DNA methylation analysis on purified neurons and glia dissects age and Alzheimer's disease-specific changes in the human cortex

Profiling of Circulating Cell-free DNA Methylation Patterns Identifies Aberrant Methylated CTBP1 Promotor Sites for Prediction of Alzheimer's Disease

BACKGROUND

Alzheimer's disease (AD) is the most common neurodegenerative disease affecting the elderly, with its diagnosis at early stages crucial for effective intervention. Recent evidence increasingly supports the role of epigenetic alterations in AD pathogenesis, highlighting the need for innovative biomarkers that reflect these changes. This study aimed to characterize the genome-wide DNA methylation profiles of cell-free DNA in peripheral blood for potential biomarkers associated with AD.

METHODS

The Illumina Infinium array was utilized to detect the methylation patterns of circulating cell-free DNA from AD patients and healthy controls. The R Bioconductor Linear Models for Microarray Data (LIMMA) package was employed to identify methylation variable positions (MVPs), and Probe Lasso was used to pinpoint differentially methylated regions (DMRs) linked to AD. Bioinformatics enrichment analysis of the annotated genes was performed using EnrichR. A second cohort was recruited to validate the methylation changes at the C-terminal binding protein1 (CTBP1) promoter cytosine-phosphate-guanine (CpG) sites via pyrosequencing. Additionally, microarray data from the Gene Expression Omnibus (GEO) database were analyzed to further validate gene expression and immune infiltration.

RESULTS

A unique DNA methylation landscape in peripheral blood was characterized for AD patients and 4335 MVPs showed significant differential methylation (p < 0.01). Functional annotation and pathway enrichment analysis underscored processes and pathways inherent in the nervous system. Probe Lasso identified 68 DMRs annotated to 10 genes, with hypermethylation of CpG islands in the CTBP1 TSS1500 promoter showing significant differences when AD and controls were compared (p < 0.01), with an area under the receiver operating characteristic (ROC) curve (AUC) of 0.779. Analysis of immune cell infiltration revealed CTBP1 expression is significantly correlated with altered distribution of immune cells (p < 0.001), underscoring its potential role in modulating immune responses in AD. Moreover, CTBP1 expression levels significantly varied across multiple GEO datasets.

CONCLUSIONS

AD displays distinct DNA methylation patterns in peripheral blood and CTBP1 promoter hypermethylation represents a promising potential biomarker for AD diagnosis.

Exploration of Epigenetic Mechanisms and Biomarkers Among Patients with Very-Late-Onset Schizophrenia-Like Psychosis

Objective

This study aimed to identify DNA methylation patterns associated with Very Late-Onset Schizophrenia-like Psychosis (VLOSLP) and to develop methylation-based biomarkers that differentiate VLOSLP from Schizophrenia (SCZ) and Alzheimer's Disease (AD).

Methods

We analyzed methylation microarray datasets (n = 1218) from SCZ and AD patients obtained from the GEO database. We then collected blood samples from VLOSLP patients and age-matched healthy controls (n = 80) at the Wuxi Mental Health Center for methylation microarray profiling and bisulfite sequencing validation. Differential methylation analysis and Gene Ontology (GO) enrichment analysis identified candidate loci. We prioritized key methylation sites through integrated analysis of methylation quantitative trait loci (meQTL), linkage disequilibrium (LD) patterns, and blood-brain methylation correlations. Machine learning algorithms generated diagnostic models, with classification performance evaluated using Area Under the Curve (AUC) metrics.

Results

Analysis revealed distinct DNA methylation signatures in VLOSLP patients compared to controls. The GNB5 gene exhibited shared epigenetic modifications across SCZ, AD, and VLOSLP, suggesting a common pathogenic mechanism. The diagnostic model discriminating AD from VLOSLP demonstrated high accuracy, achieving an AUC of 1.0 in the training set and 0.958 in the test set (95% CI: 0.875-1.000). The AD versus SCZ classification model showed similar robustness, with AUCs of 0.995 and 0.955 in training and test sets, respectively (95% CI: 0.926-0.983). The SCZ versus VLOSLP model achieved perfect discrimination (AUC = 1.0) in both training and test sets, with substantial clinical utility. Additional analyses suggested distinct molecular subtypes within VLOSLP.

Conclusion

Specific DNA methylation alterations in VLOSLP are identified as potential diagnostic biomarkers. These findings may contribute to the development of molecular diagnostic tools, though further validation in larger, independent cohorts is warranted.

Assessing DNA methylation detection for primary human tissue using Nanopore sequencing

DNA methylation most commonly occurs as 5-methylcytosine (5mC) in the human genome and has been associated with human diseases. Recent developments in single-molecule sequencing technologies (Oxford Nanopore Technologies [ONT] and Pacific Biosciences [PacBio]) have enabled readouts of long, native DNA molecules, including cytosine methylation. ONT recently upgraded their Nanopore sequencing chemistry and kits from the R9 to the R10 version, which yielded increased accuracy and sequencing throughput. However, the effects on methylation detection have not yet been documented. Here, we performed a series of computational analyses to characterize differences in Nanopore-based 5mC detection between the ONT R9 and R10 chemistries. We compared 5mC calls in R9 and R10 for three human genome data sets: a cell line, a frontal cortex brain sample, and a blood sample. We performed an in-depth analysis on CpG islands and homopolymer regions, and documented high concordance for methylation detection among sequencing technologies. The strongest correlation was observed between Nanopore R10 and Illumina bisulfite technologies for cell line-derived data sets. Subtle differences in methylation data sets between technologies can impact analysis tools such as differential methylation calling software. Our findings show that comparisons can be drawn between methylation data from different Nanopore chemistries using guided hypotheses. This work will facilitate comparison among Nanopore data cohorts derived using different chemistries from large-scale sequencing efforts, such as the NIH CARD Long Read Initiative.

In silico pan-cancer analysis of VRAC subunits and their prognostic roles in human cancers

The study focuses on the VRAC channel and its significant roles in cancer development. It addresses a research gap by conducting a pan-cancer analysis with multi-omics bioinformatics tools, integrating data from the Human Protein Atlas (HPA) and Genotype-Tissue Expression (GTEx) datasets to examine mRNA expression patterns of its Leucine Rich Repeat Containing 8 (LRRC8) subunits in various tissues and cancers. The study links variations in LRRC8s expression with patient outcomes and includes analyses of DNA and RNA methylation. The study reveals significant correlations between LRRC8s expression and immune cell infiltration, as well as a positive association with cancer-associated fibroblasts and key immune regulators such as major histocompatibility complex (MHCs) and chemokines. Furthermore, the research suggests that LRRC8s are involved in cancer-signalling pathways, which may offer new therapeutic targets. Additionally, a drug sensitivity analysis shows that LRRC8 subunits affect drug responses differently, supporting the use of personalized therapeutic strategies. In conclusion, the study emphasizes the significance of VRAC subunits in cancer biology and suggests their potential as biomarkers and targets in cancer immunotherapy and personalized medicine.

Advancing Personalized Medicine in Alzheimer's Disease: Liquid Biopsy Epigenomics Unveil APOE ε4-Linked Methylation Signatures

Recent studies show that patients with Alzheimer's disease (AD) harbor specific methylation marks in the brain that, if accessible, could be used as epigenetic biomarkers. Liquid biopsy enables the study of circulating cell-free DNA (cfDNA) fragments originated from dead cells, including neurons affected by neurodegenerative processes. Here, we isolated and epigenetically characterized plasma cfDNA from 35 patients with AD and 35 cognitively healthy controls by using the Infinium® MethylationEPIC BeadChip array. Bioinformatics analysis was performed to identify differential methylation positions (DMPs) and regions (DMRs), including APOE ε4 genotype stratified analysis. Plasma pTau181 (Simoa) and cerebrospinal fluid (CSF) core biomarkers (Fujirebio) were also measured and correlated with differential methylation marks. Validation was performed with bisulfite pyrosequencing and bisulfite cloning sequencing. Epigenome-wide cfDNA analysis identified 102 DMPs associated with AD status. Most DMPs correlated with clinical cognitive and functional tests including 60% for Mini-Mental State Examination (MMSE) and 80% for Global Deterioration Scale (GDS), and with AD blood and CSF biomarkers. In silico functional analysis connected 30 DMPs to neurological processes, identifying key regulators such as SPTBN4 and APOE genes. Several DMRs were annotated to genes previously reported to harbor epigenetic brain changes in AD (HKR1, ZNF154, HOXA5, TRIM40, ATG16L2, ADAMST2) and were linked to APOE ε4 genotypes. Notably, a DMR in the HKR1 gene, previously shown to be hypermethylated in the AD hippocampus, was validated in cfDNA from an orthogonal perspective. These results support the feasibility of studying cfDNA to identify potential epigenetic biomarkers in AD. Thus, liquid biopsy could improve non-invasive AD diagnosis and aid personalized medicine by detecting epigenetic brain markers in blood.

The night's watch: Exploring how sleep protects against neurodegeneration

Sleep loss is often regarded as an early manifestation of neurodegenerative diseases given its common occurrence and link to cognitive dysfunction. However, the precise mechanisms by which sleep disturbances contribute to neurodegeneration are not fully understood, nor is it clear why some individuals are more susceptible to these effects than others. This review addresses critical unanswered questions in the field, including whether sleep disturbances precede or result from neurodegenerative diseases, the functional significance of sleep changes during the preclinical disease phase, and the potential role of sleep homeostasis as an adaptive mechanism enhancing resilience against cognitive decline and neurodegeneration.

Integrative Epigenomic Landscape of Alzheimer's Disease Brains Reveals Oligodendrocyte Molecular Perturbations Associated with Tau

Alzheimer's disease (AD) brains are characterized by neuropathologic and biochemical changes that are highly variable across individuals. Capturing epigenetic factors that associate with this variability can reveal novel biological insights into AD pathophysiology. We conducted an epigenome-wide association study of DNA methylation (DNAm) in 472 AD brains with neuropathologic measures (Braak stage, Thal phase, and cerebral amyloid angiopathy score) and brain biochemical levels of five proteins (APOE, amyloid-β (Aβ)40, Aβ42, tau, and p-tau) core to AD pathogenesis. Using a novel regional methylation (rCpGm) approach, we identified 5,478 significant associations, 99.7% of which were with brain tau biochemical measures. Of the tau-associated rCpGms, 93 had concordant associations in external datasets comprising 1,337 brain samples. Integrative transcriptome-methylome analyses uncovered 535 significant gene expression associations for these 93 rCpGms. Genes with concurrent transcriptome-methylome perturbations were enriched in oligodendrocyte marker genes, including known AD risk genes such as BIN1 , myelination genes MYRF, MBP and MAG previously implicated in AD, as well as novel genes like LDB3 . We further annotated the top oligodendrocyte genes in an additional 6 brain single cell and 2 bulk transcriptome datasets from AD and two other tauopathies, Pick's disease and progressive supranuclear palsy (PSP). Our findings support consistent rCpGm and gene expression associations with these tauopathies and tau-related phenotypes in both bulk brain tissue and oligodendrocyte clusters. In summary, we uncover the integrative epigenomic landscape of AD and demonstrate tau-related oligodendrocyte gene perturbations as a common potential pathomechanism across different tauopathies.

A doubly robust estimator for continuous treatments in high dimensions

BACKGROUND

Generalized propensity score (GPS) methods have become popular for estimating causal relationships between a continuous treatment and an outcome in observational studies with rich covariate information. The presence of rich covariates enhances the plausibility of the unconfoundedness assumption. Nonetheless, it is also crucial to ensure the correct specification of both marginal and conditional treatment distributions, beyond the assumption of unconfoundedness.

METHOD

We address limitations in existing GPS methods by extending balance-based approaches to high dimensions and introducing the Generalized Outcome-Adaptive LASSO and Doubly Robust Estimate (GOALDeR). This novel approach integrates a balance-based method that is robust to the misspecification of distributions required for GPS methods, a doubly robust estimator that is robust to the misspecification of models, and a variable selection technique for causal inference that ensures an unbiased and statistically efficient estimation.

RESULTS

Simulation studies showed that GOALDeR was able to generate nearly unbiased estimates when either the GPS model or the outcome model was correctly specified. Notably, GOALDeR demonstrated greater precision and accuracy compared to existing methods and was slightly affected by the covariate correlation structure and ratio of sample size to covariate dimension. Real data analysis revealed no statistically significant dose-response relationship between epigenetic age acceleration and Alzheimer's disease.

CONCLUSION

In this study, we proposed GOALDeR as an advanced GPS method for causal inference in high dimensions, and empirically demonstrated that GOALDeR is doubly robust, with improved accuracy and precision compared to existing methods. The R package is available at https://github.com/QianGao-SXMU/GOALDeR .

regionalpcs improve discovery of DNA methylation associations with complex traits

We have developed the regionalpcs method, an approach for summarizing gene-level methylation. regionalpcs addresses the challenge of deciphering complex epigenetic mechanisms in diseases like Alzheimer's disease. In contrast to averaging, regionalpcs uses principal components analysis to capture complex methylation patterns across gene regions. Our method demonstrates a 54% improvement in sensitivity over averaging in simulations, providing a robust framework for identifying subtle epigenetic variations. Applying regionalpcs to Alzheimer's disease brain methylation data, combined with cell type deconvolution, we uncover 838 differentially methylated genes associated with neuritic plaque burden-significantly outperforming conventional methods. Integrating methylation quantitative trait loci with genome-wide association studies identified 17 genes with potential causal roles in Alzheimer's disease risk, including MS4A4A and PICALM. Available in the Bioconductor package regionalpcs, our approach facilitates a deeper understanding of the epigenetic landscape in Alzheimer's disease and opens avenues for research into complex diseases.

The Promise of Epigenetic Editing for Treating Brain Disorders

Brain disorders, especially neurodegenerative diseases, affect millions of people worldwide. There is no causal treatment available; therefore, there is an unmet clinical need for finding therapeutic options for these diseases. Epigenetic research has resulted in identification of various genomic loci with differential disease-specific epigenetic modifications, mainly DNA methylation. These biomarkers, although not yet translated into clinically approved options, offer therapeutic targets as epigenetic modifications are reversible. Indeed, clinical trials are designed to inhibit epigenetic writers, erasers, or readers using epigenetic drugs to interfere with epigenetic dysregulation in brain disorders. However, since such drugs elicit genome-wide effects and potentially cause toxicity, the recent developments in the field of epigenetic editing are gaining widespread attention. In this review, we provide examples of epigenetic biomarkers and epi-drugs, while describing efforts in the field of epigenetic editing, to eventually make a difference for the currently incurable brain disorders.

DNA Methylation in Alzheimer's Disease

To date, DNA methylation is the best characterized epigenetic modification in Alzheimer's disease. Involving the addition of a methyl group to the fifth carbon of the cytosine pyrimidine base, DNA methylation is generally thought to be associated with the silencing of gene expression. It has been hypothesized that epigenetics may mediate the interaction between genes and the environment in the manifestation of Alzheimer's disease, and therefore studies investigating DNA methylation could elucidate novel disease mechanisms. This chapter comprehensively reviews epigenomic studies, undertaken in human brain tissue and purified brain cell types, focusing on global methylation levels, candidate genes, epigenome wide approaches, and recent meta-analyses. We discuss key differentially methylated genes and pathways that have been highlighted to date, with a discussion on how new technologies and the integration of multiomic data may further advance the field.

Epigenetics in Neurodegenerative Diseases

Healthy brain functioning requires a continuous fine-tuning of gene expression, involving changes in the epigenetic landscape and 3D chromatin organization. Alzheimer's disease (AD), amyotrophic lateral sclerosis (ALS), and frontotemporal dementia (FTD) are three multifactorial neurodegenerative diseases (NDDs) that are partially explained by genetics (gene mutations and genetic risk factors) and influenced by non-genetic factors (i.e., aging, lifestyle, and environmental conditions). Examining comprehensive studies of global and locus-specific (epi)genomic and transcriptomic alterations in human and mouse brain samples at the cell-type resolution has uncovered important phenomena associated with AD. First, DNA methylation and histone marks at promoters contribute to transcriptional dysregulation of genes that are directly implicated in AD pathogenesis (i.e., APP), neuroplasticity and cognition (i.e., PSD95), and microglial activation (i.e., TREM2). Second, the presence of AD genetic risk variants in cell-type-specific distal enhancers (i.e., BIN1 in microglia) alters transcription, presumably by disrupting associated enhancer-promoter interactions and chromatin looping. Third, epigenomic erosion is associated with widespread transcriptional disruption and cell identity loss. And fourth, aging, high cholesterol, air pollution, and pesticides have emerged as potential drivers of AD by inducing locus-specific and global epigenetic modifications that impact key AD-related pathways. Epigenetic studies in ALS/FTD also provide evidence that genetic and non-genetic factors alter gene expression profiles in neurons and astrocytes through aberrant epigenetic mechanisms. We additionally overview the recent development of potential new therapeutic strategies involving (epi)genetic editing and the use of small chromatin-modifying molecules (epidrugs).

DMRIntTk: Integrating different DMR sets based on density peak clustering

BACKGROUND

Identifying differentially methylated regions (DMRs) is a basic task in DNA methylation analysis. However, due to the different strategies adopted, different DMR sets will be predicted on the same dataset, which poses a challenge in selecting a reliable and comprehensive DMR set for downstream analysis.

RESULTS

Here, we develop DMRIntTk, a toolkit for integrating DMR sets predicted by different methods on a same dataset. In DMRIntTk, the genome is segmented into bins, and the reliability of each DMR set at different methylation thresholds is evaluated. Then, the bins are weighted based on the covered DMR sets and integrated into final DMRs using a density peak clustering algorithm. To demonstrate the practicality of DMRIntTk, it was applied to different scenarios, including tissues with relatively large methylation differences, cancer tissues versus normal tissues with medium methylation differences, and disease tissues versus normal tissues with subtle methylation differences. Our results show that DMRIntTk can effectively trim regions with small methylation differences from the original DMR sets and thereby enriching the proportion of DMRs with larger methylation differences. In addition, the overlap analysis suggests that the integrated DMR sets are quite comprehensive, and functional analyses indicate the integrated disease-related DMRs are significantly enriched in biological pathways associated with the pathological mechanisms of the diseases. A comparative analysis of the integrated DMR set versus each original DMR set further highlights the superiority of DMRIntTk, demonstrating the unique biological insights it can provide.

CONCLUSIONS

Conclusively, DMRIntTk can help researchers obtain a reliable and comprehensive DMR set from many prediction methods.

Long-read sequencing of hundreds of diverse brains provides insight into the impact of structural variation on gene expression and DNA methylation

Structural variants (SVs) drive gene expression in the human brain and are causative of many neurological conditions. However, most existing genetic studies have been based on short-read sequencing methods, which capture fewer than half of the SVs present in any one individual. Long-read sequencing (LRS) enhances our ability to detect disease-associated and functionally relevant structural variants (SVs); however, its application in large-scale genomic studies has been limited by challenges in sample preparation and high costs. Here, we leverage a new scalable wet-lab protocol and computational pipeline for whole-genome Oxford Nanopore Technologies sequencing and apply it to neurologically normal control samples from the North American Brain Expression Consortium (NABEC) (European ancestry) and Human Brain Collection Core (HBCC) (African or African admixed ancestry) cohorts. Through this work, we present a publicly available long-read resource from 351 human brain samples (median N50: 27 Kbp and at an average depth of ~40x genome coverage). We discover approximately 234,905 SVs and produce locally phased assemblies that cover 95% of all protein-coding genes in GRCh38. Utilizing matched expression datasets for these samples, we apply quantitative trait locus (QTL) analyses and identify SVs that impact gene expression in post-mortem frontal cortex brain tissue. Further, we determine haplotype-specific methylation signatures at millions of CpGs and, with this data, identify cis-acting SVs. In summary, these results highlight that large-scale LRS can identify complex regulatory mechanisms in the brain that were inaccessible using previous approaches. We believe this new resource provides a critical step toward understanding the biological effects of genetic variation in the human brain.

Unveiling DNA methylation in Alzheimer's disease: a review of array-based human brain studies

The intricacies of Alzheimer's disease pathogenesis are being increasingly illuminated by the exploration of epigenetic mechanisms, particularly DNA methylation. This review comprehensively surveys recent human-centered studies that investigate whole genome DNA methylation in Alzheimer's disease neuropathology. The examination of various brain regions reveals distinctive DNA methylation patterns that associate with the Braak stage and Alzheimer's disease progression. The entorhinal cortex emerges as a focal point due to its early histological alterations and subsequent impact on downstream regions like the hippocampus. Notably, ANK1 hypermethylation, a protein implicated in neurofibrillary tangle formation, was recurrently identified in the entorhinal cortex. Further, the middle temporal gyrus and prefrontal cortex were shown to exhibit significant hypermethylation of genes like HOXA3, RHBDF2, and MCF2L, potentially influencing neuroinflammatory processes. The complex role of BIN1 in late-onset Alzheimer's disease is underscored by its association with altered methylation patterns. Despite the disparities across studies, these findings highlight the intricate interplay between epigenetic modifications and Alzheimer's disease pathology. Future research efforts should address methodological variations, incorporate diverse cohorts, and consider environmental factors to unravel the nuanced epigenetic landscape underlying Alzheimer's disease progression.

Consistent genes associated with structural changes in clinical Alzheimer's disease spectrum

Background

Previous studies have demonstrated widespread brain neurodegeneration in Alzheimer's disease (AD). However, the neurobiological and pathogenic substrates underlying this structural atrophy across the AD spectrum remain largely understood.

Methods

In this study, we obtained structural MRI data from ADNI datasets, including 83 participants with early-stage cognitive impairments (EMCI), 83 with late-stage mild cognitive impairments (LMCI), 83 with AD, and 83 with normal controls (NC). Our goal was to explore structural atrophy across the full clinical AD spectrum and investigate the genetic mechanism using gene expression data from the Allen Human Brain Atlas.

Results

As a result, we identified significant volume atrophy in the left thalamus, left cerebellum, and bilateral middle frontal gyrus across the AD spectrum. These structural changes were positively associated with the expression levels of genes such as ABCA7, SORCS1, SORL1, PILRA, PFDN1, PLXNA4, TRIP4, and CD2AP, while they were negatively associated with the expression levels of genes such as CD33, PLCG2, APOE, and ECHDC3 across the clinical AD spectrum. Further gene enrichment analyses revealed that the positively associated genes were mainly involved in the positive regulation of cellular protein localization and the negative regulation of cellular component organization, whereas the negatively associated genes were mainly involved in the positive regulation of iron transport.

Conclusion

Overall, these results provide a deeper understanding of the biological mechanisms underlying structural changes in prodromal and clinical AD.

Ageing-Related Changes to H3K4me3, H3K27ac, and H3K27me3 in Purified Mouse Neurons

Neurons are central to lifelong learning and memory, but ageing disrupts their morphology and function, leading to cognitive decline. Although epigenetic mechanisms are known to play crucial roles in learning and memory, neuron-specific genome-wide epigenetic maps into old age remain scarce, often being limited to whole-brain homogenates and confounded by glial cells. Here, we mapped H3K4me3, H3K27ac, and H3K27me3 in mouse neurons across their lifespan. This revealed stable H3K4me3 and global losses of H3K27ac and H3K27me3 into old age. We observed patterns of synaptic function gene deactivation, regulated through the loss of the active mark H3K27ac, but not H3K4me3. Alongside this, embryonic development loci lost repressive H3K27me3 in old age. This suggests a loss of a highly refined neuronal cellular identity linked to global chromatin reconfiguration. Collectively, these findings indicate a key role for epigenetic regulation in neurons that is inextricably linked with ageing.

Development of an epigenetic clock resistant to changes in immune cell composition

Epigenetic clocks are age predictors that use machine-learning models trained on DNA CpG methylation values to predict chronological or biological age. Increases in predicted epigenetic age relative to chronological age (epigenetic age acceleration) are connected to aging-associated pathologies, and changes in epigenetic age are linked to canonical aging hallmarks. However, epigenetic clocks rely on training data from bulk tissues whose cellular composition changes with age. Here, we found that human naive CD8+ T cells, which decrease in frequency during aging, exhibit an epigenetic age 15-20 years younger than effector memory CD8+ T cells from the same individual. Importantly, homogenous naive T cells isolated from individuals of different ages show a progressive increase in epigenetic age, indicating that current epigenetic clocks measure two independent variables, aging and immune cell composition. To isolate the age-associated cell intrinsic changes, we created an epigenetic clock, the IntrinClock, that did not change among 10 immune cell types tested. IntrinClock shows a robust predicted epigenetic age increase in a model of replicative senescence in vitro and age reversal during OSKM-mediated reprogramming.

Neuroinflammaging: A Tight Line Between Normal Aging and Age-Related Neurodegenerative Disorders

Aging in the healthy brain is characterized by a low-grade, chronic, and sterile inflammatory process known as neuroinflammaging. This condition, mainly consisting in an up-regulation of the inflammatory response at the brain level, contributes to the pathogenesis of age-related neurodegenerative disorders. Development of this proinflammatory state involves the interaction between genetic and environmental factors, able to induce age-related epigenetic modifications. Indeed, the exposure to environmental compounds, drugs, and infections, can contribute to epigenetic modifications of DNA methylome, histone fold proteins, and nucleosome positioning, leading to epigenetic modulation of neuroinflammatory responses. Furthermore, some epigenetic modifiers, which combine and interact during the life course, can contribute to modeling of epigenome dynamics to sustain, or dampen the neuroinflammatory phenotype. The aim of this review is to summarize current knowledge about neuroinflammaging with a particular focus on epigenetic mechanisms underlying the onset and progression of neuroinflammatory cascades in the central nervous system; furthermore, we describe some diagnostic biomarkers that may contribute to increase diagnostic accuracy and help tailor therapeutic strategies in patients with neurodegenerative diseases.

An improved epigenetic counter to track mitotic age in normal and precancerous tissues

The cumulative number of stem cell divisions in a tissue, known as mitotic age, is thought to be a major determinant of cancer-risk. Somatic mutational and DNA methylation (DNAm) clocks are promising tools to molecularly track mitotic age, yet their relationship is underexplored and their potential for cancer risk prediction in normal tissues remains to be demonstrated. Here we build and validate an improved pan-tissue DNAm counter of total mitotic age called stemTOC. We demonstrate that stemTOC's mitotic age proxy increases with the tumor cell-of-origin fraction in each of 15 cancer-types, in precancerous lesions, and in normal tissues exposed to major cancer risk factors. Extensive benchmarking against 6 other mitotic counters shows that stemTOC compares favorably, specially in the preinvasive and normal-tissue contexts. By cross-correlating stemTOC to two clock-like somatic mutational signatures, we confirm the mitotic-like nature of only one of these. Our data points towards DNAm as a promising molecular substrate for detecting mitotic-age increases in normal tissues and precancerous lesions, and hence for developing cancer-risk prediction strategies.

Genome-Wide DNA Methylation in Early-Onset-Dementia Patients Brain Tissue and Lymphoblastoid Cell Lines

Epigenetics, a potential underlying pathogenic mechanism of neurodegenerative diseases, has been in the scope of several studies performed so far. However, there is a gap in regard to analyzing different forms of early-onset dementia and the use of Lymphoblastoid cell lines (LCLs). We performed a genome-wide DNA methylation analysis on sixty-four samples (from the prefrontal cortex and LCLs) including those taken from patients with early-onset forms of Alzheimer's disease (AD) and frontotemporal dementia (FTD) and healthy controls. A beta regression model and adjusted p-values were used to obtain differentially methylated positions (DMPs) via pairwise comparisons. A correlation analysis of DMP levels with Clariom D array gene expression data from the same cohort was also performed. The results showed hypermethylation as the most frequent finding in both tissues studied in the patient groups. Biological significance analysis revealed common pathways altered in AD and FTD patients, affecting neuron development, metabolism, signal transduction, and immune system pathways. These alterations were also found in LCL samples, suggesting the epigenetic changes might not be limited to the central nervous system. In the brain, CpG methylation presented an inverse correlation with gene expression, while in LCLs, we observed mainly a positive correlation. This study enhances our understanding of the biological pathways that are associated with neurodegeneration, describes differential methylation patterns, and suggests LCLs are a potential cell model for studying neurodegenerative diseases in earlier clinical phases than brain tissue.

regionalpcs: improved discovery of DNA methylation associations with complex traits

We have developed the regional principal components (rPCs) method, a novel approach for summarizing gene-level methylation. rPCs address the challenge of deciphering complex epigenetic mechanisms in diseases like Alzheimer's disease (AD). In contrast to traditional averaging, rPCs leverage principal components analysis to capture complex methylation patterns across gene regions. Our method demonstrated a 54% improvement in sensitivity over averaging in simulations, offering a robust framework for identifying subtle epigenetic variations. Applying rPCs to the AD brain methylation data in ROSMAP, combined with cell type deconvolution, we uncovered 838 differentially methylated genes associated with neuritic plaque burden-significantly outperforming conventional methods. Integrating methylation quantitative trait loci (meQTL) with genome-wide association studies (GWAS) identified 17 genes with potential causal roles in AD, including MS4A4A and PICALM. Our approach is available in the Bioconductor package regionalpcs, opening avenues for research and facilitating a deeper understanding of the epigenetic landscape in complex diseases.

Epigenetic Changes in Alzheimer's Disease: DNA Methylation and Histone Modification

Alzheimer's disease (AD) is a devastating neurodegenerative disorder characterized by progressive cognitive decline and memory loss, imposing a significant burden on affected individuals and their families. Despite the recent promising progress in therapeutic approaches, more needs to be done to understand the intricate molecular mechanisms underlying the development and progression of AD. Growing evidence points to epigenetic changes as playing a pivotal role in the pathogenesis of the disease. The dynamic interplay between genetic and environmental factors influences the epigenetic landscape in AD, altering gene expression patterns associated with key pathological events associated with disease pathogenesis. To this end, epigenetic alterations not only impact the expression of genes implicated in AD pathogenesis but also contribute to the dysregulation of crucial cellular processes, including synaptic plasticity, neuroinflammation, and oxidative stress. Understanding the complex epigenetic mechanisms in AD provides new avenues for therapeutic interventions. This review comprehensively examines the role of DNA methylation and histone modifications in the context of AD. It aims to contribute to a deeper understanding of AD pathogenesis and facilitate the development of targeted therapeutic strategies.

An Overview of the Epigenetic Modifications in the Brain under Normal and Pathological Conditions

Epigenetic changes are changes in gene expression that do not involve alterations to the DNA sequence. These changes lead to establishing a so-called epigenetic code that dictates which and when genes are activated, thus orchestrating gene regulation and playing a central role in development, health, and disease. The brain, being mostly formed by cells that do not undergo a renewal process throughout life, is highly prone to the risk of alterations leading to neuronal death and neurodegenerative disorders, mainly at a late age. Here, we review the main epigenetic modifications that have been described in the brain, with particular attention on those related to the onset of developmental anomalies or neurodegenerative conditions and/or occurring in old age. DNA methylation and several types of histone modifications (acetylation, methylation, phosphorylation, ubiquitination, sumoylation, lactylation, and crotonylation) are major players in these processes. They are directly or indirectly involved in the onset of neurodegeneration in Alzheimer's or Parkinson's disease. Therefore, this review briefly describes the roles of these epigenetic changes in the mechanisms of brain development, maturation, and aging and some of the most important factors dynamically regulating or contributing to these changes, such as oxidative stress, inflammation, and mitochondrial dysfunction.

The Epigenetic Evolution of Glioma Is Determined by the IDH1 Mutation Status and Treatment Regimen

Tumor adaptation or selection is thought to underlie therapy resistance in glioma. To investigate longitudinal epigenetic evolution of gliomas in response to therapeutic pressure, we performed an epigenomic analysis of 132 matched initial and recurrent tumors from patients with IDH-wildtype (IDHwt) and IDH-mutant (IDHmut) glioma. IDHwt gliomas showed a stable epigenome over time with relatively low levels of global methylation. The epigenome of IDHmut gliomas showed initial high levels of genome-wide DNA methylation that was progressively reduced to levels similar to those of IDHwt tumors. Integration of epigenomics, gene expression, and functional genomics identified HOXD13 as a master regulator of IDHmut astrocytoma evolution. Furthermore, relapse of IDHmut tumors was accompanied by histologic progression that was associated with survival, as validated in an independent cohort. Finally, the initial cell composition of the tumor microenvironment varied between IDHwt and IDHmut tumors and changed differentially following treatment, suggesting increased neoangiogenesis and T-cell infiltration upon treatment of IDHmut gliomas. This study provides one of the largest cohorts of paired longitudinal glioma samples with epigenomic, transcriptomic, and genomic profiling and suggests that treatment of IDHmut glioma is associated with epigenomic evolution toward an IDHwt-like phenotype.

SIGNIFICANCE

Standard treatments are related to loss of DNA methylation in IDHmut glioma, resulting in epigenetic activation of genes associated with tumor progression and alterations in the microenvironment that resemble treatment-naïve IDHwt glioma.

Mechanisms linking cerebrovascular dysfunction and tauopathy: Adding a layer of epiregulatory complexity

Intracellular accumulation of hyperphosphorylated misfolded tau proteins are found in many neurodegenerative tauopathies, including Alzheimer's disease (AD). Tau pathology can impact cerebrovascular physiology and function through multiple mechanisms. In vitro and in vivo studies have shown that alterations in the blood-brain barrier (BBB) integrity and function can result in synaptic abnormalities and neuronal damage. In the present review, we will summarize how tau proteostasis dysregulation contributes to vascular dysfunction and, conversely, we will examine the factors and pathways leading to tau pathological alterations triggered by cerebrovascular dysfunction. Finally, we will highlight the role epigenetic and epitranscriptomic factors play in regulating the integrity of the cerebrovascular system and the progression of tauopathy including a few observartions on potential therapeutic interventions. LINKED ARTICLES: This article is part of a themed issue From Alzheimer's Disease to Vascular Dementia: Different Roads Leading to Cognitive Decline. To view the other articles in this section visit http://onlinelibrary.wiley.com/doi/10.1111/bph.v181.6/issuetoc.

Assessing methylation detection for primary human tissue using Nanopore sequencing

DNA methylation most commonly occurs as 5-methylcytosine (5-mC) in the human genome and has been associated with human diseases. Recent developments in single-molecule sequencing technologies (Oxford Nanopore Technologies (ONT) and Pacific Biosciences) have enabled readouts of long, native DNA molecules, including cytosine methylation. ONT recently upgraded their Nanopore sequencing chemistry and kits from R9 to the R10 version, which yielded increased accuracy and sequencing throughput. However the effects on methylation detection have not yet been documented. Here we performed a series of computational analyses to characterize differences in Nanopore-based 5mC detection between the ONT R9 and R10 chemistries. We compared 5mC calls in R9 and R10 for three human genome datasets: a cell line, a frontal cortex brain sample, and a blood sample. We performed an in-depth analysis on CpG islands and homopolymer regions, and documented high concordance for methylation detection among sequencing technologies. The strongest correlation was observed between Nanopore R10 and Illumina bisulfite technologies for cell line-derived datasets. Subtle differences in methylation datasets between technologies can impact analysis tools such as differential methylation calling software. Our findings show that comparisons can be drawn between methylation data from different Nanopore chemistries using guided hypotheses. This work will facilitate comparison among Nanopore data cohorts derived using different chemistries from large scale sequencing efforts, such as the NIH CARD Long Read Initiative.

Differential methylation analysis in neuropathologically confirmed dementia with Lewy bodies

Dementia with Lewy bodies (DLB) is a common form of dementia in the elderly population. We performed genome-wide DNA methylation mapping of cerebellar tissue from pathologically confirmed DLB cases and controls to study the epigenetic profile of this understudied disease. After quality control filtering, 728,197 CpG-sites in 278 cases and 172 controls were available for the analysis. We undertook an epigenome-wide association study, which found a differential methylation signature in DLB cases. Our analysis identified seven differentially methylated probes and three regions associated with DLB. The most significant CpGs were located in ARSB (cg16086807), LINC00173 (cg18800161), and MGRN1 (cg16250093). Functional enrichment evaluations found widespread epigenetic dysregulation in genes associated with neuron-to-neuron synapse, postsynaptic specialization, postsynaptic density, and CTCF-mediated synaptic plasticity. In conclusion, our study highlights the potential importance of epigenetic alterations in the pathogenesis of DLB and provides insights into the modified genes, regions and pathways that may guide therapeutic developments.

scMD facilitates cell type deconvolution using single-cell DNA methylation references

The proliferation of single-cell RNA-sequencing data has led to the widespread use of cellular deconvolution, aiding the extraction of cell-type-specific information from extensive bulk data. However, those advances have been mostly limited to transcriptomic data. With recent developments in single-cell DNA methylation (scDNAm), there are emerging opportunities for deconvolving bulk DNAm data, particularly for solid tissues like brain that lack cell-type references. Due to technical limitations, current scDNAm sequences represent a small proportion of the whole genome for each single cell, and those detected regions differ across cells. This makes scDNAm data ultra-high dimensional and ultra-sparse. To deal with these challenges, we introduce scMD (single cell Methylation Deconvolution), a cellular deconvolution framework to reliably estimate cell type fractions from tissue-level DNAm data. To analyze large-scale complex scDNAm data, scMD employs a statistical approach to aggregate scDNAm data at the cell cluster level, identify cell-type marker DNAm sites, and create precise cell-type signature matrixes that surpass state-of-the-art sorted-cell or RNA-derived references. Through thorough benchmarking in several datasets, we demonstrate scMD's superior performance in estimating cellular fractions from bulk DNAm data. With scMD-estimated cellular fractions, we identify cell type fractions and cell type-specific differentially methylated cytosines associated with Alzheimer's disease.

Epigenetics of Alzheimer’s Disease: Past, Present and Future

Alzheimer’s disease (AD) exemplifies a looming epidemic lacking effective treatment and manifests with the accumulation of neurofibrillary tangles, amyloid-β plaques, neuroinflammation, behavioral changes, and acute cognitive impairments. It is a complex, multifactorial disorder that arises from the intricate interaction between environment and genetic factors, restrained via epigenetic machinery. Though the research progress has improved the understanding of clinical manifestations and disease advancement, the causal mechanism of detrimental consequences remains undefined. Despite the substantial improvement in recent diagnostic modalities, it is challenging to distinguish AD from other forms of dementia. Accurate diagnosis is a major glitch in AD as it banks on the symptoms and clinical criteria. Several studies are underway in exploring novel and reliable biomarkers for AD. In this direction, epigenetic alterations have transpired as key modulators in AD pathogenesis with the impeding inferences for the management of this neurological disorder. The present chapter aims to discuss the significance of epigenetic modifications reported in the pathophysiology of AD such as DNA methylation, hydroxy-methylation, methylation of mtDNA, histone modifications, and noncoding RNAs. Additionally, the chapter also describes the possible therapeutic avenues that target epigenetic modifications in AD.

Minding the Gap: Exploring Neuroinflammatory and Microglial Sex Differences in Alzheimer's Disease

Research into Alzheimer's Disease (AD) describes a link between AD and the resident immune cells of the brain, the microglia. Further, this suspected link is thought to have underlying sex effects, although the mechanisms of these effects are only just beginning to be understood. Many of these insights are the result of policies put in place by funding agencies such as the National Institutes of Health (NIH) to consider sex as a biological variable (SABV) and the move towards precision medicine due to continued lackluster therapeutic options. The purpose of this review is to provide an updated assessment of the current research that summarizes sex differences and the research pertaining to microglia and their varied responses in AD.

Differential usage of DNA modifications in neurons, astrocytes, and microglia

BACKGROUND

Cellular identity is determined partly by cell type-specific epigenomic profiles that regulate gene expression. In neuroscience, there is a pressing need to isolate and characterize the epigenomes of specific CNS cell types in health and disease. In this study, we developed an in vivo tagging mouse model (Camk2a-NuTRAP) for paired isolation of neuronal DNA and RNA without cell sorting and then used this model to assess epigenomic regulation, DNA modifications in particular, of gene expression between neurons and glia.

RESULTS

After validating the cell-specificity of the Camk2a-NuTRAP model, we performed TRAP-RNA-Seq and INTACT-whole genome oxidative bisulfite sequencing (WGoxBS) to assess the neuronal translatome and epigenome in the hippocampus of young mice (4 months old). WGoxBS findings were validated with enzymatic methyl-Seq (EM-Seq) and nanopore sequencing. Comparing neuronal data to microglial and astrocytic data from NuTRAP models, microglia had the highest global mCG levels followed by astrocytes and then neurons, with the opposite pattern observed for hmCG and mCH. Differentially modified regions between cell types were predominantly found within gene bodies and distal intergenic regions, rather than proximal promoters. Across cell types there was a negative correlation between DNA modifications (mCG, mCH, hmCG) and gene expression at proximal promoters. In contrast, a negative correlation of gene body mCG and a positive relationship between distal promoter and gene body hmCG with gene expression was observed. Furthermore, we identified a neuron-specific inverse relationship between mCH and gene expression across promoter and gene body regions.

CONCLUSIONS

Neurons, astrocytes, and microglia demonstrate different genome-wide levels of mCG, hmCG, and mCH that are reproducible across analytical methods. However, modification-gene expression relationships are conserved across cell types. Enrichment of differential modifications across cell types in gene bodies and distal regulatory elements, but not proximal promoters, highlights epigenomic patterning in these regions as potentially greater determinants of cell identity. These findings also demonstrate the importance of differentiating between mC and hmC in neuroepigenomic analyses, as up to 30% of what is conventionally interpreted as mCG can be hmCG, which often has a different relationship to gene expression than mCG.

Reduced non-CpG methylation is a potential epigenetic target after spinal cord injury

DNA methylation is a critical epigenetic regulator in the occurrence and development of diseases and is closely related to various functional responses in relation to spinal cord injury. To investigate the role of DNA methylation in spinal cord injury, we constructed a library with reduced-representation bisulfite sequencing data obtained at various time points (day 0-42) after spinal cord injury in mice. Global DNA methylation levels, specifically non-CpG (CHG and CHH) methylation levels, decreased modestly following spinal cord injury. Stages post-spinal cord injury were classified as early (day 0-3), intermediate (day 7-14), and late (day 28-42) based on similarity and hierarchical clustering of global DNA methylation patterns. The non-CpG methylation level, which included CHG and CHH methylation levels, was markedly reduced despite accounting for a minor proportion of total methylation abundance. At multiple genomic sites, including the 5' untranslated regions, promoter, exon, intron, and 3' untranslated regions, the non-CpG methylation level was markedly decreased following spinal cord injury, whereas the CpG methylation level remained unchanged at these locations. Approximately one-half of the differentially methylated regions were located in intergenic areas; the other differentially methylated regions in both CpG and non-CpG regions were clustered in intron regions, where the DNA methylation level was highest. The function of genes associated with differentially methylated regions in promoter regions was also investigated. From Gene Ontology analysis results, DNA methylation was implicated in a number of essential functional responses to spinal cord injury, including neuronal synaptic connection creation and axon regeneration. Notably, neither CpG methylation nor non-CpG methylation was implicated in the functional response of glial or inflammatory cells. In summary, our work elucidated the dynamic pattern of DNA methylation in the spinal cord following injury and identified reduced non-CpG methylation as an epigenetic target after spinal cord injury in mice.

The role of PIMT in Alzheimer's disease pathogenesis: A novel hypothesis

There are multiple theories of Alzheimer's disease pathogenesis. One major theory is that oxidation of amyloid beta (Aβ) promotes plaque deposition that directly contributes to pathology. A competing theory is that hypomethylation of DNA (due to altered one carbon metabolism) results in pathology through altered gene regulation. Herein, we propose a novel hypothesis involving L-isoaspartyl methyltransferase (PIMT) that unifies the Aβ and DNA hypomethylation hypotheses into a single model. Importantly, the proposed model allows bidirectional regulation of Aβ oxidation and DNA hypomethylation. The proposed hypothesis does not exclude simultaneous contributions by other mechanisms (e.g., neurofibrillary tangles). The new hypothesis is formulated to encompass oxidative stress, fibrillation, DNA hypomethylation, and metabolic perturbations in one carbon metabolism (i.e., methionine and folate cycles). In addition, deductive predictions of the hypothesis are presented both to guide empirical testing of the hypothesis and to provide candidate strategies for therapeutic intervention and/or nutritional modification. HIGHLIGHTS: PIMT repairs L-isoaspartyl groups on amyloid beta and decreases fibrillation. SAM is a common methyl donor for PIMT and DNA methyltransferases. Increased PIMT activity competes with DNA methylation and vice versa. The PIMT hypothesis bridges a gap between plaque and DNA methylation hypotheses.

Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimer's disease brains

BACKGROUND

The genetic underpinnings of late-onset Alzheimer's disease (LOAD) are yet to be fully elucidated. Although numerous LOAD-associated loci have been discovered, the causal variants and their target genes remain largely unknown. Since the brain is composed of heterogenous cell subtypes, it is imperative to study the brain on a cell subtype specific level to explore the biological processes underlying LOAD.

METHODS

Here, we present the largest parallel single-nucleus (sn) multi-omics study to simultaneously profile gene expression (snRNA-seq) and chromatin accessibility (snATAC-seq) to date, using nuclei from 12 normal and 12 LOAD brains. We identified cell subtype clusters based on gene expression and chromatin accessibility profiles and characterized cell subtype-specific LOAD-associated differentially expressed genes (DEGs), differentially accessible peaks (DAPs) and cis co-accessibility networks (CCANs).

RESULTS

Integrative analysis defined disease-relevant CCANs in multiple cell subtypes and discovered LOAD-associated cell subtype-specific candidate cis regulatory elements (cCREs), their candidate target genes, and trans-interacting transcription factors (TFs), some of which, including ELK1, JUN, and SMAD4 in excitatory neurons, were also LOAD-DEGs. Finally, we focused on a subset of cell subtype-specific CCANs that overlap known LOAD-GWAS regions and catalogued putative functional SNPs changing the affinities of TF motifs within LOAD-cCREs linked to LOAD-DEGs, including APOE and MYO1E in a specific subtype of microglia and BIN1 in a subpopulation of oligodendrocytes.

CONCLUSIONS

To our knowledge, this study represents the most comprehensive systematic interrogation to date of regulatory networks and the impact of genetic variants on gene dysregulation in LOAD at a cell subtype resolution. Our findings reveal crosstalk between epigenetic, genomic, and transcriptomic determinants of LOAD pathogenesis and define catalogues of candidate genes, cCREs, and variants involved in LOAD genetic etiology and the cell subtypes in which they act to exert their pathogenic effects. Overall, these results suggest that cell subtype-specific cis-trans interactions between regulatory elements and TFs, and the genes dysregulated by these networks contribute to the development of LOAD.

Cellular specificity is key to deciphering epigenetic changes underlying Alzheimer's disease

Different cell types in the brain play distinct roles in Alzheimer's disease (AD) progression. Late onset AD (LOAD) is a complex disease, with a large genetic component, but many risk loci fall in non-coding genome regions. Epigenetics implicates the non-coding genome with control of gene expression. The epigenome is highly cell-type specific and dynamically responds to the environment. Therefore, epigenetic mechanisms are well placed to explain genetic and environmental factors that are associated with AD. However, given this cellular specificity, purified cell populations or single cells need to be profiled to avoid effect masking. Here we review the current state of cell-type specific genome-wide profiling in LOAD, covering DNA methylation (CpG, CpH, and hydroxymethylation), histone modifications, and chromatin changes. To date, these data reveal that distinct cell types contribute and react differently to AD progression through epigenetic alterations. This review addresses the current gap in prior bulk-tissue derived work by spotlighting cell-specific changes that govern the complex interplay of cells throughout disease progression and are critical in understanding and developing effective treatments for AD.

Targeting epigenetics: A novel promise for Alzheimer's disease treatment

So far, the search for a cure for Alzheimer Disease (AD) has been unsuccessful. The only approved drugs attenuate some symptoms, but do not halt the progress of this disease, which affects 50 million people worldwide and will increase its incidence in the coming decades. Such scenario demands new therapeutic approaches to fight against this devastating dementia. In recent years, multi-omics research and the analysis of differential epigenetic marks in AD subjects have contributed to our understanding of AD; however, the impact of epigenetic research is yet to be seen. This review integrates the most recent data on pathological processes and epigenetic changes relevant for aging and AD, as well as current therapies targeting epigenetic machinery in clinical trials. Evidence shows that epigenetic modifications play a key role in gene expression, which could provide multi-target preventative and therapeutic approaches in AD. Both novel and repurposed drugs are employed in AD clinical trials due to their epigenetic effects, as well as increasing number of natural compounds. Given the reversible nature of epigenetic modifications and the complexity of gene-environment interactions, the combination of epigenetic-based therapies with environmental strategies and drugs with multiple targets might be needed to properly help AD patients.

Underlying Mechanisms of Brain Aging and Neurodegenerative Diseases as Potential Targets for Preventive or Therapeutic Strategies Using Phytochemicals

During aging, several tissues and biological systems undergo a progressive decline in function, leading to age-associated diseases such as neurodegenerative, inflammatory, metabolic, and cardiovascular diseases and cancer. In this review, we focus on the molecular underpinning of senescence and neurodegeneration related to age-associated brain diseases, in particular, Alzheimer's and Parkinson's diseases, along with introducing nutrients or phytochemicals that modulate age-associated molecular dysfunctions, potentially offering preventive or therapeutic benefits. Based on current knowledge, the dysregulation of microglia genes and neuroinflammation, telomere attrition, neuronal stem cell degradation, vascular system dysfunction, reactive oxygen species, loss of chromosome X inactivation in females, and gut microbiome dysbiosis have been seen to play pivotal roles in neurodegeneration in an interactive manner. There are several phytochemicals (e.g., curcumin, EGCG, fucoidan, galangin, astin C, apigenin, resveratrol, phytic acid, acacetin, daucosterol, silibinin, sulforaphane, withaferin A, and betulinic acid) that modulate the dysfunction of one or several key genes (e.g., TREM2, C3, C3aR1, TNFA, NF-kb, TGFB1&2, SIRT1&6, HMGB1, and STING) affected in the aged brain. Although phytochemicals have shown promise in slowing down the progression of age-related brain diseases, more studies to identify their efficacy, alone or in combinations, in preclinical systems can help to design novel nutritional strategies for the management of neurodegenerative diseases in humans.

Neuroepigenetic Changes in DNA Methylation Affecting Diabetes-Induced Cognitive Impairment

Chronic diabetic conditions have been associated with certain cerebral complications, that include neurobehavioral dysfunctional patterns and morphological alterations of neurons, especially the hippocampus. Neuroanatomical studies done by the authors have shown decreased total dendritic length, intersections, dendritic length per branch order and nodes in the CA1 hippocampal region of the diabetic brain as compared to its normal control group, indicating reduced dendritic arborization of the hippocampal CA1 neurons. Epigenetic alterations in the brain are well known to affect age-associated disorders, however its association with the evolving diabetes-induced damage in the brain is still not fully understood. DNA hypermethylation within the neurons, tend to silent the gene expression of several regulatory proteins. The findings in the study have shown an increase in global DNA methylation in palmitic acid-induced lipotoxic Neuro-2a cells as well as within the diabetic mice brain. Inhibiting DNA methylation, restored the levels of HSF1 and certain HSPs, suggesting plausible effect of DNMTs in maintaining the proteostasis and synaptic fidelity. Neuroinflammation, as exhibited by the astrocyte activation (GFAP), were further significantly decreased in the 5-azadeoxycytidine group (DNMT inhibitor). This was further evidenced by decrease in proinflammatory cytokines TNF⍺, IL-6, and mediators iNOS and Phospho-NFkB. Our results suggest that changes in DNA methylation advocate epigenetic dysregulation and its involvement in disrupting the synaptic exactitude in the hippocampus of diabetic mice model, providing an insight into the pathophysiology of diabetes-induced neuroepigenetic changes.

Hierarchical deconvolution for extensive cell type resolution in the human brain using DNA methylation

Introduction

The human brain comprises heterogeneous cell types whose composition can be altered with physiological and pathological conditions. New approaches to discern the diversity and distribution of brain cells associated with neurological conditions would significantly advance the study of brain-related pathophysiology and neuroscience. Unlike single-nuclei approaches, DNA methylation-based deconvolution does not require special sample handling or processing, is cost-effective, and easily scales to large study designs. Existing DNA methylation-based methods for brain cell deconvolution are limited in the number of cell types deconvolved.

Methods

Using DNA methylation profiles of the top cell-type-specific differentially methylated CpGs, we employed a hierarchical modeling approach to deconvolve GABAergic neurons, glutamatergic neurons, astrocytes, microglial cells, oligodendrocytes, endothelial cells, and stromal cells.

Results

We demonstrate the utility of our method by applying it to data on normal tissues from various brain regions and in aging and diseased tissues, including Alzheimer's disease, autism, Huntington's disease, epilepsy, and schizophrenia.

Discussion

We expect that the ability to determine the cellular composition in the brain using only DNA from bulk samples will accelerate understanding brain cell type composition and cell-type-specific epigenetic states in normal and diseased brain tissues.

Altered DNA methylome profiles of blood leukocytes in Chinese patients with mild cognitive impairment and Alzheimer's disease

Objective: DNA methylation plays a potential role in the pathogenesis of Alzheimer's disease (AD). However, little is known about the global changes of blood leukocyte DNA methylome profiles from Chinese patients with mild cognitive impairment (MCI) and with AD, or the specific DNA methylation-based signatures associated with MCI and AD. In this study, we sought to dissect the characteristics of blood DNA methylome profiles in MCI- and AD-affected Chinese patients with the aim of identifying novel DNA methylation biomarkers for AD. Methods: In this study, we profiled the DNA methylome of peripheral blood leukocytes from 20 MCI- and 20 AD-affected Chinese patients and 20 cognitively healthy controls (CHCs) with the Infinium Methylation EPIC BeadChip array. Results: We identified significant alterations of the methylome profiles in MCI and AD blood leukocytes. A total of 2,582 and 20,829 CpG sites were significantly and differentially methylated in AD and MCI compared with CHCs (adjusted p < 0.05), respectively. Furthermore, 441 differentially methylated positions (DMPs), aligning to 213 unique genes, were overlapped by the three comparative groups of AD versus CHCs, MCI versus CHCs, and AD versus MCI, of which 6 and 5 DMPs were continuously hypermethylated and hypomethylated in MCI and AD relative to CHCs (adjusted p < 0.05), respectively, such as FLNC cg20186636 and AFAP1 cg06758191. The DMPs with an area under the curve >0.900, such as cg18771300, showed high potency for predicting MCI and AD. In addition, gene ontology and pathway enrichment results showed that these overlapping genes were mainly involved in neurotransmitter transport, GABAergic synaptic transmission, signal release from synapse, neurotransmitter secretion, and the regulation of neurotransmitter levels. Furthermore, tissue expression enrichment analysis revealed a subset of potentially cerebral cortex-enriched genes associated with MCI and AD, including SYT7, SYN3, and KCNT1. Conclusion: This study revealed a number of potential biomarkers for MCI and AD, also highlighted the presence of epigenetically dysregulated gene networks that may engage in the underlying pathological events resulting in the onset of cognitive impairment and AD progression. Collectively, this study provides prospective cues for developing therapeutic strategies to improve cognitive impairment and AD course.

Differential usage of DNA modifications in neurons, astrocytes, and microglia

Background

Cellular identity is determined partly by cell type-specific epigenomic profiles that regulate gene expression. In neuroscience, there is a pressing need to isolate and characterize the epigenomes of specific CNS cell types in health and disease. This is especially true as for DNA modifications where most data are derived from bisulfite sequencing that cannot differentiate between DNA methylation and hydroxymethylation. In this study, we developed an in vivo tagging mouse model (Camk2a-NuTRAP) for paired isolation of neuronal DNA and RNA without cell sorting and then used this model to assess epigenomic regulation of gene expression between neurons and glia.

Results

After validating the cell-specificity of the Camk2a-NuTRAP model, we performed TRAP-RNA-Seq and INTACT whole genome oxidative bisulfite sequencing to assess the neuronal translatome and epigenome in the hippocampus of young mice (3 months old). These data were then compared to microglial and astrocytic data from NuTRAP models. When comparing the different cell types, microglia had the highest global mCG levels followed by astrocytes and then neurons, with the opposite pattern observed for hmCG and mCH. Differentially modified regions between cell types were predominantly found within gene bodies and distal intergenic regions, with limited differences occurring within proximal promoters. Across cell types there was a negative correlation between DNA modifications (mCG, mCH, hmCG) and gene expression at proximal promoters. In contrast, a negative correlation of mCG with gene expression within the gene body while a positive relationship between distal promoter and gene body hmCG and gene expression was observed. Furthermore, we identified a neuron-specific inverse relationship between mCH and gene expression across promoter and gene body regions.

Conclusions

In this study, we identified differential usage of DNA modifications across CNS cell types, and assessed the relationship between DNA modifications and gene expression in neurons and glia. Despite having different global levels, the general modification-gene expression relationship was conserved across cell types. The enrichment of differential modifications in gene bodies and distal regulatory elements, but not proximal promoters, across cell types highlights epigenomic patterning in these regions as potentially greater determinants of cell identity.

Utility of DNA Methylation as a Biomarker in Aging and Alzheimer's Disease

Epigenetic mechanisms such as DNA methylation have been implicated in a number of diseases including cancer, heart disease, autoimmune disorders, and neurodegenerative diseases. While it is recognized that DNA methylation is tissue-specific, a limitation for many studies is the ability to sample the tissue of interest, which is why there is a need for a proxy tissue such as blood, that is reflective of the methylation state of the target tissue. In the last decade, DNA methylation has been utilized in the design of epigenetic clocks, which aim to predict an individual's biological age based on an algorithmically defined set of CpGs. A number of studies have found associations between disease and/or disease risk with increased biological age, adding weight to the theory of increased biological age being linked with disease processes. Hence, this review takes a closer look at the utility of DNA methylation as a biomarker in aging and disease, with a particular focus on Alzheimer's disease.

Entorhinal cortex epigenome-wide association study highlights four novel loci showing differential methylation in Alzheimer's disease

BACKGROUND

Studies on DNA methylation (DNAm) in Alzheimer's disease (AD) have recently highlighted several genomic loci showing association with disease onset and progression.

METHODS

Here, we conducted an epigenome-wide association study (EWAS) using DNAm profiles in entorhinal cortex (EC) from 149 AD patients and control brains and combined these with two previously published EC datasets by meta-analysis (total n = 337).

RESULTS

We identified 12 cytosine-phosphate-guanine (CpG) sites showing epigenome-wide significant association with either case-control status or Braak's tau-staging. Four of these CpGs, located in proximity to CNFN/LIPE, TENT5A, PALD1/PRF1, and DIRAS1, represent novel findings. Integrating DNAm levels with RNA sequencing-based mRNA expression data generated in the same individuals showed significant DNAm-mRNA correlations for 6 of the 12 significant CpGs. Lastly, by calculating rates of epigenetic age acceleration using two recently proposed "epigenetic clock" estimators we found a significant association with accelerated epigenetic aging in the brains of AD patients vs. controls.

CONCLUSION

In summary, our study represents the hitherto most comprehensive EWAS in AD using EC and highlights several novel differentially methylated loci with potential effects on gene expression.

Epigenetic Alterations of Brain Non-Neuronal Cells in Major Mental Diseases

The tissue-specific expression and epigenetic dysregulation of many genes in cells derived from the postmortem brains of patients have been reported to provide a fundamental biological framework for major mental diseases such as autism, schizophrenia, bipolar disorder, and major depression. However, until recently, the impact of non-neuronal brain cells, which arises due to cell-type-specific alterations, has not been adequately scrutinized; this is because of the absence of techniques that directly evaluate their functionality. With the emergence of single-cell technologies, such as RNA sequencing (RNA-seq) and other novel techniques, various studies have now started to uncover the cell-type-specific expression and DNA methylation regulation of many genes (e.g., TREM2, MECP2, SLC1A2, TGFB2, NTRK2, S100B, KCNJ10, and HMGB1, and several complement genes such as C1q, C3, C3R, and C4) in the non-neuronal brain cells involved in the pathogenesis of mental diseases. Additionally, several lines of experimental evidence indicate that inflammation and inflammation-induced oxidative stress, as well as many insidious/latent infectious elements including the gut microbiome, alter the expression status and the epigenetic landscapes of brain non-neuronal cells. Here, we present supporting evidence highlighting the importance of the contribution of the brain's non-neuronal cells (in particular, microglia and different types of astrocytes) in the pathogenesis of mental diseases. Furthermore, we also address the potential impacts of the gut microbiome in the dysfunction of enteric and brain glia, as well as astrocytes, which, in turn, may affect neuronal functions in mental disorders. Finally, we present evidence that supports that microbiota transplantations from the affected individuals or mice provoke the corresponding disease-like behavior in the recipient mice, while specific bacterial species may have beneficial effects.

Impact of intrauterine exposure to maternal diabetes on preterm birth: fetal DNA methylation alteration is an important mediator

BACKGROUND

In utero exposure to diabetes has been shown to contribute to preterm birth, though the underlying biological mechanisms are yet to be fully elucidated. Fetal epigenetic variations established in utero may be a possible pathway. This study aimed to investigate whether in utero exposure to diabetes was associated with a change in newborn DNA methylation, and whether the identified CpG sites mediate the association between diabetes and preterm birth in a racially diverse birth cohort population.

METHODS

This study included 954 mother-newborn pairs. Methylation levels in the cord blood were determined using the Illumina Infinium MethylationEPIC BeadChip 850 K array platform. In utero exposure to diabetes was defined by the presence of maternal pregestational or gestational diabetes. Preterm birth was defined as gestational age at birth less than 37 weeks. Linear regression analysis was employed to identify differentially methylated CpG sites. Differentially methylated regions were identified using the DMRcate Package.

RESULTS

126 (13%) newborns were born to mothers with diabetes in pregnancy and 173 (18%) newborns were born preterm, while 41 newborns were born both preterm and to mothers with diabetes in pregnancy. Genomic-wide CpG analysis found that eighteen CpG sites in cord blood were differentially methylated by maternal diabetes status at an FDR threshold of 5%. These significant CpG sites were mapped to 12 known genes, one of which was annotated to gene Major Histocompatibility Complex, Class II, DM Beta (HLA-DMB). Consistently, one of the two identified significant methylated regions overlapped with HLA-DMB. The identified differentially methylated CpG sites mediated the association between diabetes in pregnancy and preterm birth by 61%.

CONCLUSIONS

In this US birth cohort, we found that maternal diabetes was associated with altered fetal DNA methylation patterns, which substantially explained the link between diabetes and preterm birth.

Differential expression of m5C RNA methyltransferase genes NSUN6 and NSUN7 in Alzheimer's disease and traumatic brain injury

Epigenetic processes have become increasingly relevant in understanding disease-modifying mechanisms. 5-Methylcytosine methylations of DNA (5mC) and RNA (m⁵C) have functional transcriptional and RNA translational consequences and are tightly regulated by writer, reader and eraser effector proteins. To investigate the involvement of 5mC/5hmC and m⁵C effector proteins contributing to the development of dementia neuropathology, RNA sequencing data of 31 effector proteins across four brain regions was examined in 56 aged non-affected and 51 Alzheimer's disease (AD) individuals obtained from the Aging, Dementia and Traumatic Brain Injury Study. Gene expression profiles were compared between AD and controls, between neuropathological Braak and CERAD scores and in individuals with a history of traumatic brain injury (TBI). We found an increase in the DNA methylation writers DNMT1, DNMT3A and DNMT3B messenger RNA (mRNA) and a decrease in the reader UHRF1 mRNA in AD samples across three brain regions whilst the DNA erasers GADD45B and AICDA showed changes in mRNA abundance within neuropathological load groupings. RNA methylation writers NSUN6 and NSUN7 showed significant expression differences with AD and, along with the reader ALYREF, differences in expression for neuropathologic ranking. A history of TBI was associated with a significant increase in the DNA readers ZBTB4 and MeCP2 (p < 0.05) and a decrease in NSUN6 (p < 0.001) mRNA. These findings implicate regulation of protein pathways disrupted in AD and TBI via multiple pre- and post-transcriptional mechanisms including potentially acting upon transfer RNAs, enhancer RNAs as well as nuclear-cytoplasmic shuttling and cytoplasmic translational control. The targeting of such processes provides new therapeutic avenues for neurodegenerative brain conditions.

Epigenetic and epitranscriptomic regulation of axon regeneration

Effective axonal regeneration in the adult mammalian nervous system requires coordination of elevated intrinsic growth capacity and decreased responses to the inhibitory environment. Intrinsic regenerative capacity largely depends on the gene regulatory network and protein translation machinery. A failure to activate these pathways upon injury is underlying a lack of robust axon regeneration in the mature mammalian central nervous system. Epigenetics and epitranscriptomics are key regulatory mechanisms that shape gene expression and protein translation. Here, we provide an overview of different types of modifications on DNA, histones, and RNA, underpinning the regenerative competence of axons in the mature mammalian peripheral and central nervous systems. We highlight other non-neuronal cells and their epigenetic changes in determining the microenvironment for tissue repair and axon regeneration. We also address advancements of single-cell technology in charting transcriptomic and epigenetic landscapes that may further facilitate the mechanistic understanding of differential regenerative capacity in neuronal subtypes. Finally, as epigenetic and epitranscriptomic processes are commonly affected by brain injuries and psychiatric disorders, understanding their alterations upon brain injury would provide unprecedented mechanistic insights into etiology of injury-associated-psychiatric disorders and facilitate the development of therapeutic interventions to restore brain function.

ADmeth: A Manually Curated Database for the Differential Methylation in Alzheimer's Disease

Alzheimer's disease (AD) is the most common neurodegenerative disease. More and more evidence show that DNA methylation is closely related to the pathological mechanism of AD. Many AD-associated differentially methylated genes, regions and CpG sites have been identified in recent researches, which may have great potential in clinical research. However, there is no dedicated database to collect AD-related differential methylation up to now. To provide a reference to researchers, we design a database named ADmeth by manually curating relevant articles, which contains a total of 16,709 AD-related differentially methylated items identified from different brain regions and different cell types in the blood, involving 209 genes, 2,229 regions and 14,271 CpG sites. The ADmeth database provides user-friendly pages to search, submit and download data. We hope that the ADmeth database can facilitate researchers to select candidate AD-associated methylation markers in revealing the pathological mechanism of AD and promote the cell-free DNA based non-invasive diagnosis of AD. The ADmeth database is available at http://www.biobdlab.cn/ADmeth.

Mechanisms of abnormal adult hippocampal neurogenesis in Alzheimer's disease

Alzheimer's disease (AD) is a degenerative disease of the central nervous system, the most common type of dementia in old age, which causes progressive loss of cognitive functions such as thoughts, memory, reasoning, behavioral abilities and social skills, affecting the daily life of patients. The dentate gyrus of the hippocampus is a key area for learning and memory functions, and an important site of adult hippocampal neurogenesis (AHN) in normal mammals. AHN mainly consists of the proliferation, differentiation, survival and maturation of newborn neurons and occurs throughout adulthood, but the level of AHN decreases with age. In AD, the AHN will be affected to different degrees at different times, and its exact molecular mechanisms are increasingly elucidated. In this review, we summarize the changes of AHN in AD and its alteration mechanism, which will help lay the foundation for further research on the pathogenesis and diagnostic and therapeutic approaches of AD.