Biological age estimation using DNA methylation analysis: A systematic review

Epigenetic clocks are accurate predictors of human chronological age based on the analysis of DNA methylation (DNAm) at specific CpG sites. However, a systematic comparison between DNA methylation data and other omics datasets has not yet been performed. Moreover, available DNAm age predictors are based on datasets with limited ethnic representation. To address these knowledge gaps, we generated and analyzed DNA methylation datasets from two independent Chinese cohorts, revealing age-related DNAm changes. Additionally, a DNA methylation aging clock (iCAS-DNAmAge) and a group of DNAm-based multi-modal clocks for Chinese individuals were developed, with most of them demonstrating strong predictive capabilities for chronological age. The clocks were further employed to predict factors influencing aging rates. The DNAm aging clock, derived from multi-modal aging features (compositeAge-DNAmAge), exhibited a close association with multi-omics changes, lifestyles, and disease status, underscoring its robust potential for precise biological age assessment. Our findings offer novel insights into the regulatory mechanism of age-related DNAm changes and extend the application of the DNAm clock for measuring biological age and aging pace, providing the basis for evaluating aging intervention strategies.

The influence of increasing concentrations of heavy metals solutions (Pb(NO3)2, CuSO4, ZnSO4) on the modification of content of proline in the plants Cannabis sativa L was studied. It is supposed that accumulation of amino acid in the plants has an adaptive character concerning stress factors. The dependence of modification of the level of free proline from concentrations of salt in the medium of cultivation was exposed.

Epigenetic clocks were initially developed to track chronological age, but accumulating evidence indicates that they can also predict biological age. They are usually based on the analysis of DNA methylation by genome-wide methods, but targeted approaches, based on the assessment of a small number of CpG sites, are advisable in several settings. In this study, we developed a targeted epigenetic clock purposely optimized for the measurement of biological age. The clock includes six genomic regions mapping in ELOVL2, NHLRC1, AIM2, EDARADD, SIRT7 and TFAP2E genes, selected from a re-analysis of existing microarray data, whose DNA methylation is measured by EpiTYPER assay. In healthy subjects (n = 278), epigenetic age calculated using the targeted clock was highly correlated with chronological age (Spearman correlation = 0.89). Most importantly, and in agreement with previous results from genome-wide clocks, epigenetic age was significantly higher and lower than expected in models of increased (persons with Down syndrome, n = 62) and decreased (centenarians, n = 106; centenarians' offspring, n = 143; nutritional intervention in elderly, n = 233) biological age, respectively. These results support the potential of our targeted epigenetic clock as a new marker of biological age and open its evaluation in large cohorts to further promote the assessment of biological age in healthcare practice.

Age estimation based on the analysis of DNA methylation patterns has become a focus of forensic research within the past few years. However, there is little data available regarding postmortem DNA methylation analysis yet, and literature mainly encompasses analysis of blood from corpses without any signs of decomposition. It is not entirely clear yet which other types of specimen are suitable for postmortem epigenetic age estimation, and if advanced decomposition may affect methylation patterns of CpG sites. In living persons, buccal swabs are an easily accessible source of DNA for epigenetic age estimation. In this work, the applicability of this approach (buccal swabs as source of DNA) under different postmortem conditions was tested. Methylation levels of PDE4C were investigated in buccal swab samples collected from 73 corpses (0–90 years old; mean: 51.2) in different stages of decomposition. Moreover, buccal swab samples from 142 living individuals (0–89 years old; mean 41.2) were analysed. As expected, methylation levels exhibited a high correlation with age in living individuals (training set: r2 = 0.87, validation set: r2 = 0.85). This was also the case in postmortem samples (r2 = 0.90), independent of the state of decomposition. Only in advanced putrified cases with extremely low DNA amounts, epigenetic age estimation was not possible. In conclusion, buccal swabs are a suitable and easy to collect source for DNA methylation analysis as long as sufficient amounts of DNA are present.

Forensic DNA analysis has revolutionized criminal investigations by providing valuable insights into identifying perpetrators, exonerating the innocent and unravelling mysteries of the past. Various molecular biology techniques, such as Short Tandem Repeat (STR) analysis, Single Nucleotide Polymorphism (SNP) profiling, mitochondrial DNA (mtDNA) sequencing, epigenetics and DNA methylation analysis, have played crucial roles in forensic investigations. While these techniques offer exceptional sensitivity and specificity, they also come with unique challenges. This review explores the current approaches of forensic DNA analysis, highlighting each technique. STR analysis, regarded as the gold standard in forensic DNA profiling, provides high discrimination power. However, it is limited in its ability to analyze degraded or mixed samples. On the other hand, SNP profiling offers advantages in analyzing highly degraded DNA samples but lacks the discriminatory power of STRs. Meanwhile, mtDNA analysis, particularly useful in cases involving compromised nuclear DNA, presents challenges due to its maternal inheritance pattern and lower discriminatory power. Furthermore, explore the exciting realm of epigenetics and the analysis of DNA methylation in forensic investigations. Epigenetic markers offer insights into gene expression patterns influenced by environmental factors, potentially aiding in the determination of tissue origin and chronological age estimation. DNA methylation analysis holds promise in forensic applications, providing additional layers of information for identity verification and tissue differentiation. Despite these advancements, several challenges persist in forensic DNA analysis, including the interpretation of complex DNA mixtures, standardization of methodologies, ethical considerations, and privacy concerns associated with the use of genetic information. Moreover, the integration of multi-omics data and machine learning approaches presents both opportunities and challenges in enhancing the accuracy and reliability of forensic DNA analysis. Looking ahead, future directions in molecular biology research for forensic DNA analysis involve the development of novel techniques with increased sensitivity, scalability, and robustness. By addressing these challenges and embracing emerging technologies, the field of forensic DNA analysis is poised for further advancements, offering enhanced capabilities in criminal justice and humanitarian efforts.

Type 2 Diabetes (T2D) correlates with increased biological age (BA) as indicated by clinical biomarkers. Chronological age (CA) is the total years lived, while BA depicts cellular level changes. Our prior data showed that BA was accelerated in Type 1 Diabetes (T1D) and T2D with a large spread of individual BA within these groups. It is unknown whether accelerated age in diabetes mellitus (DM) is also seen at the DNA methylation (DNAm) level, the gold standard to determine BA, and which variables regulate the speed of aging in individuals. We hypothesized that DNAm would reflect accelerated aging in tissues from people with T2D and that specific biomarkers would associate with the speed of aging. The DNAm Phenotypic Age Clock was used to determine BA and showed accelerated aging in whole blood (p=0.01) and pancreatic islets (p=0.03) from people with T2D. Linear regression was used to find associations between biomarkers and speed of aging using the NHANES 2017-18 and ACCORD Trial cohorts. Avoidance of fried foods (p=0.02) and fat intake (p=0.01) , and vigorous activity (p=0.001) correlated with decreased BA in T2D. Biomarkers associated with slower aging (BA<5 years from CA) were higher albumin (p<0.04) , lower globulin (p=5.7x10-5) , lower blood pressure (p<0.005) , higher hemoglobin (p<0.03) and older age at DM diagnosis (p=0.04) . Faster aging (BA>5 years from CA) was associated with higher total and LDL-cholesterol (p<0.003) , pulse (p=0.002) , platelet count (p<0.03) , glycohemoglobin (p<3.6x10-5) and fasting glucose (p<0.04) , and lower self-perception of health (p=0.005) . Normal aging (BA within 5 years of CA) associated with greater ferritin (p=0.03) and moderate-intensity activity at work (p=0.005) . In conclusion, DNAm of blood and islets from people with T2D age faster than those without. Further analysis of specific variables associated with the speed of aging will identify crucial intervention nodes to alter the aging speed in a population with DM. Disclosure B.N.Cortez: None. H.Pan: n/a. C.Aguayo-mazzucato: Consultant; eGenesis.

A major question facing the use of epigenetic therapies in cancer is the specificity in reactivating gene expression. In addition, combined targeting of DNA and histone methylation remains largely unexplored despite the promising synergistic effects observed from combining DNA methyltransferase inhibitors with HDAC inhibitors. To address these questions, we performed RNA-seq in colon cancer (SW48) and breast cancer (MCF7) models treated with a DNA methyltransferase inhibitor (Decitabine/DAC) either alone or in combination with a LSD1 inhibitor (S2101), G9a inhibitor (UNC0638), EZH2 inhibitor (GSK343) or a HDAC inhibitor (Depsipeptide). Additionally, we performed ChIP-seq (H3K4me2, H3K9me2, and H3K27me3) and DNA methylation analysis (DREAM) on SW48 cells. Both low dose (100nM) and intermediate dose (1uM) DAC were very specific in upregulating genes with high levels of DNA methylation (86% and 78% of upregulated genes in SW48 cells, respectively). DAC alone and in combination with S2101, UNC0638, or GSK343 preferentially upregulated genes that were expressed in normal colon and silenced in SW48 cells (443, 718, 728, 1095 genes, respectively) compared to genes that didn't change expression (194, 343, 424, 479 genes, respectively). Additionally, the combination therapies specifically upregulated genes that were not DNA methylated in normal colon but gained methylation in cancer (91%, 85%, 87%, and 79% of upregulated genes, respectively). The combination therapies also preferentially upregulated genes that lost expression in cancer and were silenced by H3K9me2 and/or H3K27me3 (121, 204, 277, 380 genes, respectively) compared to genes that didn't change expression in cancer but were silenced by histone methylation (42, 82, 163, 167 genes, respectively). In contrast, Depsipeptide and the combination of Depsipeptide with DAC induced major expression changes in all genes (2167 and 2938 genes upregulated that were expressed in normal colon and silenced in SW48, compared to 1807 and 2389 genes upregulated with no change in expression, respectively). Furthermore, DAC in combination with S2101, UNC0638, or GSK343 induced a significant number of synergistic genes that were only upregulated with the combination therapy and not with either monotherapy (>490 genes for each inhibitor combination in both cancer models). These synergistic genes showed limited overlap between the three combination therapies (only 7.64% of genes commonly upregulated in YB5, 7.31% in MCF7), and formed distinct clusters in a hierarchical cluster analysis. IPA analysis demonstrated that these genes are enriched in critical cancer regulation pathways such as cell proliferation, cell death, and cell movement. Consistent with this analysis, the combination therapies were able to decrease cancer cell proliferation more effectively than monotherapy. Overall, these results demonstrate that DNA methyltransferase inhibitors preferentially target cancer relevant genes, and can be combined with epigenetic inhibitors targeting histone methylation to increase efficacy while still maintaining specificity. Citation Format: Takahiro Sato, Matteo Cesaroni, Anthony Tran, Jozef Madzo, Yasuyuki Okamoto, Hanghang Zhang, Shoghag Panjarian, Jaroslav Jelinek, Jean-Pierre Issa. Decitabine specifically targets genes that gain DNA methylation and lose expression in cancer and can be combined with histone methylation inhibitors for increased efficacy. [abstract]. In: Proceedings of the AACR Special Conference on Chromatin and Epigenetics in Cancer; Sep 24-27, 2015; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2016;76(2 Suppl):Abstract nr B42.

PurposeSARS-CoV-2 causes a severe inflammatory syndrome (COVID-19) leading, in many cases, to bilateral pneumonia, severe dyspnea and in ~5% of these, death. DNA methylation is known to play an important...

BackgroundEpigenetic age is an estimator of biological age based on DNA methylation; its discrepancy from chronologic age warrants further investigation. We recently reported that greater polyphenol intake benefitted ectopic fats, brain function, and gut microbiota profile, corresponding with elevated urine polyphenols. The effect of polyphenol-rich dietary interventions on biological aging is yet to be determined.MethodsWe calculated different biological aging epigenetic clocks of different generations (Horvath2013, Hannum2013, Li2018, Horvath skin and blood2018, PhenoAge2018, PCGrimAge2022), their corresponding age and intrinsic age accelerations, and DunedinPACE, all based on DNA methylation (Illumina EPIC array; pre-specified secondary outcome) for 256 participants with abdominal obesity or dyslipidemia, before and after the 18-month DIRECT PLUS randomized controlled trial. Three interventions were assigned: healthy dietary guidelines, a Mediterranean (MED) diet, and a polyphenol-rich, low-red/processed meat Green-MED diet. Both MED groups consumed 28 g walnuts/day (+ 440 mg/day polyphenols). The Green-MED group consumed green tea (3–4 cups/day) and Mankai (Wolffia globosa strain) 500-ml green shake (+ 800 mg/day polyphenols). Adherence to the Green-MED diet was assessed by questionnaire and urine polyphenols metabolomics (high-performance liquid chromatography quadrupole time of flight).ResultsBaseline chronological age (51.3 ± 10.6 years) was significantly correlated with all methylation age (mAge) clocks with correlations ranging from 0.83 to 0.95; p < 2.2e − 16 for all. While all interventions did not differ in terms of changes between mAge clocks, greater Green-Med diet adherence was associated with a lower 18-month relative change (i.e., greater mAge attenuation) in Li and Hannum mAge (beta = − 0.41, p = 0.004 and beta = − 0.38, p = 0.03, respectively; multivariate models). Greater Li mAge attenuation (multivariate models adjusted for age, sex, baseline mAge, and weight loss) was mostly affected by higher intake of Mankai (beta = − 1.8; p = 0.061) and green tea (beta = − 1.57; p = 0.0016) and corresponded with elevated urine polyphenols: hydroxytyrosol, tyrosol, and urolithin C (p < 0.05 for all) and urolithin A (p = 0.08), highly common in green plants. Overall, participants undergoing either MED-style diet had ~ 8.9 months favorable difference between the observed and expected Li mAge at the end of the intervention (p = 0.02).ConclusionsThis study showed that MED and green-MED diets with increased polyphenols intake, such as green tea and Mankai, are inversely associated with biological aging. To the best of our knowledge, this is the first clinical trial to indicate a potential link between polyphenol intake, urine polyphenols, and biological aging.Trial registrationClinicalTrials.gov, NCT03020186.

DNA methylation is an epigenetic modification that plays a key role in several cellular processes mediating the fine regulation of gene expression. Aberrant DNA methylation is observed in a wide range of pathologies, including cancer. Since these DNA modifications are transferred to the cell progenies and are stable over the time, the analysis of DNA methylation status has been proposed for diagnostic and prognostic purposes in cancer. Currently, DNA bisulfite conversion is the gold standard method for the high‑throughput analysis of DNA methylation alterations. However, bisulfite treatment induces DNA fragmentation affecting its quality for the downstream analyses. In this field, it is mandatory to identify novel methods to overcome the limits of conventional approaches. In the present study, the Methylation‑Sensitive Restriction Enzyme‑droplet digital PCR (MSRE‑ddPCR) assay was developed as a novel sensitive method for the analysis of DNA methylation of short genomic regions, combining the MSRE assay with the high‑sensitivity ddPCR and using an exogenous methylation sequence as control. Setup and validation experiments were performed analyzing a methylation hotspot of the Solute Carrier Family 22 Member 17 in DNA samples derived from melanoma cell lines as well as from tissues and serum samples obtained from patients with melanoma and healthy controls. Compared with the standard MSRE approaches, the MSRE‑ddPCR assay is more appropriate for the analysis of DNA methylation (methDNA) in samples with low amounts of DNA (up to 0.651 ng) showing a greater sensitivity. These findings suggested the potential clinical application of MSRE‑ddPCR paving the way to the analysis of other methDNA hotspots in different tumors.

While biological age in adults is often understood as representing general health and resilience, the conceptual interpretation of accelerated biological age in children and its relationship to development remains unclear. We aimed to clarify the relationship of accelerated biological age, assessed through two established biological age indicators, telomere length and DNA methylation age, and two novel candidate biological age indicators, to child developmental outcomes, including growth and adiposity, cognition, behavior, lung function and the onset of puberty, among European school-age children participating in the HELIX exposome cohort. The study population included up to 1173 children, aged between 5 and 12 years, from study centres in the UK, France, Spain, Norway, Lithuania, and Greece. Telomere length was measured through qPCR, blood DNA methylation, and gene expression was measured using microarray, and proteins and metabolites were measured by a range of targeted assays. DNA methylation age was assessed using Horvath's skin and blood clock, while novel blood transcriptome and 'immunometabolic' (based on plasma proteins and urinary and serum metabolites) clocks were derived and tested in a subset of children assessed six months after the main follow-up visit. Associations between biological age indicators with child developmental measures as well as health risk factors were estimated using linear regression, adjusted for chronological age, sex, ethnicity, and study centre. The clock derived markers were expressed as Δ age (i.e. predicted minus chronological age). Transcriptome and immunometabolic clocks predicted chronological age well in the test set (r=0.93 and r=0.84 respectively). Generally, weak correlations were observed, after adjustment for chronological age, between the biological age indicators.Among associations with health risk factors, higher birthweight was associated with greater immunometabolic Δ age, smoke exposure with greater DNA methylation Δ age, and high family affluence with longer telomere length.Among associations with child developmental measures, all biological age markers were associated with greater BMI and fat mass, and all markers except telomere length were associated with greater height, at least at nominal significance (p<0.05). Immunometabolic Δ age was associated with better working memory (p=4 e-3) and reduced inattentiveness (p=4 e-4), while DNA methylation Δ age was associated with greater inattentiveness (p=0.03) and poorer externalizing behaviors (p=0.01). Shorter telomere length was also associated with poorer externalizing behaviors (p=0.03). In children, as in adults, biological aging appears to be a multi-faceted process and adiposity is an important correlate of accelerated biological aging. Patterns of associations suggested that accelerated immunometabolic age may be beneficial for some aspects of child development while accelerated DNA methylation age and telomere attrition may reflect early detrimental aspects of biological aging, apparent even in children. UK Research and Innovation (MR/S03532X/1); European Commission (grant agreement numbers: 308333; 874583).

Integrative Genome-Wide DNA Methylation and Gene Expression Analysis Reveals Biological and Clinical Insights In Adult Acute Lymphoblastic Leukemia

Quantitative Analysis of Tissue and Developmental Stage-Specific Differences in DNA Methylation throughout the β-Globin Gene Locus by DNA MassARRAY,

Age prediction in living: Forensic epigenetic age estimation based on blood samples.

Background: Studies on epigenetic alterations and especially DNA methylation in liquid biopsy samples like plasma circulating tumor DNA (ctDNA) and circulating tumor cells (CTCs) are of growing interest nowadays. To ensure the reliability of DNA methylation results prior to any clinical applications in liquid biopsy, there is an urgent need to standardize a plethora of parameters. The aim of our study was to evaluate: a) the stability of DNA methylation in plasma, b) the stability of sodium bisulfite (SB) converted DNA samples under different storage temperatures, and c) the accuracy and precision of whole genome amplification (WGA) protocols for downstream DNA methylation analysis. Methods: a) Stability of DNA methylation in plasma: Plasma from healthy donors was pooled and aliquoted in six tubes and spiked with genomic DNA (gDNA) isolated from 106 MCF-7 cells. Five aliquots were kept at -700C, while one was immediately processed for ctDNA isolation and SB treatment. Stored aliquots were processed in the same way after storage for a period of 3 months. All SB-treated DNA samples were further evaluated by real time methylation specific PCR (MSP) for ACTB and SOX17. b) Stability of SB-treated DNA: gDNA was isolated from 106 SKBR3 cells and processed for downstream SB-treatment. SB-treated DNA was split into aliquots and stored at -20°C and -70°C. One aliquot, used as control, was immediately processed for SB treatment followed by real time MSP for ACTB and BRMS1 amplification. The remaining aliquots were processed in exactly the same way after storage for different time points with a maximum period of one year. Additionally, a sample that was subjected to repeated freeze-thaw cycles was added in each run. c) Evaluation of WGA for SB-treated DNA: we evaluated two different SB conversion kits, EZ DNA Methylation-Gold (Zymo), and Epitect Fast Bisulfite, (Qiagen) in combination with downstream WGA (EpiTect Whole Bisulfitome Kit, Qiagen), using 0%, 100% methylated DNA standards and MCF-7, SKBR3 cell lines. Results: a) DNA methylation in plasma is stable at -700C for at least 3 months, since the average Cqs detected, varied from 1 to 2 cycles for ACTB and SOX17, respectively, b) Quality of SB-treated DNA is not affected by repeated freezing-thawing cycles; SB-treated DNA samples are stable when kept for up to one year both at -200C and -700C. c) Identical results by real time MSP were obtained before and after WGA amplification (Qiagen), after using either the Zymo or Qiagen kits for SB conversion. Conclusions: Plasma and SB-treated DNA samples are stable and can be safely used for multiple real time MSP assays over time when kept at -70°C. Downstream WGA of SB-treated DNA could bypass the limited amount of available sample for liquid biopsy applications. In any case, quality control checking should be included in each step of analysis. Citation Format: Sofia Mastoraki, Maria Chimonidou, Eleni Tzanikou, Evi S. Lianidou. DNA methylation analysis in liquid biopsy: A detailed study on quality control, sample storage and whole genome amplification procedures for downstream applications [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3655.