Populations colonizing contrasting environments are likely to undergo adaptive divergence and evolve ecotypes with locally adapted phenotypes. While diverse molecular mechanisms underlying ecotype divergence have been identified, less is known about their interplay and degree of divergence.

Here we integrated epigenomic and transcriptomic data to explore the interactions among gene expression, alternative splicing, DNA methylation, and microRNA expression to gauge the extent to which patterns of divergence at the four molecular levels are aligned in a case of postglacial divergence between marine and freshwater ecotypes of nine-spined sticklebacks (Pungitius pungitius). Despite significant genome-wide associations between epigenomic and transcriptomic variation, we found largely non-parallel patterns of ecotype divergence across epigenomic and transcriptomic levels, with predominantly nonoverlapping (ranging from 43.40 to 87.98%) sets of differentially expressed, spliced and methylated genes, and candidate genes targeted by differentially expressed miRNA between the ecotypes. Furthermore, we found significant variation in the extent of ecotype divergence across different molecular mechanisms, with differential methylation and differential splicing showing the highest and lowest extent of divergence between ecotypes, respectively. Finally, we found a significant enrichment of genes associated with ecotype divergence in differential methylation.

Our results suggest a nuanced relationship between epigenomic and transcriptomic processes, with alignment at the genome-wide level masking relatively independent effects of different molecular mechanisms on ecotype divergence at the gene level.

Chronic exposure to inorganic arsenic (iAs) has been linked with the development of diabetes mellitus (DM). We recently showed that parental exposure to iAs (200 ppb) prior to mating was associated with diabetic phenotypes in offspring and altered gene expression in parents and offspring. The goal of the present study was to determine if DNA methylation underlies the differential gene expression in the livers of offspring. DNA methylation was assessed in paternal (G0) sperm and livers of their offspring (G1) using a genome wide DNA methylation array. We found that iAs exposure significantly altered CpG methylation (p < 0.05) in 54.3 %, 49.4 %, and 63.7 % of the differentially expressed genes in G0 sperm, G1 female livers, and G1 male livers, respectively. Importantly, a subset of differentially methylated CpG sites were shared across generations. Sensitivity analyses (FDR < 0.1) of imprinted and DM-associated genes revealed differential methylation of 74 imprinted genes and 100 DM-associated genes in the livers of G1 males. These male-specific results are intriguing given the prior findings of diabetic phenotypes found exclusively in male offspring from parents exposed to iAs. In summary, these data demonstrate that heritable changes in DNA methylation through the paternal germline may underlie the diabetogenic effects of preconception iAs exposure.

Brain metastasis represents a significant challenge in oncology, driven by complex molecular and epigenetic mechanisms that distinguish it from primary tumors. While recent research has focused on identifying genomic mutation drivers with potential clinical utility, these strategies have not pinpointed specific genetic mutations responsible for site-specific metastasis to the brain. It is now clear that successful brain colonization by metastatic cancer cells requires intricate interactions with the brain tumor ecosystem and the acquisition of specialized molecular traits that facilitate their adaptation to this highly selective environment. This is best exemplified by widespread transcriptional adaptation during brain metastasis, resulting in aberrant gene programs that promote extravasation, seeding, and colonization of the brain. Increasing evidence suggests that epigenetic mechanisms play a significant role in shaping these pro-brain metastasis traits. This review explores dysregulated chromatin patterns driven by chromatin remodeling, histone modifications, DNA/RNA methylation, and other epigenetic regulators that underpin brain metastatic seeding, initiation, and outgrowth. We provide novel insights into how these epigenetic modifications arise within both the brain metastatic tumor and the surrounding brain metastatic tumor ecosystem. Finally, we discuss how the inherent plasticity and reversibility of the epigenomic landscape in brain metastases may offer new therapeutic opportunities.

Preterm labor is a leading cause of neonatal morbidity and mortality worldwide. Previous research has indicated that an inflammatory response or microbial invasion of the amniotic cavity is a pathological condition linked to preterm birth; hence, inflammatory markers such as metalloproteinase-9 (MMP-9), interleukin-6 (IL-6), and interleukin-8 (IL-8) have been utilized to predict preterm delivery. The identification of reliable biomarkers for early prediction is critical for improving maternal, fetal, and neonatal outcomes.

To address this issue, a literature review has been conducted on PubMed/Medline and Scopus databases for articles investigating the possible correlation between IL6, IL8, and MMP9 and preterm labor.

Using a comprehensive search of the PubMed and Scopus databases, 12 studies were analyzed to identify the correlation between these biomarkers and preterm labor. Seven studies point the impact of increased IL-6 levels or polymorphisms of the gene and higher incidence of preterm labor. Two of the included studies identified the increased risk for preterm birth in elevated levels of IL-8 in amniotic fluid. Six studies highlight the increased incidence of preterm birth in women with polymorphisms of the MMP-9 gene.

Elevated IL-6 levels and specific gene polymorphisms are strongly associated with preterm delivery risk, with IL-8 concentrations correlating with systemic inflammation and histologic chorioamnionitis. MMP-9 gene variations and protein levels showed significant predictive value for membrane rupture and labor onset. The findings emphasize integrating these biomarkers into diagnostic tools for routine prenatal care, enhancing early detection, risk stratification, and timely interventions to improve maternal and neonatal outcomes.

Paternal obesity has been implicated in adult-onset metabolic disease in offspring. However, the molecular mechanisms driving these paternal effects and the developmental processes involved remain poorly understood. One underexplored possibility is the role of paternally induced effects on placenta development and function. To address this, we investigated paternal high-fat diet-induced obesity in relation to sperm histone H3 lysine 4 tri-methylation signatures, the placenta transcriptome, and cellular composition. C57BL6/J male mice were fed either a control or high-fat diet for 10 weeks beginning at 6 weeks of age. Males were timed-mated with control-fed C57BL6/J females to generate pregnancies, followed by collection of sperm, and placentas at embryonic day (E)14.5. Chromatin immunoprecipitation targeting histone H3 lysine 4 tri-methylation (H3K4me3) followed by sequencing (ChIP-seq) was performed on sperm to define obesity-associated changes in enrichment. Paternal obesity corresponded with altered sperm H3K4me3 at promoters of genes involved in metabolism and development. Notably, altered sperm H3K4me3 was also localized at placental enhancers. Bulk RNA-sequencing on placentas revealed paternal obesity-associated sex-specific changes in expression of genes involved in hypoxic processes such as angiogenesis, nutrient transport, and imprinted genes, with a subset of de-regulated genes showing changes in H3K4me3 in sperm at corresponding promoters. Paternal obesity was also linked to impaired placenta development; specifically, a deconvolution analysis revealed altered trophoblast cell lineage specification. These findings implicate paternal obesity effects on placenta development and function as one potential developmental route to offspring metabolic disease.

Genetic variation that impacts gene regulation, rather than protein function, can have strong effects on trait variation both within and between species. Epigenetic mechanisms, such as DNA methylation, are often an important intermediate link between genotype and phenotype, yet genetic effects on DNA methylation remain understudied in natural populations. To address this gap, we used reduced representation bisulfite sequencing to measure DNA methylation levels at 555,856 CpGs in peripheral whole blood of 573 samples collected from free-ranging rhesus macaques (Macaca mulatta) living on the island of Cayo Santiago, Puerto Rico. We used allele-specific methods to map cis-methylation quantitative trait loci (meQTL) and tested for effects of 243,389 single nucleotide polymorphisms (SNPs) on local DNA methylation levels. Of 776,092 tested SNP-CpG pairs, we identified 516,213 meQTL, with 69.12% of CpGs having at least one meQTL (FDR < 5%). On average, meQTL explained 21.2% of nearby methylation variance, significantly more than age or sex. meQTL were enriched in genomic compartments where methylation is likely to impact gene expression, for example, promoters, enhancers and binding sites for methylation-sensitive transcription factors. In support, using mRNA-seq data from 172 samples, we confirmed 332 meQTL as whole blood cis-expression QTL (eQTL) in the population, and found meQTL-eQTL genes were enriched for immune response functions, like antigen presentation and inflammation. Overall, our study takes an important step towards understanding the genetic architecture of DNA methylation in natural populations, and more generally points to the biological mechanisms driving phenotypic variation in our close relatives.

Phenotypic aging is ubiquitous across mammalian species, suggesting shared underlying mechanisms of aging. Aging is linked to molecular changes to DNA methylation and gene expression, and environmental factors, such as severe external challenges or adversities, can moderate these age-related changes. Yet, it remains unclear whether environmental adversities affect gene regulation via the same molecular pathways as chronological, or 'primary', aging. Investigating molecular aging in naturalistic animal populations can fill this gap by providing insight into shared molecular mechanisms of aging and the effects of a greater diversity of environmental adversities - particularly those that can be challenging to study in humans or laboratory organisms. Here, we characterised molecular aging - specifically, CpG methylation - in a sample of free-ranging rhesus macaques living off the coast of Puerto Rico (n samples = 571, n individuals = 499), which endured a major hurricane during our study. Age was associated with methylation at 78,661 sites (31% of all sites tested). Age-associated hypermethylation occurred more frequently in areas of active gene regulation, while hypomethylation was enriched in regions that show less activity in immune cells, suggesting these regions may become de-repressed in older individuals. Age-associated hypomethylation also co-occurred with increased chromatin accessibility while hypermethylation showed the opposite trend, hinting at a coordinated, multi-level loss of epigenetic stability during aging. We detected 32,048 CpG sites significantly associated with exposure to a hurricane, and these sites overlapped age-associated sites, most strongly in regulatory regions and most weakly in quiescent regions. Together, our results suggest that environmental adversity may contribute to aging-related molecular phenotypes in regions of active gene transcription, but that primary aging has specific signatures in non-regulatory regions.

Comparative genomic studies of social insects suggest that changes in gene regulation are associated with evolutionary transitions in social behavior, but the activity of predicted regulatory regions has not been tested empirically. We used self-transcribing active regulatory region sequencing, a high-throughput enhancer discovery tool, to identify and measure the activity of enhancers in the socially variable sweat bee, Lasioglossum albipes. We identified over 36,000 enhancers in the L. albipes genome from 3 social and 3 solitary populations. Many enhancers were identified in only a subset of L. albipes populations, revealing rapid divergence in regulatory regions within this species. Population-specific enhancers were often proximal to the same genes across populations, suggesting compensatory gains and losses of regulatory regions may preserve gene activity. We also identified 1,182 enhancers with significant differences in activity between social and solitary populations, some of which are conserved regulatory regions across species of bees. These results indicate that social trait variation in L. albipes is associated with the fine-tuning of ancient enhancers as well as lineage-specific regulatory changes. Combining enhancer activity with population genetic data revealed variants associated with differences in enhancer activity and identified a subset of differential enhancers with signatures of selection associated with social behavior. Together, these results provide the first empirical map of enhancers in a socially flexible bee and highlight links between cis-regulatory variation and the evolution of social behavior.

Heart failure (HF) is a leading cause of morbidity and mortality worldwide, with over 18 million deaths annually. Despite extensive research, genetic and environmental factors contributing to HF remain complex and poorly understood. Recent studies suggest that epigenetic modifications, such as DNA methylation, may play a crucial role in regulating HF-associated phenotypes. In this study, we leverage the Hybrid Mouse Diversity Panel (HMDP), a cohort of over 100 inbred mouse strains, to investigate the role of DNA methylation in HF progression.

We aim to identify epigenetic modifications associated with HF by integrating DNA methylation data with gene expression and phenotypic traits. Using isoproterenol (ISO)-induced cardiac hypertrophy and failure in HMDP mice, we explore the relationship between methylation patterns and HF susceptibility.

We performed reduced representational bisulfite sequencing (RRBS) to capture DNA methylation at single-nucleotide resolution in the left ventricles of 90 HMDP mouse strains under both control and ISO-treated conditions. We identified differentially methylated regions (DMRs) and performed an epigenome-wide association study (EWAS) using the MACAU algorithm. We identified likely candidate genes within each locus through integration of our results with previously reported sequence variation, gene expression, and HF-related phenotypes. In vitro approaches were employed to validate key findings, including gene knockdown experiments in neonatal rat ventricular myocytes (NRVMs). We also examined the effects of preventing DNA methyltransferase activity on HF progression.

Our EWAS identified 56 CpG loci significantly associated with HF phenotypes, including 18 loci where baseline DNA methylation predicted post-ISO HF progression. Key candidate genes, such as Prkag2, Anks1, and Mospd3, were identified based on their epigenetic regulation and association with HF traits. In vitro follow-up on a number of genes confirmed that knockdown of Anks1 and Mospd3 in NRVMs resulted in significant alterations in cell size and blunting of ISO-induced hypertrophy, demonstrating their functional relevance in HF pathology.Furthermore, treatment with the DNA methyltransferase inhibitor RG108 in ISO-treated BTBRT mice significantly reduced cardiac hypertrophy and preserved ejection fraction compared to mice only treated with ISO, highlighting the therapeutic potential of targeting DNA methylation in HF. Differential expression analysis revealed that RG108 treatment restored the expression of several methylation-sensitive genes, further supporting the role of epigenetic regulation in HF.

Our study demonstrates a clear interplay between DNA methylation, gene expression, and HF-associated phenotypes. We identified several novel epigenetic loci and candidate genes that contribute to HF progression, offering new insights into the molecular mechanisms of HF. These findings underscore the importance of epigenetic regulation in cardiac disease and suggest potential therapeutic strategies for modifying HF outcomes through targeting DNA methylation.

Somatic hypermutation in cancer has gained momentum with the increased use of tumour mutation burden as a biomarker for immune checkpoint inhibitors. Spontaneous deamination of 5-methylcytosine to thymine at CpG dinucleotides is one of the most ubiquitous endogenous mutational processes in normal and cancer cells. Here, we performed a systematic investigation of somatic CpG hypermutation at a pan-cancer level. We studied 30,191 cancer patients and 103 cancer types and developed an algorithm to identify somatic CpG hypermutation. Across cancer types, we observed the highest prevalence in paediatric leukaemia (3.5%), paediatric high-grade glioma (1.7%), and colorectal cancer (1%). We discovered germline variants and somatic mutations in the mismatch repair complex MutSα (MSH2-MSH6) as genetic drivers of somatic CpG hypermutation in cancer, which frequently converged on CpG sites and TP53 driver mutations. We further observe an association between somatic CpG hypermutation and response to immune checkpoint inhibitors. Overall, our study identified novel cancer types that display somatic CpG hypermutation, strong association with MutSα-deficiency, and potential utility in cancer immunotherapy.

A major goal in evolutionary biology and biomedicine is to understand the complex interactions between genetic variants, the epigenome, and gene expression. However, the causal relationships between these factors remain poorly understood. mSTARR-seq, a methylation-sensitive massively parallel reporter assay, is capable of identifying methylation-dependent regulatory activity at many thousands of genomic regions simultaneously, and allows for the testing of causal relationships between DNA methylation and gene expression on a region-by-region basis. Here, we developed a multiplexed mSTARR-seq protocol to assay naturally occurring human genetic variation from 25 individuals sampled from 10 localities in Europe and Africa. We identified 6,957 regulatory elements in either the unmethylated or methylated state, and this set was enriched for enhancer and promoter annotations, as expected. The expression of 58% of these regulatory elements was modulated by methylation, which was generally associated with decreased RNA expression. Within our set of regulatory elements, we used allele-specific expression analyses to identify 8,020 sites with genetic effects on gene regulation; further, we found that 42.3% of these genetic effects varied between methylated and unmethylated states. Sites exhibiting methylation-dependent genetic effects were enriched for GWAS and EWAS annotations, implicating them in human disease. Compared to datasets that assay DNA from a single European individual, our multiplexed assay uncovers dramatically more genetic effects and methylation-dependent genetic effects, highlighting the importance of including diverse individuals in assays which aim to understand gene regulatory processes.

Structural variation heavily influences the molecular landscape of cancer, in part by impacting DNA methylation-mediated transcriptional regulation. Here, using multi-omic datasets involving >2400 pediatric brain and central nervous system tumors of diverse histologies from the Children's Brain Tumor Network, we report hundreds of genes and associated CpG islands (CGIs) for which the nearby presence of somatic structural variant (SV) breakpoints is recurrently associated with altered expression or DNA methylation, respectively, including tumor suppressor genes ATRX and CDKN2A. Altered DNA methylation near enhancers associates with nearby somatic SV breakpoints, including MYC and MYCN. A subset of genes with SV-CGI methylation associations also have expression associations with patient survival, including BCOR, TERT, RCOR2, and PDLIM4. DNA methylation changes in recurrent or progressive tumors compared to the initial tumor within the same patient can predict survival in pediatric and adult cancers. Our comprehensive and pan-histology genomic analyses reveal mechanisms of noncoding alterations impacting cancer genes.

Cis-regulatory elements (CREs) play a pivotal role in orchestrating interactions with trans-regulatory factors such as transcription factors, RNA-binding proteins, and noncoding RNAs. These interactions are fundamental to the molecular architecture underpinning complex and diverse biological functions in living organisms, facilitating a myriad of sophisticated and dynamic processes. The rapid advancement in the identification and characterization of these regulatory elements has been marked by initiatives such as the Encyclopedia of DNA Elements (ENCODE) project, which represents a significant milestone in the field. Concurrently, the development of CRE detection technologies, exemplified by massively parallel reporter assays, has progressed at an impressive pace, providing powerful tools for CRE discovery. The exponential growth of multimodal functional genomic data has necessitated the application of advanced analytical methods. Deep learning algorithms, particularly large language models, have emerged as invaluable tools for deconstructing the intricate nucleotide sequences governing CRE function. These advancements facilitate precise predictions of CRE activity and enable the de novo design of CREs. A deeper understanding of CRE operational dynamics is crucial for harnessing their versatile regulatory properties. Such insights are instrumental in refining gene therapy techniques, enhancing the efficacy of selective breeding programs, pushing the boundaries of genetic innovation, and opening new possibilities in microbial synthetic biology.

When facing challenges, vertebrates activate a hormonal stress response that can dramatically alter behaviour and physiology. Although this response can be costly, conceptual models suggest that it can also recalibrate the stress response system, priming more effective responses to future challenges. Little is known about whether this process occurs in wild animals, particularly in adulthood, and if so, how information about prior experience with stressors is encoded. One potential mechanism is hormonally mediated changes in DNA methylation. We simulated the spikes in corticosterone that accompany a stress response using non-invasive dosing in tree swallows (Tachycineta bicolor) and monitored the phenotypic effects 1 year later. In a subset of individuals, we characterized DNA methylation using reduced representation bisulfite sequencing shortly after treatment and a year later. The year after treatment, experimental females had stronger negative feedback and initiated breeding earlier-traits that are associated with stress resilience and reproductive performance in our population-and higher baseline corticosterone. We also found that natural variation in corticosterone predicted patterns of DNA methylation. Finally, corticosterone treatment influenced methylation on short (1-2 weeks) and long (1 year) time scales; however, these changes did not have clear links to functional regulation of the stress response. Taken together, our results are consistent with corticosterone-induced priming of future stress resilience and support DNA methylation as a potential mechanism, but more work is needed to demonstrate functional consequences. Uncovering the mechanisms linking experience with the response to future challenges has implications for understanding the drivers of stress resilience.

The statistical analysis of omics data poses a great computational challenge given their ultra-high-dimensional nature and frequent between-features correlation. In this work, we extended the iterative sure independence screening (ISIS) algorithm by pairing ISIS with elastic-net (Enet) and 2 versions of adaptive elastic-net (adaptive elastic-net (AEnet) and multistep adaptive elastic-net (MSAEnet)) to efficiently improve feature selection and effect estimation in omics research. We subsequently used genome-wide human blood DNA methylation data from American Indian participants in the Strong Heart Study (n = 2235 participants; measured in 1989-1991) to compare the performance (predictive accuracy, coefficient estimation, and computational efficiency) of ISIS-paired regularization methods with that of a bayesian shrinkage and traditional linear regression to identify an epigenomic multimarker of body mass index (BMI). ISIS-AEnet outperformed the other methods in prediction. In biological pathway enrichment analysis of genes annotated to BMI-related differentially methylated positions, ISIS-AEnet captured most of the enriched pathways in common for at least 2 of all the evaluated methods. ISIS-AEnet can favor biological discovery because it identifies the most robust biological pathways while achieving an optimal balance between bias and efficient feature selection. In the extended SIS R package, we also implemented ISIS paired with Cox and logistic regression for time-to-event and binary endpoints, respectively, and a bootstrap approach for the estimation of regression coefficients.

Epigenetic Scores (EpiScores) for blood protein levels have been associated with disease outcomes and measures of brain health, highlighting their potential usefulness as clinical biomarkers. They are typically derived via penalised regression, whereby a linear weighted sum of DNA methylation (DNAm) levels at CpG sites are predictive of protein levels. Here, we examine 84 previously published protein EpiScores as possible biomarkers of cross-sectional and longitudinal measures of general cognitive function and brain health, and incident dementia across three independent cohorts.

Using 84 protein EpiScores as candidate biomarkers, associations with general cognitive function (both cross-sectionally and longitudinally) were tested in three independent cohorts: Generation Scotland (GS), and the Lothian Birth Cohorts of 1921 and 1936 (LBC1921 and LBC1936, respectively). A meta-analysis of general cognitive functioning results in all three cohorts identified 18 EpiScore associations (absolute meta-analytic standardised estimates ranged from 0.03 to 0.14, median of 0.04, PFDR < 0.05). Several associations were also observed between EpiScores and global brain volumetric measures in the LBC1936. An EpiScore for the S100A9 protein (a known Alzheimer disease biomarker) was associated with general cognitive functioning (meta-analytic standardised beta: - 0.06, P = 1.3 × 10-9), and with time-to-dementia in GS (Hazard ratio 1.24, 95% confidence interval 1.08-1.44, P = 0.003), but not in LBC1936 (Hazard ratio 1.11, P = 0.32).

EpiScores might make a contribution to the risk profile of poor general cognitive function and global brain health, and risk of dementia, however these scores require replication in further studies.

The early-life environment can profoundly shape the trajectory of an animal's life, even years or decades later. One mechanism proposed to contribute to these early-life effects is DNA methylation. However, the frequency and functional importance of DNA methylation in shaping early-life effects on adult outcomes is poorly understood, especially in natural populations. Here, we integrate prospectively collected data on fitness-associated variation in the early environment with DNA methylation estimates at 477,270 CpG sites in 256 wild baboons. We find highly heterogeneous relationships between the early-life environment and DNA methylation in adulthood: aspects of the environment linked to resource limitation (e.g., low-quality habitat, early-life drought) are associated with many more CpG sites than other types of environmental stressors (e.g., low maternal social status). Sites associated with early resource limitation are enriched in gene bodies and putative enhancers, suggesting they are functionally relevant. Indeed, by deploying a baboon-specific, massively parallel reporter assay, we show that a subset of windows containing these sites are capable of regulatory activity, and that, for 88% of early drought-associated sites in these regulatory windows, enhancer activity is DNA methylation-dependent. Together, our results support the idea that DNA methylation patterns contain a persistent signature of the early-life environment. However, they also indicate that not all environmental exposures leave an equivalent mark and suggest that socioenvironmental variation at the time of sampling is more likely to be functionally important. Thus, multiple mechanisms must converge to explain early-life effects on fitness-related traits.

Previously, we showed that a massively parallel reporter assay, mSTARR-seq, could be used to simultaneously test for both enhancer-like activity and DNA methylation-dependent enhancer activity for millions of loci in a single experiment (Lea et al., 2018). Here, we apply mSTARR-seq to query nearly the entire human genome, including almost all CpG sites profiled either on the commonly used Illumina Infinium MethylationEPIC array or via reduced representation bisulfite sequencing. We show that fragments containing these sites are enriched for regulatory capacity, and that methylation-dependent regulatory activity is in turn sensitive to the cellular environment. In particular, regulatory responses to interferon alpha (IFNA) stimulation are strongly attenuated by methyl marks, indicating widespread DNA methylation-environment interactions. In agreement, methylation-dependent responses to IFNA identified via mSTARR-seq predict methylation-dependent transcriptional responses to challenge with influenza virus in human macrophages. Our observations support the idea that pre-existing DNA methylation patterns can influence the response to subsequent environmental exposures-one of the tenets of biological embedding. However, we also find that, on average, sites previously associated with early life adversity are not more likely to functionally influence gene regulation than expected by chance.

Surrogate production by germline stem cell transplantation is a powerful method to produce donor-derived gametes via a host, a practice known as surrogacy. The gametes produced by surrogates are often analysed on the basis of their morphology and species-specific genotyping, which enables conclusion to be drawn about the donor's characteristics. However, in-depth information, such as data on epigenetic changes, is rarely acquired. Germ cells develop in close contact with supporting somatic cells during gametogenesis in vertebrates, and we hypothesize that the recipient's gonadal environment may cause epigenetic changes in produced gametes and progeny. Here, we extensively characterize the DNA methylome of donor-derived sperm and their intergenerational effects in both inter- and intraspecific surrogates.

We found more than 3000 differentially methylated regions in both the sperm and progeny derived from inter- and intraspecific surrogates. Hypermethylation in the promoter regions of the protocadherin gamma gene in the intraspecific surrogates was found to be associated with germline transmission. On the contrary, gene expression level and the embryonic development of the offspring remained unaffected. We also discovered MAPK/p53 pathway disruption in interspecific surrogates due to promoter hypermethylation and identified that the inefficient removal of meiotic-arrested endogenous germ cells in hybrid gonads led to the production of infertile spermatozoa.

Donor-derived sperm and progeny from inter- and intraspecific surrogates were more globally hypermethylated than those of the donors. The observed changes in DNA methylation marks in the surrogates had no significant phenotypic effects in the offspring.

There is great interest in exploring epigenetic modifications as drivers of adaptive organismal responses to environmental change. Extending this hypothesis to populations, epigenetically driven plasticity could influence phenotypic changes across environments. The canonical model posits that epigenetic modifications alter gene regulation and subsequently impact phenotypes. We first discuss origins of epigenetic variation in nature, which may arise from genetic variation, spontaneous epimutations, epigenetic drift, or variation in epigenetic capacitors. We then review and synthesize literature addressing three facets of the aforementioned model: (i) causal effects of epigenetic modifications on phenotypic plasticity at the organismal level, (ii) divergence of epigenetic patterns in natural populations distributed across environmental gradients, and (iii) the relationship between environmentally induced epigenetic changes and gene expression at the molecular level. We focus on DNA methylation, the most extensively studied epigenetic modification. We find support for environmentally associated epigenetic structure in populations and selection on stable epigenetic variants, and that inhibition of epigenetic enzymes frequently bears causal effects on plasticity. However, there are pervasive confounding issues in the literature. Effects of chromatin-modifying enzymes on phenotype may be independent of epigenetic marks, alternatively resulting from functions and protein interactions extrinsic of epigenetics. Associations between environmentally induced changes in DNA methylation and expression are strong in plants and mammals but notably absent in invertebrates and nonmammalian vertebrates. Given these challenges, we describe emerging approaches to better investigate how epigenetic modifications affect gene regulation, phenotypic plasticity, and divergence among populations.

Previously we showed that a massively parallel reporter assay, mSTARR-seq, could be used to simultaneously test for both enhancer-like activity and DNA methylation-dependent enhancer activity for millions of loci in a single experiment (Lea et al., 2018). Here we apply mSTARR-seq to query nearly the entire human genome, including almost all CpG sites profiled either on the commonly used Illumina Infinium MethylationEPIC array or via reduced representation bisulfite sequencing. We show that fragments containing these sites are enriched for regulatory capacity, and that methylation-dependent regulatory activity is in turn sensitive to the cellular environment. In particular, regulatory responses to interferon alpha (IFNA) stimulation are strongly attenuated by methyl marks, indicating widespread DNA methylation-environment interactions. In agreement, methylation-dependent responses to IFNA identified via mSTARR-seq predict methylation-dependent transcriptional responses to challenge with influenza virus in human macrophages. Our observations support the idea that pre-existing DNA methylation patterns can influence the response to subsequent environmental exposures-one of the tenets of biological embedding. However, we also find that, on average, sites previously associated with early life adversity are not more likely to functionally influence gene regulation than expected by chance.

Several studies suggested that transcription factor (TF) binding to DNA may be impaired or enhanced by DNA methylation. We present MeDeMo, a toolbox for TF motif analysis that combines information about DNA methylation with models capturing intra-motif dependencies. In a large-scale study using ChIP-seq data for 335 TFs, we identify novel TFs that show a binding behaviour associated with DNA methylation. Overall, we find that the presence of CpG methylation decreases the likelihood of binding for the majority of methylation-associated TFs. For a considerable subset of TFs, we show that intra-motif dependencies are pivotal for accurately modelling the impact of DNA methylation on TF binding. We illustrate that the novel methylation-aware TF binding models allow to predict differential ChIP-seq peaks and improve the genome-wide analysis of TF binding. Our work indicates that simplistic models that neglect the effect of DNA methylation on DNA binding may lead to systematic underperformance for methylation-associated TFs.

Epigenetic processes have taken center stage for the investigation of many biological processes, and epigenetic modifications have shown to influence phenotype, morphology and behavioural traits such as stress resistance by affecting gene regulation and expression without altering the underlying genomic sequence. The multiple molecular layers of epigenetics synergistically construct the cell type-specific gene regulatory networks, characterized by a high degree of plasticity and redundancy to create cell-type-specific morphology and function. DNA methylation occurring on the 5' carbon of cytosines in different genomic sequence contexts is the most studied epigenetic modification. DNA methylation has been shown to provide a molecular record of the exposure to a large variety of environmental factors, which might be persistent through the entire lifetime of an organism and even be passed onto the offspring. Animals might display altered phenotypes mediated by epigenetic modifications depending on the developmental stage or the environmental conditions as well as during evolution. Therefore, the analysis of DNA methylation patterns might allow deciphering previous exposures, explaining ecologically relevant phenotypic diversity and predicting evolutionary trajectories enabling accelerated adaption to changing environmental conditions. Despite the explanatory potential of DNA methylation integrating genetic and environmental factors to shape phenotypic variation and contribute significantly to evolutionary dynamics, studies of DNA methylation are still scarce in the field of ecology. This might be at least partly due to the complexity of DNA methylation analysis and the interpretation of the acquired data. In the current issue of Molecular Ecology Resources, Laine and colleagues (Molecular Ecology Resources, 2022) provide a detailed summary of guidelines and valuable recommendations for researchers in the field of ecology to avoid common pitfalls and perform interpretable genome-wide DNA methylation analyses.

Aging is considered the deterioration of physiological functions along with an increased mortality rate. This scientific review focuses on the central importance of genomic instability during the aging process, encompassing a range of cellular and molecular changes that occur with advancing age. In particular, this revision addresses the genetic and epigenetic alterations that contribute to genomic instability, such as telomere shortening, DNA damage accumulation, and decreased DNA repair capacity. Furthermore, the review explores the epigenetic changes that occur with aging, including modifications to histones, DNA methylation patterns, and the role of non-coding RNAs. Finally, the review discusses the organization of chromatin and its contribution to genomic instability, including heterochromatin loss, chromatin remodeling, and changes in nucleosome and histone abundance. In conclusion, this review highlights the fundamental role that genomic instability plays in the aging process and underscores the need for continued research into these complex biological mechanisms.

Integrating gene expression, DNA methylation, and genomic variants simultaneously without location coincidence (i.e., irrespective of distance from each other) or pairwise coincidence (i.e., direct identification of triplets of gene expression, DNA methylation, and genomic variants, and not integration of pairwise coincidences) is difficult. In this study, we integrated gene expression, DNA methylation, and genome variants from the iMETHYL database using the recently proposed kernel tensor decomposition-based unsupervised feature extraction method with limited computational resources (i.e., short CPU time and small memory requirements). Our methods do not require prior knowledge of the subjects because they are fully unsupervised in that unsupervised tensor decomposition is used. The selected genes and genomic variants were significantly targeted by transcription factors that were biologically enriched in KEGG pathway terms as well as in the intra-related regulatory network. The proposed method is promising for integrated analyses of gene expression, methylation, and genomic variants with limited computational resources.

Although knowledge of the genetic factors influencing kidney disease is increasing, epigenetic profiles, which are associated with chronic kidney disease (CKD), have not been fully elucidated. We sought to identify the DNA methylation status of CpG sites associated with reduced kidney function and examine whether the identified CpG sites are associated with CKD development.

We analyzed DNA methylation patterns of 440 participants in the Korean Genome and Epidemiology Study (KoGES) with estimated glomerular filtration rates (eGFRs) ≥ 60 mL/min/1.73 m² at baseline. CKD development was defined as a decrease in the eGFR of <60 at any time during an 8-year follow-up period ("CKD prediction" analysis). In addition, among the 440 participants, 49 participants who underwent a second methylation profiling were assessed for an association between a decline in kidney function and changes in the degree of methylation of CpG sites during the 8 years ("kidney function slope" analysis).

In the CKD prediction analysis, methylation profiles of a total of 403,129 CpG sites were evaluated at baseline in 440 participants, and increased and decreased methylation of 268 and 189 CpG sites, respectively, were significantly correlated with the development of CKD in multivariable logistic regression. During kidney function slope analysis using follow-up methylation profiles of 49 participants, the percent methylation changes in 913 CpG sites showed a linear relationship with the percent change in eGFR during 8 years. During functional enrichment analyses for significant CpG sites found in the CKD prediction and kidney function slope analyses, we found that those CpG sites represented MAPK, PI3K/Akt, and Rap1 pathways. In addition, three CpG sites from three genes, NPHS2, CHCHD4, and AHR, were found to be significant in the CKD prediction analysis and related to a decline in kidney function.

It is suggested that DNA methylation on specific genes is associated with the development of CKD and the deterioration of kidney function.

Epigenetic processes are proposed to be a mechanism regulating gene expression during phenotypic plasticity. However, environmentally induced changes in DNA methylation exhibit little-to-no association with differential gene expression in metazoans at a transcriptome-wide level. It remains unexplored whether associations between environmentally induced differential methylation and expression are contingent upon other epigenomic processes such as chromatin accessibility. We quantified methylation and gene expression in larvae of the purple sea urchin Strongylocentrotus purpuratus exposed to different ecologically relevant conditions during gametogenesis (maternal conditioning) and modeled changes in gene expression and splicing resulting from maternal conditioning as functions of differential methylation, incorporating covariates for genomic features and chromatin accessibility. We detected significant interactions between differential methylation, chromatin accessibility, and genic feature type associated with differential expression and splicing.

Differential gene body methylation had significantly stronger effects on expression among genes with poorly accessible transcriptional start sites while baseline transcript abundance influenced the direction of this effect. Transcriptional responses to maternal conditioning were 4-13 × more likely when accounting for interactions between methylation and chromatin accessibility, demonstrating that the relationship between differential methylation and gene regulation is partially explained by chromatin state.

DNA methylation likely possesses multiple associations with gene regulation during transgenerational plasticity in S. purpuratus and potentially other metazoans, but its effects are dependent on chromatin accessibility and underlying genic features.

Germline inactivating mutations in the BRCA1 gene lead to an increased lifetime risk of ovarian and breast cancer (BC). Most BRCA1-associated BC are triple-negative tumors (TNBC), aggressive forms of BC characterized by a lack of expression of estrogen and progesterone hormone receptors (HR) and HER2. How BRCA1 inactivation may favor the development of such a specific BC phenotype remains to be elucidated. To address this question, we focused on the role of miRNAs and their networks in mediating BRCA1 functions. miRNA, mRNA, and methylation data were retrieved from the BRCA cohort of the TCGA project. The cohort was divided into a discovery set (Hi-TCGA) and a validation set (GA-TCGA) based on the platform used for miRNA analyses. The METABRIC, GSE81002, and GSE59248 studies were used as additional validation data sets. BCs were differentiated into BRCA1-like and non-BRCA1-like based on an established signature of BRCA1 pathway inactivation. Differential expression of miRNAs, gene enrichment analysis, functional annotation, and methylation correlation analyses were performed. The miRNAs downregulated in BRCA1-associated BC were identified by comparing the miRNome of BRCA1-like with non-BRCA1-like tumors from the Hi-TCGA discovery cohort. miRNAs:gene-target anticorrelation analyses were then performed. The target genes of miRNAs downregulated in the Hi-TCGA series were enriched in the BRCA1-like tumors from the GA-TCGA and METABRIC validation data sets. Functional annotation of these genes revealed an over-representation of several biological processes ascribable to BRCA1 activity. The enrichment of genes related to DNA methylation was particularly intriguing, as this is an aspect of BRCA1 functions that has been poorly explored. We then focused on the miR-29:DNA methyltransferase network and showed that the miR-29 family, which was downregulated in BRCA1-like tumors, was associated with poor prognosis in these BCs and inversely correlated with the expression of the DNA methyltransferases DNMT3A and DNMT3B. This, in turn, correlated with the methylation extent of the promoter of HR genes. These results suggest that BRCA1 may control the expression of HR via a miR-29:DNMT3:HR axis and that disruption of this network may contribute to the receptor negative phenotype of tumors with dysfunctional BRCA1.

The early life environment can profoundly shape the trajectory of an animal's life, even years or decades later. One mechanism proposed to contribute to these early life effects is DNA methylation. However, the frequency and functional importance of DNA methylation in shaping early life effects on adult outcomes is poorly understood, especially in natural populations. Here, we integrate prospectively collected data on fitness-associated variation in the early environment with DNA methylation estimates at 477,270 CpG sites in 256 wild baboons. We find highly heterogeneous relationships between the early life environment and DNA methylation in adulthood: aspects of the environment linked to resource limitation (e.g., low-quality habitat, early life drought) are associated with many more CpG sites than other types of environmental stressors (e.g., low maternal social status). Sites associated with early resource limitation are enriched in gene bodies and putative enhancers, suggesting they are functionally relevant. Indeed, by deploying a baboon-specific, massively parallel reporter assay, we show that a subset of windows containing these sites are capable of regulatory activity, and that, for 88% of early drought-associated sites in these regulatory windows, enhancer activity is DNA methylation-dependent. Together, our results support the idea that DNA methylation patterns contain a persistent signature of the early life environment. However, they also indicate that not all environmental exposures leave an equivalent mark and suggest that socioenvironmental variation at the time of sampling is more likely to be functionally important. Thus, multiple mechanisms must converge to explain early life effects on fitness-related traits.

Aneuploidy syndromes impact multiple organ systems but understanding of tissue-specific aneuploidy effects remains limited-especially for the comparison between peripheral tissues and relatively inaccessible tissues like brain. Here, we address this gap in knowledge by studying the transcriptomic effects of chromosome X, Y, and 21 aneuploidies in lymphoblastoid cell lines, fibroblasts and iPSC-derived neuronal cells (LCLs, FCL, and iNs, respectively). We root our analyses in sex chromosome aneuploidies, which offer a uniquely wide karyotype range for dosage effect analysis. We first harness a large LCL RNA-seq dataset from 197 individuals with one of 6 sex chromosome dosages (SCDs: XX, XXX, XY, XXY, XYY, and XXYY) to i) validate theoretical models of SCD sensitivity and ii) define an expanded set of 41 genes that show obligate dosage sensitivity to SCD and are all in cis (i.e., reside on the X or Y chromosome). We then use multiple complementary analyses to show that cis effects of SCD in LCLs are preserved in both FCLs (n = 32) and iNs (n = 24), whereas trans effects (i.e., those on autosomal gene expression) are mostly not preserved. Analysis of additional datasets confirms that the greater cross-cell type reproducibility of cis vs. trans effects is also seen in trisomy 21 cell lines. These findings i) expand our understanding of X, Y, and 21 chromosome dosage effects on human gene expression and ii) suggest that LCLs may provide a good model system for understanding cis effects of aneuploidy in harder-to-access cell types.

Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on DNA methylation (DNAm) as effect sizes are expected to be larger for molecular traits compared with complex traits. Here, we investigate DNAm in healthy ageing populations-the Lothian Birth Cohorts of 1921 and 1936-and identify both transient and stable outlying DNAm levels across the genome. We find an enrichment of rare genetic single nucleotide polymorphisms (SNPs) within 1 kb of DNAm sites in individuals with stable outlying DNAm, implying genetic control of this extreme variation. Using a family-based cohort, the Brisbane Systems Genetics Study, we observed increased sharing of DNAm outliers among more closely related individuals, consistent with these outliers being driven by rare genetic variation. We demonstrated that outlying DNAm levels have a functional consequence on gene expression levels, with extreme levels of DNAm being associated with gene expression levels toward the tails of the population distribution. This study demonstrates the role of rare SNPs in the phenotypic variation of DNAm and the effect of extreme levels of DNAm on gene expression.

High-throughput methods such as RNA-seq, ChIP-seq, and ATAC-seq have well-established guidelines, commercial kits, and analysis pipelines that enable consistency and wider adoption for understanding genome function and regulation. STARR-seq, a popular assay for directly quantifying the activities of thousands of enhancer sequences simultaneously, has seen limited standardization across studies. The assay is long, with more than 250 steps, and frequent customization of the protocol and variations in bioinformatics methods raise concerns for reproducibility of STARR-seq studies. Here, we assess each step of the protocol and analysis pipelines from published sources and in-house assays, and identify critical steps and quality control (QC) checkpoints necessary for reproducibility of the assay. We also provide guidelines for experimental design, protocol scaling, customization, and analysis pipelines for better adoption of the assay. These resources will allow better optimization of STARR-seq for specific research needs, enable comparisons and integration across studies, and improve the reproducibility of results.

Terahertz (THz) radiation can affect the degree of DNA methylation, the spectral characteristics of which exist in the terahertz region. DNA methylation is an epigenetic modification in which a methyl (CH₃) group is attached to cytosine, a nucleobase in human DNA. Appropriately controlled DNA methylation leads to proper regulation of gene expression. However, abnormal gene expression that departs from controlled genetic transcription through aberrant DNA methylation may occur in cancer or other diseases. In this study, we demonstrate the modification of gene expression in cells by THz demethylation using resonant THz radiation. Using an enzyme-linked immunosorbent assay, we observed changes in the degree of global DNA methylation in the SK-MEL-3 melanoma cell line under irradiation with 1.6-THz radiation with limited spectral bandwidth. Resonant THz radiation demethylated living melanoma cells by 19%, with no significant occurrence of apurinic/apyrimidinic sites, and the demethylation ratio was linearly proportional to the power of THz radiation. THz demethylation downregulates FOS, JUN, and CXCL8 genes, which are involved in cancer and apoptosis pathways. Our results show that THz demethylation has the potential to be a gene expression modifier with promising applications in cancer treatment.

A long-standing goal of evolutionary biology is to decode how gene regulation contributes to organismal diversity. Doing so is challenging because it is hard to predict function from non-coding sequence and to perform molecular research with non-model taxa. Massively parallel reporter assays (MPRAs) enable the testing of thousands to millions of sequences for regulatory activity simultaneously. Here, we discuss the execution, advantages, and limitations of MPRAs, with a focus on evolutionary questions. We propose solutions for extending MPRAs to rare taxa and those with limited genomic resources, and we underscore MPRA's broad potential for driving genome-scale, functional studies across organisms.

Emerging evidences suggest that miRNAs can be used as theranostic biomarkers for multiple cancers, including glioma. Thus, identification of novel miRNAs for glioma treatment and prognosis becomes necessary and urgent. Here, by analyzing miRNA expression profiles in the glioma and para-cancer tissues by miRNA microarray and verified by RT-PCR, we found that miR-133a was significantly downregulated in the cancerous tissues, and patients with low-expressed miR-133a levels predicted an unfavorable prognosis. The following functional experiments confirmed that overexpression of miR-133a restrained cell proliferation and colony formation abilities, and induced cell cycle arrest to restrain cancer progression in glioma cells. Then, the underlying mechanisms were uncovered, and the peroxisome proliferator-activated receptor γ (PPARγ, PPARG) was verified as the downstream target of miR-133a. Mechanistically, miR-133a negatively regulated PPARG expressions by binding to its 3' untranslated regions (3'UTR). The following rescuing experiments evidenced that miR-133a overexpression-induced anti-cancer effects in glioma cells were abrogated by upregulating PPARγ. Interestingly, we noticed that the promoter region of miR-133a was hypermethylated, and removal of DNA methylation by 5-Azacytidine (AZA) significantly increased the expression levels of miR-133a in glioma cells. Taken together, we concluded that DNA-methylation-induced miR-133a silence contributed to cancer progression in glioma through upregulating PPARγ, and firstly identified the DNA-methylation-regulated miR-133a/PPARG axis as the novel indicators for glioma treatment and prognosis.

Obesity is accompanied by excess adipose fat storage, which may lead to adipose dysfunction, insulin resistance, and type 2 diabetes (T2D). Currently, the tendency to develop T2D in obesity cannot be explained by genetic variation alone-epigenetic mechanisms, such as DNA methylation, might be involved. Here, we aimed to identify changes in DNA methylation and gene expression in visceral adipose tissue (VAT) that might underlie T2D susceptibility in patients with obesity.

We investigated DNA methylation and gene expression in VAT biopsies from 19 women with obesity, without (OND = 9) or with T2D (OD = 10). Differences in genome-scale methylation (differentially methylated CpGs [DMCs], false discovery rate < 0.05; and differentially methylated regions [DMRs], p value < 0.05) and gene expression (DEGs, p value <0.05) between groups were assessed. We searched for overlap between altered methylation and expression and the impact of altered DNA methylation on gene expression, using bootstrap Pearson correlation. The relationship of altered DNA methylation to T2D-related traits was also tested.

We identified 11 120 DMCs and 96 DMRs distributed across all chromosomes, with the greatest density of epigenomic alterations at the MHC locus. These alterations were found in newly and previously T2D-related genes. Several of these findings were supported by validation and extended multi-ethnic analyses. Of 252 DEGs in the OD group, 68 genes contained DMCs (n = 88), of which 24 demonstrated a significant relationship between gene expression and methylation (p values <0.05). Of these, 16, including ATP11A, LPL and EHD2 also showed a significant correlation with fasting glucose and HbA1c levels.

Our results revealed novel candidate genes related to T2D pathogenesis in obesity. These genes show perturbations in DNA methylation and expression profiles in patients with obesity and diabetes. Methylation profiles were able to discriminate OND from OD individuals; DNA methylation is thus a potential biomarker.

Spastic type cerebral palsy (CP) is a complex neuromuscular disorder that involves altered skeletal muscle microanatomy and growth, but little is known about the mechanisms contributing to muscle pathophysiology and dysfunction. Traditional genomic approaches have provided limited insight regarding disease onset and severity, but recent epigenomic studies indicate that DNA methylation patterns can be altered in CP. Here, we examined whether a diagnosis of spastic CP is associated with intrinsic DNA methylation differences in myoblasts and myotubes derived from muscle resident stem cell populations (satellite cells; SCs). Twelve subjects were enrolled (6 CP; 6 control) with informed consent/assent. Skeletal muscle biopsies were obtained during orthopedic surgeries, and SCs were isolated and cultured to establish patient-specific myoblast cell lines capable of proliferation and differentiation in culture. DNA methylation analyses indicated significant differences at 525 individual CpG sites in proliferating SC-derived myoblasts (MB) and 1774 CpG sites in differentiating SC-derived myotubes (MT). Of these, 79 CpG sites were common in both culture types. The distribution of differentially methylated 1 Mbp chromosomal segments indicated distinct regional hypo- and hyper-methylation patterns, and significant enrichment of differentially methylated sites on chromosomes 12, 13, 14, 15, 18, and 20. Average methylation load across 2000 bp regions flanking transcriptional start sites was significantly different in 3 genes in MBs, and 10 genes in MTs. SC derived MBs isolated from study participants with spastic CP exhibited fundamental differences in DNA methylation compared to controls at multiple levels of organization that may reveal new targets for studies of mechanisms contributing to muscle dysregulation in spastic CP.

Aim: To explore the prognostic value of methylated snoRNA genes in glioma and construct a prognostic risk signature. Materials & methods: We retrieved clinical information and 450K methylation data from The Cancer Genome Atlas and obtained five methylated snoRNA genes. Then we established a risk signature and verified the effect of SNORA71B on glioma cells with functional assays. Results: A risk signature containing five methylated snoRNA genes was constructed and demonstrated to be an independent predictor of glioma prognosis. Silencing SNORA71B restrained the proliferation, migration and invasion of glioma cells and reduced the expression of mesenchymal and cell cycle marker proteins. Conclusion: This study constructed a methylated snoRNA gene risk signature, which may provide a reference for glioma patients' prognosis assessment.

Many inflammatory diseases that are responsible for a majority of deaths are still uncurable, in part as the underpinning pathomechanisms and how to combat them is still poorly understood. Tissue-resident macrophages play pivotal roles in the maintenance of tissue homeostasis, but if they gradually convert to proinflammatory phenotypes, or if blood-born proinflammatory macrophages persist long-term after activation, they contribute to chronic inflammation and fibrosis. While biochemical factors and how they regulate the inflammatory transcriptional response of macrophages have been at the forefront of research to identify targets for therapeutic interventions, evidence is increasing that physical factors also tune the macrophage phenotype. Recently, several mechanisms have emerged as to how physical factors impact the mechanobiology of macrophages, from the nuclear translocation of transcription factors to epigenetic modifications, perhaps even DNA methylation. Insight into the mechanobiology of macrophages and associated epigenetic modifications will deliver novel therapeutic options going forward, particularly in the context of increased inflammation with advancing age and age-related diseases. We review here how biophysical factors can co-regulate pro-inflammatory gene expression and epigenetic modifications and identify knowledge gaps that require urgent attention if this therapeutic potential is to be realized.

Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, we report an integrated DNA methylation and phenotypic study of the circulating proteome in relation to brain health. Methylome-wide association studies of 4058 plasma proteins are performed (N = 774), identifying 2928 CpG-protein associations after adjustment for multiple testing. These are independent of known genetic protein quantitative trait loci (pQTLs) and common lifestyle effects. Phenome-wide association studies of each protein are then performed in relation to 15 neurological traits (N = 1,065), identifying 405 associations between the levels of 191 proteins and cognitive scores, brain imaging measures or APOE e4 status. We uncover 35 previously unreported DNA methylation signatures for 17 protein markers of brain health. The epigenetic and proteomic markers we identify are pertinent to understanding and stratifying brain health.