scholarly journals DNA methylation aging clocks: challenges and recommendations

2019 ◽  
Vol 20 (1) ◽  
Author(s):  
Christopher G. Bell ◽  
Robert Lowe ◽  
Peter D. Adams ◽  
Andrea A. Baccarelli ◽  
Stephan Beck ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Ethical Issues ◽  
Population Studies ◽  
Age Determination ◽  
Biological Aging ◽  
Diverse Population ◽  
Cpg Sites ◽  
Age Related ◽  
Cell Tissue ◽  
Aging Rates

AbstractEpigenetic clocks comprise a set of CpG sites whose DNA methylation levels measure subject age. These clocks are acknowledged as a highly accurate molecular correlate of chronological age in humans and other vertebrates. Also, extensive research is aimed at their potential to quantify biological aging rates and test longevity or rejuvenating interventions. Here, we discuss key challenges to understand clock mechanisms and biomarker utility. This requires dissecting the drivers and regulators of age-related changes in single-cell, tissue- and disease-specific models, as well as exploring other epigenomic marks, longitudinal and diverse population studies, and non-human models. We also highlight important ethical issues in forensic age determination and predicting the trajectory of biological aging in an individual.

scholarly journals Age-related differences in monocyte DNA methylation and immune function in healthy Kenyan adults and children

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Katherine R. Dobbs ◽  
Paula Embury ◽  
Emmily Koech ◽  
Sidney Ogolla ◽  
Stephen Munga ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Young Adults ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Innate Immune ◽  
Inflammatory Gene Expression ◽  
Cpg Sites ◽  
Age Related ◽  
Adults And Children

Abstract Background Age-related changes in adaptive and innate immune cells have been associated with a decline in effective immunity and chronic, low-grade inflammation. Epigenetic, transcriptional, and functional changes in monocytes occur with aging, though most studies to date have focused on differences between young adults and the elderly in populations with European ancestry; few data exist regarding changes that occur in circulating monocytes during the first few decades of life or in African populations. We analyzed DNA methylation profiles, cytokine production, and inflammatory gene expression profiles in monocytes from young adults and children from western Kenya. Results We identified several hypo- and hyper-methylated CpG sites in monocytes from Kenyan young adults vs. children that replicated findings in the current literature of differential DNA methylation in monocytes from elderly persons vs. young adults across diverse populations. Differentially methylated CpG sites were also noted in gene regions important to inflammation and innate immune responses. Monocytes from Kenyan young adults vs. children displayed increased production of IL-8, IL-10, and IL-12p70 in response to TLR4 and TLR2/1 stimulation as well as distinct inflammatory gene expression profiles. Conclusions These findings complement previous reports of age-related methylation changes in isolated monocytes and provide novel insights into the role of age-associated changes in innate immune functions.

scholarly journals Age Prediction of Human Based on DNA Methylation by Blood Tissues

Genes ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 870
Author(s):  
Jiansheng Zhang ◽  
Hongli Fu ◽  
Yan Xu
Keyword(s):  
Dna Methylation ◽  
Pearson Correlation ◽  
Close Correlation ◽  
Gradient Boosting ◽  
Tissue Samples ◽  
Regression Methods ◽  
Cpg Sites ◽  
Testing Dataset ◽  
Age Related ◽  
Better Than

In recent years, scientists have found a close correlation between DNA methylation and aging in epigenetics. With the in-depth research in the field of DNA methylation, researchers have established a quantitative statistical relationship to predict the individual ages. This work used human blood tissue samples to study the association between age and DNA methylation. We built two predictors based on healthy and disease data, respectively. For the health data, we retrieved a total of 1191 samples from four previous reports. By calculating the Pearson correlation coefficient between age and DNA methylation values, 111 age-related CpG sites were selected. Gradient boosting regression was utilized to build the predictive model and obtained the R2 value of 0.86 and MAD of 3.90 years on testing dataset, which were better than other four regression methods as well as Horvath’s results. For the disease data, 354 rheumatoid arthritis samples were retrieved from a previous study. Then, 45 CpG sites were selected to build the predictor and the corresponded MAD and R2 were 3.11 years and 0.89 on the testing dataset respectively, which showed the robustness of our predictor. Our results were better than the ones from other four regression methods. Finally, we also analyzed the twenty-four common CpG sites in both healthy and disease datasets which illustrated the functional relevance of the selected CpG sites.

scholarly journals Age-related Differences in Monocyte DNA Methylation and Immune Function in Healthy Kenyan Adults and Children

2020 ◽  
Author(s):  
Katherine Rose Dobbs ◽  
Paula Embury ◽  
Emmily Koech ◽  
Sidney Ogolla ◽  
Stephen Munga ◽  
...  
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Young Adults ◽  
Innate Immune ◽  
European Ancestry ◽  
Inflammatory Gene Expression ◽  
Inflammatory Gene ◽  
Cpg Sites ◽  
Age Related ◽  
Adults And Children

Abstract Background: Age-related changes in adaptive and innate immune cells have been associated with a decline in effective immunity and chronic, low-grade inflammation. Epigenetic, transcriptional, and functional changes in monocytes occur with aging, though most studies to date have focused on differences between young adults and the elderly in populations with European ancestry; few data exist regarding changes that occur in circulating monocytes during the first few decades of life or in African populations. We analyzed DNA methylation profiles, cytokine production, and inflammatory gene expression profi 24 les in monocytes from young adults and children from western Kenya.Results: We identified several hypo- and hyper-methylated CpG sites in monocytes from Kenyan young adults vs. children that replicated findings in the current literature of differential DNA methylation in monocytes from elderly persons vs. young adults across diverse populations. Differentially methylated CpG sites were also noted in gene regions important to inflammation and innate immune responses. Monocytes from Kenyan young adults vs. children displayed increased production of IL-8, IL-10, and IL-12p70 in response to TLR4 and TLR2/1 stimulation as well as distinct inflammatory gene expression profiles.Conclusions: These findings complement previous reports of age-related methylation changes in isolated monocytes and provide novel insights into the role of age-associated changes in innate immune functions.

Individual DNA Methylation Profile is Correlated with Age and can be Targeted to Modulate Healthy Aging and Longevity

2019 ◽  
Vol 25 (39) ◽  
pp. 4139-4149 ◽  
Author(s):  
Francesco Guarasci ◽  
Patrizia D'Aquila ◽  
Alberto Montesanto ◽  
Andrea Corsonello ◽  
Dina Bellizzi ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Mitochondrial Dna ◽  
Aging Process ◽  
Healthy Aging ◽  
Nuclear Dna ◽  
Epigenetic Modification ◽  
Biological Aging ◽  
Biomarkers Of Aging ◽  
Age Related

: Patterns of DNA methylation, the best characterized epigenetic modification, are modulated by aging. In humans, different studies at both site-specific and genome-wide levels have reported that modifications of DNA methylation are associated with the chronological aging process but also with the quality of aging (or biological aging), providing new perspectives for establishing powerful biomarkers of aging. : In this article, the role of DNA methylation in aging and longevity has been reviewed by analysing literature data about DNA methylation variations occurring during the lifetime in response to environmental factors and genetic background, and their association with the aging process and, in particular, with the quality of aging. Special attention has been devoted to the relationship between nuclear DNA methylation patterns, mitochondrial DNA epigenetic modifications, and longevity. Mitochondrial DNA has recently been reported to modulate global DNA methylation levels of the nuclear genome during the lifetime, and, in spite of the previous belief, it has been found to be the target of methylation modifications. : Analysis of DNA methylation profiles across lifetime shows that a remodeling of the methylome occurs with age and/or with age-related decline. Thus, it can be an excellent biomarker of aging and of the individual decline and frailty status. The knowledge about the mechanisms underlying these modifications is crucial since it might allow the opportunity for targeted treatment to modulate the rate of aging and longevity.

scholarly journals High-resolution analyses of human sperm dynamic methylome reveal thousands of novel age-related epigenetic alterations

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Mingju Cao ◽  
Xiaojian Shao ◽  
Peter Chan ◽  
Warren Cheung ◽  
Tony Kwan ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Human Sperm ◽  
Distal Region ◽  
Epigenetic Alterations ◽  
Transcription Start Sites ◽  
Neurodevelopmental Disease ◽  
Cpg Sites ◽  
Age Related ◽  
Sperm Dna ◽  
Sperm Dna Methylation

Abstract Background Children of aged fathers are at a higher risk of developing mental disorders. Alterations in sperm DNA methylation have been implicated as a potential cause. However, age-dependent modifications of the germ cells’ epigenome remain poorly understood. Our objective was to assess the DNA methylation profile of human spermatozoa during aging. Results We used a high throughput, customized methylC-capture sequencing (MCC-seq) approach to characterize the dynamic DNA methylation in spermatozoa from 94 fertile and infertile men, who were categorized as young, 48 men between 18–38 years or old 46 men between 46–71 years. We identified more than 150,000 age-related CpG sites that are significantly differentially methylated among 2.65 million CpG sites covered. We conducted machine learning using our dataset to predict the methylation age of subjects; the age prediction accuracy based on our assay provided a more accurate prediction than that using the 450 K chip approach. In addition, we found that there are more hypermethylated (62%) than hypomethylated (38%) CpG sites in sperm of aged men, corresponding to 798 of total differential methylated regions (DMRs), of which 483 are hypermethylated regions (HyperDMR), and 315 hypomethylated regions (HypoDMR). Moreover, the distribution of age-related hyper- and hypomethylated CpGs in sperm is not random; the CpG sites that were hypermethylated with advanced age were frequently located in the distal region to genes, whereas hypomethylated sites were near to gene transcription start sites (TSS). We identified a high density of age-associated CpG changes in chromosomes 4 and 16, particularly HyperDMRs with localized clusters, the chr4 DMR cluster overlaps PGC1α locus, a protein involved in metabolic aging and the chr16 DMR cluster overlaps RBFOX1 locus, a gene implicated in neurodevelopmental disease. Gene ontology analysis revealed that the most affected genes by age were associated with development, neuron projection, differentiation and recognition, and behaviour, suggesting a potential link to the higher risk of neurodevelopmental disorders in children of aged fathers. Conclusion We identified thousands of age-related and sperm-specific epigenetic alterations. These findings provide novel insight in understanding human sperm DNA methylation dynamics during paternal aging, and the subsequently affected genes potentially related to diseases in offspring.

scholarly journals TRANSCRIPTOMIC AGING IN THE HRS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S431-S431
Author(s):  
Bharat Thyagarajan
Keyword(s):  
Population Studies ◽  
Expression Profiles ◽  
Large Population ◽  
Gene Expression Profiles ◽  
Biological Aging ◽  
Age Related ◽  
Whole Transcriptome Sequencing ◽  
Control Procedures ◽  
Transcriptomic Changes ◽  
Whole Transcriptome

Abstract Since age related perturbations in gene expression profiles have been described and transcriptomic changes in specific biological pathways have been implicated in the aging process, we performed whole transcriptome sequencing on 4000 HRS participants using RNA obtained from Paxgene tubes collected during the 2016 interview. We will describe design and implementation of innovative quality control procedures to minimize technical variability in transcriptomic measurements and monitor analytical variation in large population studies such as HRS. We will also report the distribution of transcriptomic profiles according to various demographic characteristics (age, sex, racial/ethnic and socioeconomic differences) and describe the prevalence of previously reported aging related transcriptomic signatures in HRS. We will describe the associations between transcriptomic profiles and other measures of biological aging in HRS and report how changes in cell composition can affect transcriptomic profiles observed in population studies such as HRS.

scholarly journals Human Age Prediction Based on DNA Methylation Using a Gradient Boosting Regressor

Genes ◽  
2018 ◽  
Vol 9 (9) ◽  
pp. 424 ◽  
Author(s):  
Xingyan Li ◽  
Weidong Li ◽  
Yan Xu
Keyword(s):  
Dna Methylation ◽  
Pearson Correlation ◽  
Training Data ◽  
Training Dataset ◽  
Gradient Boosting ◽  
Independent Dataset ◽  
Blood Samples ◽  
Cpg Sites ◽  
Age Related ◽  
Age Prediction

All tissues of organisms will become old as time goes on. In recent years, epigenetic investigations have found that there is a close correlation between DNA methylation and aging. With the development of DNA methylation research, a quantitative statistical relationship between DNA methylation and different ages was established based on the change rule of methylation with age, it is then possible to predict the age of individuals. All the data in this work were retrieved from the Illumina HumanMethylation BeadChip platform (27K or 450K). We analyzed 16 sets of healthy samples and 9 sets of diseased samples. The healthy samples included a total of 1899 publicly available blood samples (0–103 years old) and the diseased samples included 2395 blood samples. Six age-related CpG sites were selected through calculating Pearson correlation coefficients between age and DNA methylation values. We built a gradient boosting regressor model for these age-related CpG sites. 70% of the data was randomly selected as training data and the other 30% as independent data in each dataset for 25 runs in total. In the training dataset, the healthy samples showed that the correlation between predicted age and DNA methylation was 0.97, and the mean absolute deviation (MAD) was 2.72 years. In the independent dataset, the MAD was 4.06 years. The proposed model was further tested using the diseased samples. The MAD was 5.44 years for the training dataset and 7.08 years for the independent dataset. Furthermore, our model worked well when it was applied to saliva samples. These results illustrated that the age prediction based on six DNA methylation markers is very effective using the gradient boosting regressor.

scholarly journals AltumAge: A Pan-Tissue DNA-Methylation Epigenetic Clock Based on Deep Learning

2021 ◽  
Author(s):  
Lucas Paulo de Lima ◽  
Louis R Lapierre ◽  
Ritambhara Singh
Keyword(s):  
Dna Methylation ◽  
Deep Learning ◽  
Placental Tissue ◽  
Training Data ◽  
Data Sets ◽  
Epigenetic Clock ◽  
Neural Network Approach ◽  
Cpg Sites ◽  
Age Related ◽  
Model Predictions

Several age predictors based on DNA methylation, dubbed epigenetic clocks, have been created in recent years. Their accuracy and potential for generalization vary widely based on the training data. Here, we gathered 143 publicly available data sets from several human tissues to develop AltumAge, a highly accurate and precise age predictor based on deep learning. Compared to Horvath's 2013 model, AltumAge performs better across both normal and malignant tissues and is more generalizable to new data sets. Interestingly, it can predict gestational week from placental tissue with low error. Lastly, we used deep learning interpretation methods to learn which methylation sites contributed to the final model predictions. We observed that while most important CpG sites are linearly related to age, some highly-interacting CpG sites can influence the relevance of such relationships. We studied the associated genes of these CpG sites and found literary evidence of their involvement in age-related gene regulation. Using chromatin annotations, we observed that the CpG sites with the highest contribution to the model predictions were related to heterochromatin and gene regulatory regions in the genome. We also found age-related KEGG pathways for genes containing these CpG sites. In general, neural networks are better predictors due to their ability to capture complex feature interactions compared to the typically used regularized linear regression. Altogether, our neural network approach provides significant improvement and flexibility to current epigenetic clocks without sacrificing model interpretability.

Do age-related changes in DNA methylation play a role in the development of age-related diseases?

2013 ◽  
Vol 41 (3) ◽  
pp. 803-807 ◽  
Author(s):  
Sanne D. van Otterdijk ◽  
John C. Mathers ◽  
Gordon Strathdee
Keyword(s):  
Gene Expression ◽  
Dna Methylation ◽  
Cpg Islands ◽  
Large Body ◽  
Epigenetic Mechanism ◽  
Aberrant Methylation ◽  
Gene Promoters ◽  
Cpg Sites ◽  
Pathological Conditions ◽  
Age Related

DNA methylation is an important epigenetic mechanism in mammalian cells. It occurs almost exclusively at CpG sites and has a key role in a number of biological processes. It plays an important part in regulating chromatin structure and has been best studied for its role in controlling gene expression. In particular, hypermethylation of gene promoters which have high levels of CpG sites, known as CpG islands, leads to gene inactivation. In healthy cells, however, it appears that only a small number of genes are controlled through promoter hypermethylation, such as genes on the inactivated X-chromosome or at imprinted loci, and most promoter-associated CpG islands remain methylation-free regardless of gene expression status. However, a large body of evidence has now shown that this protection from methylation not only breaks down in a number of pathological conditions (e.g. cancer), but also already occurs during the normal process of aging. The present review focuses on the methylation changes that occur during healthy aging and during disease development, and the potential links between them. We focus especially on the extent to which the acquisition of aberrant methylation changes during aging could underlie the development of a number of important age-related pathological conditions.

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