A cell epigenotype specific model for the correction of brain cellular heterogeneity bias and its application to age, brain region and major depression

Genetic architecture of epigenetic cortical clock age in brain tissue from older individuals: alterations in CD46 and other loci

The cortical epigenetic clock was developed in brain tissue as a biomarker of brain aging. As one way to identify mechanisms underlying aging, we conducted a GWAS of cortical age. We leveraged postmortem cortex tissue and genotyping array data from 694 participants of the Rush Memory and Aging Project and Religious Orders Study (ROSMAP; 11000,000 SNPs), and meta-analysed ROSMAP with 522 participants of Brains for Dementia Research (5,000,000 overlapping SNPs). We confirmed results using eQTL (cortical bulk and single nucleus gene expression), cortical protein levels (ROSMAP), and phenome-wide association studies (clinical/neuropathologic phenotypes, ROSMAP). In the meta-analysis, the strongest association was rs4244620 (p = 1.29 × 10-7), which also exhibited FDR-significant cis-eQTL effects for CD46 in bulk and single nucleus (microglia, astrocyte, oligodendrocyte, neuron) cortical gene expression. Additionally, rs4244620 was nominally associated with lower cognition, faster slopes of cognitive decline, and greater Parkinsonian signs (n ~ 1700 ROSMAP with SNP/phenotypic data; all p ≤ 0.04). In ROSMAP alone, the top SNP was rs4721030 (p = 8.64 × 10-8) annotated to TMEM106B and THSD7A. Further, in ROSMAP (n = 849), TMEM106B and THSD7A protein levels in cortex were related to many phenotypes, including greater AD pathology and lower cognition (all p ≤ 0.0007). Overall, we identified converging evidence of CD46 and possibly TMEM106B/THSD7A for potential roles in cortical epigenetic clock age.

Single-nucleus transcriptomic profiling of human orbitofrontal cortex reveals convergent effects of aging and psychiatric disease

Aging is a complex biological process and represents the largest risk factor for neurodegenerative disorders. The risk for neurodegenerative disorders is also increased in individuals with psychiatric disorders. Here, we characterized age-related transcriptomic changes in the brain by profiling ~800,000 nuclei from the orbitofrontal cortex from 87 individuals with and without psychiatric diagnoses and replicated findings in an independent cohort with 32 individuals. Aging affects all cell types, with LAMP5+LHX6+ interneurons, a cell-type abundant in primates, by far the most affected. Disrupted synaptic transmission emerged as a convergently affected pathway in aged tissue. Age-related transcriptomic changes overlapped with changes observed in Alzheimer's disease across multiple cell types. We find evidence for accelerated transcriptomic aging in individuals with psychiatric disorders and demonstrate a converging signature of aging and psychopathology across multiple cell types. Our findings shed light on cell-type-specific effects and biological pathways underlying age-related changes and their convergence with effects driven by psychiatric diagnosis.

Map of epigenetic age acceleration: A worldwide analysis

We present a systematic analysis of epigenetic age acceleration based on by far the largest collection of publicly available DNA methylation data for healthy samples (93 datasets, 23 K samples), focusing on the geographic (25 countries) and ethnic (31 ethnicities) aspects around the world. We employed the most popular epigenetic tools for assessing age acceleration and examined their quality metrics and ability to extrapolate to epigenetic data from different tissue types and age ranges different from the training data of these models. In most cases, the models proved to be inconsistent with each other and showed different signs of age acceleration, with the PhenoAge model tending to systematically underestimate and different versions of the GrimAge model tending to systematically overestimate the age prediction of healthy subjects. Referring to data availability and consistency, most countries and populations are still not represented in GEO, moreover, different datasets use different criteria for determining healthy controls. Because of this, it is difficult to fully isolate the contribution of "geography/environment", "ethnicity" and "healthiness" to epigenetic age acceleration. Among the explored metrics, only the DunedinPACE, which measures aging rate, appears to adequately reflect the standard of living and socioeconomic indicators in countries, although it has a limited application to blood methylation data only. Invariably, by epigenetic age acceleration, males age faster than females in most of the studied countries and populations.

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.

Parkinson's disease-associated shifts between DNA methylation and DNA hydroxymethylation in human brain in PD-related genes, including PARK19 (DNAJC6) and PTPRN2 (IA-2β)

Background

The majority of Parkinson's disease (PD) cases are due to a complex interaction between aging, genetics, and environmental factors; epigenetic mechanisms are thought to act as important mediators of these risk factors. While multiple studies to date have explored the role of DNA modifications in PD, few focus on 5-hydroxymethylcytosine (5hmC). Because 5hmC occurs at its highest levels in the brain and is thought to be particularly important in the central nervous system, particularly in the response to neurotoxicants, it is important to explore the potential role of 5hmC in PD. This study expands on our previously published epigenome-wide association study (EWAS) performed on DNA isolated from neuron-enriched nuclei from human postmortem parietal cortex from the Banner Sun Health Research Institute Brain Bank. The study aimed to identify paired changes in 5hmC and 5mC in PD in enriched neuronal nuclei isolated from PD post-mortem parietal cortex and age- and sex-matched controls. We performed oxidative bisulfite (oxBS) conversion and paired it with our previously published bisulfite (BS)-based EWAS on the same samples to identify cytosines with significant shifts between these two related epigenetic marks. Interaction differentially modified cytosines (iDMCs) were identified using our recently published mixed-effects model for co-analyzing βmC and βhmC data.

Results

We identified 1,030 iDMCs with paired changes in 5mC and 5hmC (FDR < 0.05) that map to 695 genes, including PARK19 (DNAJC6), a familial PD gene, and PTPRN2 (IA-2), which has been previously implicated in PD in both epigenetic and mechanistic studies. The majority of iDMC-containing genes have not previously been implicated in PD and were not identified in our previous BS-based EWAS.

Conclusions

These data potentially link epigenetic regulation of the PARK19 and PTPRN2 loci in the pathogenesis of idiopathic PD. In addition, iDMC-containing genes have known functions in synaptic formation and function, cell cycle and senescence, neuroinflammation, and epigenetic regulation. These data suggest that there are significant shifts between 5mC and 5hmC associated with PD in genes relevant to PD pathogenesis that are not captured by analyzing BS-based data alone or by analyzing each mark as a distinct dataset.

A perspective on epigenomic aging processes in the human brain and their plasticity in patients with mental disorders - a systematic review

The debate surrounding nature versus nurture remains a central question in neuroscience, psychology, and in psychiatry, holding implications for both aging processes and the etiology of mental illness. Epigenetics can serve as a bridge between genetic predisposition and environmental influences, thus offering a potential avenue for addressing these questions. Epigenetic clocks, in particular, offer a theoretical framework for measuring biological age based on DNA methylation signatures, enabling the identification of disparities between biological and chronological age. This structured review seeks to consolidate current knowledge regarding the relationship between mental disorders and epigenetic age within the brain. Through a comprehensive literature search encompassing databases such as EBSCO, PubMed, and ClinicalTrials.gov, relevant studies were identified and analyzed. Studies that met inclusion criteria were scrutinized, focusing on those with large sample sizes, analyses of both brain tissue and blood samples, investigation of frontal cortex markers, and a specific emphasis on schizophrenia and depressive disorders. Our review revealed a paucity of significant findings, yet notable insights emerged from studies meeting specific criteria. Studies characterized by extensive sample sizes, analysis of brain tissue and blood samples, assessment of frontal cortex markers, and a focus on schizophrenia and depressive disorders yielded particularly noteworthy results. Despite the limited number of significant findings, these studies shed light on the complex interplay between epigenetic aging and mental illness. While the current body of literature on epigenetic aging in mental disorders presents limited significant findings, it underscores the importance of further research in this area. Future studies should prioritize large sample sizes, comprehensive analyses of brain tissue and blood samples, exploration of specific brain regions such as the frontal cortex, and a focus on key mental disorders. Such endeavors will contribute to a deeper understanding of the relationship between epigenetic aging and mental illness, potentially informing novel diagnostic and therapeutic approaches.

Brain cell-type shifts in Alzheimer's disease, autism, and schizophrenia interrogated using methylomics and genetics

Few neuropsychiatric disorders have replicable biomarkers, prompting high-resolution and large-scale molecular studies. However, we still lack consensus on a more foundational question: whether quantitative shifts in cell types-the functional unit of life-contribute to neuropsychiatric disorders. Leveraging advances in human brain single-cell methylomics, we deconvolve seven major cell types using bulk DNA methylation profiling across 1270 postmortem brains, including from individuals diagnosed with Alzheimer's disease, schizophrenia, and autism. We observe and replicate cell-type compositional shifts for Alzheimer's disease (endothelial cell loss), autism (increased microglia), and schizophrenia (decreased oligodendrocytes), and find age- and sex-related changes. Multiple layers of evidence indicate that endothelial cell loss contributes to Alzheimer's disease, with comparable effect size to APOE genotype among older people. Genome-wide association identified five genetic loci related to cell-type composition, involving plausible genes for the neurovascular unit (P2RX5 and TRPV3) and excitatory neurons (DPY30 and MEMO1). These results implicate specific cell-type shifts in the pathophysiology of neuropsychiatric disorders.

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.

The association between neighborhood deprivation and DNA methylation in an autopsy cohort

Previous research has found that living in a disadvantaged neighborhood is associated with poor health outcomes. Living in disadvantaged neighborhoods may alter inflammation and immune response in the body, which could be reflected in epigenetic mechanisms such as DNA methylation (DNAm). We used robust linear regression models to conduct an epigenome-wide association study examining the association between neighborhood deprivation (Area Deprivation Index; ADI), and DNAm in brain tissue from 159 donors enrolled in the Emory Goizueta Alzheimer's Disease Research Center (Georgia, USA). We found one CpG site (cg26514961, gene PLXNC1) significantly associated with ADI after controlling for covariates and multiple testing (p-value=5.0e-8). Effect modification by APOE ε4 was statistically significant for the top ten CpG sites from the EWAS of ADI, indicating that the observed associations between ADI and DNAm were mainly driven by donors who carried at least one APOE ε4 allele. Four of the top ten CpG sites showed a significant concordance between brain tissue and tissues that are easily accessible in living individuals (blood, buccal cells, saliva), including DNAm in cg26514961 (PLXNC1). Our study identified one CpG site (cg26514961, PLXNC1 gene) that was significantly associated with neighborhood deprivation in brain tissue. PLXNC1 is related to immune response, which may be one biological pathway how neighborhood conditions affect health. The concordance between brain and other tissues for our top CpG sites could make them potential candidates for biomarkers in living individuals.

Cortico-striatal differences in the epigenome in attention-deficit/ hyperactivity disorder

While epigenetic modifications have been implicated in ADHD through studies of peripheral tissue, to date there has been no examination of the epigenome of the brain in the disorder. To address this gap, we mapped the methylome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from fifty-eight individuals with or without ADHD. While no single probe showed adjusted significance in differential methylation, several differentially methylated regions emerged. These regions implicated genes involved in developmental processes including neurogenesis and the differentiation of oligodendrocytes and glial cells. We demonstrate a significant association between differentially methylated genes in the caudate and genes implicated by GWAS not only in ADHD but also in autistic spectrum, obsessive compulsive and bipolar affective disorders through GWAS. Using transcriptomic data available on the same subjects, we found modest correlations between the methylation and expression of genes. In conclusion, this study of the cortico-striatal methylome points to gene and gene pathways involved in neurodevelopment, consistent with studies of common and rare genetic variation, as well as the post-mortem transcriptome in ADHD.

Differential DNA methylation in the brain as potential mediator of the association between traffic-related PM2.5 and neuropathology markers of Alzheimer's disease

INTRODUCTION

Growing evidence indicates that fine particulate matter (PM2.5) is a risk factor for Alzheimer's disease (AD), but the underlying mechanisms have been insufficiently investigated. We hypothesized differential DNA methylation (DNAm) in brain tissue as a potential mediator of this association.

METHODS

We assessed genome-wide DNAm (Illumina EPIC BeadChips) in prefrontal cortex tissue and three AD-related neuropathological markers (Braak stage, CERAD, ABC score) for 159 donors, and estimated donors' residential traffic-related PM2.5 exposure 1, 3, and 5 years prior to death. We used a combination of the Meet-in-the-Middle approach, high-dimensional mediation analysis, and causal mediation analysis to identify potential mediating CpGs.

RESULTS

PM2.5 was significantly associated with differential DNAm at cg25433380 and cg10495669. Twenty-four CpG sites were identified as mediators of the association between PM2.5 exposure and neuropathology markers, several located in genes related to neuroinflammation.

DISCUSSION

Our findings suggest differential DNAm related to neuroinflammation mediates the association between traffic-related PM2.5 and AD.

HIGHLIGHTS

First study to evaluate the potential mediation effect of DNA methylation for the association between PM2.5 exposure and neuropathological changes of Alzheimer's disease. Study was based on brain tissues rarely investigated in previous air pollution research. Cg10495669, assigned to RBCK1 gene playing a role in inflammation, was associated consistently with 1-year, 3-year, and 5-year traffic-related PM2.5 exposures prior to death. Meet-in-the-middle approach and high-dimensional mediation analysis were used simultaneously to increase the potential of identifying the differentially methylated CpGs. Differential DNAm related to neuroinflammation was found to mediate the association between traffic-related PM2.5 and Alzheimer's disease.

Deciphering the role of immune cell composition in epigenetic age acceleration: Insights from cell-type deconvolution applied to human blood epigenetic clocks

Aging is a significant risk factor for various human disorders, and DNA methylation clocks have emerged as powerful tools for estimating biological age and predicting health-related outcomes. Methylation data from blood DNA has been a focus of more recently developed DNA methylation clocks. However, the impact of immune cell composition on epigenetic age acceleration (EAA) remains unclear as only some clocks incorporate partial cell type composition information when analyzing EAA. We investigated associations of 12 immune cell types measured by cell-type deconvolution with EAA predicted by six widely-used DNA methylation clocks in data from >10,000 blood samples. We observed significant associations of immune cell composition with EAA for all six clocks tested. Across the clocks, nine or more of the 12 cell types tested exhibited significant associations with EAA. Higher memory lymphocyte subtype proportions were associated with increased EAA, and naïve lymphocyte subtypes were associated with decreased EAA. To demonstrate the potential confounding of EAA by immune cell composition, we applied EAA in rheumatoid arthritis. Our research maps immune cell type contributions to EAA in human blood and offers opportunities to adjust for immune cell composition in EAA studies to a significantly more granular level. Understanding associations of EAA with immune profiles has implications for the interpretation of epigenetic age and its relevance in aging and disease research. Our detailed map of immune cell type contributions serves as a resource for studies utilizing epigenetic clocks across diverse research fields, including aging-related diseases, precision medicine, and therapeutic interventions.

Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles

BACKGROUND

Due to interindividual variation in the cellular composition of the human cortex, it is essential that covariates that capture these differences are included in epigenome-wide association studies using bulk tissue. As experimentally derived cell counts are often unavailable, computational solutions have been adopted to estimate the proportion of different cell types using DNA methylation data. Here, we validate and profile the use of an expanded reference DNA methylation dataset incorporating two neuronal and three glial cell subtypes for quantifying the cellular composition of the human cortex.

RESULTS

We tested eight reference panels containing different combinations of neuronal- and glial cell types and characterised their performance in deconvoluting cell proportions from computationally reconstructed or empirically derived human cortex DNA methylation data. Our analyses demonstrate that while these novel brain deconvolution models produce accurate estimates of cellular proportions from profiles generated on postnatal human cortex samples, they are not appropriate for the use in prenatal cortex or cerebellum tissue samples. Applying our models to an extensive collection of empirical datasets, we show that glial cells are twice as abundant as neuronal cells in the human cortex and identify significant associations between increased Alzheimer's disease neuropathology and the proportion of specific cell types including a decrease in NeuNNeg/SOX10Neg nuclei and an increase of NeuNNeg/SOX10Pos nuclei.

CONCLUSIONS

Our novel deconvolution models produce accurate estimates for cell proportions in the human cortex. These models are available as a resource to the community enabling the control of cellular heterogeneity in epigenetic studies of brain disorders performed on bulk cortex tissue.

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.

Uncertainty quantification of reference-based cellular deconvolution algorithms

The majority of epigenetic epidemiology studies to date have generated genome-wide profiles from bulk tissues (e.g., whole blood) however these are vulnerable to confounding from variation in cellular composition. Proxies for cellular composition can be mathematically derived from the bulk tissue profiles using a deconvolution algorithm; however, there is no method to assess the validity of these estimates for a dataset where the true cellular proportions are unknown. In this study, we describe, validate and characterize a sample level accuracy metric for derived cellular heterogeneity variables. The CETYGO score captures the deviation between a sample's DNA methylation profile and its expected profile given the estimated cellular proportions and cell type reference profiles. We demonstrate that the CETYGO score consistently distinguishes inaccurate and incomplete deconvolutions when applied to reconstructed whole blood profiles. By applying our novel metric to >6,300 empirical whole blood profiles, we find that estimating accurate cellular composition is influenced by both technical and biological variation. In particular, we show that when using a common reference panel for whole blood, less accurate estimates are generated for females, neonates, older individuals and smokers. Our results highlight the utility of a metric to assess the accuracy of cellular deconvolution, and describe how it can enhance studies of DNA methylation that are reliant on statistical proxies for cellular heterogeneity. To facilitate incorporating our methodology into existing pipelines, we have made it freely available as an R package (https://github.com/ds420/CETYGO).

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.

A higher dysregulation burden of brain DNA methylation in female patients implicated in the sex bias of Schizophrenia

Sex differences are pervasive in schizophrenia (SCZ), but the extent and magnitude of DNA methylation (DNAm) changes underlying these differences remain uncharacterized. In this study, sex-stratified differential DNAm analysis was performed in postmortem brain samples from 117 SCZ and 137 controls, partitioned into discovery and replication datasets. Three differentially methylated positions (DMPs) were identified (adj.p < 0.05) in females and 29 DMPs in males without overlap between them. Over 81% of these sex-stratified DMPs were directionally consistent between sexes but with different effect sizes. Females experienced larger magnitude of DNAm changes and more DMPs (based on data of equal sample size) than males, contributing to a higher dysregulation burden of DNAm in females SCZ. Additionally, despite similar proportions of female-related DMPs (fDMPs, 8%) being under genetic control compared with males (10%), significant enrichment of DMP-related single nucleotide polymorphisms (SNPs) in signals of genome-wide association studies was identified only in fDMPs. One DMP in each sex connected the SNPs and gene expression of CALHM1 in females and CCDC149 in males. PPI subnetworks revealed that both female- and male-related differential DNAm interacted with synapse-related dysregulation. Immune-related pathways were unique for females and neuron-related pathways were associated with males. This study reveals remarkable quantitative differences in DNAm-related sexual dimorphism in SCZ and that females have a higher dysregulation burden of SCZ-associated DNAm than males.

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.

Linking environmental risk factors with epigenetic mechanisms in Parkinson's disease

Sporadic Parkinson's disease (PD) is a progressive neurodegenerative disease, with a complex risk structure thought to be influenced by interactions between genetic variants and environmental exposures, although the full aetiology is unknown. Environmental factors, including pesticides, have been reported to increase the risk of developing the disease. Growing evidence suggests epigenetic changes are key mechanisms by which these environmental factors act upon gene regulation, in disease-relevant cell types. We present a systematic review critically appraising and summarising the current body of evidence of the relationship between epigenetic mechanisms and environmental risk factors in PD to inform future research in this area. Epigenetic studies of relevant environmental risk factors in animal and cell models have yielded promising results, however, research in humans is just emerging. While published studies in humans are currently relatively limited, the importance of the field for the elucidation of molecular mechanisms of pathogenesis opens clear and promising avenues for the future of PD research. Carefully designed epidemiological studies carried out in PD patients hold great potential to uncover disease-relevant gene regulatory mechanisms. Therefore, to advance this burgeoning field, we recommend broadening the scope of investigations to include more environmental exposures, increasing sample sizes, focusing on disease-relevant cell types, and recruiting more diverse cohorts.

scMD: 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 development in single-cell DNA methylation (scDNAm), new avenues have been opened for deconvolving bulk DNAm data, particularly for solid tissues like the 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 a precise cell-type signature matrix that surpasses 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.

Genome-wide methylomic regulation of multiscale gene networks in Alzheimer's disease

INTRODUCTION

Recent studies revealed the association of abnormal methylomic changes with Alzheimer's disease (AD) but there is a lack of systematic study of the impact of methylomic alterations over the molecular networks underlying AD.

METHODS

We profiled genome-wide methylomic variations in the parahippocampal gyrus from 201 post mortem control, mild cognitive impaired, and AD brains.

RESULTS

We identified 270 distinct differentially methylated regions (DMRs) associated with AD. We quantified the impact of these DMRs on each gene and each protein as well as gene and protein co-expression networks. DNA methylation had a profound impact on both AD-associated gene/protein modules and their key regulators. We further integrated the matched multi-omics data to show the impact of DNA methylation on chromatin accessibility, which further modulates gene and protein expression.

DISCUSSION

The quantified impact of DNA methylation on gene and protein networks underlying AD identified potential upstream epigenetic regulators of AD.

HIGHLIGHTS

A cohort of DNA methylation data in the parahippocampal gyrus was developed from 201 post mortem control, mild cognitive impaired, and Alzheimer's disease (AD) brains. Two hundred seventy distinct differentially methylated regions (DMRs) were found to be associated with AD compared to normal control. A metric was developed to quantify methylation impact on each gene and each protein. DNA methylation was found to have a profound impact on not only the AD-associated gene modules but also key regulators of the gene and protein networks. Key findings were validated in an independent multi-omics cohort in AD. The impact of DNA methylation on chromatin accessibility was also investigated by integrating the matched methylomic, epigenomic, transcriptomic, and proteomic data.

Differential DNA Methylation in the Brain as Potential Mediator of the Association between Traffic-related PM2.5 and Neuropathology Markers of Alzheimer's Disease

INTRODUCTION

Growing evidence indicates fine particulate matter (PM2.5) as risk factor for Alzheimer's' disease (AD), but the underlying mechanisms have been insufficiently investigated. We hypothesized differential DNA methylation (DNAm) in brain tissue as potential mediator of this association.

METHODS

We assessed genome-wide DNAm (Illumina EPIC BeadChips) in prefrontal cortex tissue and three AD-related neuropathological markers (Braak stage, CERAD, ABC score) for 159 donors, and estimated donors' residential traffic-related PM2.5 exposure 1, 3 and 5 years prior to death. We used a combination of the Meet-in-the-Middle approach, high-dimensional mediation analysis, and causal mediation analysis to identify potential mediating CpGs.

RESULTS

PM2.5 was significantly associated with differential DNAm at cg25433380 and cg10495669. Twenty-six CpG sites were identified as mediators of the association between PM2.5 exposure and neuropathology markers, several located in genes related to neuroinflammation.

DISCUSSION

Our findings suggest differential DNAm related to neuroinflammation mediates the association between traffic-related PM2.5 and AD.

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.

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.

Not every estimate counts - evaluation of cell composition estimation approaches in brain bulk tissue data

BACKGROUND

Variation in cell composition can dramatically impact analyses in bulk tissue samples. A commonly employed approach to mitigate this issue is to adjust statistical models using estimates of cell abundance derived directly from omics data. While an arsenal of estimation methods exists, the applicability of these methods to brain tissue data and whether or not cell estimates can sufficiently account for confounding cellular composition has not been adequately assessed.

METHODS

We assessed the correspondence between different estimation methods based on transcriptomic (RNA sequencing, RNA-seq) and epigenomic (DNA methylation and histone acetylation) data from brain tissue samples of 49 individuals. We further evaluated the impact of different estimation approaches on the analysis of H3K27 acetylation chromatin immunoprecipitation sequencing (ChIP-seq) data from entorhinal cortex of individuals with Alzheimer's disease and controls.

RESULTS

We show that even closely adjacent tissue samples from the same Brodmann area vary greatly in their cell composition. Comparison across different estimation methods indicates that while different estimation methods applied to the same data produce highly similar outcomes, there is a surprisingly low concordance between estimates based on different omics data modalities. Alarmingly, we show that cell type estimates may not always sufficiently account for confounding variation in cell composition.

CONCLUSIONS

Our work indicates that cell composition estimation or direct quantification in one tissue sample should not be used as a proxy to the cellular composition of another tissue sample from the same brain region of an individual-even if the samples are directly adjacent. The highly similar outcomes observed among vastly different estimation methods, highlight the need for brain benchmark datasets and better validation approaches. Finally, unless validated through complementary experiments, the interpretation of analyses outcomes based on data confounded by cell composition should be done with great caution, and ideally avoided all together.

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.

Large epigenome-wide association study identifies multiple novel differentially methylated CpG sites associated with suicidal thoughts and behaviors in veterans

Introduction

The U.S. suicide mortality rate has steadily increased during the past two decades, particularly among military veterans; however, the epigenetic basis of suicidal thoughts and behaviors (STB) remains largely unknown.

Methods

To address this issue, we conducted an epigenome-wide association study of DNA methylation (DNAm) of peripheral blood samples obtained from 2,712 U.S. military veterans.

Results

Three DNAm probes were significantly associated with suicide attempts, surpassing the multiple testing threshold (FDR q-value <0.05), including cg13301722 on chromosome 7, which lies between the genes SLC4A2 and CDK5; cg04724646 in PDE3A; and cg04999352 in RARRES3. cg13301722 was also found to be differentially methylated in the cerebral cortex of suicide decedents in a publicly-available dataset (p = 0.03). Trait enrichment analysis revealed that the CpG sites most strongly associated with STB in the present sample were also associated with smoking, alcohol consumption, maternal smoking, and maternal alcohol consumption, whereas pathway enrichment analysis revealed significant associations with circadian rhythm, adherens junction, insulin secretion, and RAP-1 signaling, each of which was recently associated with suicide attempts in a large, independent genome-wide association study of suicide attempts of veterans.

Discussion

Taken together, the present findings suggest that SLC4A2, CDK5, PDE3A, and RARRES3 may play a role in STB. CDK5, a member of the cyclin-dependent kinase family that is highly expressed in the brain and essential for learning and memory, appears to be a particularly promising candidate worthy of future study; however, additional work is still needed to replicate these finding in independent samples.

ZBTB7A regulates MDD-specific chromatin signatures and astrocyte-mediated stress vulnerability in orbitofrontal cortex

Hyperexcitability in the orbitofrontal cortex (OFC) is a key clinical feature of anhedonic domains of Major Depressive Disorder (MDD). However, the cellular and molecular substrates underlying this dysfunction remain unknown. Here, cell-population-specific chromatin accessibility profiling in human OFC unexpectedly mapped genetic risk for MDD exclusively to non-neuronal cells, and transcriptomic analyses revealed significant glial dysregulation in this region. Characterization of MDD-specific cis-regulatory elements identified ZBTB7A - a transcriptional regulator of astrocyte reactivity - as an important mediator of MDD-specific chromatin accessibility and gene expression. Genetic manipulations in mouse OFC demonstrated that astrocytic Zbtb7a is both necessary and sufficient to promote behavioral deficits, cell-type-specific transcriptional and chromatin profiles, and OFC neuronal hyperexcitability induced by chronic stress - a major risk factor for MDD. These data thus highlight a critical role for OFC astrocytes in stress vulnerability and pinpoint ZBTB7A as a key dysregulated factor in MDD that mediates maladaptive astrocytic functions driving OFC hyperexcitability.

Integrative Co-methylation Network Analysis Identifies Novel DNA Methylation Signatures and Their Target Genes in Alzheimer's Disease

BACKGROUND

DNA methylation is a key epigenetic marker, and its alternations may be involved in Alzheimer's disease (AD). CpGs sharing similar biological functions or pathways tend to be co-methylated.

METHODS

We performed an integrative network-based DNA methylation analysis on 2 independent cohorts (N = 941) using brain DNA methylation profiles and RNA-sequencing as well as AD pathology data.

RESULTS

Weighted co-methylation network analysis identified 6 modules as significantly associated with neuritic plaque burden. In total, 15 hub CpGs including 3 novel CpGs were identified and replicated as being significantly associated with AD pathology. Furthermore, we identified and replicated 4 target genes (ATP6V1G2, VCP, RAD52, and LST1) as significantly regulated by DNA methylation at hub CpGs. In particular, VCP gene expression was also associated with AD pathology in both cohorts.

CONCLUSIONS

This integrative network-based multiomics study provides compelling evidence for a potential role of DNA methylation alternations and their target genes in AD.

Epigenetic changes in the CYP2D6 gene are related to severity of suicide attempt: A cross-sectional study of suicide attempters

BACKGROUND

The ability to accurately estimate risk of suicide deaths on an individual level remains elusive.

METHODS

This study reports on a case-control study set-up from a well-characterized cohort of 88 predominantly female suicide attempters (SA), stratified into low- (n = 57) and high-risk groups (n = 31) based on reports of later death by suicide, as well as degree of intent-to-die and lethality of SA method. We perform an unbiased analysis of 12,930 whole-blood derived CpG-sites (Illumina Infinium EPIC BeadChip) previously demonstrated to be more conciliable with brain-derived variations. The candidate site was validated by pyrosequencing. External replication was performed in (1) relation to age at index suicide attempt in 97 women with emotionally unstable personality disorder (whole-blood) and (2) death by suicide in a mixed group of 183 prefrontal-cortex (PFC) derived samples who died by suicide or from non-psychiatric etiologies.

RESULTS

CYP2D6-coupled CpG-site cg07016288 was hypomethylated in severe suicidal behavior (p < 10E-06). Results were validated by pyrosequencing (p < 0.01). Replication analyses demonstrate hypomethylation of cg07016288 in relation to age at index SA in females (p < 0.05) and hypermethylation in PFC of male suicide completers (p < 0.05).

LIMITATIONS

Genotyping of CYP2D6 was not performed and CpG-site associations to gene expression were not explored.

CONCLUSIONS

CYP2D6-coupled epigenetic markers are hypomethylated in females in dependency of features known to confer increased risk of suicide deaths and hypermethylated in PFC of male suicide completers. Further elucidating the role of CYP2D6 in severe suicidality or suicide deaths hold promise to deduce clinically meaningful results.

DNA Methylation Description of Hippocampus, Cortex, Amygdala, and Blood of Drug-Resistant Temporal Lobe Epilepsy

Epigenetic changes such as DNA methylation were observed in drug-resistant temporal lobe epilepsy (DR-TLE), a disease that affects 25-30% of epilepsy patients. The main objective is to simultaneously describe DNA methylation patterns associated with DR-TLE in hippocampus, amygdala, surrounding cortex to the epileptogenic zone (SCEZ), and peripheral blood. An Illumina Infinium MethylationEPIC BeadChip array was performed in 19 DR-TLE patients and 10 postmortem non-epileptic controls. Overall, 32, 59, and 3210 differentially methylated probes (DMPs) were associated with DR-TLE in the hippocampus, amygdala, and SCEZ, respectively. These DMP-affected genes were involved in neurotrophic and calcium signaling in the hippocampus and voltage-gated channels in SCEZ, among others. One of the hippocampus DMPs (cg26834418 (CHORDC1)) showed a strong blood-brain correlation with BECon and IMAGE-CpG, suggesting that it could be a potential surrogate peripheral biomarker of DR-TLE. Moreover, in three of the top SCEZ's DMPs (SHANK3, SBF1, and MCF2L), methylation status was verified with methylation-specific qPCR. The differentially methylated CpGs were classified in DMRs: 2 in the hippocampus, 12 in the amygdala, and 531 in the SCEZ. We identified genes that had not been associated to DR-TLE so far such as TBX5, EXOC7, and WRHN. The area with more DMPs associated with DR-TLE was the SCEZ, some of them related to voltage-gated channels. The DMPs found in the amygdala were involved in inflammatory processes. We also found a potential surrogate peripheral biomarker of DR-TLE. Thus, these results provide new insights into epigenetic modifications involved in DR-TLE.

Investigating the effects of maltreatment and acute stress on the concordance of blood and DNA methylation methods of estimating immune cell proportions

BACKGROUND

Immune cell proportions can be used to detect pathophysiological states and are also critical covariates in genomic analyses. The complete blood count (CBC) is the most common method of immune cell proportion estimation, but immune cell proportions can also be estimated using whole-genome DNA methylation (DNAm). Although the concordance of CBC and DNAm estimations has been validated in various adult and clinical populations, less is known about the concordance of existing estimators among stress-exposed individuals. As early life adversity and acute psychosocial stress have both been associated with unique DNAm alterations, the concordance of CBC and DNAm immune cell proportion needs to be validated in various states of stress.

RESULTS

We report the correlation and concordance between CBC and DNAm estimates of immune cell proportions using the Illumina EPIC DNAm array within two unique studies: Study 1, a high-risk pediatric cohort of children oversampled for exposure to maltreatment (N = 365, age 8 to 14 years), and Study 2, a sample of young adults who have participated in an acute laboratory stressor with four pre- and post-stress measurements (N = 28, number of observations = 100). Comparing CBC and DNAm proportions across both studies, estimates of neutrophils (r = 0.948, p < 0.001), lymphocytes (r = 0.916, p < 0.001), and eosinophils (r = 0.933, p < 0.001) were highly correlated, while monocyte estimates were moderately correlated (r = 0.766, p < 0.001) and basophil estimates were weakly correlated (r = 0.189, p < 0.001). In Study 1, we observed significant deviations in raw values between the two approaches for some immune cell subtypes; however, the observed differences were not significantly predicted by exposure to child maltreatment. In Study 2, while significant changes in immune cell proportions were observed in response to acute psychosocial stress for both CBC and DNAm estimates, the observed changes were similar for both approaches.

CONCLUSIONS

Although significant differences in immune cell proportion estimates between CBC and DNAm exist, as well as stress-induced changes in immune cell proportions, neither child maltreatment nor acute psychosocial stress alters the concordance of CBC and DNAm estimation methods. These results suggest that the agreement between CBC and DNAm estimators of immune cell proportions is robust to exposure to child maltreatment and acute psychosocial stress.

CeDAR: incorporating cell type hierarchy improves cell type-specific differential analyses in bulk omics data

Bulk high-throughput omics data contain signals from a mixture of cell types. Recent developments of deconvolution methods facilitate cell type-specific inferences from bulk data. Our real data exploration suggests that differential expression or methylation status is often correlated among cell types. Based on this observation, we develop a novel statistical method named CeDAR to incorporate the cell type hierarchy in cell type-specific differential analyses of bulk data. Extensive simulation and real data analyses demonstrate that this approach significantly improves the accuracy and power in detecting cell type-specific differential signals compared with existing methods, especially in low-abundance cell types.

Cross-tissue correlations of genome-wide DNA methylation in Japanese live human brain and blood, saliva, and buccal epithelial tissues

Neuroepigenetics considers genetic sequences and the interplay with environmental influences to elucidate vulnerability risk for various neurological and psychiatric disorders. However, evaluating DNA methylation of brain tissue is challenging owing to the issue of tissue specificity. Consequently, peripheral surrogate tissues were used, resulting in limited progress compared with other epigenetic studies, such as cancer research. Therefore, we developed databases to establish correlations between the brain and peripheral tissues in the same individuals. Four tissues, resected brain tissue, blood, saliva, and buccal mucosa (buccal), were collected from 19 patients (aged 13-73 years) who underwent neurosurgery. Moreover, their genome-wide DNA methylation was assessed using the Infinium HumanMethylationEPIC BeadChip arrays to determine the cross-tissue correlation of each combination. These correlation analyses were conducted with all methylation sites and with variable CpGs, and with when these were adjusted for cellular proportions. For the averaged data for each CpG across individuals, the saliva-brain correlation (r = 0.90) was higher than that for blood-brain (r = 0.87) and buccal-brain (r = 0.88) comparisons. Among individual CpGs, blood had the highest proportion of CpGs correlated to the brain at nominally significant levels (19.0%), followed by saliva (14.4%) and buccal (9.8%). These results were similar to the previous IMAGE-CpG results; however, cross-database correlations of the correlation coefficients revealed a relatively low (brain vs. blood: r = 0.27, saliva: r = 0.18, and buccal: r = 0.24). To the best of our knowledge, this is the fifth study in the literature initiating the development of databases for correlations between the brain and peripheral tissues in the same individuals. We present the first database developed from an Asian population, specifically Japanese samples (AMAZE-CpG), which would contribute to interpreting individual epigenetic study results from various Asian populations.

Epigenetic age acceleration is associated with oligodendrocyte proportions in MSA and control brain tissue

AIMS

Epigenetic clocks are widely applied as surrogates for biological age in different tissues and/or diseases, including several neurodegenerative diseases. Despite white matter (WM) changes often being observed in neurodegenerative diseases, no study has investigated epigenetic ageing in white matter.

METHODS

We analysed the performances of two DNA methylation-based clocks, DNAmClockMulti and DNAmClockCortical , in post-mortem WM tissue from multiple subcortical regions and the cerebellum, and in oligodendrocyte-enriched nuclei. We also examined epigenetic ageing in control and multiple system atrophy (MSA) (WM and mixed WM and grey matter), as MSA is a neurodegenerative disease comprising pronounced WM changes and α-synuclein aggregates in oligodendrocytes.

RESULTS

Estimated DNA methylation (DNAm) ages showed strong correlations with chronological ages, even in WM (e.g., DNAmClockCortical , r = [0.80-0.97], p < 0.05). However, performances and DNAm age estimates differed between clocks and brain regions. DNAmClockMulti significantly underestimated ages in all cohorts except in the MSA prefrontal cortex mixed tissue, whereas DNAmClockCortical tended towards age overestimations. Pronounced age overestimations in the oligodendrocyte-enriched cohorts (e.g., oligodendrocyte-enriched nuclei, p = 6.1 × 10-5 ) suggested that this cell type ages faster. Indeed, significant positive correlations were observed between estimated oligodendrocyte proportions and DNAm age acceleration estimated by DNAmClockCortical (r > 0.31, p < 0.05), and similar trends were obtained with DNAmClockMulti . Although increased age acceleration was observed in MSA compared with controls, no significant differences were detected upon adjustment for possible confounders (e.g., cell-type proportions).

CONCLUSIONS

Our findings show that oligodendrocyte proportions positively influence epigenetic age acceleration across brain regions and highlight the need to further investigate this in ageing and neurodegeneration.

A Higher Dysregulation Burden of Brain DNA Methylation in Female Patients Implicated in the Sex Bias of Schizophrenia

Sex differences are pervasive in schizophrenia (SCZ), but the extent and magnitude of DNA methylation (DNAm) changes underlying these differences remain uncharacterized. In this study, sex-stratified differential DNAm analysis was performed in postmortem brain samples from 117 SCZ and 137 controls, partitioned into discovery and replication datasets. Three differentially methylated positions (DMPs) were identified (adj. p  < 0.05) in females and 29 DMPs in males without overlap between them. Over 81% of these sex-stratified DMPs were directionally consistent between sexes but with different effect sizes. Down-sampling analysis revealed more DMPs in females than in males when the sample sizes matched. Females had higher DNAm levels in healthy individuals and larger magnitude of DNAm changes in patients than males. Despite similar proportions of female-related DMPs (fDMPs, 8%) being under genetic control compared with males (10%), significant enrichment of DMP-related SNPs in signals of genome-wide association studies was identified only in fDMPs. One DMP in each sex connected the SNPs and gene expression of CALHM1 in females and CCDC149 in males. PPI subnetworks revealed that both female- and male-related differential DNAm interacted with synapse-related dysregulation. Immune-related pathways were unique for females and neuron-related pathways were associated with males. This study reveals remarkable quantitative differences in DNAm-related sexual dimorphism in SCZ and that females have a higher dysregulation burden of SCZ-associated DNAm than males.

Methylation in MAD1L1 is associated with the severity of suicide attempt and phenotypes of depression

Depression is a multifactorial disorder representing a significant public health burden. Previous studies have linked multiple single nucleotide polymorphisms with depressive phenotypes and suicidal behavior. MAD1L1 is a mitosis metaphase checkpoint protein that has been linked to depression in GWAS. Using a longitudinal EWAS approach in an adolescent cohort at two time points (n = 216 and n = 154), we identified differentially methylated sites that were associated with depression-related genetic variants in MAD1L1. Three methylation loci (cg02825527, cg18302629, and cg19624444) were consistently hypomethylated in the minor allele carriers, being cross-dependent on several SNPs. We further investigated whether DNA methylation at these CpGs is associated with depressive psychiatric phenotypes in independent cohorts. The first site (cg02825527) was hypomethylated in blood (exp(β) = 84.521, p value ~ 0.003) in participants with severe suicide attempts (n = 88). The same locus showed increased methylation in glial cells (exp(β) = 0.041, p value ~ 0.004) in the validation cohort, involving 29 depressed patients and 29 controls, and showed a trend for association with suicide (n = 40, p value ~ 0.089) and trend for association with depression treatment (n = 377, p value ~ 0.075). The second CpG (cg18302629) was significantly hypomethylated in depressed participants (exp(β) = 56.374, p value ~ 0.023) in glial cells, but did not show associations in the discovery cohorts. The last methylation site (cg19624444) was hypomethylated in the whole blood of severe suicide attempters; however, this association was at the borderline for statistical significance (p value ~ 0.061). This locus, however, showed a strong association with depression treatment in the validation cohort (exp(β) = 2.237, p value ~ 0.003) with 377 participants. The direction of associations between psychiatric phenotypes appeared to be different in the whole blood in comparison with brain samples for cg02825527 and cg19624444. The association analysis between methylation at cg18302629 and cg19624444 and MAD1L1 transcript levels in CD¹⁴⁺ cells shows a potential link between methylation at these CpGs and MAD1L1 expression. This study suggests evidence that methylation at MAD1L1 is important for psychiatric health as supported by several independent cohorts.

Integrated DNA Methylation/RNA Profiling in Middle Temporal Gyrus of Alzheimer's Disease

Alzheimer's disease is a neurodegenerative disorder clinically defined by gradual cognitive impairment and alteration in executive function. We conducted an epigenome-wide association study (EWAS) of a clinically and neuropathologically characterized cohort of 296 brains, including Alzheimer's disease (AD) and non-demented controls (ND), exploring the relationship with the RNA expression from matched donors. We detected 5246 CpGs and 832 regions differentially methylated, finding overlap with previous EWAS but also new associations. CpGs previously identified in ANK1, MYOC, and RHBDF2 were differentially methylated, and one of our top hits (GPR56) was not previously detected. ANK1 was differentially methylated at the region level, along with APOE and RHBDF2. Only a small number of genes showed a correlation between DNA methylation and RNA expression statistically significant. Multiblock partial least-squares discriminant analysis showed several CpG sites and RNAs discriminating AD and ND (AUC = 0.908) and strongly correlated with each other. Furthermore, the CpG site cg25038311 was negatively correlated with the expression of 22 genes. Finally, with the functional epigenetic module analysis, we identified a protein-protein network characterized by inverse RNA/DNA methylation correlation and enriched for "Regulation of insulin-like growth factor transport", with IGF1 as the hub gene. Our results confirm and extend the previous EWAS, providing new information about a brain region not previously explored in AD DNA methylation studies. The relationship between DNA methylation and gene expression is not significant for most of the genes in our sample, consistently with the complexities in the gene expression regulation.

Cell-Type Deconvolution of Bulk DNA Methylation Data with EpiSCORE

DNA methylation data generated from bulk tissue represents a mixture of many different cell types. Variation in the cell-type composition of tissues is thus a major confounder when inferring differential DNA methylation. Due to the high cost of single-cell methylome sequencing, computational methods that can dissect the cell-type heterogeneity of bulk DNA methylomes offer an efficient and cost-effective solution, especially in the context of large-scale EWAS. In this chapter, we present a step-by-step tutorial of Epigenetic cell-type deconvolution using Single-Cell Omic References (EpiSCORE), a reference-based method that leverages the high-resolution nature of single-cell RNA-Seq datasets to facilitate microdissection of bulk-tissue DNA methylomes.

Within subject cross-tissue analyzes of epigenetic clocks in substance use disorder postmortem brain and blood

There is a possible accelerated biological aging in patients with substance use disorders (SUD). The evaluation of epigenetic clocks, which are accurate estimators of biological aging based on DNA methylation changes, has been limited to blood tissue in patients with SUD. Consequently, the impact of biological aging in the brain of individuals with SUD remains unknown. In this study, we evaluated multiple epigenetic clocks (DNAmAge, DNAmAgeHannum, DNAmAgeSkinBlood, DNAmPhenoAge, DNAmGrimAge, and DNAmTL) in individuals with SUD (n = 42), including alcohol (n = 10), opioid (n = 19), and stimulant use disorder (n = 13), and controls (n = 10) in postmortem brain (prefrontal cortex) and blood tissue obtained from the same individuals. We found a higher DNAmPhenoAge (β = 0.191, p-value = 0.0104) and a nominally lower DNAmTL (β = -0.149, p-value = 0.0603) in blood from individuals with SUD compared to controls. SUD subgroup analysis showed a nominally lower brain DNAmTL in subjects with alcohol use disorder, compared to stimulant use disorder and controls (β = 0.0150, p-value = 0.087). Cross-tissue analyzes indicated a lower blood DNAmTL and a higher blood DNAmAge compared to their respective brain values in the SUD group. This study highlights the relevance of tissue specificity in biological aging studies and suggests that peripheral measures of epigenetic clocks in SUD may depend on the specific type of drug used.

Methylation differences in Alzheimer's disease neuropathologic change in the aged human brain

Alzheimer's disease (AD) is the most common cause of dementia with advancing age as its strongest risk factor. AD neuropathologic change (ADNC) is known to be associated with numerous DNA methylation changes in the human brain, but the oldest old (> 90 years) have so far been underrepresented in epigenetic studies of ADNC. Our study participants were individuals aged over 90 years (n = 47) from The 90+ Study. We analyzed DNA methylation from bulk samples in eight precisely dissected regions of the human brain: middle frontal gyrus, cingulate gyrus, entorhinal cortex, dentate gyrus, CA1, substantia nigra, locus coeruleus and cerebellar cortex. We deconvolved our bulk data into cell-type-specific (CTS) signals using computational methods. CTS methylation differences were analyzed across different levels of ADNC. The highest amount of ADNC related methylation differences was found in the dentate gyrus, a region that has so far been underrepresented in large scale multi-omic studies. In neurons of the dentate gyrus, DNA methylation significantly differed with increased burden of amyloid beta (Aβ) plaques at 5897 promoter regions of protein-coding genes. Amongst these, higher Aβ plaque burden was associated with promoter hypomethylation of the Presenilin enhancer 2 (PEN-2) gene, one of the rate limiting genes in the formation of gamma-secretase, a multicomponent complex that is responsible in part for the endoproteolytic cleavage of amyloid precursor protein into Aβ peptides. In addition to novel ADNC related DNA methylation changes, we present the most detailed array-based methylation survey of the old aged human brain to date. Our open-sourced dataset can serve as a brain region reference panel for future studies and help advance research in aging and neurodegenerative diseases.

Meta-analysis of epigenome-wide association studies of major depressive disorder

Epigenetic mechanisms have been hypothesized to play a role in the etiology of major depressive disorder (MDD). In this study, we performed a meta-analysis between two case-control MDD cohorts to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs) in MDD. Using samples from two Cohorts (a total of 298 MDD cases and 63 controls with repeated samples, on average ~ 1.8 samples/subject), we performed an EWAS meta-analysis. Multiple cytosine-phosphate-guanine sites annotated to TNNT3 were associated with MDD reaching study-wide significance, including cg08337959 (p = 2.3 × 10^-11). Among DMPs with association p values less than 0.0001, pathways from REACTOME such as Ras activation upon Ca²⁺ influx through the NMDA receptor (p = 0.0001, p-adjusted = 0.05) and long-term potentiation (p = 0.0002, p-adjusted = 0.05) were enriched in this study. A total of 127 DMRs with Sidak-corrected p value < 0.05 were identified from the meta-analysis, including DMRs annotated to TNNT3 (chr11: 1948933 to 1949130 [6 probes], Sidak corrected P value = 4.32 × 10^-41), S100A13 (chr1: 153599479 to 153600972 [22 probes], Sidak corrected P value = 5.32 × 10^-18), NRXN1 (chr2: 50201413 to 50201505 [4 probes], Sidak corrected P value = 1.19 × 10^-11), IL17RA (chr22: 17564750 to 17565149, Sidak corrected P value = 9.31 × 10^-8), and NPFFR2 (chr4: 72897565 to 72898212, Sidak corrected P value = 8.19 × 10^-7). Using 2 Cohorts of depression case-control samples, we identified DMPs and DMRs associated with MDD. The molecular pathways implicated by these data include mechanisms involved in neuronal synaptic plasticity, calcium signaling, and inflammation, consistent with reports from previous genetic and protein biomarker studies indicating that these mechanisms are involved in the neurobiology of depression.

A comparison of blood and brain-derived ageing and inflammation-related DNA methylation signatures and their association with microglial burdens

Inflammation and ageing-related DNA methylation patterns in the blood have been linked to a variety of morbidities, including cognitive decline and neurodegenerative disease. However, it is unclear how these blood-based patterns relate to patterns within the brain and how each associates with central cellular profiles. In this study, we profiled DNA methylation in both the blood and in five post mortem brain regions (BA17, BA20/21, BA24, BA46 and hippocampus) in 14 individuals from the Lothian Birth Cohort 1936. Microglial burdens were additionally quantified in the same brain regions. DNA methylation signatures of five epigenetic ageing biomarkers ('epigenetic clocks'), and two inflammatory biomarkers (methylation proxies for C-reactive protein and interleukin-6) were compared across tissues and regions. Divergent associations between the inflammation and ageing signatures in the blood and brain were identified, depending on region assessed. Four out of the five assessed epigenetic age acceleration measures were found to be highest in the hippocampus (β range = 0.83-1.14, p ≤ 0.02). The inflammation-related DNA methylation signatures showed no clear variation across brain regions. Reactive microglial burdens were found to be highest in the hippocampus (β = 1.32, p = 5 × 10-4 ); however, the only association identified between the blood- and brain-based methylation signatures and microglia was a significant positive association with acceleration of one epigenetic clock (termed DNAm PhenoAge) averaged over all five brain regions (β = 0.40, p = 0.002). This work highlights a potential vulnerability of the hippocampus to epigenetic ageing and provides preliminary evidence of a relationship between DNA methylation signatures in the brain and differences in microglial burdens.

Genetics and epigenetics of self-injurious thoughts and behaviors: Systematic review of the suicide literature and methodological considerations

Suicide is a multifaceted and poorly understood clinical outcome, and there is an urgent need to advance research on its phenomenology and etiology. Epidemiological studies have demonstrated that suicidal behavior is heritable, suggesting that genetic and epigenetic information may serve as biomarkers for suicide risk. Here we systematically review the literature on genetic and epigenetic alterations observed in phenotypes across the full range of self-injurious thoughts and behaviors (SITB). We included 577 studies focused on genome-wide and epigenome-wide associations, candidate genes (SNP and methylation), noncoding RNAs, and histones. Convergence of specific genes is limited across units of analysis, although pathway-based analyses do indicate nervous system development and function and immunity/inflammation as potential underlying mechanisms of SITB. We provide suggestions for future work on the genetic and epigenetic correlates of SITB with a specific focus on measurement issues.

Sex-specific epigenetic development in the mouse hypothalamic arcuate nucleus pinpoints human genomic regions associated with body mass index

Recent genome-wide association studies corroborate classical research on developmental programming indicating that obesity is primarily a neurodevelopmental disease strongly influenced by nutrition during critical ontogenic windows. Epigenetic mechanisms regulate neurodevelopment; however, little is known about their role in establishing and maintaining the brain's energy balance circuitry. We generated neuron and glia methylomes and transcriptomes from male and female mouse hypothalamic arcuate nucleus, a key site for energy balance regulation, at time points spanning the closure of an established critical window for developmental programming of obesity risk. We find that postnatal epigenetic maturation is markedly cell type and sex specific and occurs in genomic regions enriched for heritability of body mass index in humans. Our results offer a potential explanation for both the limited ontogenic windows for and sex differences in sensitivity to developmental programming of obesity and provide a rich resource for epigenetic analyses of developmental programming of energy balance.

DNA methylation signatures of Alzheimer's disease neuropathology in the cortex are primarily driven by variation in non-neuronal cell-types

Alzheimer's disease (AD) is a chronic neurodegenerative disease characterized by the progressive accumulation of amyloid-beta and neurofibrillary tangles of tau in the neocortex. We profiled DNA methylation in two regions of the cortex from 631 donors, performing an epigenome-wide association study of multiple measures of AD neuropathology. We meta-analyzed our results with those from previous studies of DNA methylation in AD cortex (total n = 2013 donors), identifying 334 cortical differentially methylated positions (DMPs) associated with AD pathology including methylomic variation at loci not previously implicated in dementia. We subsequently profiled DNA methylation in NeuN+ (neuronal-enriched), SOX10+ (oligodendrocyte-enriched) and NeuN-/SOX10- (microglia- and astrocyte-enriched) nuclei, finding that the majority of DMPs identified in 'bulk' cortex tissue reflect DNA methylation differences occurring in non-neuronal cells. Our study highlights the power of utilizing multiple measures of neuropathology to identify epigenetic signatures of AD and the importance of characterizing disease-associated variation in purified cell-types.

Parkinson's disease-associated, sex-specific changes in DNA methylation at PARK7 (DJ-1), SLC17A6 (VGLUT2), PTPRN2 (IA-2β), and NR4A2 (NURR1) in cortical neurons

Evidence for epigenetic regulation playing a role in Parkinson's disease (PD) is growing, particularly for DNA methylation. Approximately 90% of PD cases are due to a complex interaction between age, genes, and environmental factors, and epigenetic marks are thought to mediate the relationship between aging, genetics, the environment, and disease risk. To date, there are a small number of published genome-wide studies of DNA methylation in PD, but none accounted for cell type or sex in their analyses. Given the heterogeneity of bulk brain tissue samples and known sex differences in PD risk, progression, and severity, these are critical variables to account for. In this genome-wide analysis of DNA methylation in an enriched neuronal population from PD postmortem parietal cortex, we report sex-specific PD-associated methylation changes in PARK7 (DJ-1), SLC17A6 (VGLUT2), PTPRN2 (IA-2β), NR4A2 (NURR1), and other genes involved in developmental pathways, neurotransmitter packaging and release, and axon and neuron projection guidance.

Epigenetic clock indicates accelerated aging in glial cells of progressive multiple sclerosis patients

Background

Multiple sclerosis (MS) is a chronic inflammatory neurodegenerative disease of the central nervous system (CNS) characterized by irreversible disability at later progressive stages. A growing body of evidence suggests that disease progression depends on age and inflammation within the CNS. We aimed to investigate epigenetic aging in bulk brain tissue and sorted nuclei from MS patients using DNA methylation-based epigenetic clocks.

Methods

We applied Horvath’s multi-tissue and Shireby’s brain-specific Cortical clock on bulk brain tissue (n = 46), sorted neuronal (n = 54), and glial nuclei (n = 66) from post-mortem brain tissue of progressive MS patients and controls.

Results

We found a significant increase in age acceleration residuals, corresponding to 3.6 years, in glial cells of MS patients compared to controls (P = 0.0024) using the Cortical clock, which held after adjustment for covariates (P_adj = 0.0263). The 4.8-year age acceleration found in MS neurons (P = 0.0054) did not withstand adjustment for covariates and no significant difference in age acceleration residuals was observed in bulk brain tissue between MS patients and controls.

Conclusion

While the findings warrant replication in larger cohorts, our study suggests that glial cells of progressive MS patients exhibit accelerated biological aging.

Epigenome-wide association study of human frontal cortex identifies differential methylation in Lewy body pathology

Parkinson's disease (PD) and dementia with Lewy bodies (DLB) are closely related progressive disorders with no available disease-modifying therapy, neuropathologically characterized by intraneuronal aggregates of misfolded α-synuclein. To explore the role of DNA methylation changes in PD and DLB pathogenesis, we performed an epigenome-wide association study (EWAS) of 322 postmortem frontal cortex samples and replicated results in an independent set of 200 donors. We report novel differentially methylated replicating loci associated with Braak Lewy body stage near TMCC2, SFMBT2, AKAP6 and PHYHIP. Differentially methylated probes were independent of known PD genetic risk alleles. Meta-analysis provided suggestive evidence for a differentially methylated locus within the chromosomal region affected by the PD-associated 22q11.2 deletion. Our findings elucidate novel disease pathways in PD and DLB and generate hypotheses for future molecular studies of Lewy body pathology.