Parkinson's disease (PD) is a progressive movement disorder that affects over ten million individuals worldwide. While the involvement of genetically-driven cellular mechanisms in PD pathogenesis is well-established, there is increasing evidence that epigenetic dysregulation also plays a key role. We profiled genome-wide DNA methylation in isolated neuronal, oligodendrocyte and other glial nuclei populations from the prefrontal cortex of 71 PD and 56 control individuals. We identified seven significant differentially methylated positions in neuronal nuclei associated with PD. All these sites were hypermethylated in PD, with five of the differentially methylated positions located in the following genes: ROBO4, SSBP2, PDE4B, NPHP1, and HSD17B12. No differentially methylated positions were observed in oligodendrocyte or other glial nuclei, highlighting the neuronal specificity of PD-associated methylation changes. Comparison with a large bulk brain meta-analysis of Lewy body pathology confirmed concordant directionality for ~79% of neuronal differentially methylated positions, indicating that bulk tissue signals primarily reflect neuronal alterations. Together, these findings provide the first cell type-resolved map of DNA methylation changes in the PD cortex, revealing neuronal-specific hypermethylation at novel loci and emphasizing the importance of cell type-specific analyses in disentangling the molecular heterogeneity of PD. This study lays the groundwork for future multi-omics and region-specific studies aimed at uncovering mechanisms underlying disease vulnerability and progression at the cellular level. ### Competing Interest Statement The authors have declared no competing interest. ### Funding Statement This research was supported by the Wellcome Trust Seed Award in Science (217561/Z/19/Z) and research grants from the Medical Research Council (MRC) (MR/S011625/1). A.K. was funded by the GW4 BioMed MRC Doctoral Training Partnership. E.H., E.L.D., and J.M. were supported by MRC grants K013807 and W004984 (awarded to J.M.). Data analysis was undertaken using high-performance computing supported by a MRC Clinical Infrastructure award (M008924 awarded to J.M.). This study was also supported by the National Institute for Health and Care Research Exeter Biomedical Research Centre. The views expressed are those of the author(s) and not necessarily those of the NIHR or the Department of Health and Social Care. ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: Ethics committee of University of Exeter gave ethical approval for this work I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable. Yes DNA methylation data will be made available on the Gene Expression Omnibus platform upon final publication.

Collectively, neurodegenerative diseases impose an escalating global health burden, representing one of the leading causes of death and disability worldwide. Despite their growing prevalence, diagnosis and treatment remain major challenges, partly due to the absence of specific and reliable biomarkers for early detection, disease monitoring, and prognosis. Epigenetic biomarkers are emerging as promising clinical tools, although their potential in the context of neurodegenerative diseases is not yet fully realised. In this review, we provide an overview of advances in the understanding of DNA modifications and chromatin architecture in neurodegeneration, highlighting translational relevance for biomarker discovery and therapeutic development. Finally, building on insights from other diseases where epigenetic biomarkers are already applied, we discuss the key steps required to enable implementation in neurodegenerative diseases.

Background and Hypothesis SETD1A, a histone methyltransferase, is implicated in schizophrenia through rare loss-of-function mutations. While SETD1A regulates gene expression via histone H3K4 methylation, its influence on broader epigenetic dysregulation remains incompletely understood. We explored the hypothesis that SETD1A haploinsufficiency contributes to neurodevelopmental disruptions associated with schizophrenia risk via alterations in DNA methylation.Study Design We profiled DNA methylation in the frontal cortex of Setd1a+/- mice across prenatal and postnatal development using Illumina Mouse Methylation arrays. Differentially methylated positions and regions were identified, and their functional relevance was examined through gene and biological annotation. We integrated these findings with transcriptomic and proteomics datasets, and assessed mitochondrial complex I activity to explore potential downstream functional effects.Study Results Setd1a haploinsufficiency resulted in widespread hypomethylation of genes related to ribosomal function and RNA processing that persisted across all developmental stages. Setd1a-targeted promoter regions and noncoding small nucleolar RNAs were also enriched for differentially methylated sites. Despite the downregulation of mitochondrial gene expression, the same genes were not differentially methylated, and complex I activity in Setd1a+/- mice did not differ significantly from controls. Genes overlapping hypomethylated regions were enriched for common genetic associations with schizophrenia.Conclusions Our findings suggest that SETD1A haploinsufficiency disrupts the epigenetic regulation of ribosomal pathways. These results provide insight into an alternative mechanism through which genetic variation in SETD1A influences developmental and synaptic plasticity, contributing to schizophrenia pathophysiology.

We first proposed the prenatal sex steroid theory of autism 25 years ago to account for a number of then-unexplained observations around autism, including (1) the more frequent diagnosis of autism in male than in female individuals and (2) apparent 'male-type' shifts in cognitive traits associated with autism, such as empathizing and systemizing. Here we review 25 years of research testing this theory. Early studies found that higher prenatal testosterone levels were associated with slower social, language and empathy development, greater attention to detail, stronger systemizing and more autistic traits. Subsequent studies suggested that both prenatal androgens and oestrogens are associated with autism. New methods in genetics and using stem-cell-derived neural organoids have further indicated the importance of sex steroid hormones for neurodevelopment, as well as atypical patterns in autism. These new findings support and open new lines of research into the prenatal sex steroid theory of autism.

Most mental disorders emerge before age 24, yet the mechanisms shaping youth mental health trajectories remain poorly understood. Here, we present the Youth-GEMs consortium performing a multidisciplinary, multisite research project funded by a European Union Horizon-Staying-Healthy-2021 grant. The Youth-GEMs project (Gene Environment interactions in Mental health trajectorieS of Youth) has an integrated, developmental framework that examines how genetic, epigenetic, and environmental factors dynamically interact to influence risk and resilience across adolescence and young adulthood. The project combines developmental (epi)genomic mapping of the human brain, genomic analyses of trans-syndromal phenotypes, exposome-wide environmental assessment, and Artificial Intelligence-based modelling to identify predictive and actionable markers of mental health trajectories of young people. By harmonizing multimodal data from existing population-based cohorts and by establishing the first international, trans-syndromal clinical cohort of help-seeking young people, Youth-GEMs is generating biologically informed polygenic and exposomic scores, cell-type-specific regulatory annotations, and interpretable machine-learning models. Continuous engagement with young people, clinicians, and stakeholders ensures that findings translate into tools for early detection, monitoring, and personalized intervention. Together, these efforts aim to advance mechanistic understandings of youth mental health, improve prediction of emerging illness, and support the development of evidence-based, developmentally sensitive approaches to prevention and care.

Increased understanding of the functional complexity of the genome has led to growing recognition about the role of epigenetic/transcriptional variation in health and disease. Current analyses of the human brain, however, are limited by the use of “bulk” tissue, comprising a heterogeneous mix of different neural cell types. As epigenetic processes play a critical role in determining cell type-specific patterns of gene regulation it is important to consider cellular composition in regulatory genomic studies of human post-mortem tissue, and there is a need for methods to purify populations of specific cell-types. Furthermore, the valuable nature of human post-mortem tissue means it is important to use methods that maximize the amount of genomic data generated on each sample. This protocol describes a method that uses fluorescence-activated nuclei sorting (FANS) to isolate and profile nuclei from multiple different human brain cell-types from frozen post-mortem tissue. This protocol can be used to robustly purify populations of neuronal (NeuN+ve), oligodendrocytes (SOX10+ve), microglia (IRF8+ve) and other glial origin nuclei (NeuN-ve/SOX10-ve/IRF8-ve) from adult post-mortem frozen brain, with each tissue sample yielding purified populations of nuclei amenable to simultaneous analysis of i) DNA modifications (via bisulfite sequencing / array), ii) histone modifications (CUT&Tag), iii) open chromatin analysis (ATAC-seq), and iv) gene expression (snRNA-seq).

Increased understanding of the functional complexity of the genome has led to growing recognition about the role of epigenetic/transcriptional variation in health and disease. Because epigenetic processes play a critical role in determining cell type-specific patterns of gene regulation it is important to consider cellular composition in regulatory genomic studies of heterogeneous tissue like the brain. Building on a previous protocol for isolating purified populations of nuclei from different cortical cell types from human post-mortem brain tissue, this protocol uses fluorescence-activated nuclei sorting (FANS) to isolate and profile nuclei from multiple different cell types from frozen mouse cortex. This protocol can be used to robustly purify populations of neuronal (NeuN+ve) and microglia (PU.1+ve) and other glial origin nuclei (NeuN-ve/PU.1-ve) from frozen mouse cortex tissue, with each sample yielding purified populations of nuclei amenable to simultaneous analysis of i) DNA modifications (via bisulfite sequencing/microarray), ii) histone modifications, iii) chromatin accessibility (via ATAC-seq), and iv) gene expression (via RNA-seq).

Alzheimer’s disease (AD) is characterized by progressive neurodegeneration driven by tau and amyloid-β (Aβ) pathology, although the underlying molecular mechanisms remain incompletely understood. Emerging evidence implicates altered DNA methylation (DNAm) in AD but comprehensive analyses in experimental models are limited. Here, we profile DNAm dynamics in two widely used transgenic mouse models of tau (rTg4510) and Aβ (J20) neuropathology, focusing on the entorhinal cortex and hippocampus. Using reduced representation bisulfite sequencing (RRBS) and methylation arrays across multiple disease stages, we identified widespread pathology-associated DNAm alterations in both models. Tau pathology in rTg4510 mice was associated with extensive DNAm remodeling at genes involved in neuronal plasticity, apoptosis, and lipid metabolism, including Dcaf5, Creb3l4, and As3mt. In contrast, J20 mice exhibited more modest changes, primarily at immune-related loci such as Grk2, Ncam2, and Prmt8. Tau-associated DNAm changes were more consistent across brain areas than those associated with Aβ pathology. Comparison with human AD DNAm datasets revealed overlapping DNAm differences, including hypermethylation at Ank1 and Prdm16 in rTg4510 mice. These findings provide robust evidence for early, pathology-associated epigenetic alterations in AD and highlight the utility of epigenomic profiling in transgenic models for identifying novel targets for early intervention in AD.

Lewy body (LB) diseases are an umbrella term encompassing a range of neurodegenerative conditions all characterized by the hallmark of intra-neuronal α-synuclein associated with the development of motor and cognitive dysfunction. In this study, we have conducted a large meta-analysis of DNA methylation across multiple cortical brain regions, in relation to increasing burden of LB pathology. Utilizing a combined dataset of 1239 samples across 855 unique donors, we identified a set of 30 false discovery rate (FDR) significant loci that are differentially methylated in association with LB pathology, the most significant of which were located in UBASH3B and PTAFR, as well as an intergenic locus. Ontological enrichment analysis of our meta-analysis results highlights several neurologically relevant traits, including synaptic, inflammatory and vascular alterations. We leverage our summary statistics to compare DNA methylation signatures between different neurodegenerative pathologies and highlight a shared epigenetic profile across LB diseases, Alzheimer's disease and Huntington's disease, although the top-ranked loci show disease specificity. Finally, utilizing summary statistics from previous large-scale genome-wide association studies we report FDR significant enrichment of DNA methylation differences with respect to increasing LB pathology in the SNCA genomic region, a gene previously associated with Parkinson's disease and dementia with Lewy bodies.

Background Sex differences are a key feature of numerous neurodevelopmental conditions but most notably in autism where four males have a diagnosis for every one female. There is increasing recognition that epigenetic dysregulation plays a role in autism, but its relationship across sexes and different neural cell-types has not been fully elucidated. In this study, we aimed to explore the role of sex differences in gene regulation in autism, with a focus on DNA methylation (DNAm), by profiling different neural cell-types from post-mortem cortex tissue. Methods We obtained post-mortem prefrontal cortex tissue from 47 donors with and without an autism diagnosis (autism n=24, control n=23; females (XX) n=14, males (XY) n=33; aged 6-91 years). We used fluorescence activated nuclei sorting (FANS) to isolate nuclei populations from different cell-types prior to DNAm profiling, collecting samples from NeuN+ (neuron-enriched) (n=44), SOX10+ (oligodendrocyte-enriched) (n=44), IRF8+ (microglia-enriched) (n=42) and triple-negative (astrocyte-enriched) (n=45) populations. DNAm was quantified using the Illumina EPICv2 array followed by stringent quality control and normalisation. Epigenome-wide association studies were performed within each cell-type to test the association between DNAm at each individual site (n=889,069) and sex, case/control status (group) and an interaction between sex and group. Results We identified widespread sex differences in DNAm irrespective of group status, including on autosomal chromosomes, many of which were specific to individual cell-types. Of note, we identified a substantial depletion of X-chromosome sex differences in microglia compared to the other cell-types, potentially reflecting cell-type-specific X-chromosome inactivation patterns with implications for dosage compensation. These cell-type-specific sex differences were validated in other FANS DNAm datasets generated on human cortex by our group. Additionally, we highlight cell-type-specific autism vs control (group) differences, including several sex-specific interactions with group and cell-type. The majority of these loci are microglial-specific and many reside in genes previously implicated in autism, building on previous data highlighting the importance of glial cells in autism. Discussion The cell-type-specific sex differences identified in this study have the potential to further our understanding of the mechanisms underpinning sexually dimorphic neurodevelopmental conditions such as autism. The identification of cell-type– and sex-specific differences in DNAm between autistic and non-autistic individuals might provide novel mechanistic insights into the profound sex differences in autism prevalence observed between males and females.

Recent studies on the role of epigenetics in disease have focused on DNA methylation (DNAm) profiled in bulk tissues limiting the detection of the cell type affected by disease-related changes. Advances in isolating homogeneous populations of cells now make it possible to identify DNAm differences associated with disease in specific cell types. Critically, these datasets will require a bespoke analytical framework that can characterize whether the difference affects multiple or is specific to a particular cell type. We take advantage of a large set of DNAm profiles (n = 751) obtained from five different purified cell populations isolated from human prefrontal cortex samples and evaluate the effects on study design, data preprocessing, and statistical analysis for cell-specific studies, particularly for scenarios where multiple cell types are included. We describe novel quality control metrics that confirm successful isolation of purified cell populations, which when included in standard preprocessing pipelines provide confidence in the dataset. Our power calculations show substantial gains in detecting differentially methylated positions for some purified cell populations compared to bulk tissue analyses, countering concerns regarding the feasibility of generating large enough sample sizes for informative epidemiological studies. In a simulation study, we evaluated different regression models finding that this choice impacts on the robustness of the results. These findings informed our proposed two-stage framework for association analyses. Overall, our results provide guidance for cell-specific epigenome-wide association studies, establishing standards for study design and analysis, while showcasing the potential of cell-specific DNAm analyses to reveal links between epigenetic dysregulation and disease.

Smoking is the most important behavioural determinant of morbidity and mortality. Using machine learning on plasma levels of 2,917 proteins in the UK Biobank (n = 43,914), we develop a proteomic Smoking Index (pSIN) comprising 51 proteins that accurately distinguish current from never smokers (AUC = 0.95; 95% CI 0.94-0.95). Validation in the China Kadoorie Biobank (n = 3,977) shows similar accuracy (AUC = 0.91; 95% CI 0.89-0.92). pSIN is significantly associated with the risk of all-cause mortality and 18 major chronic diseases, including cardiovascular, renal, pulmonary, neurodegenerative, and cancer outcomes. Among current and former smokers, pSIN predicts death and 11 diseases independently of self-reported smoking history and lifestyle factors. Genome-wide analysis identifies 125 genes (e.g., ALPP, CST5, IL12B) associated with pSIN, while exposome analysis highlights maternal smoking, diet, physical activity, and air pollution as key modifiers. Notably, pSIN tracks recovery among former smokers and identifies those whose disease risks remain comparable to current smokers. These findings demonstrate that plasma proteomics effectively capture the biological imprint of smoking and predict smoking-related morbidity and mortality, offering a more nuanced, molecularly grounded assessment of individual variation in biological response to smoking.

Transactive response DNA binding protein 43 kDa (TDP43) proteinopathy, characterized by the mislocalization and aggregation of TDP43, is a hallmark of several neurodegenerative diseases including Amyotrophic Lateral Sclerosis (ALS). In this study, we describe the development of a new model of TDP43 proteinopathy using human induced pluripotent stem cell (iPSC)-derived neurons. Utilizing a genome engineering approach, we induced the mislocalization of endogenous TDP43 from the nucleus to the cytoplasm without mutating the TDP43 gene or using chemical stressors. Our model successfully recapitulates key early and late pathological features of TDP43 proteinopathy, including neuronal loss, reduced neurite complexity, and cytoplasmic accumulation and aggregation of TDP43. Concurrently, the loss of nuclear TDP43 leads to splicing defects, while its cytoplasmic gain adversely affects microRNA expression. Strikingly, our observations suggest that TDP43 is capable of sustaining its own mislocalization, thereby perpetuating and further aggravating the proteinopathy. This innovative model provides a valuable tool for the in-depth investigation of the consequences of TDP43 proteinopathy. It offers a clinically relevant platform that will accelerate identification of potential therapeutic targets for the treatment of TDP43-associated neurodegenerative diseases including sporadic ALS.

APOE4 is one of the strongest genetic risk factors for developing Alzheimer's disease. Additionally in 80% of severe cases of Alzheimer's disease, TDP43 inclusions have been found in post mortem brain slices, this suggests TDP43 inclusions may play a role in the progression of Alzheimer's disease. This project aims to investigate if a dual-hit model of both APOE4 expression and TDP43 mislocalisation can result in a synergistic increase in neurodegeneration in IPSC-derived cortical neurones. We optimised a technique for generating BRN2 positive cortical neurones from human IPSCs via over-expression of various transcription factors via lentiviral vectors and addition of various small molecules. Immunostaining and RTQPCR techniques were used to identify these population of neurones. We intend to create our dual hit APOE4-TDP43 mislocalisation model via overexpression of APOE4 via lentiviral factors. TDP43 mislocalisation will be achieved by use of TDP43-GFP tagged IPSCs, and the expression of GFP-specific nanobodies tagged with a nuclear export signal. Quantification of Alzheimer's disease biomarkers such as amyloid beta and phospho-tau will be performed via indirect sandwich ELISA and western blotting. Neurodegeneration will be quantified via multiplex cell viability assay utilising Calcein AM and ethidium homodimer-1. RNA sequencing will identify differences between our dual hit model and controls. We will examine epigenetic changes between our model and compare to Alzheimer's disease to assess the model's validity. Furthermore, we are generating protocols to produce cortical neurones for both cortical layers 2-3 and deeper layers positive for markers such as ISL-1, and CTIP2. Our lab has already previously generated GFP-specific nanobodies that can be expressed via lentiviruses, in addition to a GFP tagged TDP43 IPSC line. We are currently generating lentiviral vectors to transduce our cells with APOE4. Overall our results show great promise as several previous studies provided sufficient justification that demonstrates a role for TDP43 mislocalisation in Alzheimer's disease, thus the establishment of a synergistic effect on the progression of neurodegeneration could open new pathways for research and clinical studies.

Amyotrophic lateral sclerosis (ALS) lacks a specific biomarker, but is defined by relatively selective toxicity to motor neurons (MN). As others have highlighted, this offers an opportunity to develop a sensitive and specific biomarker based on detection of DNA released from dying MN within accessible biofluids. Here we have performed whole genome bisulfite sequencing (WGBS) of iPSC-derived MN from neurologically normal individuals. By comparing MN methylation with an atlas of tissue methylation we have derived a MN-specific signature of hypomethylated genomic regions, which accords with genes important for MN function. Through simulation we have optimised the selection of regions for biomarker detection in plasma and CSF cell-free DNA (cfDNA). However, we show that MN-derived DNA is not detectable via WGBS in plasma cfDNA. In support of our experimental finding, we show theoretically that the relative sparsity of lower MN sets a limit on the proportion of plasma cfDNA derived from MN which is below the threshold for detection via WGBS. Our findings are important for the ongoing development of ALS biomarkers. The MN-specific hypomethylated genomic regions we have derived could be usefully combined with more sensitive detection methods and perhaps with study of CSF instead of plasma. Indeed we demonstrate that neuronal-derived DNA is detectable in CSF. Our work is relevant for all diseases featuring death of rare cell-types.

Increasing evidence suggests that alternative splicing plays an important role in Alzheimer’s disease (AD), a devastating neurodegenerative disorder involving the intracellular aggregation of hyperphosphorylated tau. We used whole transcriptome and targeted long-read cDNA sequencing to profile transcript diversity in the entorhinal cortex of wild-type (WT) and transgenic (TG) mice harbouring a mutant form of human tau. Whole transcriptome profiling showed that previously reported gene-level expression differences between WT and TG mice reflect changes in the abundance of specific transcripts. Ultradeep targeted long-read cDNA sequencing of genes implicated in AD revealed hundreds of novel isoforms and identified specific transcripts associated with the development of tau pathology. Our results highlight the importance of differential transcript usage, even in the absence of gene-level expression alterations, as a mechanism underpinning gene regulation in the development of neuropathology. Our transcript annotations and a novel informatics pipeline for the analysis of long-read transcript sequencing data are provided as a resource to the community.

Prenatal exposure to maternal asthma may influence DNA methylation patterns in offspring, potentially affecting their susceptibility to later diseases including asthma. To investigate the relationship between parental asthma and newborn blood DNA methylation. Epigenome-wide association analyses were conducted in 13 cohorts on 7433 newborns with blood methylation data from the Illumina450K or EPIC array. We used fixed effects meta-analyses to identify differentially methylated CpGs (DMCs) and comb-p to identify differentially methylated regions (DMRs) associated with maternal asthma during pregnancy and maternal asthma ever. Paternal asthma was analyzed for comparison. Models were adjusted for covariates and cell-type composition. We examined whether implicated sites related to gene expression analyses in publicly available data for childhood blood and adult lung. We identified 27 CpGs associated with maternal asthma during pregnancy at False Discovery Rate < 0.05 but none for maternal asthma ever. Two distinct CpGs were associated with paternal asthma. We observed 5 DMRs associated with maternal asthma during pregnancy 3 associated with maternal asthma ever and 13 DMRs associated with paternal asthma. Gene expression analysis using data in blood from 832 children and lung from 424 adults showed associations between identified DMCs using maternal asthma and expression of several genes, including HLA genes and HOXA5, previously implicated in asthma or lung function. Parental asthma, especially maternal asthma during pregnancy, may be associated with alterations in newborn DNA methylation. These findings might shed light on underlying mechanisms for asthma susceptibility.

The Illumina Infinium MethylationEPIC v2.0 BeadChip (EPICv2 array) is a microarray for assessment of the human epigenome. Sites on the EPICv2 array are annotated with an open-source file provided by Illumina, the EPICv2 manifest. Of the 923,452 unique genomic sites targeted by the EPICv2 array, the Illumina manifest identifies just 214,808 as mapping to a gene, excluding many sites located within a gene body. Based on the genomic coordinates of probes, we have mapped each site assayed on the Illumina EPICv2 array using publicly available data, comprehensively annotating affiliated genes and regulatory elements. We have found that a total of 700,392 EPICv2 array sites are located within a gene body (exon, intron, or UTR) according to the GENCODE Human release 47 (GENCODEv47) database. 509,940 of these sites were not annotated as being within a gene in the Illumina EPICv2 manifest, primarily because the Illumina manifest does not annotate introns - 498,407 of the excluded sites, or 97.74%, are located within the intron of at least one transcript. The Illumina EPICv2 manifest annotates 358,539 sites as being within 1500bp of a transcription start site (TSS). Using a distance-based approach, we have labelled 267,183 sites as being within promoter distance of a gene (<1500bp upstream or <500bp downstream of the TSS), and 140,123 sites as being within enhancer distance (1501-5000bp upstream of the TSS, excluding sites located within a gene body). We re-annotated the EPICv2 manifest using GENCODEv47 data to label intragenic features, and a distance-based approach to label the regulatory genome. We also include a column indicating whether a site is located in any promoter or enhancer, according to the GeneHancer database. The re-annotated manifest additionally labels which sites are required for the Horvath DNA Methylation Age Calculator and MethylDetectR epigenetic clocks, to facilitate data preparation for these tools. In conclusion, we have re-annotated the EPICv2 manifest, allowing more complete assessment of EPICv2 sites associated with gene bodies and regulatory regions during the interpretation of epigenetic studies. The re-annotated manifest is publicly available - see the Data Availability section of this article. ### Competing Interest Statement The authors have declared no competing interest.

Major depression (MD) is a leading cause of global disease burden, and both experimental and population-based studies suggest that differences in DNA methylation may be associated with the condition. However, previous DNA methylation studies have, so far, not been widely replicated, suggesting a need for larger meta-analysis studies. Here we conducted a meta-analysis of methylome-wide association analysis for lifetime MD across 18 studies of 24,754 European-ancestry participants (5,443 MD cases) and an East Asian sample (243 cases, 1,846 controls). We identified 15 CpG sites associated with lifetime MD with methylome-wide significance. The methylation score created using the methylome-wide association analysis summary statistics was significantly associated with MD status in an out-of-sample classification analysis (area under the curve 0.53). Methylation score was also associated with five inflammatory markers, with the strongest association found with tumor necrosis factor beta. Mendelian randomization analysis revealed 23 CpG sites potentially causally linked to MD, with 7 replicated in an independent dataset. Our study provides evidence that variations in DNA methylation are associated with MD, and further evidence supporting involvement of the immune system.