Epigenetic Aging Signatures Are Coherently Modified in Cancer

Towards a Novel Frontier in the Use of Epigenetic Clocks in Epidemiology

Health problems associated with aging are a major public health concern for the future. Aging is a complex process with wide intervariability among individuals. Therefore, there is a need for innovative public health strategies that target factors associated with aging and the development of tools to assess the effectiveness of these strategies accurately. Novel approaches to measure biological age, such as epigenetic clocks, have become relevant. These clocks use non-sequential variable information from the genome and employ mathematical algorithms to estimate biological age based on DNA methylation levels. Therefore, in the present study, we comprehensively review the current status of the epigenetic clocks and their associations across the human phenome. We emphasize the potential utility of these tools in an epidemiological context, particularly in evaluating the impact of public health interventions focused on promoting healthy aging. Our review describes associations between epigenetic clocks and multiple traits across the life and health span. Additionally, we highlighted the evolution of studies beyond mere associations to establish causal mechanisms between epigenetic age and disease. We explored the application of epigenetic clocks to measure the efficacy of interventions focusing on rejuvenation.

Bidirectional relationship between epigenetic age and brain health events

Chronological age offers an imperfect estimate of the molecular changes that occur with aging. Epigenetic age, which is derived from DNA methylation data, provides a more nuanced representation of aging-related biological processes. This study examines the bidirectional relationship between epigenetic age and the occurrence of brain health events (stroke, dementia, and late-life depression). Using data from the Health and Retirement Study, we analyzed blood samples from over 4,000 participants to determine how epigenetic age relates to past and future brain health events. Study participants with a prior brain health event prior to blood collection were 4% epigenetically older (beta 0.04, SE 0.01), suggesting that these conditions are associated with faster aging than that captured by chronological age. Furthermore, a one standard deviation increase in epigenetic age was associated with 70% higher odds of experiencing a brain health event in the next four years after blood collection (OR 1.70, 95%CI 1.16-2.50), indicating that epigenetic age is not just a consequence but also a predictor of poor brain health. Both results were replicated through Mendelian Randomization analyses, supporting their causal nature. Our findings support the utilization of epigenetic age as a useful biomarker to evaluate the role of interventions aimed at preventing and promoting recovery after a brain health event.

Semimethylation is a feature of diffuse large B-cell lymphoma, and subgroups with poor prognosis are characterized by global hypomethylation and short telomere length

BACKGROUND

Large B-cell lymphoma (LBCL) is the most common lymphoma and is known to be a biologically heterogeneous disease regarding genetic, phenotypic, and clinical features. Although the prognosis is good, one-third has a primary refractory or relapsing disease which underscores the importance of developing predictive biological markers capable of identifying high- and low-risk patients. DNA methylation (DNAm) and telomere maintenance alterations are hallmarks of cancer and aging. Both these alterations may contribute to the heterogeneity of the disease, and potentially influence the prognosis of LBCL.

RESULTS

We studied the DNAm profiles (Infinium MethylationEPIC BeadChip) and relative telomere lengths (RTL) with qPCR of 93 LBCL cases: Diffuse large B-cell lymphoma not otherwise specified (DLBCL, n = 66), High-grade B-cell lymphoma (n = 7), Primary CNS lymphoma (n = 8), and transformation of indolent B-cell lymphoma (n = 12). There was a substantial methylation heterogeneity in DLBCL and other LBCL entities compared to normal cells and other B-cell neoplasms. LBCL cases had a particularly aberrant semimethylated pattern (0.15 ≤ β ≤ 0.8) with large intertumor variation and overall low hypermethylation (β > 0.8). DNAm patterns could not be used to distinguish between germinal center B-cell-like (GC) and non-GC DLBCL cases. In cases treated with R-CHOP-like regimens, a high percentage of global hypomethylation (β < 0.15) was in multivariable analysis associated with worse disease-specific survival (DSS) (HR 6.920, 95% CI 1.499-31.943) and progression-free survival (PFS) (HR 4.923, 95% CI 1.286-18.849) in DLBCL and with worse DSS (HR 5.147, 95% CI 1.239-21.388) in LBCL. These cases with a high percentage of global hypomethylation also had a higher degree of CpG island methylation, including islands in promoter-associated regions, than the cases with less hypomethylation. Additionally, telomere length was heterogenous in LBCL, with a subset of the DLBCL-GC cases accounting for the longest RTL. Short RTL was independently associated with worse DSS (HR 6.011, 95% CI 1.319-27.397) and PFS (HR 4.689, 95% CI 1.102-19.963) in LBCL treated with R-CHOP-like regimens.

CONCLUSION

We hypothesize that subclones with high global hypomethylation and hypermethylated CpG islands could have advantages in tumor progression, e.g. by inactivating tumor suppressor genes or promoting treatment resistance. Our findings suggest that cases with high global hypomethylation and thus poor prognosis could be candidates for alternative treatment regimens including hypomethylating drugs.

Biomarkers of Aging and Relevant Evaluation Techniques: A Comprehensive Review

The risk of developing chronic illnesses and disabilities is increasing with age. To predict and prevent aging, biomarkers relevant to the aging process must be identified. This paper reviews the known molecular, cellular, and physiological biomarkers of aging. Moreover, we discuss the currently available technologies for identifying these biomarkers, and their applications and potential in aging research. We hope that this review will stimulate further research and innovation in this emerging and fast-growing field.

Development and validation of prognostic nomograms for adult with papillary renal cell carcinoma: A retrospective study

OBJECTIVE

The aim of the study was to create two consensus nomograms for predicting Overall Survival (OS) and Cancer-Specific Survival (CSS) in adults with papillary Renal Cell Carcinoma (pRCC).

METHODS

Using the Surveillance, Epidemiology, and End Results databases, a retrospective analysis of 1,074 adults with pRCC from 2004 to 2015 was performed. These patients were then randomly divided into two independent cohorts with a ratio of 7:3 (training cohort: 752; validation cohort: 322). In a retrospective analysis of 752 patients from the training cohort, independent prognostic variables affecting OS and CSS were found. R software was used to create prognostic nomograms based on the findings of Cox regression analysis. The performance of the nomograms was assessed using the Concordance Index (C-index), the Area Under Curve (AUC), a calibration curve, and Decision Curve Analysis (DCA). Data from the 107 postoperative pRCC patients at the Affiliated Hospital of Xuzhou Medical University were used for external validation of the nomogram.

RESULTS

For OS and CSS, the C-indices and AUCs of the training cohort and the validation cohort indicated that the model had excellent discrimination. The DCA demonstrated that the model was clinically applicable, and the calibration curves in the internal and external validations showed that the model's accuracy was high.

CONCLUSION

The authors developed and validated a prognostic nomogram that accurately predicted the 3-, 5-, and 8-year OS and CSS of adults with pRCC. Clinicians can use this knowledge to direct the clinical management and counseling of patients with pRCC.

Comparative prognosis and risk assessment in gallbladder neuroendocrine neoplasms versus adenocarcinomas

Background

Gallbladder neuroendocrine neoplasms (GB-NENs) are a rare malignant disease, with most cases diagnosed at advanced stages, often resulting in poor prognosis. However, studies regarding the prognosis of this condition and its comparison with gallbladder adenocarcinomas (GB-ADCs) have yet to yield convincing conclusions.

Methods

We extracted cases of GB-NENs and GB-ADCs from the Surveillance, Epidemiology, and End Results (SEER) database in the United States. Firstly, we corrected differences in clinical characteristics between the two groups using propensity score matching (PSM). Subsequently, we visualized and compared the survival outcomes of the two groups using the Kaplan-Meier method. Next, we employed the least absolute shrinkage and selection operator (LASSO) regression and Cox regression to identify prognostic factors for GB-NENs and constructed two nomograms for predicting prognosis. These nomograms were validated with an internal validation dataset from the SEER database and an external validation dataset from a hospital. Finally, we categorized patients into high-risk and low-risk groups based on their overall survival (OS) scores.

Results

A total of 7,105 patients were enrolled in the study, comprising 287 GB-NENs patients and, 6,818 GB-ADCs patients. There were substantial differences in clinical characteristics between patients, and GB-NENs exhibited a significantly better prognosis. Even after balancing these differences using PSM, the superior prognosis of GB-NENs remained evident. Independent prognostic factors selected through LASSO and Cox regression were age, histology type, first primary malignancy, tumor size, and surgery. Two nomograms for prognosis were developed based on these factors, and their performance was verified from three perspectives: discrimination, calibration, and clinical applicability using training, internal validation, and external validation datasets, all of which exhibited excellent validation results. Using a cutoff value of 166.5 for the OS nomogram score, patient mortality risk can be identified effectively.

Conclusion

Patients with GB-NENs have a better overall prognosis compared to those with GB-ADCs. Nomograms for GB-NENs prognosis have been effectively established and validated, making them a valuable tool for assessing the risk of mortality in clinical practice.

A study on metabolic characteristics and metabolic markers of gastrointestinal tumors

Tumor cells have significant heterogeneity in metabolism and are closely related to prognosis, gene mutation, and subtype. However, this association has not been demonstrated in reports of gastrointestinal tumors. In this study, we constructed four metabolic subtypes and identified four gene signatures using the expression data and clinical information of 252 metabolism-related genes from TCGA and NCBI databases for gastric adenocarcinoma (STAD) and colorectal cancer (COAD and READ). MC1 had the worst prognosis compared to other classifications. GSig1 was mainly related to drug metabolism and was the highest in MC1 with the worst prognosis, while the other subtypes were mainly related to glucose metabolism pathways. This difference also existed in other different malignant tumors. In addition, metabolic typing was associated with chemotherapeutic drug response and tumor heterogeneity, which indicated that monitoring metabolic typing could contribute to drug efficacy and gene-targeted therapy. In conclusion, we identified differences among subtypes in clinical characteristics such as prognosis and revealed the potential function of metabolic subtype in response to chemotherapeutic agents and oncogene mutations. This work highlighted the potential clinical meaning of metabolic subtype and characteristics in drug therapy and prognosis assessment of malignant tumors.

Are housing circumstances associated with faster epigenetic ageing?

BACKGROUND

Numerous aspects of housing are associated with health. However, the pathways between housing and health, particularly the psychosocial elements of housing, are less well understood. Epigenetic information alongside social survey data offers an opportunity to explore biological ageing, measured using DNA methylation, as a potential pathway through which housing affects health.

METHODS

We use data on housing and DNA methylation from the UK Household Longitudinal Study, linked with prior survey responses from the British Household Panel Survey, covering adults in Great Britain. We explore the association between epigenetic ageing and housing circumstances, both contemporary and historical, using hierarchical regression.

RESULTS

We find that living in a privately rented home is related to faster biological ageing. Importantly, the impact of private renting (coefficient (SE) 0.046 years (0.011) vs owned outright, p<0.001) is greater than the impact of experiencing unemployment (coefficient 0.027 years (0.012) vs employed, p<0.05) or being a former smoker (coefficient 0.021 years (0.005) vs never smoker, p<0.001). When we include historical housing circumstances in the analysis, we find that repeated housing arrears and exposure to pollution/environmental problems are also associated with faster biological ageing.

CONCLUSION

Our results suggest that challenging housing circumstances negatively affect health through faster biological ageing. However, biological ageing is reversible, highlighting the significant potential for housing policy changes to improve health.

Smoking affects epigenetic ageing of lung bronchoalveolar lavage cells in Multiple Sclerosis

BACKGROUND

A compelling body of evidence implicates cigarette smoking and lung inflammation in Multiple Sclerosis (MS) susceptibility and progression. Previous studies have reported epigenetic age (DNAm age) acceleration in blood immune cells and in glial cells of people with MS (pwMS) compared to healthy controls (HC).

OBJECTIVES

We aimed to examine biological ageing in lung immune cells in the context of MS and smoking.

METHODS

We analyzed age acceleration residuals in lung bronchoalveolar lavage (BAL) cells, constituted of mainly alveolar macrophages, from 17 pwMS and 22 HC in relation to smoking using eight DNA methylation-based clocks, namely AltumAge, Horvath, GrimAge, PhenoAge, Zhang, SkinBlood, Hannum, Monocyte clock as well as two RNA-based clocks, which capture different aspects of biological ageing.

RESULTS

After adjustment for covariates, five epigenetic clocks showed significant differences between the groups. Four of them, Horvath (Padj = 0.028), GrimAge (Padj = 4.28 × 10-7), SkinBlood (Padj = 0.001) and Zhang (Padj = 0.02), uncovered the sole effect of smoking on ageing estimates, irrespective of the clinical group. The Horvath, SkinBlood and Zhang clocks showed a negative impact of smoking while GrimAge detected smoking-associated age acceleration in BAL cells. On the contrary, the AltumAge clock revealed differences between pwMS and HC and indicated that, in the absence of smoking, BAL cells of pwMS were epigenetically 5.4 years older compared to HC (Padj = 0.028). Smoking further affected epigenetic ageing in BAL cells of pwMS specifically as non-smoking pwMS exhibited a 10.2-year AltumAge acceleration compared to pwMS smokers (Padj = 0.0049). Of note, blood-derived monocytes did not show any MS-specific or smoking-related AltumAge differences. The difference between BAL cells of pwMS smokers and non-smokers was attributable to the differential methylation of 114 AltumAge-CpGs (Padj < 0.05) affecting genes involved in innate immune processes such as cytokine production, defense response and cell motility. These changes functionally translated into transcriptional differences in BAL cells between pwMS smokers and non-smokers.

CONCLUSIONS

BAL cells of pwMS display inflammation-related and smoking-dependent changes associated to epigenetic ageing captured by the AltumAge clock. Future studies examining potential confounders, such as the distribution of distinct BAL myeloid cell types in pwMS compared to control individuals in relation to smoking may clarify the varying performance and DNAm age estimations among epigenetic clocks.

Development and validation of prognostic nomogram for elderly patients with clear cell renal cell carcinoma based on the SEER database

This study sought to establish nomogram models of overall survival (OS) in patients with elderly clear cell renal cell carcinoma (ECCRCC). The Surveillance, Epidemiology, and End Results database provided data of the ECCRCC-afflicted patients diagnosed during the period from 2010 to 2015. This data was subsequently segregated into the training and validation sets randomly in a 7:3 ratio. The calibration curves, the receiver operating characteristic curves, the decision curve analysis and the Concordance index (C-index) were applied for the model evaluation. 9201 eligible cases from 2010 to 2015 were extracted; 6441 were included in the training cohort and 2760 in the validation cohort. The C-index for the training and validation sets were 0.710 and 0.709, respectively. The receiver operating characteristic and decision curve analysis curves demonstrated that nomograms outperformed the AJCC stage in predictive performance. Moreover, the nomogram was found to match closely with the actual observation, as indicated by the calibration plots. To make predictions with regard to the survival of the ECCRCC-afflicted individuals, and as a guide for treatment, the new nomogram could be used.

Aging and Age-Related Epigenetic Drift in the Pathogenesis of Leukemia and Lymphomas: New Therapeutic Targets

One of the traits of cancer cells is abnormal DNA methylation patterns. The idea that age-related epigenetic changes may partially explain the increased risk of cancer in the elderly is based on the observation that aging is also accompanied by comparable changes in epigenetic patterns. Lineage bias and decreased stem cell function are signs of hematopoietic stem cell compartment aging. Additionally, aging in the hematopoietic system and the stem cell niche have a role in hematopoietic stem cell phenotypes linked with age, such as leukemia and lymphoma. Understanding these changes will open up promising pathways for therapies against age-related disorders because epigenetic mechanisms are reversible. Additionally, the development of high-throughput epigenome mapping technologies will make it possible to identify the "epigenomic identity card" of every hematological disease as well as every patient, opening up the possibility of finding novel molecular biomarkers that can be used for diagnosis, prediction, and prognosis.

Parental education and epigenetic aging in middle-aged and older adults in the United States: A life course perspective

Epigenetic aging is one plausible mechanism by which socioeconomic status (SES) contributes to disparities in morbidity and mortality. Although the association between SES and epigenetic aging is well documented, the role of parental education into adulthood remains understudied. We examined (1) if parental education was independently associated with epigenetic aging, (2) whether upward educational mobility buffered this association, and (3) if the benefit of parental education was differentiated by race/ethnicity. Secondary data analysis of a subsample (n = 3875) of Non-Hispanic [NH] Black, Hispanic, NH White, and NH other race participants from the Venous Blood Study within Health and Retirement Study were examined. Thirteen clocks based on DNA methylation of cytosine-phosphate-guanine sites were used to calculate epigenetic aging. Participants' education (personal) and their report of their respective parent's education (parental; mother's and/or father's) were included as independent variables; several potential confounders were also included. Direct associations and interactions between parental and personal education were estimated via survey-weighted generalized linear models; marginal means for epigenetic aging were estimated and contrasts were made between the education subcategories. Analyses were also stratified by race/ethnicity. Our results showed that higher parental education was independently associated with slower epigenetic aging among four clocks, whereas higher personal education magnified this association among four different epigenetic clocks. Participants with the lowest parental and personal education had higher marginal means (i.e., accelerated aging) compared to participants with the highest parental and personal education, and there was little evidence of upward mobility. These associations were more frequently observed among NH White participants, whereas fewer were observed for Hispanic and NH Black participants. Overall, our findings support that early-life circumstances may be biologically embedded through epigenetic aging, which may also limit the biological benefits associated with one's own education.

Reduced Epigenetic Age in Older Adults With High Sense of Purpose in Life

Psychosocial risk factors have been linked with accelerated epigenetic aging, but little is known about whether psychosocial resilience factors (eg, Sense of Purpose in Life) might reduce epigenetic age acceleration. In this study, we tested if older adults who experience high levels of Purpose might show reduced epigenetic age acceleration. We evaluated the relationship between Purpose and epigenetic age acceleration as measured by 13 DNA methylation (DNAm) "epigenetic clocks" assessed in 1 572 older adults from the Health and Retirement Study (mean age 70 years). We quantified the total association between Purpose and DNAm age acceleration as well as the extent to which that total association might be attributable to demographic factors, chronic disease, other psychosocial variables (eg, positive affect), and health-related behaviors (heavy drinking, smoking, physical activity, and body mass index [BMI]). Purpose in Life was associated with reduced epigenetic age acceleration across 4 "second-generation" DNAm clocks optimized for predicting health and longevity (false discovery rate [FDR] q < 0.0001: PhenoAge, GrimAge, Zhang epigenetic mortality index; FDR q < 0.05: DunedinPoAm). These associations were independent of demographic and psychosocial factors, but substantially attenuated after adjusting for health-related behaviors (drinking, smoking, physical activity, and BMI). Purpose showed no significant association with 9 "first-generation" DNAm epigenetic clocks trained on chronological age. Older adults with greater Purpose in Life show "younger" DNAm epigenetic age acceleration. These results may be due in part to associated differences in health-related behaviors. Results suggest new opportunities to reduce biological age acceleration by enhancing Purpose and its behavioral sequelae in late adulthood.

Reduced epigenetic age in older adults who volunteer

BACKGROUND

Volunteering is associated with improved health and well-being outcomes, including a reduced risk of mortality. However, the biological mechanisms underlying the association between volunteering and healthy aging and longevity have not been well-established. We evaluated if volunteering was associated with reduced epigenetic age acceleration in older adults.

METHODS

We evaluated associations between volunteering and age acceleration, measured by 13 DNA methylation (DNAm) "epigenetic clocks" in 4011 older adults (M_age=69 years; SD_age=10 years) who participated in the Health and Retirement Study. We assessed 9 first-generation clocks (Horvath, Hannum, Horvath Skin, Lin, Garagnani, Vidalbralo, Weidner, Yang, and Bocklandt, which predict chronological age) and 4 second-generation clocks (Zhang, PhenoAge, GrimAge, and DunedinPoAm, which predict future disease or longevity). We quantified the total associations between volunteering and DNAm age acceleration as well as the extent to which these associations might be attributable to potential confounding by individual demographics (e.g., race), social demographics (e.g., income), health factors (e.g., diabetes), and health behaviors (e.g., smoking).

RESULTS

Volunteering was associated with reduced epigenetic age acceleration across 6 epigenetic clocks optimized for predicting health and longevity (False Discovery Rate [FDR] q < 0.0001 for epigenetic clocks: PhenoAge, GrimAge, DunedinPoAm, Zhang mortality, Yang mitotic; FDR q < 0.01: Hannum). These associations were mostly independent of demographic and health factors, but substantially attenuated after adjusting for health behaviors.

CONCLUSION

Volunteering was associated with reduced epigenetic age acceleration in 6 of 13 (mostly second-generation) epigenetic clocks. Results provide preliminary evidence that volunteering might provide health benefits through slower biological aging and implicate health behaviors as one potential mechanism of such effects.

Development and validation of a nomogram to predict cancer-specific survival in middle-aged patients with papillary thyroid cancer: A SEER database study

Background

Thyroid cancer (TC) accounts for more than 90% of endocrine tumours and is a typical head and neck tumour in adults. The aim of this study was to develop a predictive tool to predict cancer-specific survival (CSS) in middle-aged patients with papillary thyroid carcinoma (PTC).

Methods

The patients from 2004 to 2015 were randomly divided into a training cohort (n = 25,342) and a internal validation cohort (n = 10,725). The patients from 2016 to 2018 were treated as an external validation cohort (n = 11353). COX proportional hazard model was used to screen meaningful independent risk factors. These factors were constructed into a nomogram to predict CSS in middle-aged patients with PTC. The performance and accuracy of the nomogram were then evaluated using the concordance index (C-index), calibration curve and the area under the curve (AUC). The clinical value of nomogram was evaluated by decision curve analysis (DCA).

Results

Age, gender, marriage, tumour grade, T stage, N stage, M stage, surgery, chemotherapy, and tumour size were independent prognostic factors. The C-indexes of the training, internal validation, and external validation cohorts were 0.906, 0.887, and 0.962, respectively. The AUC and calibration curves show good accuracy. DCA shows that the clinical value of the nomogram is higher than that of Tumour, Node and Metastasis (TNM) staging.

Conclusion

We developed a new prediction tool to predict CSS in middle-aged patients with PTC. The model has good performance after internal and external validation, which can be friendly to help doctors and patients predict CSS.

Long-term variability in physiological measures in relation to mortality and epigenetic aging: prospective studies in the USA and China

BACKGROUND

Visit-to-visit body weight variability (BWV), pulse rate variability (PRV), and blood pressure variability (BPV) have been respectively linked to multiple health outcomes. The associations of the combination of long-term variability in physiological measures with mortality and epigenetic age acceleration (EAA) remain largely unknown.

METHODS

We constructed a composite score of physiological variability (0-3) of large variability in BWV, PRV, and BPV (the top tertiles) in 2006/2008-2014/2016 in the Health and Retirement Study (HRS) and 2011-2015 in the China Health and Retirement Longitudinal Study (CHARLS). All-cause mortality was documented through 2018. EAA was calculated using thirteen DNA methylation-based epigenetic clocks among 1047 participants in a substudy of the HRS. We assessed the relation of the composite score to the risk of mortality among 6566 participants in the HRS and 6906 participants in the CHARLS by Cox proportional models and then investigated its association with EAA using linear regression models.

RESULTS

A higher score of variability was associated with higher mortality risk in both cohorts (pooled hazard ratio [HR] per one-point increment, 1.27; 95% confidence interval [CI], 1.18, 1.39; P-heterogeneity = 0.344), after adjustment for multiple confounders and baseline physiological measures. Specifically, each SD increment in BWV, PRV, and BPV was related to 21% (95% CI: 15%, 28%), 6% (0%, 13%), and 12% (4%, 19%) higher hazard of mortality, respectively. The composite score was significantly related to EAA in second-generation clocks trained on health outcomes (e.g., standardized coefficient = 0.126 in the Levine clock, 95% CI: 0.055, 0.196) but not in most first-generation clocks trained on chronological age.

CONCLUSIONS

Larger variability in physiological measures was associated with a higher risk of mortality and faster EAA.

A nomogram for predicting cancer-specific survival and overall survival in elderly patients with nonmetastatic renal cell carcinoma

Background

Renal cell carcinoma (RCC) is a common malignant tumor in the elderly, with an increasing trend in recent years. We aimed to construct a nomogram of cancer-specific survival (CSS) and overall survival (OS) in elderly patients with nonmetastatic renal cell carcinoma (nmRCC).

Methods

Clinicopathological information was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program in elderly patients with nmRCC from 2010 to 2015. All patients were randomly assigned to a training cohort (70%) or a validation cohort (30%). Univariate and multivariate Cox regression analyses were used to identify independent risk factors for patient outcomes in the training cohort. A nomogram was constructed based on these independent risk factors to predict the 1-, 3-, and 5-year CSS and OS in elderly patients with nmRCC. We used a range of methods to validate the accuracy and reliability of the model, including the calibration curve, consistency index (C-index), and the area under the receiver operating curve (AUC). Decision curve analysis (DCA) was used to test the clinical utility of the model.

Results

A total of 12,116 patients were enrolled in the study. Patients were randomly assigned to the training cohort (N = 8,514) and validation cohort (N = 3,602). In the training cohort, univariate and multivariate Cox regression analysis showed that age, marriage, tumor histological type, histological tumor grade, TN stage, tumor size, and surgery are independent risk factors for prognosis. A nomogram was constructed based on independent risk factors to predict CSS and OS at 1-, 3-, and 5- years in elderly patients with nmRCC. The C-index of the training and validation cohorts in CSS were 0.826 and 0.831; in OS, they were 0.733 and 0.734, respectively. The AUC results of the training and validation cohort were similar to the C-index. The calibration curve indicated that the observed value is highly consistent with the predicted value, meaning the model has good accuracy. DCA results suggest that the clinical significance of the nomogram is better than that of traditional TNM staging.

Conclusions

We built a nomogram prediction model to predict the 1-, 3- and 5-year CSS and OS of elderly nmRCC patients. This model has good accuracy and discrimination and can help doctors and patients make clinical decisions and active monitoring.

Aging and cancer epigenetics: Where do the paths fork?

Aging and cancer are clearly associated processes, at both the epidemiological and molecular level. Epigenetic mechanisms are good candidates to explain the molecular links between the two phenomena, but recent reports have also revealed considerable differences, particularly regarding the loss of DNA methylation in the two processes. The large-scale generation and availability of genome-wide epigenetic data now permits systematic studies to be undertaken which may help clarify the similarities and differences between aging and cancer epigenetic alterations. In addition, the development of epigenetic clocks provides a new dimension in which to investigate diseases at the molecular level. Here, we examine current and future questions about the roles of DNA methylation mechanisms as causal factors in the processes of aging and cancer so that we may better understand if and how aging-associated epigenetic alterations lead to tumorigenesis. It seems certain that comprehending the molecular mechanisms underlying epigenetic clocks, especially with regard to somatic stem cell aging, combined with applying single-cell epigenetic-age profiling technologies to aging and cancer cohorts, and the integration of existing and upcoming epigenetic evidence within the genetic damage models of aging will prove to be crucial to improving understanding of these two interrelated phenomena.

Methylation associated with long- or short-term survival in glioblastoma patients from the Nordic phase 3 trial

Patients with glioblastoma (GBM) have a poor outcome, but even among patients receiving the same therapies and with good prognostic factors, one can find those with exceptionally short and long survival. From the Nordic trial, which randomized GBM patients of 60 years or older between two radiotherapy arms (60 Gy or 34 Gy) or temozolomide (TMZ), we selected 59 with good prognostic factors. These selected GBM patients were equally distributed according to treatment and MGMT promoter methylation status but had long or short survival. Methylation profiling with the Illumina Infinium Methylation EPIC BeadChip arrays was performed and utilized for methylation-based CNS tumor classification, and pathway enrichment analysis of differentially methylated CpG sites (DMCs), as well as calculation of epigenetic age acceleration with three different algorithms, to compare the long and short survival groups. Samples identified by the classifier as non-GBM IDH wildtype were excluded. DMCs between long- and short-term survivors were found in patients with methylated MGMT promoter treated with TMZ (123,510), those with unmethylated MGMT treated with 60Gy radiotherapy (4,086), and with methylated MGMT promoter treated with 34Gy radiotherapy (39,649). Long-term survivors with methylated MGMT promoter treated with TMZ exhibited hypermethylation of the Wnt signaling and the platelet activation, signaling, and aggregation pathways. The joint analysis of radiotherapy arms revealed 319 DMCs between long- and short-term survivors with unmethylated MGMT and none for samples with methylated MGMT promoter. An analysis comparing epigenetic age acceleration between patients with long- and short-term survival across all treatment arms showed a decreased epigenetic age acceleration for the latter. We identified DMCs for both TMZ and RT-treated patients and epigenetic age acceleration as a potential prognostic marker, but further systematic analysis of larger patient cohorts is necessary for confirmation of their prognostic and/or predictive properties.

Inflammatory aging clock: A cancer clock to characterize the patients’ subtypes and predict the overall survival in glioblastoma

Background: Many biological clocks related to aging have been linked to the development of cancer. A recent study has identified that the inflammatory aging clock was an excellent indicator to track multiple diseases. However, the role of the inflammatory aging clock in glioblastoma (GBM) remains to be explored. This study aimed to investigate the expression patterns and the prognostic values of inflammatory aging (iAge) in GBM, and its relations with stem cells.

Methods: Inflammation-related genes (IRG) and their relations with chronological age in normal samples from the Cancer Genome Atlas (TCGA) were identified by the Spearman correlation analysis. Then, we calculated the iAge and computed their correlations with chronological age in 168 patients with GBM. Next, iAge was applied to classify the patients into high- and low-iAge subtypes. Next, the survival analysis was performed. In addition, the correlations between iAge and stem cell indexes were evaluated. Finally, the results were validated in an external cohort.

Results: Thirty-eight IRG were significantly associated with chronological age (|coefficient| > 0.5), and were used to calculate the iAge. Correlation analysis showed that iAge was positively correlated with chronological age. Enrichment analysis demonstrated that iAge was highly associated with immune cells and inflammatory activities. Survival analysis showed the patients in the low-iAge subtype had significantly better overall survival (OS) than those in the high-iAge subtype (p < 0.001). In addition, iAge outperformed the chronological age in revealing the correlations with stem cell stemness. External validation demonstrated that iAge was an excellent method to classify cancer subtypes and predict survival in patients with GBM.

Conclusions: Inflammatory aging clock may be involved in the GBM via potential influences on immune-related activities. iAge could be used as biomarkers for predicting the OS and monitoring the stem cell.

Development and Validation of a Competitive Risk Model in Elderly Patients With Chromophobe Cell Renal Carcinoma: A Population-Based Study

Background

Renal cell carcinoma (RCC) is the most common renal malignancy in adults, and chromophobe renal cell carcinoma (chRCC) is the third most common subtype of RCC. We aimed to construct a competitive risk model to predict cancer-specific survival (CSS) in elderly patients with chRCC.

Methods

The clinicopathological information of the patients was downloaded from the SEER database, and the patients were randomly divided into the training and validation cohorts. Patients' risk factors for cancer-specific death (CSM) were analyzed using proportional subdistribution hazard (SH). We constructed a competitive risk model to predict the CSS of elderly chRCC patients. Consistency index (C-index), the area under receiver operating curve (AUC), and a calibration curve were used to validate the model's accuracy. Decision curve analysis (DCA) was used to test the clinical value of the model.

Results

A total of 3,522 elderly patients with chRCC were included in the analysis. Patients were randomly assigned to either the training cohort (N = 2,474) or the validation cohort (N = 1,048). SH analysis found that age, race, T, N, and M stage, tumor size, and surgery were risk factors for CSM. We constructed a competitive risk model to predict patients' CSS. In the training set, the model predicted patients' 1-, 3-, and 5-year CSS with C-indices of 82.2, 80.8, and 78.2, respectively. The model predicted patient 1-, 3-, and 5-year CSS in the validation cohort with C-indices of 84.7, 83.4, and 76.9, respectively. The calibration curve showed that the model's predicted value is almost consistent with the observed value, which indicated that the model has good accuracy. The AUC of the training set and validation queue also suggested that the model has good discrimination. The clinical utility of the DCA model in predicting patients' CSS is higher than that of traditional TNM staging.

Conclusions

We constructed a competitive risk model to predict CSS in elderly patients with chRCC. The model has good accuracy and reliability, which can help doctors and patients to make clinical decisions and follow-up strategies.

A Web-Based Prediction Model for Cancer-Specific Survival of Elderly Patients With Clear Cell Renal Cell Carcinoma: A Population-Based Study

Background

Clear cell renal cell carcinoma (ccRCC) is expected in the elderly and poor prognosis. We aim to explore prognostic factors of ccRCC in the elderly and construct a nomogram to predict cancer-specific survival (CSS) in elderly patients with ccRCC.

Methods

Clinicopathological information for all elderly patients with ccRCC from 2004 to 2018 was downloaded from the Surveillance, Epidemiology, and End Results (SEER) program. All patients were randomly assigned to a training cohort (70%) or a validation cohort (30%). Univariate and multivariate Cox regression models were used to identify the independent risk factors for CSS. A new nomogram was constructed to predict CSS at 1-, 3-, and 5 years in elderly patients with ccRCC based on independent risk factors. Subsequently, we used the consistency index (C-index), calibration curves, and the area under the receiver operating curve (AUC) and decision curve analysis (DCA) to test the prediction accuracy of the model.

Results

A total of 33,509 elderly patients with ccRCC were enrolled. Univariate and multivariate Cox regression analyses results showed that age, sex, race, marriage, tumor size, histological grade, tumor, nodes, and metastases (TNM) stage, and surgery were independent risk factors for CSS in elderly patients with ccRCC. We constructed a nomogram to predict CSS in elderly patients with ccRCC. The C-index of the training cohort and validation cohort was 0.81 (95% CI: 0.802-0.818) and 0.818 (95% CI: 0.806-0.830), respectively. The AUC of the training cohort and validation cohort also suggested that the prediction model had good accuracy. The calibration curve showed that the observed value of the prediction model was highly consistent with the predicted value. DCA showed good clinical application value of the nomogram.

Conclusion

In this study, we explored prognostic factors in elderly patients with ccRCC. We found that age, sex, marriage, TNM stage, surgery, and tumor size were independent risk factors for CSS. We constructed a new nomogram to predict CSS in elderly patients with ccRCC with good accuracy and reliability, providing clinical guidance for patients and physicians.

The Transcriptome and Methylome of the Developing and Aging Brain and Their Relations to Gliomas and Psychological Disorders

Mutually linked expression and methylation dynamics in the brain govern genome regulation over the whole lifetime with an impact on cognition, psychological disorders, and cancer. We performed a joint study of gene expression and DNA methylation of brain tissue originating from the human prefrontal cortex of individuals across the lifespan to describe changes in cellular programs and their regulation by epigenetic mechanisms. The analysis considers previous knowledge in terms of functional gene signatures and chromatin states derived from independent studies, aging profiles of a battery of chromatin modifying enzymes, and data of gliomas and neuropsychological disorders for a holistic view on the development and aging of the brain. Expression and methylation changes from babies to elderly adults decompose into different modes associated with the serial activation of (brain) developmental, learning, metabolic and inflammatory functions, where methylation in gene promoters mostly represses transcription. Expression of genes encoding methylome modifying enzymes is very diverse reflecting complex regulations during lifetime which also associates with the marked remodeling of chromatin between permissive and restrictive states. Data of brain cancer and psychotic disorders reveal footprints of pathophysiologies related to brain development and aging. Comparison of aging brains with gliomas supports the view that glioblastoma-like and astrocytoma-like tumors exhibit higher cellular plasticity activated in the developing healthy brain while oligodendrogliomas have a more stable differentiation hierarchy more resembling the aged brain. The balance and specific shifts between volatile and stable and between more irreversible and more plastic epigenomic networks govern the development and aging of healthy and diseased brain.

MKL1 regulates hepatocellular carcinoma cell proliferation, migration and apoptosis via the COMPASS complex and NF-κB signaling

Background

Histone modification plays essential roles in hepatocellular carcinoma (HCC) pathogenesis, but the regulatory mechanisms remain poorly understood. In this study, we aimed to analyze the roles of Megakaryoblastic leukemia 1 (MKL1) and its regulation of COMPASS (complex of proteins associated with Set1) in HCC cells.

Methods

MKL1 expression in clinical tissues and cell lines were detected by bioinformatics, qRT-PCR and western blot. MKL1 expression in HCC cells were silenced with siRNA, followed by cell proliferation evaluation via Edu staining and colony formation, migration and invasion using the Transwell system, and apoptosis by Hoechst staining. HCC cell tumorigenesis was assessed by cancer cell line-based xenograft model, combined with H&E staining and IHC assays.

Results

MKL1 expression was elevated in HCC cells and clinical tissues which was correlated with poor prognosis. MKL1 silencing significantly repressed proliferation, migration, invasion and colony formation but enhanced apoptosis in HepG2 and Huh-7 cells. MKL1 silencing also inhibited COMPASS components and p65 protein expression in HepG2 and Huh-7 cells. HepG2 cell tumorigenesis in nude mice was severely impaired by MKL1 knockdown, resulted into suppressed Ki67 expression and cell proliferation.

Conclusion

MKL1 promotes HCC pathogenesis by regulating hepatic cell proliferation, migration and apoptosis via the COMPASS complex and NF-κB signaling.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-08185-w.

Biomarkers of geroprotection and cardiovascular health: An overview of omics studies and established clinical biomarkers in the context of diet

The slowdown, inhibition, or reversal of age-related decline (as a composite of disease, dysfunction, and, ultimately, death) by diet or natural compounds can be defined as dietary geroprotection. While there is no single reliable biomarker to judge the effects of dietary geroprotection, biomarker signatures based on omics (epigenetics, gene expression, microbiome composition) are promising candidates. Recently, omic biomarkers started to supplement established clinical ones such as lipid profiles and inflammatory cytokines. In this review, we focus on human data. We first summarize the current take on genetic biomarkers based on epidemiological studies. However, most of the remaining biomarkers that we describe, whether omics-based or clinical, are related to intervention studies. Then, because of their promising potential in the context of dietary geroprotection, we focus on the effects of berry-based interventions, which up to now have been mostly described employing clinical markers. We provide an aggregation and tabulation of all the recent systematic reviews and meta-analyses that we could find related to this topic. Finally, we present evidence for the importance of the "nutribiography," that is, the influence that an individual's history of diet and natural compound consumption can have on the effects of dietary geroprotection.

DNA Methylation Age Drift Is Associated with Poor Outcomes and De-Differentiation in Papillary and Follicular Thyroid Carcinomas

Simple Summary

Normal human tissues contain an epigenetic clock resulting from the age-dependent DNA methylation signature, which is the so-called DNA methylation (DNAm) age and can be used to precisely predict chronological age of healthy individuals. Abnormal DNAm age drift has been implicated in cancer risk and pathogenesis. Here, we observed that highly drifted DNAm age (HDDA) occurred in approximately 1/3 tumors derived from patients with papillary and follicular thyroid carcinomas. HDDA is significantly associated with dedifferentiation of tumor cells and poor patient outcomes. Thus, HDDA may serve as a new prognostic factor for thyroid carcinoma.

Abstract

Alterations in global DNA methylation play a critical role in both aging and cancer, and DNA methylation (DNAm) age drift has been implicated in cancer risk and pathogenesis. In the present study, we analyzed the TCGA cohort of papillary and follicular thyroid carcinoma (PTC and FTC) for their DNAm age and association with clinic-pathological features. In 54 noncancerous thyroid (NT) samples, DNAm age was highly correlated with patient chronological age (R² = 0.928, p = 2.6 × 10⁻³¹), but drifted to younger than chronological age in most specimens, especially those from patients >50 years old. DNAm age in 502 tumors was also correlated with patient chronological age, but to a much lesser extent (R² = 0.403). Highly drifted DNAm age (HDDA) was identified in 161 tumors, among which were 101 with DNAm age acceleration while 60 with DNAm age deceleration. Tumors with HDDA were characterized by the robust aberrations in metabolic activities, extracellular microenvironment components and inflammation/immunology responses, and dedifferentiation. Importantly, HDDA in tumors independently predicted shorter disease-free survival of patients. Collectively, NT thyroids from TC patients have younger DNAm age, while HDDA frequently occurs in TCs, and contributes to the TC progression and poor patient outcomes. HDDA may serve as a new prognostic factor for TCs.

Associations of Age, Sex, Race/Ethnicity, and Education With 13 Epigenetic Clocks in a Nationally Representative U.S. Sample: The Health and Retirement Study

BACKGROUND

Many DNA methylation-based indicators have been developed as summary measures of epigenetic aging. We examine the associations between 13 epigenetic clocks, including 4 second generation clocks, as well as the links of the clocks to social, demographic, and behavioral factors known to be related to health outcomes: sex, race/ethnicity, socioeconomic status, obesity, and lifetime smoking pack-years.

METHODS

The Health and Retirement Study is the data source which is a nationally representative sample of Americans over age 50. Assessment of DNA methylation was based on the EPIC chip and epigenetic clocks were developed based on existing literature.

RESULTS

The clocks vary in the strength of their relationships with age, with each other and with independent variables. Second generation clocks trained on health-related characteristics tend to relate more strongly to the sociodemographic and health behaviors known to be associated with health outcomes in this age group.

CONCLUSIONS

Users of this publicly available data set should be aware that epigenetic clocks vary in their relationships to age and to variables known to be related to the process of health change with age.

Specific epigenetic age acceleration patterns among four molecular subtypes of gastric cancer and their prognostic value

Aims: To determine the association of the methylation age (Horvath epigenetic clock) of gastric cancer (GC) tissues with molecular subtypes and patient survival. Materials & methods: Multivariate regression models were used to determine the association of methylation age acceleration (AA) with the clinical and molecular characteristics of 333 GC patients. Results: Relative to the chromosomal instability subtype, the epigenetic AA was 49.8 (95% CI: 42.7-56.9) years for Epstein-Barr virus, 16.1 (10.6-21.6) years for microsatellite instability, and 6.05 (0.1-11.1) years for genomic stability subtype. GC patients with accelerated aging of tumor tissues had better outcomes (adjusted hazard ratio: 3.13; p = 0.03). Differentially methylated probes in patients with accelerated and decelerated methylation aging enriched in pathways including BMP signaling, HMGB1 signaling, STAT3 signaling and human embryonic stem cell pluripotency. Conclusions: Our results highlight the prognostic value of epigenetic AA in GC and suggest that epigenetic AA is also an indicator of molecular subtype in GC.

Implementing Precision Medicine in Human Frailty through Epigenetic Biomarkers

The main epigenetic features in aging are: reduced bulk levels of core histones, altered pattern of histone post-translational modifications, changes in the pattern of DNA methylation, replacement of canonical histones with histone variants, and altered expression of non-coding RNA. The identification of epigenetic mechanisms may contribute to the early detection of age-associated subclinical changes or deficits at the molecular and/or cellular level, to predict the development of frailty, or even more interestingly, to improve health trajectories in older adults. Frailty reflects a state of increased vulnerability to stressors as a result of decreased physiologic reserves, and even dysregulation of multiple physiologic systems leading to adverse health outcomes for individuals of the same chronological age. A key approach to overcome the challenges of frailty is the development of biomarkers to improve early diagnostic accuracy and to predict trajectories in older individuals. The identification of epigenetic biomarkers of frailty could provide important support for the clinical diagnosis of frailty, or more specifically, to the evaluation of its associated risks. Interventional studies aimed at delaying the onset of frailty and the functional alterations associated with it, would also undoubtedly benefit from the identification of frailty biomarkers. Specific to the article yet reasonably common within the subject discipline.

DNA methylation age as a biomarker for cancer

Cancer is well established as an age-associated disease, and there is substantial overlap in the molecular, cellular and physiological changes observed with both ageing and the progression of cancer. Age-specific declines in resilience mechanisms such as DNA repair or epigenetic maintenance may contribute to the development of cancer. These declines may be assessed through biomarkers that measure biological age and through the related concept of "age acceleration". Epigenetic clocks, assessed through DNA methylation levels, are among the most widely used biological age markers in cancer studies. In this review, we discuss the use of DNA methylation ageing measures to predict population cancer incidence, mortality and survival. Blood-based DNA methylation age estimators appear to be promising measures of increased cancer risk and mortality, although their reported effects are generally weak, thus its clinical relevance remains to be validated in large case-cohort and longitudinal studies. Future development of epigenetic and other biological age biomarkers will likely further elucidate the links between ageing and cancer.

Epigenetic age acceleration of early stage hepatocellular carcinoma tightly associated with hepatitis B virus load, immunoactivation, and improved survival

Properly stratifying high-risk individuals with early stage hepatocellular carcinoma (HCC) is essential to identify patients in which the potentially therapies can be offered. To this context, we systematically investigated the prognostic value of epigenetic clock with early stage HCC as well as the association with other molecular characteristics.

We computed DNA methylation (DNAm) age of 256 early stage HCC patients and 50 normal samples from TCGA by Horvath clock model. The characteristics of two DNAm age subgroups were differentiated regarding HBV expression, pathway activity, epigenomic, and genomic alteration. Cox regression and restricted cubic spline (RCS) analysis were utilized to evaluate the prognostic value of epigenetic acceleration.

DNAm age was significantly associated with chronological age in normal tissue but largely disrupted in tumors (P< .001), and showed significant negative correlation with HBV expression (P< .05). We identified two DNAm age groups (DNAmAge-ACC and DNAmAge-DEC), and the former presented with an immunoactive phenotype (all FDRs<0.05 in enrichment analysis), CpG island hypermethylation (P< .001), and lower mutation burden (P= .018). Every 10-year increase in DNAm age was associated with a 18% decrease in fatality after adjustment for major clinical variables; DNAmAge-ACC had 50% lower mortality risk than DNAmAge-DEC (HR: 0.50, 95% CI: 0.27-0.94, P= .03). RCS revealed the fatality risk significantly decreased as epigenetic age accelerated (P = .04). Conclusions.

In summary, we highlighted the prognostic value of epigenetic age acceleration for early stage HCC; better prognosis, relatively lower HBV load, and higher enrichment of immune signatures were tightly associated with epigenetic age accelerated tumors.

RNAAgeCalc: A multi-tissue transcriptional age calculator

Biological aging reflects decline in physiological functions and is an effective indicator of morbidity and mortality. Numerous epigenetic age calculators are available, however biological aging calculators based on transcription remain scarce. Here, we introduce RNAAgeCalc, a versatile across-tissue and tissue-specific transcriptional age calculator. By performing a meta-analysis of transcriptional age signature across multi-tissues using the GTEx database, we identify 1,616 common age-related genes, as well as tissue-specific age-related genes. Based on these genes, we develop new across-tissue and tissue-specific age predictors. We show that our transcriptional age calculator outperforms other prior age related gene signatures as indicated by the higher correlation with chronological age as well as lower median and median error. Our results also indicate that both racial and tissue differences are associated with transcriptional age. Furthermore, we demonstrate that the transcriptional age acceleration computed from our within-tissue predictor is significantly correlated with mutation burden, mortality risk and cancer stage in several types of cancer from the TCGA database, and offers complementary information to DNA methylation age. RNAAgeCalc is available at http://www.ams.sunysb.edu/~pfkuan/softwares.html#RNAAgeCalc, both as Bioconductor and Python packages, accompanied by a user-friendly interactive Shiny app.

Schizophrenia and Epigenetic Aging Biomarkers: Increased Mortality, Reduced Cancer Risk, and Unique Clozapine Effects

BACKGROUND

Schizophrenia (SZ) is associated with increased all-cause mortality, smoking, and age-associated proteins, yet multiple previous studies found no association between SZ and biological age using Horvath's epigenetic clock, a well-established aging biomarker based on DNA methylation. However, numerous epigenetic clocks that may capture distinct aspects of aging have been developed. This study tested the hypothesis that altered aging in SZ manifests in these other clocks.

METHODS

We performed a comprehensive analysis of 14 epigenetic clocks categorized according to what they were trained to predict: chronological age, mortality, mitotic divisions, or telomere length. To understand the etiology of biological age differences, we also examined DNA methylation predictors of smoking, alcohol, body mass index, serum proteins, and cell proportions. We independently analyzed 3 publicly available multiethnic DNA methylation data sets from whole blood, a total of 567 SZ cases and 594 nonpsychiatric controls.

RESULTS

All data sets showed accelerations in SZ for the 3 mortality clocks up to 5 years, driven by smoking and elevated levels of 6 age-associated proteins. The 2 mitotic clocks were decelerated in SZ related to antitumor natural killer and CD8T cells, which may help explain conflicting reports about low cancer rates in epidemiological studies of SZ. One cohort with available medication data showed that clozapine is associated with male-specific decelerations up to 7 years in multiple chronological age clocks.

CONCLUSIONS

Our study demonstrates the utility of studying the various epigenetic clocks in tandem and highlights potential mechanisms by which mental illness influences long-term outcomes, including cancer and early mortality.

Epigenetic age acceleration and clinical outcomes in gliomas

Epigenetic age acceleration-the difference between an individual's DNA methylation age and chronological age-is associated with many diseases including cancer. This study aims to evaluate epigenetic age acceleration as a prognostic biomarker for gliomas. DNA methylation data of gliomas patients (516 low-grade and intermediate-grade gliomas and 140 glioblastoma) were obtained from The Cancer Genome Atlas (TCGA) and patient epigenetic ages were computed using Horvath's age prediction model. We used multivariate linear regression to assess the association of epigenetic age acceleration with tumor molecular subtypes, including Codel, Classic-like, G-CIMP-high, G-CIMP-low, Mesenchymal-like and PA-like. Compared with Codel subtype, epigenetic ages in other molecular subtypes show deceleration after controlling age and race. Age deceleration for Classic-like, G-CIMP-high, G-CIMP-low, Mesenchymal-like and PA-like were 15.42 years (CI: 7.98-22.86, p = 5.38E-05), 25.00 years (CI: 20.79-29.22, p = 4.06E-28), 28.56 years (CI: 14.37-42.74, p = 8.75E-05), 45.34 years (CI: 38.80-51.88, p = 2.15E-36), and 53.58 years (CI: 44.90-62.26, p = 4.81E-30), respectively. Then, Cox proportional hazards regression was used to assess the association of epigenetic age acceleration with patient overall survival. Our results show epigenetic age acceleration is positively associated with patient overall survival (per 10-year age acceleration, HR = 0.89; 95%CI: 0.82-0.97; p = 9.04E-03) in multivariate analysis. When stratified by molecular subtypes, epigenetic age acceleration remains positively associated with patient survival after adjusting age and tumor grade. In conclusion, epigenetic age acceleration is significantly associated with molecular subtypes and patient overall survival in gliomas, indication that epigenetic age acceleration has potential as a quantitative prognostic biomarker for gliomas.

Epigenetic clocks may come out of rhythm-implications for the estimation of chronological age in forensic casework

There is a growing perception that DNA methylation may be influenced by exogenous and endogenous parameters. Knowledge of these factors is of great relevance for the interpretation of DNA-methylation data for the estimation of chronological age in forensic casework. We performed a literature review to identify parameters, which might be of relevance for the prediction of chronological age based on DNA methylation. The quality of age predictions might particularly be influenced by lifetime adversities (chronic stress, trauma/post-traumatic stress disorder (PTSD), violence, low socioeconomic status/education), cancer, obesity and related diseases, infectious diseases (especially HIV and Cytomegalovirus (CMV) infections), sex, ethnicity and exposure to toxins (alcohol, smoking, air pollution, pesticides). Such factors may alter the DNA methylation pattern and may explain the partly high deviations between epigenetic age and chronological age in single cases (despite of low mean absolute deviations) that can also be observed with “epigenetic clocks” comprising a high number of CpG sites. So far, only few publications dealing with forensic age estimation address these confounding factors. Future research should focus on the identification of further relevant confounding factors and the development of models that are “robust” against the influence of such biological factors by systematic investigations under targeted inclusion of diverse and defined cohorts.

Wandering along the epigenetic timeline

BACKGROUND

Increasing life expectancy but also healthspan seems inaccessible as of yet but it may become a reality in the foreseeable future. To extend lifespan, it is essential to unveil molecular mechanisms involved in ageing. As for healthspan, a better understanding of the mechanisms involved in age-related pathologies is crucial.

MAIN BODY

We focus on the epigenetic side of ageing as ageing is traced by specific epigenetic patterns and can be measured by epigenetic clocks. We discuss to what extent exposure to environmental factor, such as alcohol use, unhealthy diet, tobacco and stress, promotes age-related conditions. We focused on inflammation, cancer and Alzheimer's disease. Finally, we discuss strategies to reverse time based on epigenetic reprogramming.

CONCLUSIONS

Reversibility of the epigenetic marks makes them promising targets for rejuvenation. For this purpose, a better understanding of the epigenetic mechanisms underlying ageing is essential. Epigenetic clocks were successfully designed to monitor these mechanisms and the influence of environmental factors. Further studies on age-related diseases should be conducted to determine their epigenetic signature, but also to pinpoint the defect in the epigenetic machinery and thereby identify potential therapeutic targets. As for rejuvenation, epigenetic reprogramming is still at an early stage.

New targeted approaches for epigenetic age predictions

Background

Age-associated DNA methylation changes provide a promising 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 high-throughput analysis.

Results

In this study, we utilized 4647 Illumina BeadChip profiles of blood to select CpG sites that facilitate reliable age-predictions based on pyrosequencing. We demonstrate that the precision of DNA methylation measurements can be further increased with droplet digital PCR (ddPCR). In comparison, bisulfite barcoded amplicon sequencing (BBA-seq) gave slightly lower correlation between chronological age and DNA methylation at individual CpGs, while the age-predictions were overall relatively accurate. Furthermore, BBA-seq data revealed that the correlation of methylation levels with age at neighboring CpG sites follows a bell-shaped curve, often associated with a CTCF binding site. 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 a new approach 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.

Conclusion

Targeted DNA methylation analysis at few age-associated CpGs by pyrosequencing, BBA-seq, and particularly ddPCR enables high precision of epigenetic age-predictions. Furthermore, we demonstrate that the stochastic evolution of age-associated DNA methylation patterns in BBA-seq data enables epigenetic clocks for individual DNA strands.

Blood-derived DNA methylation predictors of mortality discriminate tumor and healthy tissue in multiple organs

Evidence has shown that certain methylation markers derived from blood can mirror corresponding methylation signatures in internal tissues. In the current study, we aimed to investigate two strong epigenetic predictors for life span, derived from blood DNA methylation data, in tissue samples of solid cancer patients. Using data from the Cancer Genome Atlas (TCGA) and the German DACHS study, we compared a mortality risk score (MRscore) and DNAmPhenoAge in paired tumor and adjacent normal tissue samples of patients with lung (N = 69), colorectal (n = 299), breast (n = 90), head/neck (n = 50), prostate (n = 50), and liver (n = 50) cancer. To explore the concordance across tissue and blood, we additionally assessed the two markers in blood samples of colorectal cancer (CRC) cases and matched controls (n = 93) in the DACHS+ study. The MRscore was significantly elevated in tumor tissues compared to normal tissues of all cancers except prostate cancer, for which an opposite pattern was observed. DNAmPhenoAge was consistently higher in all tumor tissues. The MRscore discriminated lung, colorectal, and prostate tumor tissues from normal tissues with very high accuracy [AUCs of 0.87, 0.99 (TCGA) /0.94 (DACHS), and 0.92, respectively]. DNAmPhenoAge accurately discriminated five types of tumor tissues from normal tissues (except prostate cancer), with AUCs of 0.82–0.93. The MRscore was also significantly higher in blood samples of CRC cases than in controls, with areas under the curve (AUC) of 0.74, whereas DNAmPhenoAge did not distinguish cases from controls, with AUC of 0.54. This study provides compelling evidence that blood‐derived DNAm markers could reflect methylation changes in less accessible tissues. Further research should explore the potential use of these findings for cancer diagnosis and early detection.

Molecular Aging Markers in Patients with Klinefelter Syndrome

Molecular aging markers provide the opportunity for biological age determination in humans and to study factors, such as genetic determinants, affecting the ageing process. In males with Klinefelter syndrome (KS, non-mosaic karyotype 47, XXY), which is the most common sex chromosome aneuploidy, age-related morbidity and mortality are increased, and a significantly reduced life span has been observed. The aim of this study was to investigate whether Klinefelter patients exhibit molecular signs of premature ageing. We studied, specifically, age-associated DNA methylation patterns (by pyrosequencing) and relative telomere length (TL; by quantitative polymerase chain reaction) in blood in a cohort of Klinefelter patients (n=178 and 266 for DNA methylation and TL, respectively) aged 18-71 years and compared them to the data of age-matched healthy male (n = 184 and 196 for DNA methylation and TL, respectively) and female controls (n = 50). Age-associated DNA methylation patterns were not indicative of accelerated ageing in Klinefelter men. Significantly longer telomeres were found in the young Klinefelter subjects aged 18-24 years (mean=1.51 vs. 1.09 and 1.26 in female and male controls, respectively). However, telomere length in subsequent age groups showed no difference to controls. Gonosomal aneuploidy in Klinefelter syndrome is associated with higher baseline TL at adolescent age, but comparable TL with progressive age in other age groups.

Epigenetic age acceleration of cervical squamous cell carcinoma converged to human papillomavirus 16/18 expression, immunoactivation, and favourable prognosis

BACKGROUND

Ageing-associated molecular changes have been assumed to trigger malignant transformations and the epigenetic clock, and the DNA methylation age has been shown to be highly correlated with chronological age. However, the associations between the epigenetic clock and cervical squamous cell carcinoma (CSCC) prognosis, other molecular characteristics, and clinicopathological features have not been systematically investigated. To this end, we computed the DNA methylation (DNAm) age of 252 CSCC patients and 200 normal samples from TCGA and three external cohorts by using the Horvath clock model. We characterized the differences in human papillomavirus (HPV) 16/18 expression, pathway activity, genomic alteration, and chemosensitivity between two DNAm age subgroups. We then used Cox proportional hazards regression and restricted cubic spline (RCS) analysis to assess the prognostic value of epigenetic acceleration.

RESULTS

DNAm age was significantly associated with chronological age, but it was differentiated between tumour and normal tissue (P < 0.001). Two DNAm age groups, i.e. DNAmAge-ACC and DNAmAge-DEC, were identified; the former had high expression of the E6/E7 oncoproteins of HPV16/18 (P < 0.05), an immunoactive phenotype (all FDRs < 0.05 in enrichment analysis), CpG island hypermethylation (P < 0.001), and lower mutation load (P = 0.011), including for TP53 (P = 0.002). When adjusted for chronological age and tumour stage, every 10-year increase in DNAm age was associated with a 12% decrease in fatality (HR 0.88, 95% CI 0.78-0.99, P = 0.03); DNAmAge-ACC had a 41% lower mortality risk and 47% lower progression rate than DNAmAge-DEC and was more likely to benefit from chemotherapy. RCS revealed a positive non-linear association between DNAm age and both mortality and progression risk (both, P < 0.05).

CONCLUSIONS

DNAm age is an independent predictor of CSCC prognosis. Better prognosis, overexpression of HPV E6/E7 oncoproteins, and higher enrichment of immune signatures were observed in DNAmAge-ACC tumours.

Dysfunctional epigenetic aging of the normal colon and colorectal cancer risk

Background

Chronological age is a prominent risk factor for many types of cancers including colorectal cancer (CRC). Yet, the risk of CRC varies substantially between individuals, even within the same age group, which may reflect heterogeneity in biological tissue aging between people. Epigenetic clocks based on DNA methylation are a useful measure of the biological aging process with the potential to serve as a biomarker of an individual’s susceptibility to age-related diseases such as CRC.

Methods

We conducted a genome-wide DNA methylation study on samples of normal colon mucosa (N = 334). Subjects were assigned to three cancer risk groups (low, medium, and high) based on their personal adenoma or cancer history. Using previously established epigenetic clocks (Hannum, Horvath, PhenoAge, and EpiTOC), we estimated the biological age of each sample and assessed for epigenetic age acceleration in the samples by regressing the estimated biological age on the individual’s chronological age. We compared the epigenetic age acceleration between different risk groups using a multivariate linear regression model with the adjustment for gender and cell-type fractions for each epigenetic clock. An epigenome-wide association study (EWAS) was performed to identify differential methylation changes associated with CRC risk.

Results

Each epigenetic clock was significantly correlated with the chronological age of the subjects, and the Horvath clock exhibited the strongest correlation in all risk groups (r > 0.8, p < 1 × 10⁻³⁰). The PhenoAge clock (p = 0.0012) revealed epigenetic age deceleration in the high-risk group compared to the low-risk group.

Conclusions

Among the four DNA methylation-based measures of biological age, the Horvath clock is the most accurate for estimating the chronological age of individuals. Individuals with a high risk for CRC have epigenetic age deceleration in their normal colons measured by the PhenoAge clock, which may reflect a dysfunctional epigenetic aging process.

Epigenetic Aging: More Than Just a Clock When It Comes to Cancer

The incidence of cancer, adjusted for secular trends, is directly related to age, and advanced chronologic age is one of the most significant risk factors for cancer. Organismal aging is associated with changes at the molecular, cellular, and tissue levels and is affected by both genetic and environmental factors. The specific mechanisms through which these age-associated molecular changes contribute to the increased risk of aging-related disease, such as cancer, are incompletely understood. DNA methylation, a prominent epigenetic mark, also changes over a lifetime as part of an "epigenetic aging" process. Here, we give an update and review of epigenetic aging, in particular, the phenomena of epigenetic drift and epigenetic clock, with regard to its implication in cancer etiology. We discuss the discovery of the DNA methylation-based biomarkers for biological tissue age and the construction of various epigenetic age estimators for human clinical outcomes and health/life span. Recent studies in various types of cancer point to the significance of epigenetic aging in tumorigenesis and its potential use for cancer risk prediction. Future studies are needed to assess the potential clinical impact of strategies focused on lowering cancer risk by preventing premature aging or promoting healthy aging.

Different epigenetic clocks reflect distinct pathophysiological features of multiple sclerosis

Aim: Accumulating evidence links epigenetic age to diseases and age-related conditions, but little is known about its association with multiple sclerosis (MS). Materials & methods: We estimated epigenetic age acceleration measures using DNA methylation from blood or sorted cells of MS patients and controls. Results: In blood, sex (p = 4.39E-05) and MS (p = 2.99E-03) explained the variation in age acceleration, and isolated blood cell types showed different epigenetic age. Intrinsic epigenetic age acceleration and extrinsic epigenetic age acceleration were only associated with sex (p = 2.52E-03 and p = 1.58E-04, respectively), while PhenoAge Acceleration displayed positive association with MS (p = 3.40E-02). Conclusion: Different age acceleration measures are distinctly influenced by phenotypic factors, and they might measure separate pathophysiological aspects of MS. Data deposition: DNA methylation data can be accessed at Gene Expression Omnibus database under accession number GSE35069, GSE43976, GSE106648, GSE130029, GSE130030.

Association between giant cell glioblastoma and glioblastoma multiforme in the United States: A retrospective cohort study

OBJECTIVES

The current study aims to find the differences between glioblastoma multiforme (GBM) and giant cell glioblastoma (GCG) regarding mortality and prognosis among adults and elderly patients in the U.S.

METHODS AND MATERIALS

This study is a historical cohort type of study and is conducted on adults and elderly individuals with GBM or GCG from the years 1985-2014 in the U.S. Data were collected from the Surveillance, Epidemiology, and End Results Program (SEER) database. The study exposure was GBM or GCG and the outcome was mortality. The potential confounders were age, sex, race, ethnicity, year of diagnosis, primary site, brain overlap, and surgery. A chi-square test was used for categorical data. A univariate analysis was used for variables having a p-value <.05. Potential confounders were selected and evaluated using multivariate logistic regression models to calculate the odds ratio with stepwise selection.

RESULTS

The study sample was 25,117. The incidences of GBM and GCG were not similar in relation to age group. Also, Spanish-Hispanic ethnicity was independently protective of GBM and GCG as compared to Non-Spanish-Hispanic ethnicity patients with GBM have a higher mortality rate than do GCG patients. The mortality rate was higher among patients diagnosed before 2010.

CONCLUSION

GCG was not statistically significant in association to reduced mortality. Non-Spanish-Hispanics with GBM or GCG had a higher mortality rate than did Spanish-Hispanics. Factors such as being female, being age 59-65, and having a year of diagnosis before 2010 were independently associated with increased mortality.

Chicken or Egg: Is Clonal Hematopoiesis Primarily Caused by Genetic or Epigenetic Aberrations?

Hematopoietic malignancies, including multiple myeloma, are associated with characteristic mutations and genetic instabilities that drive malignant transformation. On the other hand, tumor formation is also associated with drastic epigenetic aberrations, which can impact the genetic sequence. Therefore, the question arises if malignant transformation is primarily caused by genetic or epigenetic events. The tight connection of these processes becomes obvious by the fact that in several malignancies, as well as in age-related clonal hematopoiesis, mutations are particularly observed in epigenetic writers such as DNMT3A and TET2. On the other hand, specific epigenetic aberrations, so-called “epimutations,” can mimic genomic mutations. In contrast to the genetic sequence, which remains relatively stable throughout life, the epigenome notoriously undergoes drastic changes in normal hematopoietic development and aging. It is conceivable that such epigenetic reorganization, e.g., in 3D chromatin conformation, paves the way for secondary chromosomal instabilities, which then result in tumor-specific genomic changes that further trigger disease progression. This scenario might explain the occurrence of tumor-specific mutations particularly in the elderly. Taken together, the causality dilemma is difficult to solve because genetic and epigenetic aberrations are interlinked during disease development. A better understanding of how the chromatin structure or 3D nuclear organization can evoke specific mutations might provide new perspectives for prevention, early diagnostics, and targeted therapy.

Relationships of Long-Term Smoking and Moist Snuff Consumption With a DNA Methylation Age Relevant Smoking Index: An Analysis in Buccal Cells

INTRODUCTION

Currently, there is no widely accepted, non-self-report measure that simultaneously reflects smoking behaviors and is molecularly informative of general disease processes. Recently, researchers developed a smoking index (SI) using nucleated blood cells and a multi-tissue DNA methylation-based predictor of chronological age and disease (DNA methylation age [DNAm-age]). To better understand the utility of this novel SI in readily accessible cell types, we used buccal cell DNA methylation to examine SI relationships with long-term tobacco smoking and moist snuff consumption.

METHODS

We used a publicly available dataset composed of buccal cell DNA methylation values from 120 middle-aged men (40 long-term smokers, 40 moist snuff consumers, and 40 nonsmokers). DNAm-age (353-CpGs) and SI (66-CpGs) were calculated using CpG sites measured using the Illumina HumanMethylation450 BeadChip. We estimated associations of tobacco consumption habits with both SI and DNAm-age using linear regression models adjusted for chronological age, race, and methylation technical covariates.

RESULTS

In fully adjusted models with nonsmokers as the reference, smoking (β = 1.08, 95% CI = 0.82 to 1.33, p < .0001) but not snuff consumption (β = .06, 95% CI = -0.19 to 0.32, p = .63) was significantly associated with SI. SI was an excellent predictor of smoking versus nonsmoking (area under the curve = 0.92, 95% CI = 0.85 to 0.98). Four DNAm-age CpGs were differentially methylated between smokers and nonsmokers including cg14992253 [EIF3I], which has been previously shown to be differentially methylated with exposure to long-term fine-particle air pollution (PM2.5).

CONCLUSIONS

The 66-CpG SI appears to be a useful tool for measuring smoking-specific behaviors in buccal cells. Still, further research is needed to broadly confirm our findings and SI relationships with DNAm-age.

IMPLICATIONS

Our findings demonstrate that this 66-CpG blood-derived SI can reflect long-term tobacco smoking, but not long-term snuff consumption, in buccal cells. This evidence will be useful as the field works to identify an accurate non-self-report smoking biomarker that can be measured in an easily accessible tissue. Future research efforts should focus on (1) optimizing the relationship of the SI with DNAm-age so that the metric can maximize its utility as a tool for understanding general disease processes, and (2) determining normal values for the SI CpGs so that the measure is not as study sample specific.

Novel age-associated DNA methylation changes and epigenetic age acceleration in middle-aged African Americans and whites

Background

African Americans (AAs) experience premature chronic health outcomes and longevity disparities consistent with an accelerated aging phenotype. DNA methylation (DNAm) levels at specific CpG positions are hallmarks of aging evidenced by the presence of age-associated differentially methylated CpG positions (aDMPs) that are the basis for the epigenetic clock for measuring biological age acceleration. Since DNAm has not been widely studied among non-European populations, we examined the association between DNAm and chronological age in AAs and whites, and the association between race, poverty, sex, and epigenetic age acceleration.

Results

We measured genome-wide DNA methylation (866,836 CpGs) using the Illumina MethylationEPIC BeadChip in blood DNA extracted from 487 middle-aged AA (N = 244) and white (N = 243), men (N = 248), and women (N = 239). The mean (sd) age was 48.4 (8.8) in AA and 49.0 (8.7) in whites (p = 0.48). We identified 4930 significantly associated aDMPs in AAs and 469 in whites. Of these, 75.6% and 53.1% were novel, largely driven by the increased number of measured CpGs in the EPIC array, in AA and whites, respectively. AAs had more age-associated DNAm changes than whites in genes implicated in age-related diseases and cellular pathways involved in growth and development. We assessed three epigenetic age acceleration measures (universal, intrinsic, and extrinsic). AAs had a significantly slower extrinsic aging compared to whites. Furthermore, compared to AA women, both AA and white men had faster aging in the universal age acceleration measure (+ 2.04 and + 1.24 years, respectively, p < 0.05).

Conclusions

AAs have more wide-spread methylation changes than whites. Race and sex interact to underlie biological age acceleration suggesting altered DNA methylation patterns may be important in age-associated health disparities.

Electronic supplementary material

The online version of this article (10.1186/s13148-019-0722-1) contains supplementary material, which is available to authorized users.

Association of Epigenetic Clock with Consensus Molecular Subtypes and Overall Survival of Colorectal Cancer

BACKGROUND

Epigenetic clock, or DNA methylation age, has been shown to highly correlate with chronologic age. Epigenetic age acceleration, the difference between DNA methylation age and individual's chronologic age, was observed in colorectal cancer. However, the association of epigenetic age acceleration with colorectal cancer tumor molecular characteristics, clinical characteristics, and patient outcomes has not been systematically investigated.

METHODS

DNA methylation ages of 345 patients with colorectal cancer from The Cancer Genome Atlas (TCGA) were computed using the Horvath age prediction model. Multivariate linear regression was used to assess the association of epigenetic age acceleration with molecular and clinical features of colorectal cancer, including consensus molecular subtypes (CMS1-CMS4) and tumor stage Cox proportional hazards regression was used to assess the association of epigenetic age acceleration with survival.

RESULTS

Epigenetic age acceleration is significantly associated with CMS. Compared with CMS2, epigenetic age acceleration for CMS1, CMS3, and CMS4 was 23.90 years [P = 5.55E-11; 95% confidence interval (CI): 17.10-30.69], 9.16 years (P = 5.84E-03; 95% CI: 2.68-15.65), and 6.05 years (P = 2.69E-02; 95% CI: 0.70-11.41), respectively. Furthermore, epigenetic age acceleration is statistically significantly and positively associated with total mortality (HR = 1.97; 95% CI: 1.14-3.39; P = 0.014).

CONCLUSIONS

Epigenetic age acceleration is associated with colorectal cancer tumor molecular characteristics, and a significant predictor of overall survival of colorectal cancer, along with age and tumor stage.

IMPACT

Combining information of colonic tissue epigenetic age acceleration and tumor molecular characteristics may improve prognosis prediction in colorectal cancer.