Epigenetic alterations in aging

Epigenetics in the formation of pathological aggregates in amyotrophic lateral sclerosis

The progressive degeneration of motor neurons in amyotrophic lateral sclerosis (ALS) is accompanied by the formation of a broad array of cytoplasmic and nuclear neuronal inclusions (protein aggregates) largely containing RNA-binding proteins such as TAR DNA-binding protein 43 (TDP-43) or fused in sarcoma/translocated in liposarcoma (FUS/TLS). This process is driven by a liquid-to-solid phase separation generally from proteins in membrane-less organelles giving rise to pathological biomolecular condensates. The formation of these protein aggregates suggests a fundamental alteration in the mRNA expression or the levels of the proteins involved. Considering the role of the epigenome in gene expression, alterations in DNA methylation, histone modifications, chromatin remodeling, non-coding RNAs, and RNA modifications become highly relevant to understanding how this pathological process takes effect. In this review, we explore the evidence that links epigenetic mechanisms with the formation of protein aggregates in ALS. We propose that a greater understanding of the role of the epigenome and how this inter-relates with the formation of pathological LLPS in ALS will provide an attractive therapeutic target.

DeepBAM: a high-accuracy single-molecule CpG methylation detection tool for Oxford nanopore sequencing

Recent nanopore sequencing system (R10.4) has enhanced base calling accuracy and is being increasingly utilized for detecting CpG methylation state. However, the robustness and universality of the methylation calling model in officially supplied Dorado remains poorly tested. In this study, we obtained heterogeneous datasets from human and plant sources to carry out comprehensive evaluations, which showed that Dorado performed significantly different across datasets. We therefore developed deep neural networks and implemented several optimizations in training a new model called DeepBAM. DeepBAM achieved superior and more stable performances compared with Dorado, including higher area under the ROC curves (98.47% on average and up to 7.36% improvement) and F1 scores (94.97% on average and up to 16.24% improvement) across the datasets. DeepBAM-based whole genome methylation frequencies have achieved >0.95 correlations with BS-seq on four of five datasets, outperforming Dorado in all instances. It enables unraveling allele-specific methylation patterns, including regions of transposable elements. The enhanced performance of DeepBAM paves the way for broader applications of nanopore sequencing in CpG methylation studies.

Effective training of nanopore callers for epigenetic marks with limited labelled data

Nanopore sequencing platforms combined with supervised machine learning (ML) have been effective at detecting base modifications in DNA such as 5-methylcytosine (5mC) and N6-methyladenine (6mA). These ML-based nanopore callers have typically been trained on data that span all modifications on all possible DNA [Formula: see text]-mer backgrounds-a complete training dataset. However, as nanopore technology is pushed to more and more epigenetic modifications, such complete training data will not be feasible to obtain. Nanopore calling has historically been performed with hidden Markov models (HMMs) that cannot make successful calls for [Formula: see text]-mer contexts not seen during training because of their independent emission distributions. However, deep neural networks (DNNs), which share parameters across contexts, are increasingly being used as callers, often outperforming their HMM cousins. It stands to reason that a DNN approach should be able to better generalize to unseen [Formula: see text]-mer contexts. Indeed, herein we demonstrate that a common DNN approach (DeepSignal) outperforms a common HMM approach (Nanopolish) in the incomplete data setting. Furthermore, we propose a novel hybrid HMM-DNN approach, amortized-HMM, that outperforms both the pure HMM and DNN approaches on 5mC calling when the training data are incomplete. This type of approach is expected to be useful for calling other base modifications such as 5-hydroxymethylcytosine and for the simultaneous calling of different modifications, settings in which complete training data are not likely to be available.

Targeting the epigenetically older individuals for geroprotective trials: the use of DNA methylation clocks

Chronological age is the most important risk factor for the incidence of age-related diseases. The pace of ageing determines the magnitude of that risk and can be expressed as biological age. Targeting fundamental pathways of human aging with geroprotectors has the potential to lower the biological age and therewith prolong the healthspan, the period of life one spends in good health. Target populations for geroprotective interventions should be chosen based on the ageing mechanisms being addressed and the expected effect of the geroprotector on the primary outcome. Biomarkers of ageing, such as DNA methylation age, can be used to select populations for geroprotective interventions and as a surrogate outcome. Here, the use of DNA methylation clocks for selecting target populations for geroprotective intervention is explored.

In vivo cyclic overexpression of Yamanaka factors restricted to neurons reverses age-associated phenotypes and enhances memory performance

In recent years, there has been success in partially reprogramming peripheral organ cells using cyclic Yamanaka transcription factor (YF) expression, resulting in the reversal of age-related pathologies. In the case of the brain, the effects of partial reprogramming are scarcely known, and only some of its effects have been observed through the widespread expression of YF. This study is the first to exclusively partially reprogram a specific subpopulation of neurons in the cerebral cortex of aged mice. The in vivo model demonstrate that YF expression in postmitotic neurons does not dedifferentiate them, and it avoids deleterious effects observed with YF expression in other cell types. Additionally, our study demonstrates that only cyclic, not continuous, expression of YF result in a noteworthy enhancement of cognitive function in adult mice. This enhancement is closely tied to increased neuronal activation in regions related to memory processes, reversed aging-related epigenetic markers and to increased plasticity, induced by the reorganization of the extracellular matrix. These findings support the therapeutic potential of targeted partial reprogramming of neurons in addressing age-associated phenotypes and neurodegenerative diseases correlated with aging.

Molecular hallmarks of ageing in amyotrophic lateral sclerosis

Amyotrophic lateral sclerosis (ALS) is a fatal, severely debilitating and rapidly progressing disorder affecting motor neurons in the brain, brainstem, and spinal cord. Unfortunately, there are few effective treatments, thus there remains a critical need to find novel interventions that can mitigate against its effects. Whilst the aetiology of ALS remains unclear, ageing is the major risk factor. Ageing is a slowly progressive process marked by functional decline of an organism over its lifespan. However, it remains unclear how ageing promotes the risk of ALS. At the molecular and cellular level there are specific hallmarks characteristic of normal ageing. These hallmarks are highly inter-related and overlap significantly with each other. Moreover, whilst ageing is a normal process, there are striking similarities at the molecular level between these factors and neurodegeneration in ALS. Nine ageing hallmarks were originally proposed: genomic instability, loss of telomeres, senescence, epigenetic modifications, dysregulated nutrient sensing, loss of proteostasis, mitochondrial dysfunction, stem cell exhaustion, and altered inter-cellular communication. However, these were recently (2023) expanded to include dysregulation of autophagy, inflammation and dysbiosis. Hence, given the latest updates to these hallmarks, and their close association to disease processes in ALS, a new examination of their relationship to pathophysiology is warranted. In this review, we describe possible mechanisms by which normal ageing impacts on neurodegenerative mechanisms implicated in ALS, and new therapeutic interventions that may arise from this.

Hypomethylation-Mediated Upregulation of NFE2L3 Promotes Malignant Phenotypes of Clear Cell Renal Cell Carcinoma Cells

This work aimed to study the effect of NFE2 like bZIP transcription factor 3 (NFE2L3) on clear cell renal cell carcinoma (ccRCC) cells and whether NFE2L3 expression was mediated by DNA methylation. Twenty-one ccRCC patients were collected. The gene methylation and expression data of TCGA-KIRC were accessed from TCGA. Candidate methylation driver genes were identified by "MethylMix" package, and finally, NFE2L3 was selected as the target gene. The methylation of NFE2L3 was assayed by Ms PCR and QMSP. mRNA level of NFE2L3 was analyzed by qRT-PCR. Protein level of NFE2L3 was measured by Western blot. Demethylation was performed with methylation inhibitor 5-Aza-2'-deoxycytidine (5-Aza-CdR). Proliferative, migratory, and invasive abilities of ccRCC cells were assayed via cell colony formation assay, scratch healing assay, and transwell assay, respectively. Analysis of TCGA database presented that DNA hypomethylation occurred in the NFE2L3 promoter region in ccRCC tissues. NFE2L3 was significantly upregulated in ccRCC tissues and cells. Its expression in cells treated with 5-Aza-CdR was proportional to the concentration of methylation inhibitor. In cell function experiments, overexpressing NFE2L3 or demethylation could stimulate proliferation, migration, and invasion abilities of ccRCC and normal cells. 5-Aza-CdR treatment rescued repressive impact of knockdown NFE2L3 on malignant phenotypes of ccRCC and normal cells. DNA hypomethylation could induce high expression of NFE2L3 and facilitate malignant phenotypes of ccRCC cells. These results may generate insights into ccRCC therapy.

Evaluation of possible cytotoxic, genotoxic and epigenotoxic effects of titanium dioxide nanoparticles and possible protective effect of melatonin

Nanoparticles (NPs) are particles of matter that are between 1 to 100 nm in diameter. They are suggested to cause toxic effects in both humans and environment thorough different mechanisms. However, their toxicity profile may be different from the parent material. Titanium dioxide (TiO2) NPs are widely used in cosmetic, pharmaceutical and food industries. As a white pigment, the use of TiO2 is used in food coloring, industrial paints, clothing and UV filters has increased tremendously in recent years. Melatonin, on the other hand, is a well-known antioxidant and may prevent oxidative stress caused by a variety of different substances, including NPs. In the current study, we aimed to comparatively investigate the effects of normal-sized TiO2 (220 nm) and nano-sized TiO2 (21 nm) on cytopathology, cytotoxicity, oxidative damage (lipid peroxidation, protein oxidation and glutathione), genotoxicity (8-hydroxydeoxyguanosine), apoptosis (caspase 3, 8 and 9) and epigenetic alterations (global DNA methylation, H3 acetylation) on 3T3 fibroblast cells. In addition, the possible protective effects of melatonin, which is known to have strong antioxidant effects, against the toxicity of TiO2 were also evaluated. Study groups were: a. the control group; b. melatonin group; c. TiO2 group; d. nano-sized TiO2 group; e. TiO2 + melatonin group and f. nano-sized TiO2 + melatonin group. We observed that both normal-sized and nano-sized TiO2 NPs showed significant toxic effects. However, TiO2 NPs caused higher DNA damage and global DNA methylation compared to normal-sized TiO2 whereas normal-sized TiO2 led to lower H3 acetylation vs. TiO2 NPs. Melatonin showed partial protective effect against the toxicity caused by TiO2 NPs.

Metabolomics to Study Human Aging: A Review

In the last years, with the increase in the average life expectancy, the world's population is progressively aging, which entails social, health and economic problems. In this sense, the need to better understand the physiology of the aging process becomes an urgent need. Since the study of aging in humans is challenging, cellular and animal models are widely used as alternatives. Omics, namely metabolomics, have emerged in the study of aging, with the aim of biomarker discovering, which may help to uncomplicate this complex process. This paper aims to summarize different models used for aging studies with their advantages and limitations. Also, this review gathers the published articles referring to biomarkers of aging already discovered using metabolomics approaches, comparing the results obtained in the different studies. Finally, the most frequently used senescence biomarkers are described, along with their importance in understanding aging.

Old age as a risk factor for liver diseases: Modern therapeutic approaches

Recent scientific interest has been directed towards age-related diseases, driven by the significant increase in global life expectancy and the growing population of individuals aged 65 and above. The ageing process encompasses various biological, physiological, environmental, psychological, behavioural, and social changes, leading to an augmented susceptibility to chronic illnesses. Cardiovascular, neurological, musculoskeletal, liver and oncological diseases are prevalent in the elderly. Moreover, ageing individuals demonstrate reduced regenerative capacity and decreased tolerance towards therapeutic interventions, including organ transplantation. Liver diseases, such as non-alcoholic fatty liver disease, alcoholic liver disease, hepatitis, fibrosis, and cirrhosis, have emerged as significant public health concerns. Paradoxically, these conditions remain underestimated despite their substantial global impact. Age-related factors are closely associated with the severity and unfavorable prognosis of various liver diseases, warranting further investigation to enhance clinical management and develop novel therapeutic strategies. This comprehensive review focuses specifically on age-related liver diseases, their treatment strategies, and contemporary practices. It provides a detailed account of the global burden, types, molecular mechanisms, and epigenetic alterations underlying these liver pathologies.

Decelerated Epigenetic Aging in Long Livers

Epigenetic aging is a hot topic in the field of aging research. The present study estimated epigenetic age in long-lived individuals, who are currently actively being studied worldwide as an example of successful aging due to their longevity. We used Bekaert's blood-based age prediction model to estimate the epigenetic age of 50 conditionally "healthy" and 45 frail long-livers over 90 years old. Frailty assessment in long-livers was conducted using the Frailty Index. The control group was composed of 32 healthy individuals aged 20-60 years. The DNA methylation status of 4 CpG sites (ASPA CpG1, PDE4C CpG1, ELOVL2 CpG6, and EDARADD CpG1) included in the epigenetic clock was assessed through pyrosequencing. According to the model calculations, the epigenetic age of long-livers was significantly lower than their chronological age (on average by 21 years) compared with data from the group of people aged 20 to 60 years. This suggests a slowing of epigenetic and potentially biological aging in long livers. At the same time, the obtained results showed no statistically significant differences in delta age (difference between the predicted and chronological age) between "healthy" long livers and long livers with frailty. We also failed to detect sex differences in epigenetic age either in the group of long livers or in the control group. It is possible that the predictive power of epigenetic clocks based on a small number of CpG sites is insufficient to detect such differences. Nevertheless, this study underscores the need for further research on the epigenetic status of centenarians to gain a deeper understanding of the factors contributing to delayed aging in this population.

DNA methylation-based subtypes of acute myeloid leukemia with distinct prognosis and clinical features

Acute myeloid leukemia (AML) is a malignancy of the stem cell precursors of the myeloid lineage. DNA methylation is an important DNA modification that regulates gene expression. Investigating AML heterogeneity based on DNA methylation could be clinically informative for improving clinical diagnosis and prognosis. The AML subtypes based on DNA methylation were identified by unsupervised consensus clustering. The association of these subtypes with gene mutation, copy number variations, immune infiltration and clinical features were further explored. Finally, univariate, LASSO and multivariate cox regression analyses were used to identify prognosis-associated genes and construct risk model for AML patients. In addition, we validated this model by using other datasets and explored the involved biological functions and pathways of its related genes. Three CpG island methylator phenotypes (CIMP-H, CIMP-M and CIMP-L) were identified using the 91 differential CpG sites. Overall survival, morphology, macrophages M0 and monocytes were distinct from each other. The most frequently mutated gene in CIMP-L was DNMT3A while which in CIMP-M that was RUNX1. In addition, the TIDE scores, used to predict the response to immune checkpoint inhibitors, were significantly different among CIMPs. The CIMP-associated prognosis risk model (CPM) using 32 key genes had convinced accuracy of prediction to forecast 0.5-year, 1-year, 3-year and 5-year survival rates. Moreover, the risk score-related genes were significantly enriched in pattern specification process, regionalization, embryonic organ morphogenesis and other critical cancer-related biological functions. We systematically and comprehensively analyzed the DNA methylation in AML. The risk model we constructed is an independent predictor of overall survival in AML and could be used as prognostic factor for AML treatment.

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.

Carvacrol improved learning and memory and attenuated the brain tissue oxidative damage in aged male rats

Introduction: Aging is an unavoidable process in the body that is accompanied by impaired tissue homeostasis and various changes. Carvacrol has attracted considerable attention for its wide range of pharmacological activities. Therefore, this study attempted to explore the protective effect of carvacrol in aged rats.Materiel and methods: The aged rats were given carvacrol (15 or 30 mg/kg/day) for 4 weeks. Morris water maze and passive avoidance tests were used to determine the learning and memory abilities of the rats. The hippocampus and cortex samples were taken for biochemical analysis.Results: In comparison to young control rats, aged control rats showed learning and memory deficits. There was improvement in the Morris water navigation test and passive avoidance test performance in the treatment groups versus the aged control group. An increment in malondialdehyde (MDA) and a decrease in total thiol groups in the hippocampus and cortex samples of aged control rats in comparison to the young control group were observed. Carvacrol decreased MDA levels and increased total thiol groups in the hippocampus and cortex samples of aged rats.Conclusion: Carvacrol improved learning and memory in aged rats, probably through its anti-oxidation effects.

Urgent needs of caregiving in ageing populations with Alzheimer's disease and other chronic conditions: Support our loved ones

The ageing process begins at birth. It is a life-long process, and its exact origins are still unknown. Several hypotheses attempt to describe the normal ageing process, including hormonal imbalance, formation of reactive oxygen species, DNA methylation & DNA damage accumulation, loss of proteostasis, epigenetic alterations, mitochondrial dysfunction, senescence, inflammation, and stem cell depletion. With increased lifespan in elderly individuals, the prevalence of age-related diseases including, cancer, diabetes, obesity, hypertension, Alzheimer's, Alzheimer's disease and related dementias, Parkinson's, and other mental illnesses are increased. These increased age-related illnesses, put tremendous pressure & burden on caregivers, family members, and friends who are living with patients with age-related diseases. As medical needs evolve, the caregiver is expected to experience an increase in duties and challenges, which may result in stress on themselves, and impact their own family life. In the current article, we assess the biological mechanisms of ageing and its effect on body systems, exploring lifestyle and ageing, with a specific focus on age-related disorders. We also discussed the history of caregiving and specific challenges faced by caregivers in the presence of multiple comorbidities. We also assessed innovative approaches to funding caregiving, and efforts to improve the medical system to better organize chronic care efforts, while improving the skill and efficiency of both informal and formal caregivers. We also discussed the role of caregiving in end-of-life care. Our critical analysis strongly suggests that there is an urgent need for caregiving in aged populations and support from local, state, and federal agencies.

Long-term exposure to ambient fine particulate components and leukocyte epigenome-wide DNA Methylation in older men: the Normative Aging Study

BACKGROUND

Epigenome-wide association studies of ambient fine particulate matter (PM2.5) have been reported. However, few have examined PM2.5 components (PMCs) and sources or included repeated measures. The lack of high-resolution exposure measurements is the key limitation. We hypothesized that significant changes in DNA methylation might vary by PMCs and the sources.

METHODS

We predicted the annual average of 14 PMCs using novel high-resolution exposure models across the contiguous U.S., between 2000-2018. The resolution was 50 m × 50 m in the Greater Boston Area. We also identified PM2.5 sources using positive matrix factorization. We repeatedly collected blood samples and measured leukocyte DNAm with the Illumina HumanMethylation450K BeadChip in the Normative Aging Study. We then used median regression with subject-specific intercepts to estimate the associations between long-term (one-year) exposure to PMCs / PM2.5 sources and DNA methylation at individual cytosine-phosphate-guanine CpG sites. Significant probes were identified by the number of independent degrees of freedom approach, using the number of principal components explaining > 95% of the variation of the DNA methylation data. We also performed regional and pathway analyses to identify significant regions and pathways.

RESULTS

We included 669 men with 1,178 visits between 2000-2013. The subjects had a mean age of 75 years. The identified probes, regions, and pathways varied by PMCs and their sources. For example, iron was associated with 6 probes and 6 regions, whereas nitrate was associated with 15 probes and 3 regions. The identified pathways from biomass burning, coal burning, and heavy fuel oil combustion sources were associated with cancer, inflammation, and cardiovascular diseases, whereas there were no pathways associated with all traffic.

CONCLUSIONS

Our findings showed that the effects of PM2.5 on DNAm varied by its PMCs and sources.

Intrinsic and environmental basis of aging: A narrative review

Longevity has been a topic of interest since the beginnings of humanity, yet its aetiology and precise mechanisms remain to be elucidated. Aging is currently viewed as a physiological phenomenon characterized by the gradual degeneration of organic physiology and morphology due to the passage of time where both external and internal stimuli intervene. The influence of intrinsic factors, such as progressive telomere shortening, genome instability due to mutation buildup, the direct or indirect actions of age-related genes, and marked changes in epigenetic, metabolic, and mitochondrial patterns constitute a big part of its underlying endogenous mechanisms. On the other hand, several psychosocial and demographic factors, such as diet, physical activity, smoking, and drinking habits, may have an even more significant impact on shaping the aging process. Consequentially, implementing dietary and exercise patterns has been proposed as the most viable alternative strategy for attenuating the most typical degenerative aging changes, thus increasing the likelihood of prolonging lifespan and achieving successful aging.

DNA 5-methylcytosine detection and methylation phasing using PacBio circular consensus sequencing

Long single-molecular sequencing technologies, such as PacBio circular consensus sequencing (CCS) and nanopore sequencing, are advantageous in detecting DNA 5-methylcytosine in CpGs (5mCpGs), especially in repetitive genomic regions. However, existing methods for detecting 5mCpGs using PacBio CCS are less accurate and robust. Here, we present ccsmeth, a deep-learning method to detect DNA 5mCpGs using CCS reads. We sequence polymerase-chain-reaction treated and M.SssI-methyltransferase treated DNA of one human sample using PacBio CCS for training ccsmeth. Using long (≥10 Kb) CCS reads, ccsmeth achieves 0.90 accuracy and 0.97 Area Under the Curve on 5mCpG detection at single-molecule resolution. At the genome-wide site level, ccsmeth achieves >0.90 correlations with bisulfite sequencing and nanopore sequencing using only 10× reads. Furthermore, we develop a Nextflow pipeline, ccsmethphase, to detect haplotype-aware methylation using CCS reads, and then sequence a Chinese family trio to validate it. ccsmeth and ccsmethphase can be robust and accurate tools for detecting DNA 5-methylcytosines.

Stress, diet, exercise: Common environmental factors and their impact on epigenetic age

Epigenetic aging clocks have gained significant attention as a tool for predicting age-related health conditions in clinical and research settings. They have enabled geroscientists to study the underlying mechanisms of aging and assess the effectiveness of anti-aging therapies, including diet, exercise and environmental exposures. This review explores the effects of modifiable lifestyle factors' on the global DNA methylation landscape, as seen by aging clocks. We also discuss the underlying mechanisms through which these factors contribute to biological aging and provide comments on what these findings mean for people willing to build an evidence-based pro-longevity lifestyle.

Technologies and applications of single-cell DNA methylation sequencing

DNA methylation is the most stable epigenetic modification. In mammals, it usually occurs at the cytosine of CpG dinucleotides. DNA methylation is essential for many physiological and pathological processes. Aberrant DNA methylation has been observed in human diseases, particularly cancer. Notably, conventional DNA methylation profiling technologies require a large amount of DNA, often from a heterogeneous cell population, and provide an average methylation level of many cells. It is often not realistic to collect sufficient numbers of cells, such as rare cells and circulating tumor cells in peripheral blood, for bulk sequencing assays. It is therefore essential to develop sequencing technologies that can accurately profile DNA methylation using small numbers of cells or even single cells. Excitingly, many single-cell DNA methylation sequencing and single-cell omics sequencing technologies have been developed, and applications of these methods have greatly expanded our understanding of the molecular mechanism of DNA methylation. Here, we summaries single-cell DNA methylation and multi-omics sequencing methods, delineate their applications in biomedical sciences, discuss technical challenges, and present our perspective on future research directions.

I kappa B kinase interacting protein as a promising biomarker in pan-cancer: A multi-omics analysis

Background: Human chromosome 12 contains I kappa B kinase interacting protein (IKBIP) is also commonly known as IKIP. The involvement of IKBIP in the growth of tumors has only been discussed in a small number of publications.

Purpose: To explore the role that IKBIP plays in the development of a wide variety of neoplasms, as well as the tumor immunological microenvironment.

Methods: UALCAN, HPA, Genotype Tissue Expression, Cancer Genome Maps, and other datasets were used to analyze IKBIP expression. We thoroughly investigated the predictive importance of IKBIP in pan-cancer, clinical traits, and genetic anomalies. We studied whether there is a link between IKBIP and immune-related genes, microsatellite instability (MSI), and the incidence of tumor mutational burden (TMB). The link between immune cell infiltration and IKBIP expression was examined using data on immune cell infiltration from ImmuCellAI, TIMER2, and earlier studies. Finally, gene set enrichment analysis (GSEA) was performed to determine the signaling pathways associated with IKBIP.

Results: IKBIP is highly expressed in most cancers and is negatively associated with the prognosis of several major cancer types. Furthermore, IKBIP expression was linked to TMB in 13 cancers and MSI in seven cancers. Additionally, IKBIP is associated with numerous immunological and cancer-promoting pathways. Simultaneously, various cancer types have unique tumor-infiltrating immune cell profiles.

Conclusion: IKBIP has the potential to act as a pan-cancer oncogene and is crucial for both carcinogenesis and cancer immunity. Elevated IKBIP expression implies an immunosuppressive environment and may be used as a prognostic biomarker and therapeutic target.

In Vitro Drug Repurposing: Focus on Vasodilators

Drug repurposing aims to identify new therapeutic uses for drugs that have already been approved for other conditions. This approach can save time and resources compared to traditional drug development, as the safety and efficacy of the repurposed drug have already been established. In the context of cancer, drug repurposing can lead to the discovery of new treatments that can target specific cancer cell lines and improve patient outcomes. Vasodilators are a class of drugs that have been shown to have the potential to influence various types of cancer. These medications work by relaxing the smooth muscle of blood vessels, increasing blood flow to tumors, and improving the delivery of chemotherapy drugs. Additionally, vasodilators have been found to have antiproliferative and proapoptotic effects on cancer cells, making them a promising target for drug repurposing. Research on vasodilators for cancer treatment has already shown promising results in preclinical and clinical studies. However, additionally research is needed to fully understand the mechanisms of action of vasodilators in cancer and determine the optimal dosing and combination therapy for patients. In this review, we aim to explore the molecular mechanisms of action of vasodilators in cancer cell lines and the current state of research on their repurposing as a treatment option. With the goal of minimizing the effort and resources required for traditional drug development, we hope to shed light on the potential of vasodilators as a viable therapeutic strategy for cancer patients.

Aging: Epigenetic modifications

Aging is one of the most complex and irreversible health conditions characterized by continuous decline in physical/mental activities that eventually poses an increased risk of several diseases and ultimately death. These conditions cannot be ignored by anyone but there are evidences that suggest that exercise, healthy diet and good routines may delay the Aging process significantly. Several studies have demonstrated that Epigenetics plays a key role in Aging and Aging-associated diseases through methylation of DNA, histone modification and non-coding RNA (ncRNA). Comprehension and relevant alterations in these epigenetic modifications can lead to new therapeutic avenues of age-delaying contrivances. These processes affect gene transcription, DNA replication and DNA repair, comprehending epigenetics as a key factor in understanding Aging and developing new avenues for delaying Aging, clinical advancements in ameliorating aging-related diseases and rejuvenating health. In the present article, we have described and advocated the epigenetic role in Aging and associated diseases.

Improving the effectiveness of anti-aging modalities by using the constrained disorder principle-based management algorithms

Aging is a complex biological process with multifactorial nature underlined by genetic, environmental, and social factors. In the present paper, we review several mechanisms of aging and the pre-clinically and clinically studied anti-aging therapies. Variability characterizes biological processes from the genome to cellular organelles, biochemical processes, and whole organs' function. Aging is associated with alterations in the degrees of variability and complexity of systems. The constrained disorder principle defines living organisms based on their inherent disorder within arbitrary boundaries and defines aging as having a lower variability or moving outside the boundaries of variability. We focus on associations between variability and hallmarks of aging and discuss the roles of disorder and variability of systems in the pathogenesis of aging. The paper presents the concept of implementing the constrained disease principle-based second-generation artificial intelligence systems for improving anti-aging modalities. The platform uses constrained noise to enhance systems' efficiency and slow the aging process. Described is the potential use of second-generation artificial intelligence systems in patients with chronic disease and its implications for the aged population.

Consequences of aberrated DNA methylation in Colon Adenocarcinoma: a bioinformatic-based multi-approach

INTRODUCTION

The biology of colorectal cancer (CRC) is remained to be elucidated. Numerous genetic and epigenetic modifications are in concert to create and progress CRC. DNA methylation as a principal epigenetic factor has gained increased attention and could be utilized for biological studies. This study aims to find novel methylated and downregulated genes with a focus on HAND2 in CRC and decipher the biological consequences.

MATERIAL AND METHOD

Data on DNA methylation from GEO and SMART databases and the expression GEPIA2 database were downloaded. Afterward, a set of hypermethylated and downregulated genes in CRC was chosen by overlapping genes. Consequently, HAND2 was selected as a key gene for further investigation and confirmed with cell lines methylation and expression data. The functions of HAND2 were further analyzed using gene ontology analyses and the protein-protein interaction network.

RESULTS

The methylation (p < 0.01) and expression (p < 0.01) of HAND2 are significantly varied in CRC compared to normal control. The correlation analysis (Pearson's correlation coefficient = -0.44, p = 6.6e-14) conveys that HAND2 significantly downregulated and has a reverse correlation with the methylation status of CpG islands. The biological process analysis of HAND2 target genes conveyed that disruption in HAND2 expression could dysregulate ERK1 and ERK2 signaling pathways.

CONCLUSION

Together, the findings showed that DNA hypermethylation of HAND2 was critical evidence in CRC. Further validation and prospective studies are needed to utilize HAND2 methylation as a promising biomarker.

Comparative analysis of sperm DNA methylation supports evolutionary acquired epigenetic plasticity for organ speciation

Aim: To perform a comparative epigenomic analysis of DNA methylation in spermatozoa from humans, mice, rats and mini-pigs. Materials & methods: Genome-wide DNA methylation analysis was used to compare the methylation profiles of orthologous CpG sites. Transcription profiles of early embryo development were analyzed to provide insight into the association between sperm methylation and gene expression programming. Results: We identified DNA methylation variation near genes related to the central nervous system and signal transduction. Gene expression dynamics at different time points of preimplantation stages were modestly associated with spermatozoal DNA methylation at the nearest promoters. Conclusion: Conserved genomic regions subject to epigenetic variation across different species were associated with specific organ functions, suggesting their potential contribution to organ speciation and long-term adaptation to the environment.

DNA methylation changes and inflammaging in aging-associated diseases

Aging as an inevitable phenomenon is associated with pervasive changes in physiological functions. There is a relationship between aging and the increase of several chronic diseases. Most age-related disorders are accompanied by an underlying chronic inflammatory state, as demonstrated by local infiltration of inflammatory cells and greater levels of proinflammatory cytokines in the bloodstream. Within inflammaging, many epigenetic events, especially DNA methylation, change. During the aging process, due to aberrations of DNA methylation, biological processes are disrupted, leading to the emergence or progression of a variety of human diseases, including cancer, neurodegenerative disorders, cardiovascular disease and diabetes. The focus of this review is on DNA methylation, which is involved in inflammaging-related activities, and how its dysregulation leads to human disorders.

Deep6mAPred: A CNN and Bi-LSTM-based deep learning method for predicting DNA N6-methyladenosine sites across plant species

DNA N6-methyladenine (6mA) is a key DNA modification, which plays versatile roles in the cellular processes, including regulation of gene expression, DNA repair, and DNA replication. DNA 6mA is closely associated with many diseases in the mammals and with growth as well as development of plants. Precisely detecting DNA 6mA sites is of great importance to exploration of 6mA functions. Although many computational methods have been presented for DNA 6mA prediction, there is still a wide gap in the practical application. We presented a convolution neural network (CNN) and bi-directional long-short term memory (Bi-LSTM)-based deep learning method (Deep6mAPred) for predicting DNA 6mA sites across plant species. The Deep6mAPred stacked the CNNs and the Bi-LSTMs in a paralleling manner instead of a series-connection manner. The Deep6mAPred also employed the attention mechanism for improving the representations of sequences. The Deep6mAPred reached an accuracy of 0.9556 over the independent rice dataset, far outperforming the state-of-the-art methods. The tests across plant species showed that the Deep6mAPred is of a remarkable advantage over the state of the art methods. We developed a user-friendly web application for DNA 6mA prediction, which is freely available at http://106.13.196.152:7001/ for all the scientific researchers. The Deep6mAPred would enrich tools to predict DNA 6mA sites and speed up the exploration of DNA modification.

Comprehensive analysis of miRNA-mRNA interactions in ovaries of aged mice

Advanced maternal age and ovarian aging are deleterious to the quantity and quality of oocytes and epigenetic modifications, which can affect the health of offspring. However, relatively little is known about the regulation of microRNA-mediated transcription during ovarian aging. We therefore aimed to identify age-related mRNA and microRNA changes and their interactions in the ovaries of aged mice. We performed QuantSeq 3'mRNA and small RNA sequencing to compare their expression patterns in post-ovulation ovaries from young (12-week-old) and old (44-week-old) mice. Functional annotation and integrative analyses were performed to identify the potential functions of differentially expressed genes and identify binding sites for critical microRNAs. We found 343 differentially expressed genes and 9 microRNAs in our comparison of the two mouse groups, with fold changes >2.0 (P < 0.01). Furthermore, we identified possible direct interactions between 24 differentially expressed mRNAs and 8 microRNAs. The differentially expressed genes are involved in fat digestion and absorption, the PI3K-Akt signaling pathway, serotonergic synapse, and ovarian steroidogenesis, which are important for folliculogenesis and oocyte growth. During ovarian aging, changes in gene expression induce alterations in folliculogenesis, oocyte growth, and steroidogenesis, resulting in decreased oocyte quality and reproductive outcomes.

Leveraging Spaceflight to Advance Cardiovascular Research on Earth

The direct (eg, radiation, microgravity) and indirect (eg, lifestyle perturbations) effects of spaceflight extend across multiple systems resulting in whole-organism cardiovascular deconditioning. For over 50 years, National Aeronautics and Space Administration has continually enhanced a countermeasures program designed to characterize and offset the adverse cardiovascular consequences of spaceflight. In this review, we provide a historical overview of research evaluating the effects of spaceflight on cardiovascular health in astronauts and outline mechanisms underpinning spaceflight-related cardiovascular alterations. We also discuss how spaceflight could be leveraged for aging, industry, and model systems such as human induced pluripotent stem cell-derived cardiomyocytes, organoid, and organ-on-a-chip technologies. Finally, we outline the increasing opportunities for scientists and clinicians to engage in cardiovascular research in space and on Earth.

Role of senescence in the chronic health consequences of COVID-19

While the full impact of COVID-19 is not yet clear, early studies have indicated that upwards of 10% of patients experience COVID-19 symptoms longer than 3 weeks, known as Long-Hauler's Syndrome or PACS (postacute sequelae of SARS-CoV-2 infection). There is little known about risk factors or predictors of susceptibility for Long-Hauler's Syndrome, but older adults are at greater risk for severe outcomes and mortality from COVID-19. The pillars of aging (including cellular senescence, telomere dysfunction, impaired proteostasis, mitochondrial dysfunction, deregulated nutrient sensing, genomic instability, progenitor cell exhaustion, altered intercellular communication, and epigenetic alterations) that contribute to age-related dysfunction and chronic diseases (the "Geroscience Hypothesis") may interfere with defenses against viral infection and consequences of these infections. Heightening of the low-grade inflammation that is associated with aging may generate an exaggerated response to an acute COVID-19 infection. Innate immune system dysfunction that leads to decreased senescent cell removal and/or increased senescent cell formation could contribute to accumulation of senescent cells with both aging and viral infections. These processes may contribute to increased risk for long-term COVID-19 sequelae in older or chronically ill patients. Hence, senolytics and other geroscience interventions that may prolong healthspan and alleviate chronic diseases and multimorbidity linked to fundamental aging processes might be an option for delaying, preventing, or alleviating Long-Hauler's Syndrome.

Stage-differentiated ensemble modeling of DNA methylation landscapes uncovers salient biomarkers and prognostic signatures in colorectal cancer progression

Background

Aberrant DNA methylation acts epigenetically to skew the gene transcription rate up or down, contributing to cancer etiology. A gap in our understanding concerns the epigenomics of stagewise cancer progression. In this study, we have developed a comprehensive computational framework for the stage-differentiated modelling of DNA methylation landscapes in colorectal cancer (CRC).

Methods

The methylation β-matrix was derived from the public-domain TCGA data, converted into M-value matrix, annotated with AJCC stages, and analysed for stage-salient genes using an ensemble of approaches involving stage-differentiated modelling of methylation patterns and/or expression patterns. Differentially methylated genes (DMGs) were identified using a contrast against controls (adjusted p-value <0.001 and |log fold-change of M-value| >2), and then filtered using a series of all possible pairwise stage contrasts (p-value <0.05) to obtain stage-salient DMGs. These were then subjected to a consensus analysis, followed by matching with clinical data and performing Kaplan–Meier survival analysis to evaluate the impact of methylation patterns of consensus stage-salient biomarkers on disease prognosis.

Results

We found significant genome-wide changes in methylation patterns in cancer cases relative to controls agnostic of stage. The stage-differentiated models yielded the following consensus salient genes: one stage-I gene (FBN1), one stage-II gene (FOXG1), one stage-III gene (HCN1) and four stage-IV genes (NELL1, ZNF135, FAM123A, LAMA1). All the biomarkers were significantly hypermethylated in the promoter regions, indicating down-regulation of expression and implying a putative CpG island Methylator Phenotype (CIMP) manifestation. A prognostic signature consisting of FBN1 and FOXG1 survived all the analytical filters, and represents a novel early-stage epigenetic biomarker / target.

Conclusions

We have designed and executed a workflow for stage-differentiated epigenomic analysis of colorectal cancer progression, and identified several stage-salient diagnostic biomarkers, and an early-stage prognostic biomarker panel. The study has led to the discovery of an alternative CIMP-like signature in colorectal cancer, reinforcing the role of CIMP drivers in tumor pathophysiology.

Epigenetic Modifications and Neurodegenerative Disorders: A Biochemical Perspective

Methylations in living cells are methyl groups attached to amino acids, DNA, RNA, and so on. However, their biochemical roles have not been fully defined. A theory has been postulated that methylation leads to hyperconjugation, and the electron-donating feature weakens a nearby chemical bond, which increases the bond length of C⁴-N⁴ of 5-methylcytosine, therefore weakening the C⁴-N⁴ bond and resulting in stronger protonation or hydrogen bonding of the N⁴ nitrogen atom. Protonation can give rise to the generation of mutagenic and carcinogenic strong acids such as HCl, which are also capable of solubilizing stressful, insoluble, and stiff salts. Insoluble and rigid salts such as calcium oxalate and/or calcium phosphate were recently proposed as a primary cause of some neurodegenerative disorders. Protonation of nitrogen atoms in 5-methylcytosine enhances the interaction with negatively charged phosphate groups and contributes to the formation of compact heterochromatin. The electronegativity of the oxygen atoms in the modifications of 5-hydroxymethylcytosine or 5-formylcytosine can shorten the lengths of adjacent bonds with no increase of cation affinity in N⁴. The carboxyl group in 5-carboxylcytosine is a weak acid capable of antagonizing mutagenic HCl and modestly helping solubilize insoluble salts. Electron delocalization of the methyl group in N4-methylcytosine results in a lower affinity of N⁴ to cations. The positive charge at N³ in the resonance structure of 3-methylcytosine is lessened by the electron-donating attribute of the methyl group attached to the N³ atom, consequently reducing acid formation. The electron delocalization of three methyl groups decreases the positive charge in the amino nitrogen in the side group of lysine 4 in histone H3, weakening interactions with phosphate groups and consequently activating gene expression. The carbonyl oxygen in 8-oxo-7,8-dihydroguanine draws protons and accumulates HCl, accounting for its moderate mutation propensity and potential capacity to solubilize stiff salts. The biochemical insight will further our understanding on the crosstalk of genetics and epigenetics in the etiology of neurodegenerative diseases.

PTEN promoter methylation predicts 10-year prognosis in hormone receptor-positive early breast cancer patients who received adjuvant tamoxifen endocrine therapy

Purpose

There remain a lack of biomarkers for endocrine therapy resistance in patients with breast cancer (BC), which is proving to be a great challenge. In vitro experiments have shown that downregulation of PTEN expression leads to resistance to tamoxifen (TAM) in BC cells. We aimed to investigate the predictive role of tumor PTEN promoter methylation and PTEN expression in long-term survival after TAM adjuvant therapy in patients with early-stage BC.

Methods

From 2001 to 2013, 105 patients with stage I–III BC who were treated with standardized adjuvant TAM for 5 years or until relapse in West China Hospital (WCH) were enrolled in this study. PTEN expression and DNA methylation of three specified sequences from the PTEN promoter in primary tumors were measured using immunohistochemistry and pyrosequencing. A cohort of 159 hormone receptor-positive patients receiving TAM treatment from The Cancer Genome Atlas (TCGA) database was used for verification.

Results

Median follow-up time for the WCH cohort was 141.7 months. The low, moderate, and high PTEN expression groups had differing 10-year disease-free survival (DFS) (42.3%, 55%, 81%, respectively, P = 0.027) and overall survival (OS) rates (65%, 84.2%, 90.5%, respectively, P = 0.027). Higher methylation levels of the second sequence (− 819 to − 787 bp), rather than the first (− 1143 to − 1107 bp) or third sequence (− 663 to − 593 bp), independently increased the risk of disease recurrence (hazard ratio = 2.60) and death (hazard ratio = 3.79) in the WCH cohort, according to multivariate Cox regression analysis. Importantly, out of the five CpG islands located within this sequence, only high methylation of the − 796 CpG island predicted shorter DFS and OS. In TCGA validation cohort, there was also a trend of higher methylation of the − 796 CpG island correlating with shorter disease-free intervals, with borderline significance (P = 0.057).

Conclusion

Low PTEN expression and high methylation of its promoter (sequence − 819 to − 787 bp) in tissue predict poor DFS and OS in hormone receptor-positive early BC patients who received adjuvant TAM.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10549-021-06463-6.

DNA Methylation Imputation Across Platforms

In this chapter, we will provide a review on imputation in the context of DNA methylation, specifically focusing on a penalized functional regression (PFR) method we have previously developed. We will start with a brief review of DNA methylation, genomic and epigenomic contexts where imputation has proven beneficial in practice, and statistical or computational methods proposed for DNA methylation in the recent literature (Subheading 1). The rest of the chapter (Subheadings 2-4) will provide a detailed review of our PFR method proposed for across-platform imputation, which incorporates nonlocal information using a penalized functional regression framework. Subheading 2 introduces commonly employed technologies for DNA methylation measurement and describes the real dataset we have used in the development of our method: the acute myeloid leukemia (AML) dataset from The Cancer Genome Atlas (TCGA) project. Subheading 3 comprehensively reviews our method, encompassing data harmonization prior to model building, the actual building of penalized functional regression model, post-imputation quality filter, and imputation quality assessment. Subheading 4 shows the performance of our method in both simulation and the TCGA AML dataset, demonstrating that our penalized functional regression model is a valuable across-platform imputation tool for DNA methylation data, particularly because of its ability to boost statistical power for subsequent epigenome-wide association study. Finally, Subheading 5 provides future perspectives on imputation for DNA methylation data.

Short- and intermediate-term exposure to ambient fine particulate elements and leukocyte epigenome-wide DNA methylation in older men: the Normative Aging Study

BACKGROUND

Several epigenome-wide association studies (EWAS) of ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM_2.5) have been reported. However, EWAS of PM_2.5 elements (PEs), reflecting different emission sources, are very limited.

OBJECTIVES

We performed EWAS of short- and intermediate-term exposure to PM_2.5 and 13 PEs. We hypothesized that significant changes in DNAm may vary by PM_2.5 mass and its elements.

METHODS

We repeatedly collected blood samples in the Normative Aging Study and measured leukocyte DNA methylation (DNAm) with the Illumina HumanMethylation450K BeadChip. We collected daily PM_2.5 and 13 PEs at a fixed central site. To estimate the associations between each PE and DNAm at individual cytosine-phosphate-guanine (CpG) sites, we incorporated a distributed-lag (0-27 d) term in the setting of median regression with subject-specific intercept and examined cumulative lag associations. We also accounted for selection bias due to loss to follow-up and mortality prior to enrollment. Significantly differentially methylated probes (DMPs) were identified using Bonferroni correction for multiple testing. We further conducted regional and pathway analyses to identify significantly differentially methylated regions (DMRs) and pathways.

RESULTS

We included 695 men with 1,266 visits between 1999 and 2013. The subjects had a mean age of 75 years. The significant DMPs, DMRs, and pathways varied by to PM_2.5 total mass and PEs. For example, PM_2.5 total mass was associated with 2,717 DMPs and 10,470 DMRs whereas Pb was associated with 3,173 DMPs and 637 DMRs. The identified pathways by PM_2.5 mass were mostly involved in mood disorders, neuroplasticity, immunity, and inflammation, whereas the pathways associated with motor vehicles (BC, Cu, Pb, and Zn) were related with cardiovascular disease and cancer (e.g., "PPARs signaling").

CONCLUSIONS

PM_2.5 and PE were associated with methylation changes at multiple probes and along multiple pathways, in ways that varied by particle components.

Association of Promoter Methylation and Expression of Inflammatory Genes IL-6 and TNF-α with the Risk of Coronary Artery Disease in Diabetic and Obese Subjects among Asian Indians

The inflammatory cytokines such as interleukin-6 (IL-6) and tumour necrosis factor-alpha (TNF-α) are considered as the most important contributors to the endothelial dysfunction in subjects with type 2 diabetes mellitus (T2DM) and obesity. The hypomethylation of CpG sites in the promoter region of the IL-6 and TNF-α have shown to be associated with the increased expression of IL-6 and TNF-α. However, there are no studies on the methylation and expression of IL-6 and TNF-α with the risk of coronary artery disease (CAD) in subjects with T2DM and obesity in Asian Indians. Hence, the present study was aimed to investigate whether the IL-6, TNF-α promoter methylation and expression in blood leukocyte DNA is associated with the risk of CAD in diabetic and obese subjects in Asian Indians. For this study, we recruited 574 subjects which includes, 207 angiographically confirmed CAD patients, 100 T2DM patients, 82 obese subjects and 185 healthy controls. The methylation status of IL-6 and TNF-α gene loci was determined by methylation specific PCR (MPCR) and gene expression was determined by qPCR. We found significant hypomethylation of IL-6 in CAD and T2DM subjects (OR 1.98 95% CI: 1.32-2.97, p = 0.001, OR: 2.23 95% CI:1.34-3.76, p = 0.001, respectively). Further, a significant increase in the expression of IL-6 in CAD and T2DM subjects (fold change: 26.39 & 14.7, p = 0.0001) compared to the control subjects was observed. A significant increase in the hypomethylation of TNF-α in CAD, T2DM and obese subjects was observed as compared to the control (OR: 2.04 95% CI: 1.36-3.05, p = 0.0005, OR: 1.81 95% CI 1.10-2.96, p = 0.01, and OR: 2.1 95% CI 1.24-3.57, p = 0.007, respectively).We also found an increased expression of TNF-α in CAD, T2DM and obese subjects as compared to controls. In addition, presence of low folate, and hyperhomocysteinemia was observed in the present study, may be the contributing factors for the hypomethylation of IL-6 and TNF-α and oxidative stress. In conclusion, increased expression of IL-6 and TNF-α due to hypomethylation in T2DM and obese individuals may contribute to CAD risk in these subjects. The presence of hyperhomocysteinemia and increased oxidative risk may enhance the CAD risk further.

The bladder epicheck test and cytology in the follow-up of patients with non-muscle-invasive high grade bladder carcinoma

BACKGROUND

The management of non-muscle invasive bladder carcinoma (NMIBC) after transurethral resection of a bladder tumor consists of adjuvant intravesical therapy and strict and long surveillance with urine cytology and cystoscopy. The Bladder EpiCheck test (Nucleix Ltd) (BE) is a newly developed urinary markers based on DNA methylation changes in a panel of 15 genomic biomarkers, with a promising performance in term of non-invasive NMIBC detection.

METHODS

In this study we prospectively enrolled 151 consecutive patients with high grade NMIBC, treated with intravesical BCG and mitomycin C therapy and evaluated during the follow-up by voided urine cytology and white-light cystoscopy, according to the European Association of Urology Guidelines. The Bladder EpiCheck test was performed at the same time of urine cytology in voided specimen. In all cases with positive cytology the diagnosis was confirmed by histology and a diagnosis was made according to the 2017 tumor, node, metastasis (TNM) classification and graded using both the 1973 and the 2004 World Health Organization (WHO) classifications.

RESULTS

At three months of follow-up, we reported similar overall specificity rates for BE and urine cytology (85,1% vs 86,3%). In the group of patients with carcinoma in situ (CIS), we found the same specificity for BE and urine cytology (81,4%), while in the groups of patients with papillary high grade NMIBC, the specificity of BE was higher compared to cytology (96,3% vs 90,4%). The sensitivity of BE was always higher compared to cytology during all the follow-up both for papillary NMIBC and CIS.

CONCLUSION

In the early follow-up of NMIBC the EpiCheck test might replace urinary cytology.

How Immunosenescence and Inflammaging May Contribute to Hyperinflammatory Syndrome in COVID-19

Aging is characterized by the dynamic remodeling of the immune system designated “immunosenescence,” and is associated with altered hematopoiesis, thymic involution, and lifelong immune stimulation by multitudinous chronic stressors, including the cytomegalovirus (CMV). Such alterations may contribute to a lowered proportion of naïve T-cells and to reduced diversity of the T-cell repertoire. In the peripheral circulation, a shift occurs towards accumulations of T and B-cell populations with memory phenotypes, and to accumulation of putatively senescent and exhausted immune cells. The aging-related accumulations of functionally exhausted memory T lymphocytes, commonly secreting pro-inflammatory cytokines, together with mediators and factors of the innate immune system, are considered to contribute to the low-grade inflammation (inflammaging) often observed in elderly people. These senescent immune cells not only secrete inflammatory mediators, but are also able to negatively modulate their environments. In this review, we give a short summary of the ways that immunosenescence, inflammaging, and CMV infection may cause insufficient immune responses, contribute to the establishment of the hyperinflammatory syndrome and impact the severity of the coronavirus disease 2019 (COVID-19) in elderly people.

Application of droplet digital PCR method for DNA methylation-based age prediction from saliva

The recent studies reported that DNA methylation markers show changes with age, and expected that the DNA methylation markers can be effectively used for estimation of age in forensic genetics. In this study, we applied droplet digital PCR (ddPCR) method to investigate the DNA methylation pattern in the CpG sites, and we constructed an age prediction model based on the ddPCR method. The ddPCR is capable of highly sensitive quantitation of nucleic acid and detection of sequence variations in gene by separating the sample into large number of partitions and clonally amplifying nucleic acids in each partition. We extracted DNA from saliva samples collected from several age groups. The DNA was bisulfite converted and subjected to ddPCR using specifically designed primers and probes. The methylation ratio of each sample was calculated and correlation between the methylation ratio and the chronological age was analyzed. In the results, methylated DNA ratio at the 4 CpG sites (cg14361627, cg14361627, cg08928145 and cg07547549) showed strong correlation with chronological age. Percent-methylation values at 4 CpG markers and chronological ages of the 76 individuals were analyzed by multiple regression analysis, and we constructed an age prediction model. We observed a strong correlation (Spearman's rho = 0.922) between predicted and chronological ages of 76 individuals with a MAD from chronological age of 3.3 years. Collectively, the result in this study showed the potential applicability of ddPCR to predict age from saliva.

DeepMP: a deep learning tool to detect DNA base modifications on Nanopore sequencing data

MOTIVATION

DNA methylation plays a key role in a variety of biological processes. Recently, Nanopore long-read sequencing has enabled direct detection of these modifications. As a consequence, a range of computational methods have been developed to exploit Nanopore data for methylation detection. However, current approaches rely on a human-defined threshold to detect the methylation status of a genomic position and are not optimized to detect sites methylated at low frequency. Furthermore, most methods use either the Nanopore signals or the basecalling errors as the model input and do not take advantage of their combination.

RESULTS

Here, we present DeepMP, a convolutional neural network-based model that takes information from Nanopore signals and basecalling errors to detect whether a given motif in a read is methylated or not. Besides, DeepMP introduces a threshold-free position modification calling model sensitive to sites methylated at low frequency across cells. We comprehensively benchmarked DeepMP against state-of-the-art methods on Escherichia coli, human and pUC19 datasets. DeepMP outperforms current approaches at read-based and position-based methylation detection across sites methylated at different frequencies in the three datasets.

AVAILABILITY AND IMPLEMENTATION

DeepMP is implemented and freely available under MIT license at https://github.com/pepebonet/DeepMP.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Integrative Predictive Modeling of Metastasis in Melanoma Cancer Based on MicroRNA, mRNA, and DNA Methylation Data

Introduction: Despite the significant progress in understanding cancer biology, the deduction of metastasis is still a challenge in the clinic. Transcriptional regulation is one of the critical mechanisms underlying cancer development. Even though mRNA, microRNA, and DNA methylation mechanisms have a crucial impact on the metastatic outcome, there are no comprehensive data mining models that combine all transcriptional regulation aspects for metastasis prediction. This study focused on identifying the regulatory impact of genetic biomarkers for monitoring metastatic molecular signatures of melanoma by investigating the consolidated effect of miRNA, mRNA, and DNA methylation.

Method: We developed multiple machine learning models to distinguish the metastasis by integrating miRNA, mRNA, and DNA methylation markers. We used the TCGA melanoma dataset to differentiate between metastatic melanoma samples by assessing a set of predictive models. For this purpose, machine learning models using a support vector machine with different kernels, artificial neural networks, random forests, AdaBoost, and Naïve Bayes are compared. An iterative combination of differentially expressed miRNA, mRNA, and methylation signatures is used as a candidate marker to reveal each new biomarker category’s impact. In each iteration, the performances of the combined models are calculated. During all comparisons, the choice of the feature selection method and under and oversampling approaches are analyzed. Selected biomarkers of the highest performing models are further analyzed for the biological interpretation of functional enrichment.

Results: In the initial model, miRNA biomarkers can identify metastatic melanoma with an 81% F-score. The addition of mRNA markers upon miRNA increased the F-score to 92%. In the final integrated model, the addition of the methylation data resulted in a similar F-score of 92% but produced a stable model with low variance across multiple trials.

Conclusion: Our results support the role of miRNA regulation in metastatic melanoma as miRNA markers model metastasis outcomes with high accuracy. Moreover, the integrated evaluation of miRNA with mRNA and methylation biomarkers increases the model’s power. It populates selected biomarkers on the metastasis-associated pathways of melanoma, such as the “osteoclast”, “Rap1 signaling”, and “chemokine signaling” pathways.

Source Code:https://github.com/aysegul-kt/MelonomaMetastasisPrediction/

Upper urothelial tract high-grade carcinoma: comparison of urine cytology and DNA methylation analysis in urinary samples

Numerous studies showed that bladder urothelial carcinoma and upper urothelial tract carcinoma (UTUC) display clinical and genomic similarities. In order to analyze that the same panel of biomarkers used in the diagnosis of bladder urothelial carcinoma could be suitable for early detection of UTUC, we performed a retrospective study in which we analyzed Bladder EpiCheck scores in the urinary samples obtained by selective ureteral catheterization in a high-grade UTUC cohort, correlating the results with urinary cytology and diagnostic urethral biopsies. The present study represents a retrospective analysis of 82 patients with clinically localized high-grade UTUC (60 renal pelvis UTUC, 22 ureter UTUC) who had undergone a radical nephroureterectomy (RNU) at our Urology department from June 2018 to November 2020. Before any surgical procedure, one sample of urine, obtained by selective ureteral catheterization, was collected for each patient for cytological examination, and the remaining material was stored for the Bladder EpiCheck test. Our results showed that the sensitivity of the methylation test for high-grade UTUC was about 97.4%, significantly higher than the sensitivity of urinary cytology either considering the HGUC cytological diagnosis or including in the positive cases the SHGUC cytological diagnosis (97.4% versus 59% or 70.5%). The methylation analysis of urinary samples may represent a valid tool in the diagnostic process of patients with suspected UTUC. In cases with a difficult clinical decision after upper urinary tract biopsy and cytology, the methylation test could assist in the clinical management of UTUC patients.

CUE: CpG impUtation ensemble for DNA methylation levels across the human methylation450 (HM450) and EPIC (HM850) BeadChip platforms

DNA methylation at CpG dinucleotides is one of the most extensively studied epigenetic marks. With technological advancements, geneticists can profile DNA methylation with multiple reliable approaches. However, profiling platforms can differ substantially in the CpGs they assess, consequently hindering integrated analysis across platforms. Here, we present CpG impUtation Ensemble (CUE), which leverages multiple classical statistical and modern machine learning methods, to impute from the Illumina HumanMethylation450 (HM450) BeadChip to the Illumina HumanMethylationEPIC (HM850) BeadChip. Data were analysed from two population cohorts with methylation measured both by HM450 and HM850: the Extremely Low Gestational Age Newborns (ELGAN) study (n = 127, placenta) and the VA Boston Posttraumatic Stress Disorder (PTSD) genetics repository (n = 144, whole blood). Cross-validation results show that CUE achieves the lowest predicted root-mean-square error (RMSE) (0.026 in PTSD) and the highest accuracy (99.97% in PTSD) compared with five individual methods tested, including k-nearest-neighbours, logistic regression, penalized functional regression, random forest, and XGBoost. Finally, among all 339,033 HM850-only CpG sites shared between ELGAN and PTSD, CUE successfully imputed 289,604 (85.4%) sites, where success was defined as RMSE < 0.05 and accuracy >95% in PTSD. In summary, CUE is a valuable tool for imputing CpG methylation from the HM450 to HM850 platform.

Epigenetics of Triple-negative breast cancer via natural compounds

Triple-negative breast cancer (TNBC) is a highly resistant, lethal, and metastatic sub-division of breast carcinoma, characterized by the deficiency of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). In women, TNBC shows a higher aggressive behavior with poor patient prognosis and a higher recurrence rate during reproductive age. TNBC is defined by the presence of epithelial-to-mesenchymal-transition (EMT), which shows a significant role in cancer progression. At the epigenetic level, TNBC is characterized by epigenetic signatures, such as DNA methylation, histone remodeling, and a host of miRNA, MiR-193, LncRNA, HIF-2α, eEF2K, LIN9/NEK2, IMP3, LISCH7/TGF-β1, GD3s and KLK12 mediated regulation. These modifications either are silenced or activate the necessary genes that are prevalent in TNBC. The review is based on epigenetic mediated mechanistic changes in TNBC. Furthermore, Thymoquinone (TQ), Regorafenib, Fangjihuangqi decoction, Saikosaponin A, and Huaier, etc., are potent antitumor natural compounds extensively reported in the literature. Further, the review emphasizes the role of these natural compounds in TNBC and their possible epigenetic targets, which can be utilized as a potential therapeutic strategy in treatment of TNBC.

Histone Acetylation Dynamics during In Vivo and In Vitro Oocyte Aging in Common Carp Cyprinus carpio

Aging is the most critical factor that influences the quality of post-ovulatory oocytes. Age-related molecular pathways remain poorly understood in fish oocytes. In this study, we examined the effect of oocyte aging on specific histone acetylation in common carp Cyprinus carpio. The capacity to progress to the larval stage in oocytes that were aged for 28 h in vivo and in vitro was evaluated. Global histone modifications and specific histone acetylation (H3K9ac, H3K14ac, H4K5ac, H4K8ac, H4K12ac, and H4K16ac) were investigated during oocyte aging. Furthermore, the activity of histone acetyltransferase (HAT) was assessed in fresh and aged oocytes. Global histone modifications did not exhibit significant alterations during 8 h of oocyte aging. Among the selected modifications, H4K12ac increased significantly at 28 h post-stripping (HPS). Although not significantly different, HAT activity exhibited an upward trend during oocyte aging. Results of our current study indicate that aging of common carp oocytes for 12 h results in complete loss of egg viability rates without any consequence in global and specific histone modifications. However, aging oocytes for 28 h led to increased H4K12ac. Thus, histone acetylation modification as a crucial epigenetic mediator may be associated with age-related defects, particularly in oocytes of a more advanced age.

Coronavirus Disease 19 and Future Ecological Crises: Hopes from Epigenomics and Unraveling Genome Regulation in Humans and Infectious Agents

With coronavirus disease 19 (COVID-19), we have witnessed a shift from public health to planetary health and a growing recognition of the importance of systems science in developing effective solutions against pandemics in the 21st century. COVID-19 and the history of frequent infectious outbreaks in the last two decades suggest that COVID-19 is likely a dry run for future ecological crises. Now is the right time to plan ahead and deploy the armamentarium of systems science scholarship for planetary health. The science of epigenomics, which investigates both genetic and nongenetic traits regarding heritable phenotypic alterations, and new approaches to understanding genome regulation in humans and pathogens offer veritable prospects to boost the global scientific capacities to innovate therapeutics and diagnostics against novel and existing infectious agents. Several reversible epigenetic alterations, such as chromatin remodeling and histone methylation, control and influence gene expression. COVID-19 lethality is linked, in part, to the cytokine storm, age, and status of the immune system in a given person. Additionally, due to reduced human mobility and daily activities, effects of the pandemic on the environment have been both positive and negative. For example, reduction in environmental pollution and lesser extraction from nature have potential positive corollaries on water and air quality. Negative effects include pollution as plastics and other materials were disposed in unconventional places and spaces in the course of the pandemic. I discuss the opportunities and challenges associated with the science of epigenomics, specifically with an eye to inform and prevent future ecological crises and pandemics that are looming on the horizon in the 21st century. In particular, this article underscores that epigenetics of both viruses and the host may influence virus infectivity and severity of attendant disease.