on the y-axis. The second color band encodes the age relationships of each gene. Genes with positive age correlations are colored in blue. (b) Barplots showing age relationships of modules. Specifically, the y-axis shows the mean Student T-statistic testing whether the methylation status of a probe is correlated with age. Note that the green module is enriched for probes that have a significant positive correlation with age. A t-statistic value of 2 or higher indicates a significant correlation (p<0.05).CC BY · PubMed Central
Figure 2 Percentage methylation versus age for three markers validated in three sample sets. Original twin samples are blue, male control samples are red, female control samples green. Linear trendlines are shown in the colors of the individual sample sets a) Edaradd r = −0.81 (twins), r = −0.73 (male controls), r = −0.75 (female controls) b) NPTX2 r = 0.52 (twins), r = 0.79 (male controls), r = 0.03 (female controls) c) Tom1L1 r = −0.70 (twins), r = −0.49 (male controls), r = −0.24 (female controls).
Figure 2 Percentage methylation versus age for three markers validated in three sample sets. Original twin samples are blue, male control samples are red, female control samples green. Linear trendlines are shown in the colors of the individual sample sets a) Edaradd r = −0.81 (twins), r = −0.73 (male controls), r = −0.75 (female controls) b) NPTX2 r = 0.52 (twins), r = 0.79 (male controls), r = 0.03 (female controls) c) Tom1L1 r = −0.70 (twins), r = −0.49 (male controls), r = −0.24 (female controls).CC BY · PubMed Central
Figure 3 Predicted versus observed age of all subjects using a leave-one-out model. A multivariate regression model was fit on all but one sample and its predicted age (y-axis) was related to the truly observed age of the left out sample (x-axis). The predicted values are highly correlated with the observed ages (r = 0.83, p = 2.2×10−16, n = 66), and the average absolute difference between the predicted and the observed age is 5.2 years.
Figure 3 Predicted versus observed age of all subjects using a leave-one-out model. A multivariate regression model was fit on all but one sample and its predicted age (y-axis) was related to the truly observed age of the left out sample (x-axis). The predicted values are highly correlated with the observed ages (r = 0.83, p = 2.2×10−16, n = 66), and the average absolute difference between the predicted and the observed age is 5.2 years.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 22 references

Cited by

Sorted by citations

Items 701–800 of 999

Related

See all

Metadata

Authors
Bocklandt, S., Lin, W., Sehl, M. E., Sánchez, F. J., Sinsheimer, J. S., Horvath, S., & Vilain, E.
Affiliations
University of California, Los Angeles (US)
Corresponding author
Vilain, Eric
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2011-06-22
Volume
6
Issue
6
Pages
e14821
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0014821
PMC
PMC3120753
OpenAlex
W2080644309
Cited by
1,012
References
22
Citations by year
2026: 56 · 2025: 71 · 2024: 83 · 2023: 92 · 2022: 95 · 2021: 108 · 2020: 87 · 2019: 64 · 2018: 52 · 2017: 65 · 2016: 58 · 2015: 63 · 2014: 43 · 2013: 40 · 2012: 30
FWCI
14.97
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • eScholarship (California Digital Library) (submittedVersion)
  • Figshare (submittedVersion, cc-by)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Cell Biology › Telomeres, Telomerase, and Senescence
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Syndromes and Imprinting
Keywords
DNA methylation, age prediction, epigenetic clocks, saliva, EDARADD, NPTX2, promoter methylation, forensic age estimation, age-related disease risk
MeSH terms
Adolescent, Adult, Aged, Aging, Female, Humans, Male, Middle Aged, Models, Genetic, Saliva, Twins, Reproducibility of Results, DNA Probes, DNA Methylation, Oligonucleotide Array Sequence Analysis, Epigenesis, Genetic, Young Adult, Genetic Loci

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review