Epigenetic age predictions based on buccal swabs are more precise in combination with cell type-specific DNA methylation signatures

Eipel, Monika; Mayer, Felix P.; Arent, Tanja; Ferreira, Marcelo Rodrigo Portela; Birkhofer, Carina; Gerstenmaier, Uwe; Costa, Ivan G.; Ritz‐Timme, Stefanie; Wagner, Wolfgang

doi:10.18632/aging.100972

Cited by 102 publications

(113 citation statements)

References 40 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The accuracy could be slightly increased by Lasso ( Figure 3E) and elastic net algorithms ( Figure 3F) that were generated based on all CpGs of the amplicons, but it remained lower than 12 for blood samples. This might be due to the heterogeneous composition of buccal epithelial cells and leukocytes in buccal swab samples (Eipel et al 2016).…”

Section: Epigenetic Age-predictions With Bisulfite Barcoded Ampliconmentioning

confidence: 99%

New Targeted Approaches for Epigenetic Age Predictions

Han

Franzen

Stiehl

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

Aging causes epigenetic modifications, which are utilized as a biomarker for the aging process.While genome-wide DNA methylation profiles enable robust age-predictors by integration of many age-associated CG dinucleotides (CpGs), there are various alternative approaches for targeted measurements at specific CpGs that better support standardized and cost-effective highthroughput analysis. In this study, we utilized 4,650 Illumina BeadChip datasets of blood to select the best suited CpG sites for targeted analysis. DNA methylation analysis at these sites with either pyrosequencing or droplet digital PCR (ddPCR) revealed a high correlation with chronological age.In comparison, bisulfite barcoded amplicon sequencing (BBA-seq) gave slightly lower precision at individual CpGs. However, BBA-seq data revealed that the correlation of methylation levels with age at neighboring CpG sites follows a bell-shaped curve, often accompanied by a CTCF binding site at the peak. We demonstrate that within individual BBA-seq reads the DNA methylation at neighboring CpGs is not coherently modified but reveals a stochastic pattern. Based on this, we have developed an alternative model for epigenetic age predictions based on the binary sequel of methylated and non-methylated sites in individual reads, which reflects heterogeneity in epigenetic aging within a sample. Thus, the stochastic evolution of age-associated DNA methylation patterns, which seems to resemble epigenetic drift, enables epigenetic clocks for individual DNA strands.

show abstract

Section: Epigenetic Age-predictions With Bisulfite Barcoded Ampliconmentioning

confidence: 99%

New Targeted Approaches for Epigenetic Age Predictions

Han

Franzen

Stiehl

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Several DNA methylation markers have been investigated in various tissues and body fluids using DNA-based methodologies such as bisulfite pyrosequencing (3)(4)(5)(6)(7)(8)(9), EpiTYPER technology (10), massively parallel sequencing (11)(12)(13), or SNaPshot assays (14)(15)(16).This allowed the identification of many CpG markers showing high correlations with chronological age, potentially useful as forensic age predictors. Thus, a number of high accurate age prediction models have been proposed for specific tissues, including blood (6,7,12), teeth (17), buccal swabs (8) or saliva (15), or as multi-tissue models (13,16,18,19).…”

mentioning

confidence: 99%

Age Estimation Based on DNA Methylation Using Blood Samples From Deceased Individuals

Dias

Cordeiro

Real

et al. 2019

Journal of Forensic Sciences

View full text Add to dashboard Cite

Age estimation using DNA methylation levels has been widely investigated in recent years because of its potential application in forensic genetics. The main aim of this study was to develop an age predictor model (APM) for blood samples of deceased individuals based in five age‐correlated genes. Fifty‐one samples were analyzed through the bisulfite polymerase chain reaction (PCR) sequencing method for DNA methylation evaluation in genes ELOVL2, FHL2, EDARADD, PDE4C, and C1orf132. Linear regression was used to analyze relationships between methylation levels and age. The model using the highest age‐correlated CpG from each locus revealed a correlation coefficient of 0.888, explaining 76.3% of age variation, with a mean absolute deviation from the chronological age (MAD) of 6.08 years. The model was validated in an independent test set of 19 samples producing a MAD of 8.84 years. The developed APM seems to be informative and could have potential application in forensic analysis.

show abstract

“…The separation by age still held when cohort effects were considered ( Figure S4-6). These data demonstrate that development and age modify the buccal swab methylome [19,23,25,26]. PC2, which accounts for 20.7% of the variance, was the dominant component distinguishing samples of different ages ( Figure 2B).…”

Section: Methylation Level Changes Across Individuals Reflect Postnatmentioning

confidence: 70%

Intra-individual methylomics detects the impact of early-life adversity

Jiang¹,

Kamei²,

Bolton³

et al. 2018

Preprint

View full text Add to dashboard Cite

Genetic and environmental factors interact during sensitive periods early in life to influence mental health and disease via epigenetic processes such as DNA methylation. However, it is not known if DNA methylation changes outside the brain provide an 'epigenetic signature' of earlylife experiences. Here, we employed a novel intra-individual approach by testing DNA methylation from buccal cells of individual rats before and immediately after exposure to one week of typical or adverse life experience. We find that whereas inter-individual changes in DNA methylation reflect the effect of age, DNA methylation changes within paired DNA samples from the same individual reflect the impact of diverse neonatal experiences. Genes coding for critical cellular-metabolic enzymes, ion channels and receptors were more methylated in pups exposed to the adverse environment, predictive of their repression. In contrast, the adverse experience was associated with less methylation on genes involved in pathways of death and inflammation as well as cell-fate related transcription factors, indicating their potential upregulation. Thus, intraindividual methylome signatures indicate large-scale transcription-driven alterations of cellular fate, growth and function.

show abstract

Epigenetic age predictions based on buccal swabs are more precise in combination with cell type-specific DNA methylation signatures

Cited by 102 publications

References 40 publications

New Targeted Approaches for Epigenetic Age Predictions

New Targeted Approaches for Epigenetic Age Predictions

Age Estimation Based on DNA Methylation Using Blood Samples From Deceased Individuals

Intra-individual methylomics detects the impact of early-life adversity

Contact Info

Product

Resources

About