Age determination through DNA methylation patterns of fingernails and toenails

Over the past decade, age prediction based on DNA methylation has become a vastly investigated topic; many age prediction models have been developed based on different DNAm markers and using various tissues. However, the potential of using nails to this end has not yet been explored. Their inherent resistance to decay and ease of sampling would offer an advantage in cases where post-mortem degradation poses challenges concerning sample collection and DNA-extraction. In the current study, clippings from both fingernails and toenails were collected from 108 living test subjects (age range: 0 – 96 years). The methylation status of 15 CpGs located in 4 previously established age-related markers (ASPA, EDARADD, PDE4C, ELOVL2) was investigated through pyrosequencing of bisulphite converted DNA. Significant dissimilarities in methylation levels were observed between all four limbs, hence limb-specific age prediction models were developed using ordinary least squares, weighted least squares and quantile regression analysis. When applied to their respective test sets, these models yielded a mean absolute deviation between predicted and chronological age ranging from 6.71 to 8.48 years. In addition, the assay was tested on methylation data derived from 5 nail samples collected from deceased individuals, demonstrating its feasibility for application in post-mortem cases. In conclusion, this study provides the first proof that chronological age can be assessed through DNA methylation patterns in nails.

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Front Cover: Genetic analyzer‐dependent DNA methylation detection and its application to existing age prediction models

Electrophoresis ◽

10.1002/elps.202170091 ◽

2021 ◽

Vol 42 (14-15) ◽

Author(s):

Moon Hyun So ◽

Hwan Young Lee

Keyword(s):

Dna Methylation ◽

Prediction Models ◽

Front Cover ◽

Genetic Analyzer ◽

Age Prediction

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Abstract 40: Disturbed Flow Alters Genomewide DNA Methylation Patterns, Regulating Endothelial Gene Expression and Atherosclerosis

Arteriosclerosis Thrombosis and Vascular Biology ◽

10.1161/atvb.34.suppl_1.40 ◽

2014 ◽

Vol 34 (suppl_1) ◽

Author(s):

Jessilyn Dunn ◽

Haiwei Qiu ◽

Soyeon Kim ◽

Daudi Jjingo ◽

Ryan Hoffman ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Dna Methyltransferase ◽

Methylation Status ◽

Western Diet ◽

Dependent Manner ◽

Gene Promoters ◽

Genome Wide ◽

Methylation Patterns ◽

Endothelial Gene Expression

Atherosclerosis preferentially occurs in arterial regions of disturbed blood flow (d-flow), which alters gene expression, endothelial function, and atherosclerosis. Here, we show that d-flow regulates genome-wide DNA methylation patterns in a DNA methyltransferase (DNMT)-dependent manner. We found that d-flow induced expression of DNMT1, but not DNMT3a or DNMT3b, in mouse arterial endothelium in vivo and in cultured endothelial cells by oscillatory shear (OS) compared to unidirectional laminar shear in vitro. The DNMT inhibitor 5-Aza-2’deoxycytidine (5Aza) or DNMT1 siRNA significantly reduced OS-induced endothelial inflammation. Moreover, 5Aza reduced lesion formation in two atherosclerosis models using ApoE-/- mice (western diet for 3 months and the partial carotid ligation model with western diet for 3 weeks). To identify the 5Aza mechanisms, we conducted two genome-wide studies: reduced representation bisulfite sequencing (RRBS) and transcript microarray using endothelial-enriched gDNA and RNA, respectively, obtained from the partially-ligated left common carotid artery (LCA exposed to d-flow) and the right contralateral control (RCA exposed to s-flow) of mice treated with 5Aza or vehicle. D-flow induced DNA hypermethylation in 421 gene promoters, which was significantly prevented by 5Aza in 335 genes. Systems biological analyses using the RRBS and the transcriptome data revealed 11 mechanosensitive genes whose promoters were hypermethylated by d-flow but rescued by 5Aza treatment. Of those, five genes contain hypermethylated cAMP-response-elements in their promoters, including the transcription factors HoxA5 and Klf3. Their methylation status could serve as a mechanosensitive master switch in endothelial gene expression. Our results demonstrate that d-flow controls epigenomic DNA methylation patterns in a DNMT-dependent manner, which in turn alters endothelial gene expression and induces atherosclerosis.

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Detection of LINE-1 hypomethylation in cfDNA of Esophageal Adenocarcinoma Patients

International Journal of Molecular Sciences ◽

10.3390/ijms21041547 ◽

2020 ◽

Vol 21 (4) ◽

pp. 1547 ◽

Cited By ~ 2

Author(s):

Elisa Boldrin ◽

Matteo Curtarello ◽

Marco Dallan ◽

Rita Alfieri ◽

Stefano Realdon ◽

...

Keyword(s):

Dna Methylation ◽

Esophageal Adenocarcinoma ◽

Methodological Approach ◽

Methylation Status ◽

Dna Amplification ◽

Restriction Enzymes ◽

Poor Quality ◽

Bisulfite Conversion ◽

Dna Hypomethylation ◽

Methylation Patterns

DNA methylation plays an important role in cancer development. Cancer cells exhibit two types of DNA methylation alteration: site-specific hypermethylation at promoter of oncosuppressor genes and global DNA hypomethylation. This study evaluated the methylation patterns of long interspersed nuclear element (LINE-1) sequences which, due to their relative abundance in the genome, are considered a good surrogate indicator of global DNA methylation. LINE-1 methylation status was investigated in the cell-free DNA (cfDNA) of 21 patients, 19 with esophageal adenocarcinoma (EADC) and 2 with Barrett’s esophagus (BE). The two BE patients and one EADC patient were also analyzed longitudinally. Methylation status was analyzed using restriction enzymes and DNA amplification. This methodology was chosen to avoid bisulfite conversion, which we considered inadequate for cfDNA analysis. Indeed, cfDNA is characterized by poor quality and low concentration, and bisulfite conversion might worsen these conditions. Results showed that hypomethylated LINE-1 sequences are present in EADC cfDNA. Furthermore, longitudinal studies in BE suggested a correlation between methylation status of LINE-1 sequences in cfDNA and progression to EADC. In conclusion, our study indicated the feasibility of our methodological approach to detect hypomethylation events in cfDNA from EADC patients, and suggests LINE-1 methylation analysis as a new possible molecular assay to integrate into patient monitoring.

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Prediction of voluntary Intake of grass silage by growing cattle using ridge regression

Proceedings of the British Society of Animal Production (1972) ◽

10.1017/s0308229600010618 ◽

1989 ◽

Vol 1989 ◽

pp. 68-68 ◽

Cited By ~ 1

Author(s):

A. J. Rook ◽

M. Gill ◽

M. S. Dhanoa

Keyword(s):

Least Squares ◽

Ridge Regression ◽

Prediction Models ◽

Ordinary Least Squares ◽

Independent Data ◽

College Of Agriculture ◽

Grass Silage ◽

Backward Elimination ◽

Growing Cattle ◽

Controlled Experimentation

Due to collinearity among the independent varlates, intake prediction models based on least squares multiple regression are likely to predict poorly with independent data. In addition, the regression coefficients are sensitive to small changes in the estimation data and tend not to reflect causal relationships expected from the results of controlled experimentation. Ridge regression (Hoerl and Kennard, 1970) allows the estimation of new coefficients for the independent variables which overcome these effects of collinearity. In order to assess the usefulness of the method for Intake prediction, ordinary least squares (OLS) models, obtained using backward elimination of variables, and ridge regression models were constructed from the same data and then tested with independent data.Estimation data consisted of results of experiments of IGAP, Hurley and Greenmount College of Agriculture in which growing cattle were individually fed grass silage ad-libitum with or without supplementary feeds. Two subsets of the estimation data were used. Subset A included 395 animals and 36 silages; subset B included 192 animals and 16 silages and was for Hurley data only.

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High Throughput Methylation Arrays Allow for Identification of Complex Methylation Patterns in MDS.

Blood ◽

10.1182/blood.v110.11.2437.2437 ◽

2007 ◽

Vol 110 (11) ◽

pp. 2437-2437

Author(s):

Ying Jiang ◽

Christine L. OKeefe ◽

Andrew Dunbar ◽

Anjali Advani ◽

Mikkael A. Sekeres ◽

...

Keyword(s):

Dna Methylation ◽

Tumor Suppressor ◽

High Throughput ◽

Tumor Suppressor Genes ◽

Methylation Status ◽

Epigenetic Silencing ◽

Low Grade ◽

High Grade ◽

Methylation Patterns ◽

Hypermethylated Genes

Abstract Genomic imprinting and epigenetic silencing determine tissue-specific methylation patterns. Altered methylation of CpG islands within gene promoters has been hypothesized as one pathogenetic mechanism operative in myelodysplastic syndrome (MDS). Promoter hypermethylation of various empirically selected tumor suppressor genes has been found in MDS prompting application of hypomethylating drugs in this disease. Identification of hypermethylated genes predicting response to these drugs would have a major impact on clinical practice. However, to date methylation-based prognostic algorithms have not been established. Global analysis of DNA methylation patterns may help to identify hypermethylated genes/promoters associated with the pathogenesis of MDS. Recently, microarray-based DNA methylation analysis platforms enabled a powerful, high-throughput analysis of the methylation status of hundreds of genes. The GoldenGate Methylation Cancer Panel I, spanning 1,536 independent CpG sites selected from 807 selected genes was applied to determine the methylation status in MDS patients (N=51; 21 low grade (RA, MDS-U, RARS or RCMD), 26 high grade (AML or RAEB) and 4 CMML). The methylation status was determined based on an internal reference and compared to healthy controls (N=22). Methylation values were averaged among the patients or analyzed separately for each patient in comparison to average values obtained in controls. Overall, controls showed a lesser degree of methylation than advanced MDS patients (average intensity 0.326 vs. 0.339, p<0.05). Subsequently, we concentrated on hypermethylated genes. There were no genes uniformly hypermethylated in all patients. For 70%, 50%, and 30% of patients with advanced MDS, 1, 26, and 85 loci were concordantly hypermethylated, while in 70%, 50% and 30% of low risk patients 5, 23 and 31 were hypermethylated, respectively. The most consistently hypermethylated genes (>50% of patients), included tumor suppressor genes (DCC, SLC22A18, FAT, TUSC3), genes involved in DNA repair (OGG1, DDB2, BCR, PARP1), cell cycle control (DBC1, SMARCB1), differentiation (MYOD1, TDGF1, FGF2, NOTCH4) and apoptosis (HDAC1, ALOX12, AXIN1). Despite the variability, the aberrant methylation spectrum in CMML, low grade MDS and high grade MDS showed significant overlap (for example FZD9, IL16, EVI2A, MBD2 and BCR), which suggests that these genes may relate to the common tumorigenesis in MDS. Certain genes show specific methylation correlating to the morphologic diagnosis and may serve as diagnostic markers. For example, the promoter of HDAC1 is hypomethylated in 81% of sAML/RAEB1/2 patients but hypermethylated in 81% of low risk cases. To assess the link between epigenetic changes and chromosomal abnormalities, we also investigated methylation pattern of MDS with del5q for selected genes at the 5q locus. Some genes that are involved in apoptosis (WNT1, TNF receptor) and proliferation (MAP3K8, CSF3) were found to be hypermethylated in comparison to controls, suggesting that epigenetic silencing may enhance the effect of haploinsuffciency for some of the genes. In sum, our study, the first application of a high-throughput microarray methylation assay in MDS, demonstrates that complex methylation patterns exist in MDS and may allow for identification for clinically relevant methylation markers.

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Pubertal development in healthy children is mirrored by DNA methylation patterns in peripheral blood

Scientific Reports ◽

10.1038/srep28657 ◽

2016 ◽

Vol 6 (1) ◽

Cited By ~ 22

Author(s):

Kristian Almstrup ◽

Marie Lindhardt Johansen ◽

Alexander S. Busch ◽

Casper P. Hagen ◽

John E. Nielsen ◽

...

Keyword(s):

Dna Methylation ◽

Peripheral Blood ◽

Prediction Models ◽

Pubertal Timing ◽

Pubertal Development ◽

Healthy Children ◽

Secondary Sexual Characteristics ◽

Sexual Characteristics ◽

Methylation Patterns ◽

Secondary Sexual

Abstract Puberty marks numerous physiological processes which are initiated by central activation of the hypothalamic–pituitary–gonadal axis, followed by development of secondary sexual characteristics. To a large extent, pubertal timing is heritable, but current knowledge of genetic polymorphisms only explains few months in the large inter-individual variation in the timing of puberty. We have analysed longitudinal genome-wide changes in DNA methylation in peripheral blood samples (n = 102) obtained from 51 healthy children before and after pubertal onset. We show that changes in single methylation sites are tightly associated with physiological pubertal transition and altered reproductive hormone levels. These methylation sites cluster in and around genes enriched for biological functions related to pubertal development. Importantly, we identified that methylation of the genomic region containing the promoter of TRIP6 was co-ordinately regulated as a function of pubertal development. In accordance, immunohistochemistry identified TRIP6 in adult, but not pre-pubertal, testicular Leydig cells and circulating TRIP6 levels doubled during puberty. Using elastic net prediction models, methylation patterns predicted pubertal development more accurately than chronological age. We demonstrate for the first time that pubertal attainment of secondary sexual characteristics is mirrored by changes in DNA methylation patterns in peripheral blood. Thus, modulations of the epigenome seem involved in regulation of the individual pubertal timing.

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Correlation Constraints for Regression Models: Controlling Bias in Brain Age Prediction

Frontiers in Psychiatry ◽

10.3389/fpsyt.2021.615754 ◽

2021 ◽

Vol 12 ◽

Author(s):

Matthias S. Treder ◽

Jonathan P. Shock ◽

Dan J. Stein ◽

Stéfan du Plessis ◽

Soraya Seedat ◽

...

Keyword(s):

Regression Models ◽

Optimization Problem ◽

Prediction Models ◽

Chronological Age ◽

Training Procedure ◽

Constrained Optimization Problem ◽

The Difference ◽

Model Training ◽

Brain Age ◽

Age Prediction

In neuroimaging, the difference between chronological age and predicted brain age, also known as brain age delta, has been proposed as a pathology marker linked to a range of phenotypes. Brain age delta is estimated using regression, which involves a frequently observed bias due to a negative correlation between chronological age and brain age delta. In brain age prediction models, this correlation can manifest as an overprediction of the age of young brains and an underprediction for elderly ones. We show that this bias can be controlled for by adding correlation constraints to the model training procedure. We develop an analytical solution to this constrained optimization problem for Linear, Ridge, and Kernel Ridge regression. The solution is optimal in the least-squares sense i.e., there is no other model that satisfies the correlation constraints and has a better fit. Analyses on the PAC2019 competition data demonstrate that this approach produces optimal unbiased predictive models with a number of advantages over existing approaches. Finally, we introduce regression toolboxes for Python and MATLAB that implement our algorithm.

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Evidence for differences in DNA methylation between Germans and Japanese

International Journal of Legal Medicine ◽

10.1007/s00414-021-02736-3 ◽

2021 ◽

Author(s):

J. Becker ◽

P. Böhme ◽

A. Reckert ◽

S. B. Eickhoff ◽

B. E. Koop ◽

...

Keyword(s):

Dna Methylation ◽

Age Estimation ◽

Prediction Models ◽

Total Sample ◽

Training Data ◽

Research Strategies ◽

Different Populations ◽

The Impact ◽

Age Prediction

AbstractAs a contribution to the discussion about the possible effects of ethnicity/ancestry on age estimation based on DNA methylation (DNAm) patterns, we directly compared age-associated DNAm in German and Japanese donors in one laboratory under identical conditions. DNAm was analyzed by pyrosequencing for 22 CpG sites (CpGs) in the genes PDE4C, RPA2, ELOVL2, DDO, and EDARADD in buccal mucosa samples from German and Japanese donors (N = 368 and N = 89, respectively).Twenty of these CpGs revealed a very high correlation with age and were subsequently tested for differences between German and Japanese donors aged between 10 and 65 years (N = 287 and N = 83, respectively). ANCOVA was performed by testing the Japanese samples against age- and sex-matched German subsamples (N = 83 each; extracted 500 times from the German total sample). The median p values suggest a strong evidence for significant differences (p < 0.05) at least for two CpGs (EDARADD, CpG 2, and PDE4C, CpG 2) and no differences for 11 CpGs (p > 0.3).Age prediction models based on DNAm data from all 20 CpGs from German training data did not reveal relevant differences between the Japanese test samples and German subsamples. Obviously, the high number of included “robust CpGs” prevented relevant effects of differences in DNAm at two CpGs.Nevertheless, the presented data demonstrates the need for further research regarding the impact of confounding factors on DNAm in the context of ethnicity/ancestry to ensure a high quality of age estimation. One approach may be the search for “robust” CpG markers—which requires the targeted investigation of different populations, at best by collaborative research with coordinated research strategies.

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Determining the human chronological age from the blood samples on the basis of the analysis of CpG-dinucleotides methylation

Doklady of the National Academy of Sciences of Belarus ◽

10.29235/1561-8323-2021-65-5-582-591 ◽

2021 ◽

Vol 65 (5) ◽

pp. 582-591

Author(s):

V. A. Lemesh ◽

V. N. Kipen ◽

M. V. Bahdanava ◽

A. A. Burakova ◽

A. A. Bulgak ◽

...

Keyword(s):

Dna Methylation ◽

Correlation Coefficients ◽

Chronological Age ◽

Blood Samples ◽

Cpg Dinucleotides ◽

Human Dna ◽

Genome Wide ◽

Average Accuracy ◽

The Republic ◽

Age Prediction

Based on the bioinformatic and statistical analysis of the GEO-projects to determine the genome-wide profile of human DNA methylation, a list of 27 CpG dinucleotides with a high predictive potential was formed to create models for prediction of the human age from blood samples. The methylation level was determined for 245 samples of individuals from the Republic of Belarus. The correlation coefficients R were calculated, and the mathematical models for determining the age of an individual were constructed. The average accuracy value of the age prediction from blood samples using 12 CpG-dinucleotides was 3.4 years (for men – 3.3, for women – 3.5). The results obtained will be used as a basis for development of calculators for predicting the age of an individual based on the biological traces for forensic experts.

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