Epigenome-wide meta-analysis of DNA methylation differences in prefrontal cortex implicates the immune processes in Alzheimer's disease

Epigenome-wide association study of long-term psychosocial stress in older adults

Long-term psychosocial stress is strongly associated with negative physical and mental health outcomes, as well as adverse health behaviours; however, little is known about the role that stress plays on the epigenome. One proposed mechanism by which stress affects DNA methylation is through health behaviours. We conducted an epigenome-wide association study (EWAS) of cumulative psychosocial stress (n = 2,689) from the Health and Retirement Study (mean age = 70.4 years), assessing DNA methylation (Illumina Infinium HumanMethylationEPIC Beadchip) at 789,656 CpG sites. For identified CpG sites, we conducted a formal mediation analysis to examine whether smoking, alcohol use, physical activity, and body mass index (BMI) mediate the relationship between stress and DNA methylation. Nine CpG sites were associated with psychosocial stress (all p < 9E-07; FDR q < 0.10). Additionally, health behaviours and/or BMI mediated 9.4% to 21.8% of the relationship between stress and methylation at eight of the nine CpGs. Several of the identified CpGs were in or near genes associated with cardiometabolic traits, psychosocial disorders, inflammation, and smoking. These findings support our hypothesis that psychosocial stress is associated with DNA methylation across the epigenome. Furthermore, specific health behaviours mediate only a modest percentage of this relationship, providing evidence that other mechanisms may link stress and DNA methylation.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC v1.0 BeadChip microarrays

DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC v1.0 arrays. We conducted a comprehensive assessment of the EPIC v1.0 array probe reliability using 69 blood DNA samples, each measured twice, generated by the Alzheimer's Disease Neuroimaging Initiative study. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliability information for probes on the EPIC v1.0 array, will serve as a valuable resource for future DNAm studies.

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

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

MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease

Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledgebase containing manually curated summary statistics from 98 published tables in 38 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels-at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD. Database URL: https://miami-ad.org/.

Genome-wide Methylation Dynamics and Context-dependent Gene Expression Variability in Differentiating Preadipocytes

Obesity, characterized by the accumulation of excess fat, is a complex condition resulting from the combination of genetic and epigenetic factors. Recent studies have found correspondence between DNA methylation and cell differentiation, suggesting a role of the former in cell fate determination. There is a lack of comprehensive understanding concerning the underpinnings of preadipocyte differentiation, specifically when cells are undergoing terminal differentiation (TD). To gain insight into dynamic genome-wide methylation, 3T3 L1 preadipocyte cells were differentiated by a hormone cocktail. The genomic DNA was isolated from undifferentiated cells and 4 hours, 2 days postdifferentiated cells, and 15 days TD cells. We employed whole-genome bisulfite sequencing (WGBS) to ascertain global genomic DNA methylation alterations at single base resolution as preadipocyte cells differentiate. The genome-wide distribution of DNA methylation showed similar overall patterns in pre-, post-, and terminally differentiated adipocytes, according to WGBS analysis. DNA methylation decreases at 4 hours after differentiation initiation, followed by methylation gain as cells approach TD. Studies revealed novel differentially methylated regions (DMRs) associated with adipogenesis. DMR analysis suggested that though DNA methylation is global, noticeable changes are observed at specific sites known as "hotspots." Hotspots are genomic regions rich in transcription factor (TF) binding sites and exhibit methylation-dependent TF binding. Subsequent analysis indicated hotspots as part of DMRs. The gene expression profile of key adipogenic genes in differentiating adipocytes is context-dependent, as we found a direct and inverse relationship between promoter DNA methylation and gene expression.

Testing for differences in polygenic scores in the presence of confounding

Polygenic scores have become an important tool in human genetics, enabling the prediction of individuals' phenotypes from their genotypes. Understanding how the pattern of differences in polygenic score predictions across individuals intersects with variation in ancestry can provide insights into the evolutionary forces acting on the trait in question, and is important for understanding health disparities. However, because most polygenic scores are computed using effect estimates from population samples, they are susceptible to confounding by both genetic and environmental effects that are correlated with ancestry. The extent to which this confounding drives patterns in the distribution of polygenic scores depends on patterns of population structure in both the original estimation panel and in the prediction/test panel. Here, we use theory from population and statistical genetics, together with simulations, to study the procedure of testing for an association between polygenic scores and axes of ancestry variation in the presence of confounding. We use a general model of genetic relatedness to describe how confounding in the estimation panel biases the distribution of polygenic scores in a way that depends on the degree of overlap in population structure between panels. We then show how this confounding can bias tests for associations between polygenic scores and important axes of ancestry variation in the test panel. Specifically, for any given test, there exists a single axis of population structure in the GWAS panel that needs to be controlled for in order to protect the test. Based on this result, we propose a new approach for directly estimating this axis of population structure in the GWAS panel. We then use simulations to compare the performance of this approach to the standard approach in which the principal components of the GWAS panel genotypes are used to control for stratification.

DNA methylation and stroke prognosis: an epigenome-wide association study

BACKGROUND AND AIMS

Stroke is the leading cause of adult-onset disability. Although clinical factors influence stroke outcome, there is a significant variability among individuals that may be attributed to genetics and epigenetics, including DNA methylation (DNAm). We aimed to study the association between DNAm and stroke prognosis.

METHODS AND RESULTS

To that aim, we conducted a two-phase study (discovery-replication and meta-analysis) in Caucasian patients with ischemic stroke from two independent centers (BasicMar [discovery, N = 316] and St. Pau [replication, N = 92]). Functional outcome was assessed using the modified Rankin Scale (mRS) at three months after stroke, being poor outcome defined as mRS > 2. DNAm was determined using the 450K and EPIC BeadChips in whole-blood samples collected within the first 24 h. We searched for differentially methylated positions (DMPs) in 370,344 CpGs, and candidates below p-value < 10-5 were subsequently tested in the replication cohort. We then meta-analyzed DMP results from both cohorts and used them to identify differentially methylated regions (DMRs). After doing the epigenome-wide association study, we found 29 DMPs at p-value < 10-5 and one of them was replicated: cg24391982, annotated to thrombospondin-2 (THBS2) gene (p-valuediscovery = 1.54·10-6; p-valuereplication = 9.17·10-4; p-valuemeta-analysis = 6.39·10-9). Besides, four DMRs were identified in patients with poor outcome annotated to zinc finger protein 57 homolog (ZFP57), Arachidonate 12-Lipoxygenase 12S Type (ALOX12), ABI Family Member 3 (ABI3) and Allantoicase (ALLC) genes (p-value < 1·10-9 in all cases).

DISCUSSION

Patients with poor outcome showed a DMP at THBS2 and four DMRs annotated to ZFP57, ALOX12, ABI3 and ALLC genes. This suggests an association between stroke outcome and DNAm, which may help identify new stroke recovery mechanisms.

Antidepressant Exposure and DNA Methylation: Insights from a Methylome-Wide Association Study

Importance

Understanding antidepressant mechanisms could help design more effective and tolerated treatments.

Objective

Identify DNA methylation (DNAm) changes associated with antidepressant exposure.

Design

Case-control methylome-wide association studies (MWAS) of antidepressant exposure were performed from blood samples collected between 2006-2011 in Generation Scotland (GS). The summary statistics were tested for enrichment in specific tissues, gene ontologies and an independent MWAS in the Netherlands Study of Depression and Anxiety (NESDA). A methylation profile score (MPS) was derived and tested for its association with antidepressant exposure in eight independent cohorts, alongside prospective data from GS.

Setting

Cohorts; GS, NESDA, FTC, SHIP-Trend, FOR2107, LBC1936, MARS-UniDep, ALSPAC, E-Risk, and NTR.

Participants

Participants with DNAm data and self-report/prescription derived antidepressant exposure.

Main Outcomes and Measures

Whole-blood DNAm levels were assayed by the EPIC/450K Illumina array (9 studies, N exposed = 661, N unexposed = 9,575) alongside MBD-Seq in NESDA (N exposed = 398, N unexposed = 414). Antidepressant exposure was measured by self- report and/or antidepressant prescriptions.

Results

The self-report MWAS (N = 16,536, N exposed = 1,508, mean age = 48, 59% female) and the prescription-derived MWAS (N = 7,951, N exposed = 861, mean age = 47, 59% female), found hypermethylation at seven and four DNAm sites (p < 9.42x10 -8 ), respectively. The top locus was cg26277237 ( KANK1, p self-report = 9.3x10 -13 , p prescription = 6.1x10 -3 ). The self-report MWAS found a differentially methylated region, mapping to DGUOK-AS1 ( p adj = 5.0x10 -3 ) alongside significant enrichment for genes expressed in the amygdala, the "synaptic vesicle membrane" gene ontology and the top 1% of CpGs from the NESDA MWAS (OR = 1.39, p < 0.042). The MPS was associated with antidepressant exposure in meta-analysed data from external cohorts (N studies = 9, N = 10,236, N exposed = 661, f3 = 0.196, p < 1x10 -4 ).

Conclusions and Relevance

Antidepressant exposure is associated with changes in DNAm across different cohorts. Further investigation into these changes could inform on new targets for antidepressant treatments.

3 Key Points

Question: Is antidepressant exposure associated with differential whole blood DNA methylation?Findings: In this methylome-wide association study of 16,536 adults across Scotland, antidepressant exposure was significantly associated with hypermethylation at CpGs mapping to KANK1 and DGUOK-AS1. A methylation profile score trained on this sample was significantly associated with antidepressant exposure (pooled f3 [95%CI]=0.196 [0.105, 0.288], p < 1x10 -4 ) in a meta-analysis of external datasets. Meaning: Antidepressant exposure is associated with hypermethylation at KANK1 and DGUOK-AS1 , which have roles in mitochondrial metabolism and neurite outgrowth. If replicated in future studies, targeting these genes could inform the design of more effective and better tolerated treatments for depression.

regionalpcs: improved discovery of DNA methylation associations with complex traits

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

Genome-wide DNA methylation analysis related to ALS patient progression and survival

BACKGROUND

Epigenetics contributes to the pathogenesis of amyotrophic lateral sclerosis (ALS). We aimed to characterize the DNA methylation profiles associated with clinical heterogeneity in disease progression and survival among patients.

METHODS

We included a cohort of 41 patients with sporadic ALS, with a median follow-up of 86.9 months, and 27 rigorously matched healthy controls. Blood-based genome-wide DNA methylation analysis was conducted.

RESULTS

A total of 948 progression rate-associated differentially methylated positions, 298 progression rate-associated differentially methylated regions (R-DMRs), 590 survival time-associated DMPs, and 197 survival time-associated DMRs (S-DMRs) were identified, using complementary grouping strategies. Enrichment analysis of differentially methylated genes highlighted the involvement of synapses and axons in ALS progression and survival. Clinical analysis revealed a positive correlation between the average methylation levels of the R-DMR in PRDM8 and disease progression rate (r = 0.479, p = 0.002). Conversely, there was an inverse correlation between the average methylation levels of the R-DMR in ANKRD33 and disease progression rate (r = - 0.476, p = 0.002). In addition, patients with higher methylation levels within the S-DMR of ZNF696 experienced longer survival (p = 0.016), while those with elevated methylation levels in the S-DMR of RAI1 had shorter survival (p = 0.006).

CONCLUSION

DNA methylation holds promise as a potential biomarker for tracking disease progression and predicting survival outcome and also offers targets for precision medicine.

DNA methylation of imprint control regions associated with Alzheimer's disease in non-Hispanic Blacks and non-Hispanic Whites

Alzheimer's disease (AD) prevalence is twice as high in non-Hispanic Blacks (NHBs) as in non-Hispanic Whites (NHWs). The objective of this study was to determine whether aberrant methylation at imprint control regions (ICRs) is associated with AD. Differentially methylated regions (DMRs) were bioinformatically identified from whole-genome bisulfite sequenced DNA derived from brain tissue of 9 AD (5 NHBs and 4 NHWs) and 8 controls (4 NHBs and 4 NHWs). We identified DMRs located within 120 regions defined as candidate ICRs in the human imprintome ( https://genome.ucsc.edu/s/imprintome/hg38.AD.Brain_track ). Eighty-one ICRs were differentially methylated in NHB-AD, and 27 ICRs were differentially methylated in NHW-AD, with two regions common to both populations that are proximal to the inflammasome gene, NLRP1, and a known imprinted gene, MEST/MESTIT1. These findings indicate that early developmental alterations in DNA methylation of regions regulating genomic imprinting may contribute to AD risk and that this epigenetic risk differs between NHBs and NHWs.

Blood DNA Methylation Analysis Reveals a Distinctive Epigenetic Signature of Vasospasm in Aneurysmal Subarachnoid Hemorrhage

Vasospasm is a potentially preventable cause of poor prognosis in patients with aneurysmal subarachnoid hemorrhage (aSAH). Epigenetics might provide insight on its molecular mechanisms. We aimed to analyze the association between differential DNA methylation (DNAm) and development of vasospasm. We conducted an epigenome-wide association study in 282 patients with aSAH admitted to our hospital. DNAm was assessed with the EPIC Illumina chip (> 850 K CpG sites) in whole-blood samples collected at hospital admission. We identified differentially methylated positions (DMPs) at the CpG level using Cox regression models adjusted for potential confounders, and then we used the DMP results to find differentially methylated regions (DMRs) and enriched biological pathways. A total of 145 patients (51%) experienced vasospasm. In the DMP analysis, we identified 31 CpGs associated with vasospasm at p-value < 10-5. One of them (cg26189827) was significant at the genome-wide level (p-value < 10-8), being hypermethylated in patients with vasospasm and annotated to SUGCT gene, mainly expressed in arteries. Region analysis revealed 13 DMRs, some of them annotated to interesting genes such as POU5F1, HLA-DPA1, RUFY1, and CYP1A1. Functional enrichment analysis showed the involvement of biological processes related to immunity, inflammatory response, oxidative stress, endothelial nitric oxide, and apoptosis. Our findings show, for the first time, a distinctive epigenetic signature of vasospasm in aSAH, establishing novel links with essential biological pathways, including inflammation, immune responses, and oxidative stress. Although further validation is required, our results provide a foundation for future research into the complex pathophysiology of vasospasm.

MIDASim: a fast and simple simulator for realistic microbiome data

Background

Advances in sequencing technology has led to the discovery of associations between the human microbiota and many diseases, conditions, and traits. With the increasing availability of microbiome data, many statistical methods have been developed for studying these associations. The growing number of newly developed methods highlights the need for simple, rapid, and reliable methods to simulate realistic microbiome data, which is essential for validating and evaluating the performance of these methods. However, generating realistic microbiome data is challenging due to the complex nature of microbiome data, which feature correlation between taxa, sparsity, overdispersion, and compositionality. Current methods for simulating microbiome data are deficient in their ability to capture these important features of microbiome data, or can require exorbitant computational time.

Methods

We develop MIDASim ( MI crobiome DA ta Sim ulator), a fast and simple approach for simulating realistic microbiome data that reproduces the distributional and correlation structure of a template microbiome dataset. MIDASim is a two-step approach. The first step generates correlated binary indicators that represent the presence-absence status of all taxa, and the second step generates relative abundances and counts for the taxa that are considered to be present in step 1, utilizing a Gaussian copula to account for the taxon-taxon correlations. In the second step, MIDASim can operate in both a nonparametric and parametric mode. In the nonparametric mode, the Gaussian copula uses the empirical distribution of relative abundances for the marginal distributions. In the parametric mode, an inverse generalized gamma distribution is used in place of the empirical distribution.

Results

We demonstrate improved performance of MIDASim relative to other existing methods using gut and vaginal data. MIDASim showed superior performance by PER-MANOVA and in terms of alpha diversity and beta dispersion in either parametric or nonparametric mode. We also show how MIDASim in parametric mode can be used to assess the performance of methods for finding differentially abundant taxa in a compositional model.

Conclusions

MIDASim is easy to implement, flexible and suitable for most microbiome data simulation situations. MIDASim has three major advantages. First, MIDASim performs better in reproducing the distributional features of real data compared to other methods at both presence-absence level and relative-abundance level. MIDASim-simulated data are more similar to the template data than competing methods, as quantified using a variety of measures. Second, MIDASim makes few distributional assumptions for the relative abundances, and thus can easily accommodate complex distributional features in real data. Third, MIDASim is computationally efficient and can be used to simulate large microbiome datasets.

Distinctive cell-free DNA methylation characterizes presymptomatic genetic frontotemporal dementia

OBJECTIVE

Methylation of plasma cell-free DNA (cfDNA) has potential as a marker of brain damage in neurodegenerative diseases such as frontotemporal dementia (FTD). Here, we study methylation of cfDNA in presymptomatic and symptomatic carriers of genetic FTD pathogenic variants, next to healthy controls.

METHODS

cfDNA was isolated from cross-sectional plasma of 10 presymptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), 10 symptomatic carriers (4 C9orf72, 4 GRN, and 2 MAPT), and 9 healthy controls. Genome-wide methylation of cfDNA was determined using a high-resolution sequencing technique (MeD-seq). Cumulative scores based on the identified differentially methylated regions (DMRs) were estimated for presymptomatic carriers (vs. controls and symptomatic carriers), and reevaluated in a validation cohort (8 presymptomatic: 3 C9orf72, 3 GRN, and 2 MAPT; 26 symptomatic: 7 C9orf72, 6 GRN, 12 MAPT, and 1 TARDBP; 13 noncarriers from genetic FTD families).

RESULTS

Presymptomatic carriers showed a distinctive methylation profile compared to healthy controls and symptomatic carriers. Cumulative DMR scores in presymptomatic carriers enabled to significantly differentiate presymptomatic carriers from healthy controls (p < 0.001) and symptomatic carriers (p < 0.001). In the validation cohort, these scores differentiated presymptomatic carriers from symptomatic carriers (p ≤ 0.007) only. Transcription-start-site methylation in presymptomatic carriers, generally associated with gene downregulation, was enriched for genes involved in ubiquitin-dependent processes, while gene body methylation, generally associated with gene upregulation, was enriched for genes involved in neuronal cell processes.

INTERPRETATION

A distinctive methylation profile of cfDNA characterizes the presymptomatic stage of genetic FTD, and could reflect neuronal death in this stage.

Nanopore-based DNA long-read sequencing analysis of the aged human brain

Aging disrupts cellular processes such as DNA repair and epigenetic control, leading to a gradual buildup of genomic alterations that can have detrimental effects in post-mitotic cells. Genomic alterations in regions of the genome that are rich in repetitive sequences, often termed "dark loci," are difficult to resolve using traditional sequencing approaches. New long-read technologies offer promising avenues for exploration of previously inaccessible regions of the genome. Using nanopore-based long-read whole-genome sequencing of DNA extracted from aged 18 human brains, we identify previously unreported structural variants and methylation patterns within repetitive DNA, focusing on transposable elements ("jumping genes") as crucial sources of variation, particularly in dark loci. Our analyses reveal potential somatic insertion variants and provides DNA methylation frequencies for many retrotransposon families. We further demonstrate the utility of this technology for the study of these challenging genomic regions in brains affected by Alzheimer's disease and identify significant differences in DNA methylation in pathologically normal brains versus those affected by Alzheimer's disease. Highlighting the power of this approach, we discover specific polymorphic retrotransposons with altered DNA methylation patterns. These retrotransposon loci have the potential to contribute to pathology, warranting further investigation in Alzheimer's disease research. Taken together, our study provides the first long-read DNA sequencing-based analysis of retrotransposon sequences, structural variants, and DNA methylation in the aging brain affected with Alzheimer's disease neuropathology.

Blood DNA methylation signature of diet quality and association with cardiometabolic traits

AIMS

Diet quality might influence cardiometabolic health through epigenetic changes, but this has been little investigated in adults. Our aims were to identify cytosine-phosphate-guanine (CpG) dinucleotides associated with diet quality by conducting an epigenome-wide association study (EWAS) based on blood DNA methylation (DNAm) and to assess how diet-related CpGs associate with inherited susceptibility to cardiometabolic traits: body mass index (BMI), systolic blood pressure (SBP), triglycerides, type 2 diabetes (T2D), and coronary heart disease (CHD).

METHODS AND RESULTS

Meta-EWAS including 5274 participants in four cohorts from Spain, the USA, and the UK. We derived three dietary scores (exposures) to measure adherence to a Mediterranean diet, to a healthy plant-based diet, and to the Dietary Approaches to Stop Hypertension. Blood DNAm (outcome) was assessed with the Infinium arrays Human Methylation 450K BeadChip and MethylationEPIC BeadChip. For each diet score, we performed linear EWAS adjusted for age, sex, blood cells, smoking and technical variables, and BMI in a second set of models. We also conducted Mendelian randomization analyses to assess the potential causal relationship between diet-related CpGs and cardiometabolic traits. We found 18 differentially methylated CpGs associated with dietary scores (P < 1.08 × 10-7; Bonferroni correction), of which 12 were previously associated with cardiometabolic traits. Enrichment analysis revealed overrepresentation of diet-associated genes in pathways involved in inflammation and cardiovascular disease. Mendelian randomization analyses suggested that genetically determined methylation levels corresponding to lower diet quality at cg02079413 (SNORA54), cg02107842 (MAST4), and cg23761815 (SLC29A3) were causally associated with higher BMI and at cg05399785 (WDR8) with greater SBP, and methylation levels associated with higher diet quality at cg00711496 (PRMT1) with lower BMI, T2D risk, and CHD risk and at cg0557921 (AHRR) with lower CHD risk.

CONCLUSION

Diet quality in adults was related to differential methylation in blood at 18 CpGs, some of which related to cardiometabolic health.

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

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

MIAMI-AD (Methylation in Aging and Methylation in AD): an integrative knowledgebase that facilitates explorations of DNA methylation across sex, aging, and Alzheimer's disease

Alzheimer's disease (AD) is a common neurodegenerative disorder with a significant impact on aging populations. DNA methylation (DNAm) alterations have been implicated in both the aging processes and the development of AD. Given that AD affects more women than men, it is also important to explore DNAm changes that occur specifically in each sex. We created MIAMI-AD, a comprehensive knowledge base containing manually curated summary statistics from 97 published tables in 37 studies, all of which included at least 100 participants. MIAMI-AD enables easy browsing, querying, and downloading DNAm associations at multiple levels - at individual CpG, gene, genomic regions, or genome-wide, in one or multiple studies. Moreover, it also offers tools to perform integrative analyses, such as comparing DNAm associations across different phenotypes or tissues, as well as interactive visualizations. Using several use case examples, we demonstrated that MIAMI-AD facilitates our understanding of age-associated CpGs in AD and the sex-specific roles of DNAm in AD. This open-access resource is freely available to the research community, and all the underlying data can be downloaded. MIAMI-AD (https://miami-ad.org/) facilitates integrative explorations to better understand the interplay between DNAm across aging, sex, and AD.

Liquid Biopsy in Alzheimer's Disease Patients Reveals Epigenetic Changes in the PRLHR Gene

In recent years, new DNA methylation variants have been reported in genes biologically relevant to Alzheimer's disease (AD) in human brain tissue. However, this AD-specific epigenetic information remains brain-locked and unreachable during patients' lifetimes. In a previous methylome performed in the hippocampus of 26 AD patients and 12 controls, we found higher methylation levels in AD patients in the promoter region of PRLHR, a gene involved in energy balance regulation. Our aim was to further characterize PRLHR's role in AD and to evaluate if the liquid biopsy technique would provide life access to this brain information in a non-invasive way. First, we extended the methylation mapping of PRLHR and validated previous methylome results via bisulfite cloning sequencing. Next, we observed a positive correlation between PRLHR methylation levels and AD-related neuropathological changes and a decreased expression of PRLHR in AD hippocampus. Then, we managed to replicate the hippocampal methylation differences in plasma cfDNA from an additional cohort of 35 AD patients and 35 controls. The isolation of cfDNA from the plasma of AD patients may constitute a source of potential epigenetic biomarkers to aid AD clinical management.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC BeadChip microarrays

DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC arrays. We conducted a comprehensive assessment of the EPIC array probe reliability using 138 duplicated blood DNAm samples generated by the Alzheimer's Disease Neuroimaging Initiative study. We introduced a novel statistical measure, the modified intraclass correlation, to better account for the disagreement in duplicate measurements. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliable information for probes on the EPIC array, will serve as a valuable resource for future DNAm studies.

Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA

Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

Critical evaluation of the reliability of DNA methylation probes on the Illumina MethylationEPIC BeadChip microarrays

DNA methylation (DNAm) plays a crucial role in a number of complex diseases. However, the reliability of DNAm levels measured using Illumina arrays varies across different probes. Previous research primarily assessed probe reliability by comparing duplicate samples between the 450k-450k or 450k-EPIC platforms, with limited investigations on Illumina EPIC arrays. We conducted a comprehensive assessment of the EPIC array probe reliability using 138 duplicated blood DNAm samples generated by the Alzheimer's Disease Neuroimaging Initiative study. We introduced a novel statistical measure, the modified intraclass correlation, to better account for the disagreement in duplicate measurements. We observed higher reliability in probes with average methylation beta values of 0.2 to 0.8, and lower reliability in type I probes or those within the promoter and CpG island regions. Importantly, we found that probe reliability has significant implications in the analyses of Epigenome-wide Association Studies (EWAS). Higher reliability is associated with more consistent effect sizes in different studies, the identification of differentially methylated regions (DMRs) and methylation quantitative trait locus (mQTLs), and significant correlations with downstream gene expression. Moreover, blood DNAm measurements obtained from probes with higher reliability are more likely to show concordance with brain DNAm measurements. Our findings, which provide crucial reliable information for probes on the EPIC array, will serve as a valuable resource for future DNAm studies.

Tau protein modulates an epigenetic mechanism of cellular senescence in human SH-SY5Y neuroblastoma cells

Introduction: Progressive Tau deposition in neurofibrillary tangles and neuropil threads is the hallmark of tauopathies, a disorder group that includes Alzheimer's disease. Since Tau is a microtubule-associated protein, a prevalent concept to explain the pathogenesis of tauopathies is that abnormal Tau modification contributes to dissociation from microtubules, assembly into multimeric β-sheets, proteotoxicity, neuronal dysfunction and cell loss. Tau also localizes in the cell nucleus and evidence supports an emerging function of Tau in DNA stability and epigenetic modulation. Methods: To better characterize the possible role of Tau in regulation of chromatin compaction and subsequent gene expression, we performed a bioinformatics analysis of transcriptome data obtained from Tau-depleted human neuroblastoma cells. Results: Among the transcripts deregulated in a Tau-dependent manner, we found an enrichment of target genes for the polycomb repressive complex 2. We further describe decreased cellular amounts of the core components of the polycomb repressive complex 2 and lower histone 3 trimethylation in Tau deficient cells. Among the de-repressed polycomb repressive complex 2 target gene products, IGFBP3 protein was found to be linked to increased senescence induction in Tau-deficient cells. Discussion: Our findings propose a mechanism for Tau-dependent epigenetic modulation of cell senescence, a key event in pathologic aging.

Identification of methylation-regulated genes modulating microglial phagocytosis in hyperhomocysteinemia-exacerbated Alzheimer's disease

BACKGROUND

Hyperhomocysteinemia (HHcy) has been linked to development of Alzheimer's disease (AD) neuropathologically characterized by the accumulation of amyloid β (Aβ). Microglia (MG) play a crucial role in uptake of Aβ fibrils, and its dysfunction worsens AD. However, the effect of HHcy on MG Aβ phagocytosis remains unstudied.

METHODS

We isolated MG from the cerebrum of HHcy mice with genetic cystathionine-β-synthase deficiency (Cbs-/-) and performed bulk RNA-seq. We performed meta-analysis over transcriptomes of Cbs-/- mouse MG, human and mouse AD MG, MG Aβ phagocytosis model, human AD methylome, and GWAS AD genes.

RESULTS

HHcy and hypomethylation conditions were identified in Cbs-/- mice. Through Cbs-/- MG transcriptome analysis, 353 MG DEGs were identified. Phagosome formation and integrin signaling pathways were found suppressed in Cbs-/- MG. By analyzing MG transcriptomes from 4 AD patient and 7 mouse AD datasets, 409 human and 777 mouse AD MG DEGs were identified, of which 37 were found common in both species. Through further combinatory analysis with transcriptome from MG Aβ phagocytosis model, we identified 130 functional-validated Aβ phagocytic AD MG DEGs (20 in human AD, 110 in mouse AD), which reflected a compensatory activation of Aβ phagocytosis. Interestingly, we identified 14 human Aβ phagocytic AD MG DEGs which represented impaired MG Aβ phagocytosis in human AD. Finally, through a cascade of meta-analysis of transcriptome of AD MG, functional phagocytosis, HHcy MG, and human AD brain methylome dataset, we identified 5 HHcy-suppressed phagocytic AD MG DEGs (Flt1, Calponin 3, Igf1, Cacna2d4, and Celsr) which were reported to regulate MG/MΦ migration and Aβ phagocytosis.

CONCLUSIONS

We established molecular signatures for a compensatory response of Aβ phagocytosis activation in human and mouse AD MG and impaired Aβ phagocytosis in human AD MG. Our discoveries suggested that hypomethylation may modulate HHcy-suppressed MG Aβ phagocytosis in AD.

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

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

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

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

Multi-ancestry epigenome-wide analyses identify methylated sites associated with aortic augmentation index in TOPMed MESA

Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

The contribution of DNA methylation to the (dys)function of oligodendroglia in neurodegeneration

Neurodegenerative diseases encompass a heterogeneous group of conditions characterised by the progressive degeneration of the structure and function of the central or peripheral nervous systems. The pathogenic mechanisms underlying these diseases are not fully understood. However, a central feature consists of regional aggregation of proteins in the brain, such as the accumulation of β-amyloid plaques in Alzheimer's disease (AD), inclusions of hyperphosphorylated microtubule-binding tau in AD and other tauopathies, or inclusions containing α-synuclein in Parkinson's disease (PD), dementia with Lewy bodies (DLB) and multiple system atrophy (MSA). Various pathogenic mechanisms are thought to contribute to disease, and an increasing number of studies implicate dysfunction of oligodendrocytes (the myelin producing cells of the central nervous system) and myelin loss. Aberrant DNA methylation, the most widely studied epigenetic modification, has been associated with many neurodegenerative diseases, including AD, PD, DLB and MSA, and recent findings highlight aberrant DNA methylation in oligodendrocyte/myelin-related genes. Here we briefly review the evidence showing that changes to oligodendrocytes and myelin are key in neurodegeneration, and explore the relevance of DNA methylation in oligodendrocyte (dys)function. As DNA methylation is reversible, elucidating its involvement in pathogenic mechanisms of neurodegenerative diseases and in dysfunction of specific cell-types such as oligodendrocytes may bring opportunities for therapeutic interventions for these diseases.

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

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

Therapeutic Potential of Nanomedicine in Management of Alzheimer's Disease and Glioma

Neoplasm (Glioblastoma) and Alzheimer's disease (AD) comprise two of the most chronic psychological ailments. Glioblastoma is one of the aggressive and prevalent malignant diseases characterized by rapid growth and invasion resulting from cell migration and degradation of extracellular matrix. While the latter is characterized by extracellular plaques of amyloid and intracellular tangles of tau proteins. Both possess a high degree of resistance to treatment owing to the restricted transport of corresponding drugs to the brain protected by the blood-brain barrier (BBB). Development of optimized therapies using advanced technologies is a great need of today. One such approach is the designing of nanoparticles (NPs) to facilitate the drug delivery at the target site. The present article elaborates the advances in nanomedicines in treatment of both AD as well as Gliomas. The intention of this review is to provide an overview of different types of NPs with their physical properties emphasizing their importance in traversing the BBB and hitting the target site. Further, we discuss the therapeutic applications of these NPs along with their specific targets. Multiple overlapping factors with a common pathway in development of AD and Glioblastoma are discussed in details that will assist the readers in developing the conceptual approach to target the NP for an aging population in the given circumstances with limitations of currently designed NPs, and the challenges to meet and the future perspectives.

Brain DNA methylomic analysis of frontotemporal lobar degeneration reveals OTUD4 in shared dysregulated signatures across pathological subtypes

Frontotemporal lobar degeneration (FTLD) is an umbrella term describing the neuropathology of a clinically, genetically and pathologically heterogeneous group of diseases, including frontotemporal dementia (FTD) and progressive supranuclear palsy (PSP). Among the major FTLD pathological subgroups, FTLD with TDP-43 positive inclusions (FTLD-TDP) and FTLD with tau-positive inclusions (FTLD-tau) are the most common, representing about 90% of the cases. Although alterations in DNA methylation have been consistently associated with neurodegenerative diseases, including Alzheimer's disease and Parkinson's disease, little is known for FTLD and its heterogeneous subgroups and subtypes. The main goal of this study was to investigate DNA methylation variation in FTLD-TDP and FTLD-tau. We used frontal cortex genome-wide DNA methylation profiles from three FTLD cohorts (142 FTLD cases and 92 controls), generated using the Illumina 450K or EPIC microarrays. We performed epigenome-wide association studies (EWAS) for each cohort followed by meta-analysis to identify shared differentially methylated loci across FTLD subgroups/subtypes. In addition, we used weighted gene correlation network analysis to identify co-methylation signatures associated with FTLD and other disease-related traits. Wherever possible, we also incorporated relevant gene/protein expression data. After accounting for a conservative Bonferroni multiple testing correction, the EWAS meta-analysis revealed two differentially methylated loci in FTLD, one annotated to OTUD4 (5'UTR-shore) and the other to NFATC1 (gene body-island). Of these loci, OTUD4 showed consistent upregulation of mRNA and protein expression in FTLD. In addition, in the three independent co-methylation networks, OTUD4-containing modules were enriched for EWAS meta-analysis top loci and were strongly associated with the FTLD status. These co-methylation modules were enriched for genes implicated in the ubiquitin system, RNA/stress granule formation and glutamatergic synaptic signalling. Altogether, our findings identified novel FTLD-associated loci, and support a role for DNA methylation as a mechanism involved in the dysregulation of biological processes relevant to FTLD, highlighting novel potential avenues for therapeutic development.

Exploring the mediation of DNA methylation across the epigenome between childhood adversity and First Episode of Psychosis-findings from the EU-GEI study

ABTRACT

Studies conducted in psychotic disorders have shown that DNA-methylation (DNAm) is sensitive to the impact of Childhood Adversity (CA). However, whether it mediates the association between CA and psychosis is yet to be explored. Epigenome wide association studies (EWAS) using the Illumina Infinium-Methylation EPIC array in peripheral blood tissue from 366 First-episode of psychosis and 517 healthy controls was performed. Adversity scores were created for abuse, neglect and composite adversity with the Childhood Trauma Questionnaire (CTQ). Regressions examining (I) CTQ scores with psychosis; (II) with DNAm EWAS level and (III) between DNAm and caseness, adjusted for a variety of confounders were conducted. Divide-Aggregate Composite-null Test for the composite null-hypothesis of no mediation effect was conducted. Enrichment analyses were conducted with missMethyl package and the KEGG database. Our results show that CA was associated with psychosis (Composite: OR = 1.68; p = <0.001; abuse: OR = 2.16; p < 0.001; neglect: OR = 2.27; p = <0.001). None of the CpG sites significantly mediated the adversity-psychosis association after Bonferroni correction (p < 8.1 × 10-8). However, 28, 34 and 29 differentially methylated probes associated with 21, 27, 20 genes passed a less stringent discovery threshold (p < 5 × 10-5) for composite, abuse and neglect respectively, with a lack of overlap between abuse and neglect. These included genes previously associated to psychosis in EWAS studies, such as PANK1, SPEG TBKBP1, TSNARE1 or H2R. Downstream gene ontology analyses did not reveal any biological pathways that survived false discovery rate correction. Although at a non-significant level, DNAm changes in genes previously associated with schizophrenia in EWAS studies may mediate the CA-psychosis association. These results and associated involved processes such as mitochondrial or histaminergic disfunction, immunity or neural signalling requires replication in well powered samples. The lack of overlap between mediating genes associated with abuse and neglect suggests differential biological trajectories linking CA subtypes and psychosis.

Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects

BACKGROUND

Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis.

METHODS

We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ42, phosphorylated tau181 (pTau181), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset.

RESULTS

We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker.

CONCLUSIONS

Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.

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

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

Ultrasensitive photoelectrochemical biosensor for DNA 5-methylcytosine analysis based on co-sensitization strategy combined with bridged DNA nanoprobe

Altered DNA methylation in the form of 5-methylcytosine (5-mC) patterns is correlated with disease diagnosis, prognosis, and treatment response. Therefore, accurate analysis of 5-mC is of great significance for the diagnosis of diseases. Here, an efficient enhanced photoelectrochemical (PEC) biosensor was designed for the quantitative analysis of DNA 5-mC based on a cascaded energy level aligned co-sensitization strategy coupling with the bridged DNA nanoprobe (BDN). Firstly, Au nanoparticle/graphite phase carbon nitride/titanium dioxide (AuNPs/g-C₃N₄@TiO₂) nanocomposite was synthesized through in situ growth of AuNPs on g-C₃N₄@TiO₂ surface as a matrix to provide a stable background signal. Next, BDN with a high mass transfer rate synthesized from a pair of DNA tetrahedral as nanomechanical handles was used as a capture probe to bind to the target sequence. The polydopamine nanosphere was applied to load with CdTe QDs (PDANS-CdTe QDs) as a photocurrent label of 5-mC antibodies. When the 5-mC existed, a large number of PDANS-Ab-CdTe QDs were introduced to the electrode surface, the formed CdTe QDs/AuNPs/g-C₃N₄@TiO₂ co-sensitive structure could effectively enhance the electron transfer capability and photocurrent response rate due to the effective cascade energy level arrangement, leading to a significantly enhanced photocurrent signal. The proposed PEC biosensor manifested a wide range from 10^-17 M to 10^-7 M and a detection limit of 2.2 aM. Meanwhile, the excellent performance indicated the practicability of the designed strategy, thus being capable of the clinical diagnosis of 5-mC.

Distinct CSF biomarker-associated DNA methylation in Alzheimer's disease and cognitively normal subjects

Background Growing evidence has demonstrated that DNA methylation (DNAm) plays an important role in Alzheimer's disease (AD) and that DNAm differences can be detected in the blood of AD subjects. Most studies have correlated blood DNAm with the clinical diagnosis of AD in living individuals. However, as the pathophysiological process of AD can begin many years before the onset of clinical symptoms, there is often disagreement between neuropathology in the brain and clinical phenotypes. Therefore, blood DNAm associated with AD neuropathology, rather than with clinical data, would provide more relevant information on AD pathogenesis. Methods We performed a comprehensive analysis to identify blood DNAm associated with cerebrospinal fluid (CSF) pathological biomarkers for AD. Our study included matched samples of whole blood DNA methylation, CSF Aβ 42 , phosphorylated tau 181 (pTau 181 ), and total tau (tTau) biomarkers data, measured on the same subjects and at the same clinical visits from a total of 202 subjects (123 CN or cognitively normal, 79 AD) in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. To validate our findings, we also examined the association between premortem blood DNAm and postmortem brain neuropathology measured on a group of 69 subjects in the London dataset. Results We identified a number of novel associations between blood DNAm and CSF biomarkers, demonstrating that changes in pathological processes in the CSF are reflected in the blood epigenome. Overall, the CSF biomarker-associated DNAm is relatively distinct in CN and AD subjects, highlighting the importance of analyzing omics data measured on cognitively normal subjects (which includes preclinical AD subjects) to identify diagnostic biomarkers, and considering disease stages in the development and testing of AD treatment strategies. Moreover, our analysis revealed biological processes associated with early brain impairment relevant to AD are marked by DNAm in the blood, and blood DNAm at several CpGs in the DMR on HOXA5 gene are associated with pTau 181 in the CSF, as well as tau-pathology and DNAm in the brain, nominating DNAm at this locus as a promising candidate AD biomarker. Conclusions Our study provides a valuable resource for future mechanistic and biomarker studies of DNAm in AD.

Factors and Methods for the Detection of Gene Expression Regulation

Gene-expression regulation involves multiple processes and a range of regulatory factors. In this review, we describe the key factors that regulate gene expression, including transcription factors (TFs), chromatin accessibility, histone modifications, DNA methylation, and RNA modifications. In addition, we also describe methods that can be used to detect these regulatory factors.

Differential Gene Expression and DNA Methylation in the Risk of Depression in LOAD Patients

Depression is common among late-onset Alzheimer's Disease (LOAD) patients. Only a few studies investigated the genetic variability underlying the comorbidity of depression in LOAD. Moreover, the epigenetic and transcriptomic factors that may contribute to comorbid depression in LOAD have yet to be studied. Using transcriptomic and DNA-methylomic datasets from the ROSMAP cohorts, we investigated differential gene expression and DNA-methylation in LOAD patients with and without comorbid depression. Differential expression analysis did not reveal significant association between differences in gene expression and the risk of depression in LOAD. Upon sex-stratification, we identified 25 differential expressed genes (DEG) in males, of which CHI3L2 showed the strongest upregulation, and only 3 DEGs in females. Additionally, testing differences in DNA-methylation found significant hypomethylation of CpG (cg20442550) on chromosome 17 (log2FC = -0.500, p = 0.004). Sex-stratified differential DNA-methylation analysis did not identify any significant CpG probes. Integrating the transcriptomic and DNA-methylomic datasets did not discover relationships underlying the comorbidity of depression and LOAD. Overall, our study is the first multi-omics genome-wide exploration of the role of gene expression and epigenome alterations in the risk of comorbid depression in LOAD patients. Furthermore, we discovered sex-specific differences in gene expression underlying the risk of depression symptoms in LOAD.

Epigenome-Wide Association Study in Peripheral Tissues Highlights DNA Methylation Profiles Associated with Episodic Memory Performance in Humans

The decline in episodic memory (EM) performance is a hallmark of cognitive aging and an early clinical sign in Alzheimer’s disease (AD). In this study, we conducted an epigenome-wide association study (EWAS) using DNA methylation (DNAm) profiles from buccal and blood samples for cross-sectional (n = 1019) and longitudinal changes in EM performance (n = 626; average follow-up time 5.4 years) collected under the auspices of the Lifebrain consortium project. The mean age of participants with cross-sectional data was 69 ± 11 years (30−90 years), with 50% being females. We identified 21 loci showing suggestive evidence of association (p < 1 × 10−5) with either or both EM phenotypes. Among these were SNCA, SEPW1 (both cross-sectional EM), ITPK1 (longitudinal EM), and APBA2 (both EM traits), which have been linked to AD or Parkinson’s disease (PD) in previous work. While the EM phenotypes were nominally significantly (p < 0.05) associated with poly-epigenetic scores (PESs) using EWASs on general cognitive function, none remained significant after correction for multiple testing. Likewise, estimating the degree of “epigenetic age acceleration” did not reveal significant associations with either of the two tested EM phenotypes. In summary, our study highlights several interesting candidate loci in which differential DNAm patterns in peripheral tissue are associated with EM performance in humans.

An integrative machine-learning meta-analysis of high-throughput omics data identifies age-specific hallmarks of Alzheimer's disease

Alzheimer's disease (AD) is an incredibly complex and presently incurable age-related brain disorder. To better understand this debilitating disease, we collated and performed a meta-analysis on publicly available RNA-Seq, microarray, proteomics, and microRNA samples derived from AD patients and non-AD controls. 4089 samples originating from brain tissues and blood remained after applying quality filters. Since disease progression in AD correlates with age, we stratified this large dataset into three different age groups: < 75 years, 75-84 years, and ≥ 85 years. The RNA-Seq, microarray, and proteomics datasets were then combined into different integrated datasets. Ensemble machine learning was employed to identify genes and proteins that can accurately classify samples as either AD or control. These predictive inputs were then subjected to network-based enrichment analyses. The ability of genes/proteins associated with different pathways in the Molecular Signatures Database to diagnose AD was also tested. We separately identified microRNAs that can be used to make an AD diagnosis and subjected the predicted gene targets of the most predictive microRNAs to an enrichment analysis. The following key themes emerged from our machine learning and bioinformatics analyses: cell death, cellular senescence, energy metabolism, genomic integrity, glia, immune system, metal ion homeostasis, oxidative stress, proteostasis, and synaptic function. Many of the results demonstrated unique age-specificity. For example, terms highlighting cellular senescence only emerged in the earliest and intermediate age ranges while the majority of results relevant to cell death appeared in the youngest patients. Existing literature corroborates the importance of these hallmarks in AD.

Gene-environment interactions in Alzheimer disease: the emerging role of epigenetics

With the exception of a few monogenic forms, Alzheimer disease (AD) has a complex aetiology that is likely to involve multiple susceptibility genes and environmental factors. The role of environmental factors is difficult to determine and, until a few years ago, the molecular mechanisms underlying gene-environment (G × E) interactions in AD were largely unknown. Here, we review evidence that has emerged over the past two decades to explain how environmental factors, such as diet, lifestyle, alcohol, smoking and pollutants, might interact with the human genome. In particular, we discuss how various environmental AD risk factors can induce epigenetic modifications of key AD-related genes and pathways and consider how epigenetic mechanisms could contribute to the effects of oxidative stress on AD onset. Studies on early-life exposures are helping to uncover critical time windows of sensitivity to epigenetic influences from environmental factors, thereby laying the foundations for future primary preventative approaches. We conclude that epigenetic modifications need to be considered when assessing G × E interactions in AD.

Distinct sex-specific DNA methylation differences in Alzheimer's disease

BACKGROUND

Sex is increasingly recognized as a significant factor contributing to the biological and clinical heterogeneity in AD. There is also growing evidence for the prominent role of DNA methylation (DNAm) in Alzheimer's disease (AD).

METHODS

We studied sex-specific DNA methylation differences in the blood samples of AD subjects compared to cognitively normal subjects, by performing sex-specific meta-analyses of two large blood-based epigenome-wide association studies (ADNI and AIBL), which included DNA methylation data for a total of 1284 whole blood samples (632 females and 652 males). Within each dataset, we used two complementary analytical strategies, a sex-stratified analysis that examined methylation to AD associations in male and female samples separately, and a methylation-by-sex interaction analysis that compared the magnitude of these associations between different sexes. After adjusting for age, estimated immune cell type proportions, batch effects, and correcting for inflation, the inverse-variance fixed-effects meta-analysis model was used to identify the most consistent DNAm differences across datasets. In addition, we also evaluated the performance of the sex-specific methylation-based risk prediction models for AD diagnosis using an independent external dataset.

RESULTS

In the sex-stratified analysis, we identified 2 CpGs, mapped to the PRRC2A and RPS8 genes, significantly associated with AD in females at a 5% false discovery rate, and an additional 25 significant CpGs (21 in females, 4 in males) at P-value < 1×10^-5. In methylation-by-sex interaction analysis, we identified 5 significant CpGs at P-value < 10^-5. Out-of-sample validations using the AddNeuroMed dataset showed in females, the best logistic prediction model included age, estimated immune cell-type proportions, and methylation risk scores (MRS) computed from 9 of the 23 CpGs identified in AD vs. CN analysis that are also available in AddNeuroMed dataset (AUC = 0.74, 95% CI: 0.65-0.83). In males, the best logistic prediction model included only age and MRS computed from 2 of the 5 CpGs identified in methylation-by-sex interaction analysis that are also available in the AddNeuroMed dataset (AUC = 0.70, 95% CI: 0.56-0.82).

CONCLUSIONS

Overall, our results show that the DNA methylation differences in AD are largely distinct between males and females. Our best-performing sex-specific methylation-based prediction model in females performed better than that for males and additionally included estimated cell-type proportions. The significant discriminatory classification of AD samples with our methylation-based prediction models demonstrates that sex-specific DNA methylation could be a predictive biomarker for AD. As sex is a strong factor underlying phenotypic variability in AD, the results of our study are particularly relevant for a better understanding of the epigenetic architecture that underlie AD and for promoting precision medicine in AD.

Pathogenesis, therapeutic strategies and biomarker development based on "omics" analysis related to microglia in Alzheimer's disease

Alzheimer's disease (AD) is the most common neurodegenerative disease and the most common cause of dementia. Among various pathophysiological aspects, microglia are considered to play important roles in the pathogenesis of AD. Genome wide association studies (GWAS) showed that the majority of AD risk genes are highly or exclusively expressed in microglia, underscoring the critical roles of microglia in AD pathogenesis. Recently, omics technologies have greatly advanced our knowledge of microglia biology in AD. Omics approaches, including genomics, epigenomics, transcriptomics, proteomics, and metabolomics/lipidomics, present remarkable opportunities to delineate the underlying mechanisms, discover novel diagnostic biomarkers, monitor disease progression, and shape therapeutic strategies for diseases. In this review, we summarized research based on microglial "omics" analysis in AD, especially the recent research advances in the identification of AD-associated microglial subsets. This review reinforces the important role of microglia in AD and advances our understanding of the mechanism of microglia in AD pathogenesis. Moreover, we proposed the value of microglia-based omics in the development of therapeutic strategies and biomarkers for AD.

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

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

Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer's disease

To better understand DNA methylation in Alzheimer's disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 - 0.770, P-value = 2.78 × 10^-5). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery.

Quantitative proteomics on the cerebrospinal fluid of hydrocephalus in neonatal bacterial meningitis

Objective

Hydrocephalus in bacterial meningitis (BM) is a devastating infectious neurological disease and the proteins and pathways involved in its pathophysiology are not fully understood.

Materials and methods

Label-free quantitative (LFQ) proteomics analyses was used to identify differentially expressed proteins (DEPs) in cerebrospinal fluid (CSF) samples from infants with hydrocephalus and bacterial meningitis (HBM group, N = 8), infants with bacterial meningitis (BM group, N = 9); and healthy infants (N group, N = 11). Bioinformatics analysis was subsequently performed to investigate Gene Ontology (GO) functional annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) enriched signaling pathways of these DEPs. Six proteins (AZU1, COX4I1, EDF1, KRT31, MMP12, and PRG2) were selected for further validation via enzyme-linked immunosorbent assay (ELISA).

Results

Compared with BM group and N group, HBM group had a higher whole CSF protein level (5.6 ± 2.7 vs. 1.7 ± 1.0 vs. 1.2 ± 0.5 g/l) and lower whole CSF glucose level (0.8 ± 0.6 vs. 1.8 ± 0.7 vs. 3.3 ± 0.8 mmol/l) (both P < 0.05). Over 300 DEPs were differentially expressed in HBM group compared with BM group and BM compared with N group, of which 78% were common to both. Cluster analysis indicated that the levels of 226 proteins were increased in BM group compared with N group and were decreased in HBM group compared with BM group. Bioinformatics analysis indicated the involvement of the cell adhesion, immune response and extracellular exosome signaling were significantly enriched in HBM compared with BM group and BM compared with N group. 267 DEPs were identified between HBM group with N group, KEGG analysis indicated that DEPs mainly involved in filament cytoskeleton and immune response. The ELISA results further verified that the expression levels of AZU1 were significantly different from among three groups (both P < 0.05).

Conclusion

This is the first reported characterization of quantitative proteomics from the CSF of infants with HBM. Our study also demonstrated that AZU1 could be a potential biomarker for the diagnosis of hydrocephalus in bacterial meningitis.

Integration of RNA-seq and ATAC-seq identifies muscle-regulated hub genes in cattle

As the main product of livestock, muscle itself plays an irreplaceable role in maintaining animal body movement and regulating metabolism. Therefore, it is of great significance to explore its growth, development and regeneration to improve the meat yield and quality of livestock. In this study, we attempted to use RNA-seq and ATAC-seq techniques to identify differentially expressed genes (DEGs) specifically expressed in bovine skeletal muscle as potential candidates for studying the regulatory mechanisms of muscle development. Microarray data from 8 tissue samples were selected from the GEO database for analysis. First, we obtained gene modules related to each tissue through WGCNA analysis. Through Gene Ontology (GO) functional annotation, the module of lightyellow (ME_lightyellow) was closely related to muscle development, and 213 hub genes were screened as follow-up research targets. Further, the difference analysis showed that, except for PREB, all other candidate hub genes were up-regulated (muscle group vs. other-group). ATAC-seq analysis showed that muscle-specific accessible chromatin regions were mainly located in promoter of genes related to muscle structure development (GO:0061061), muscle cell development (GO:0055001) and muscle system process (GO:0003012), which were involved in cAMP, CGMP-PKG, MAPK, and other signaling pathways. Next, we integrated the results of RNA-seq and ATAC-seq analysis, and 54 of the 212 candidate hub genes were identified as key regulatory genes in skeletal muscle development. Finally, through motif analysis, 22 of the 54 key genes were found to be potential target genes of transcription factor MEF2C. Including CAPN3, ACTN2, MB, MYOM3, SRL, CKM, ALPK3, MAP3K20, UBE2G1, NEURL2, CAND2, DOT1L, HRC, MAMSTR, FSD2, LRRC2, LSMEM1, SLC29A2, FHL3, KLHL41, ATXN7L2, and PDRG1. This provides a potential reference for studying the molecular mechanism of skeletal muscle development in mammals.

MethReg: estimating the regulatory potential of DNA methylation in gene transcription

Epigenome-wide association studies often detect many differentially methylated sites, and many are located in distal regulatory regions. To further prioritize these significant sites, there is a critical need to better understand the functional impact of CpG methylation. Recent studies demonstrated that CpG methylation-dependent transcriptional regulation is a widespread phenomenon. Here, we present MethReg, an R/Bioconductor package that analyzes matched DNA methylation and gene expression data, along with external transcription factor (TF) binding information, to evaluate, prioritize and annotate CpG sites with high regulatory potential. At these CpG sites, TF-target gene associations are often only present in a subset of samples with high (or low) methylation levels, so they can be missed by analyses that use all samples. Using colorectal cancer and Alzheimer's disease datasets, we show MethReg significantly enhances our understanding of the regulatory roles of DNA methylation in complex diseases.