Decoding depression: a comprehensive multi-cohort exploration of blood DNA methylation using machine learning and deep learning approaches.

The causes of depression are complex, and the current diagnosis methods rely solely on psychiatric evaluations with no incorporation of laboratory biomarkers in clinical practices. We investigated the stability of blood DNA methylation depression signatures in six different populations using six public and two domestic cohorts (n = 1942) conducting mega-analysis and meta-analysis of the individual studies. We evaluated 12 machine learning and deep learning strategies for depression classification both in cross-validation (CV) and in hold-out tests using merged data from 8 separate batches, constructing models with both biased and unbiased feature selection. We found 1987 CpG sites related to depression in both mega- and meta-analysis at the nominal level, and the associated genes were nominally related to axon guidance and immune pathways based on enrichment analysis and eQTM data. Random forest classifiers achieved the highest performance (AUC 0.73 and 0.76) in CV and hold-out tests respectively on the batch-level processed data. In contrast, the methylation showed low predictive power (all AUCs < 0.57) for all classifiers in CV and no predictive power in hold-out tests when used with harmonized data. All models achieved significantly better performance (>14% gain in AUCs) with pre-selected features (selection bias), with some of the models (joint autoencoder-classifier) reaching AUCs of up to 0.91 in the final testing regardless of data preparation. Different algorithmic feature selection approaches may outperform limma, however, random forest models perform well regardless of the strategy. The results provide an overview over potential future biomarkers for depression and highlight many important methodological aspects for DNA methylation-based depression profiling including the use of machine learning strategies.

High amphipathicity of α-helical peptides enhances unmethylated CpG DNA-induced activation of mouse macrophage-like RAW264.7 cells.

The α-helical antimicrobial peptide Kn2-7 enhances the activation of mouse macrophage-like RAW264.7 induced by DNA containing unmethylated cytosine-guanine motifs (CpG DNA). This enhancement is related to increased cellular uptake of DNA by Kn2-7, but the relevant properties of Kn2-7 are unknown. Physicochemical property analysis revealed that Kn2-7 has high amphipathicity. In contrast, the α-helical antimicrobial peptide L5, which increases the cellular uptake of CpG DNA but does not enhance CpG DNA-induced activation, has low amphipathicity. Kn2-7 derivatives with decreased amphipathicity but the same amino acid composition as Kn2-7 did not enhance CpG DNA-induced activation. On the other hand, L5 derivatives with high amphipathicity but the same amino acid composition as L5 enhanced CpG DNA-induced activation. Cellular uptake of DNA was not increased by the L5 derivatives, indicating that high amphipathicity does not affect DNA uptake. Furthermore, α-helical peptides with reversed sequences relative to the Kn2-7 and L5 derivatives with high amphipathicity were synthesized. The reversed-sequence peptides, which had the same amphipathicity but different amino acid sequences from their counterparts, enhanced CpG DNA-induced activation. Taken together, these observations indicate that the high amphipathicity of α-helical peptides enhances the CpG DNA-induced activation of RAW264.7.

Epigenetic and sex differences in opioid use disorder in chronic pain: A real-world study linked with OPRM1 DNA methylation.

Opioid use disorder (OUD) is a multifaceted condition influenced by sex, genetic and environmental factors that could be linked with epigenetic changes. Understanding how these factors interact is crucial to understand and address the development and progression of this disorder. Our aim was to elucidate different potential epigenetic and genetic mechanisms between women and men that correlate with OUD under real-world pain unit conditions. Associations between analgesic response and the DNA methylation level of the opioid mu receptor (OPRM1) gene (CpG sites 1-5 selected in the promoter region) were evaluated in 345 long opioid-treated chronic non cancer pain: cases with OUD (n = 67) and controls (without OUD, n = 278). Cases showed younger ages, low employment status and quality of life, but higher morphine equivalent daily dose and psychotropic use, compared to the controls. The patients with OUD showed a significant decrease in OPRM1 DNA methylation, which correlated with clinical outcomes like pain relief, depression and different adverse events. Significant differences were found at the five CpG sites studied for men, and exclusively in women for CpG site 3, in relation to OUD diagnosis. These findings support the importance of epigenetics and sex as biological variables to be considered toward efficient OUD understanding and therapy development.

Hypomethylation of the RUNX2 Gene Is a New Potential Biomarker of Primary Osteoporosis in Men and Women.

The search for the molecular markers of osteoporosis (OP), based on the analysis of differential deoxyribonucleic acid (DNA) methylation in bone cells and peripheral blood cells, is promising for developments in the field of the early diagnosis and targeted therapy of the disease. The Runt-related transcription factor 2 (RUNX2) gene is one of the key genes of bone metabolism, which is of interest in the search for epigenetic signatures and aberrations associated with the risk of developing OP. Based on pyrosequencing, the analysis of the RUNX2 methylation profile from a pool of peripheral blood cells in men and women over 50 years of age of Russian ethnicity from the Volga-Ural region of Russia was carried out. The level of DNA methylation in three CpG sites of the RUNX2 gene was assessed and statistically significant hypomethylation was revealed in all three studied CpG sites in men (U = 746.5, p = 0.004; U = 784, p = 0.01; U = 788.5, p = 0.01, respectively) and in one CpG site in women (U = 537, p = 0.03) with primary OP compared with control. In the general sample, associations were preserved for the first CpG site (U = 2561, p = 0.0001766). The results were obtained for the first time and indicate the existence of potentially new epigenetic signatures of RUNX2 in individuals with OP.

Respiratory infection- and asthma-prone, low vaccine responder children demonstrate distinct mononuclear cell DNA methylation pathways.

BACKGROUND: Infants with frequent viral and bacterial respiratory infections exhibit compromised immunity to routine immunizations. They are also more likely to develop chronic respiratory diseases in later childhood. This study investigated the feasibility of epigenetic profiling to reveal endotype-specific molecular pathways with potential for early identification and immuno-modulation. Peripheral blood mononuclear cells from respiratory infection allergy/asthma-prone (IAP) infants and non-infection allergy/asthma prone (NIAP) were retrospectively selected for genome-wide DNA methylation and single nucleotide polymorphism analysis. The IAP infants were enriched for the low vaccine responsiveness (LVR) phenotype (Fisher's exact p-value = 0.02). RESULTS: An endotype signature of 813 differentially methylated regions (DMRs) comprising 238 lead CpG associations (FDR < 0.05) emerged, implicating pathways related to asthma, mucin production, antigen presentation and inflammasome activation. Allelic variation explained only a minor portion of this signature. Stimulation of mononuclear cells with monophosphoryl lipid A (MPL), a TLR agonist, partially reversed this signature at a subset of CpGs, suggesting the potential for epigenetic remodeling. CONCLUSIONS: This proof-of-concept study establishes a foundation for precision endotyping of IAP children and highlights the potential for immune modulation strategies using adjuvants for future investigation.

MIMOSA: a resource consisting of improved methylome prediction models increases power to identify DNA methylation-phenotype associations.

Although DNA methylation (DNAm) has been implicated in the pathogenesis of numerous complex diseases, from cancer to cardiovascular disease to autoimmune disease, the exact methylation sites that play key roles in these processes remain elusive. One strategy to identify putative causal CpG sites and enhance disease etiology understanding is to conduct methylome-wide association studies (MWASs), in which predicted DNA methylation that is associated with complex diseases can be identified. However, current MWAS models are primarily trained using the data from single studies, thereby limiting the methylation prediction accuracy and the power of subsequent association studies. Here, we introduce a new resource, MWAS Imputing Methylome Obliging Summary-level mQTLs and Associated LD matrices (MIMOSA), a set of models that substantially improve the prediction accuracy of DNA methylation and subsequent MWAS power through the use of a large summary-level mQTL dataset provided by the Genetics of DNA Methylation Consortium (GoDMC). Through the analyses of GWAS (genome-wide association study) summary statistics for 28 complex traits and diseases, we demonstrate that MIMOSA considerably increases the accuracy of DNA methylation prediction in whole blood, crafts fruitful prediction models for low heritability CpG sites, and determines markedly more CpG site-phenotype associations than preceding methods. Finally, we use MIMOSA to conduct a case study on high cholesterol, pinpointing 146 putatively causal CpG sites.

Generation of Whole-Genome Bisulfite Sequencing Libraries for Comprehensive DNA Methylome Analysis.

Whole-genome bisulfite sequencing (WGBS) enables the detection of DNA methylation at a single base-pair resolution. The treatment of DNA with sodium bisulfite allows the discrimination of methylated and unmethylated cytosines, but the power of this technology can be limited by the input amounts of DNA and the length of DNA fragments due to DNA damage caused by the desulfonation process. Here, we describe a WGBS library preparation protocol that minimizes the loss and damage of DNA, generating high-quality libraries amplified with fewer polymerase chain reaction (PCR) cycles, and hence data with fewer PCR duplicates, from lower amounts of input material. Briefly, genomic DNA is sheared, end-repaired, 3'-adenylated, and ligated to adaptors with fewer clean-up steps in between, minimizing DNA loss. The adapter-ligated DNA is then treated with sodium bisulfite and amplified with a few PCR cycles to reach the yield needed for sequencing.

Approaches for the Analysis and Interpretation of Whole-Genome Bisulfite Sequencing Data.

DNA methylation is a covalent modification of DNA that plays important roles in processes such as the regulation of gene expression, transcription factor binding, and suppression of transposable elements. The use of whole-genome bisulfite sequencing (WGBS) enables the genome-wide identification and quantification of DNA methylation patterns at single-base resolution and is the gold standard for the analysis of DNA methylation. However, the computational analysis of WGBS data can be particularly challenging, as many computationally intensive steps are required. Here, we outline step-by-step an approach for the analysis and interpretation of WGBS data. First, sequencing reads must be trimmed, quality-checked, and aligned to the genome. Second, DNA methylation levels are estimated at each cytosine position using the aligned sequence reads of the bisulfite-treated DNA. Third, regions of differential cytosine methylation between samples can be identified. Finally, these data need to be visualized and interpreted in the context of the biological question at hand.

hTERT Epigenetics Provides New Perspectives for Diagnosis and Evidence-Based Guidance of Chemotherapy in Cancer.

Strong epigenetic pan-cancer biomarkers are required to meet several current, urgent clinical needs and to further improve the present chemotherapeutic standard. We have concentrated on the investigation of epigenetic alteration of the hTERT gene, which is frequently epigenetically dysregulated in a number of cancers in specific developmental stages. Distinct DNA methylation profiles were identified in our data on early urothelial cancer. An efficient EpihTERT assay could be developed utilizing suitable combinations with sequence-dependent thermodynamic parameters to distinguish between differentially methylated states. We infer from this data set, the epigenetic context, and the related literature that a CpG-rich, 2800 bp region, a prominent CpG island, surrounding the transcription start of the hTERT gene is the crucial epigenetic zone for the development of a potent biomarker. In order to accurately describe this region, we have named it "Acheron" (Ἀχέρων). In Greek mythology, this is the river of woe and misery and the path to the underworld. Exploitation of the DNA methylation profiles focused on this region, e.g., idiolocal normalized Methylation Specific PCR (IDLN-MSP), opens up a wide range of new possibilities for diagnosis, determination of prognosis, follow-up, and detection of residual disease. It may also have broad implications for the choice of chemotherapy.

Systemic interindividual DNA methylation variants in cattle share major hallmarks with those in humans.

BACKGROUND: We recently identified ~ 10,000 correlated regions of systemic interindividual epigenetic variation (CoRSIVs) in the human genome. These methylation variants are amenable to population studies, as DNA methylation measurements in blood provide information on epigenetic regulation throughout the body. Moreover, establishment of DNA methylation at human CoRSIVs is labile to periconceptional influences such as nutrition. Here, we analyze publicly available whole-genome bisulfite sequencing data on multiple tissues of each of two Holstein cows to determine whether CoRSIVs exist in cattle. RESULTS: Focusing on genomic blocks with ≥ 5 CpGs and a systemic interindividual variation index of at least 20, our approach identifies 217 cattle CoRSIVs, a subset of which we independently validate by bisulfite pyrosequencing. Similar to human CoRSIVs, those in cattle are strongly associated with genetic variation. Also as in humans, we show that establishment of DNA methylation at cattle CoRSIVs is particularly sensitive to early embryonic environment, in the context of embryo culture during assisted reproduction. CONCLUSIONS: Our data indicate that CoRSIVs exist in cattle, as in humans, suggesting these systemic epigenetic variants may be common to mammals in general. To the extent that individual epigenetic variation at cattle CoRSIVs affects phenotypic outcomes, assessment of CoRSIV methylation at birth may become an important tool for optimizing agriculturally important traits. Moreover, adjusting embryo culture conditions during assisted reproduction may provide opportunities to tailor agricultural outcomes by engineering CoRSIV methylation profiles.

Epigenetic signals associated with delirium replicated across four independent cohorts.

Delirium is risky and indicates poor outcomes for patients. Therefore, it is crucial to create an effective delirium detection method. However, the epigenetic pathophysiology of delirium remains largely unknown. We aimed to discover reliable and replicable epigenetic (DNA methylation: DNAm) markers that are associated with delirium including post-operative delirium (POD) in blood obtained from patients among four independent cohorts. Blood DNA from four independent cohorts (two inpatient cohorts and two surgery cohorts; 16 to 88 patients each) were analyzed using the Illumina EPIC array platform for genome-wide DNAm analysis. We examined DNAm differences in blood between patients with and without delirium including POD. When we compared top CpG sites previously identified from the initial inpatient cohort with three additional cohorts (one inpatient and two surgery cohorts), 11 of the top 13 CpG sites showed statistically significant differences in DNAm values between the delirium group and non-delirium group in the same directions as found in the initial cohort. This study demonstrated the potential value of epigenetic biomarkers as future diagnostic tools. Furthermore, our findings provide additional evidence of the potential role of epigenetics in the pathophysiology of delirium including POD.

TET1 displays catalytic and non-catalytic functions in the adult mouse cortex.

TET1/2/3 dioxygenases iteratively demethylate 5-methylcytosine, beginning with the formation of 5-hydroxymethylcytosine (5hmC). The post-mitotic brain maintains higher levels of 5hmC than most peripheral tissues, and TET1 ablation studies have underscored the critical role of TET1 in brain physiology. However, deletion of Tet1 precludes the disentangling of the catalytic and non-catalytic functions of TET1. Here, we dissect these functions of TET1 by comparing adult cortex of Tet1 wildtype (Tet1 WT), a novel Tet1 catalytically dead mutant (Tet1 HxD), and Tet1 knockout (Tet1 KO) mice. Using DNA methylation array, we uncover that Tet1 HxD and KO mutations perturb the methylation status of distinct subsets of CpG sites. Gene ontology (GO) analysis on specific differential 5hmC regions indicates that TET1's catalytic activity is linked to neuronal-specific functions. RNA-Seq further shows that Tet1 mutations predominantly impact the genes that are associated with alternative splicing. Lastly, we performed High-performance Liquid Chromatography Mass-Spectrometry lipidomics on WT and mutant cortices and uncover accumulation of lysophospholipids lysophosphatidylethanolamine and lysophosphatidylcholine in Tet1 HxD cortex. In summary, we show that Tet1 HxD does not completely phenocopy Tet1 KO, providing evidence that TET1 modulates distinct cortical functions through its catalytic and non-catalytic roles.

Epigenetic alterations affecting hematopoietic regulatory networks as drivers of mixed myeloid/lymphoid leukemia.

Leukemias with ambiguous lineage comprise several loosely defined entities, often without a clear mechanistic basis. Here, we extensively profile the epigenome and transcriptome of a subgroup of such leukemias with CpG Island Methylator Phenotype. These leukemias exhibit comparable hybrid myeloid/lymphoid epigenetic landscapes, yet heterogeneous genetic alterations, suggesting they are defined by their shared epigenetic profile rather than common genetic lesions. Gene expression enrichment reveals similarity with early T-cell precursor acute lymphoblastic leukemia and a lymphoid progenitor cell of origin. In line with this, integration of differential DNA methylation and gene expression shows widespread silencing of myeloid transcription factors. Moreover, binding sites for hematopoietic transcription factors, including CEBPA, SPI1 and LEF1, are uniquely inaccessible in these leukemias. Hypermethylation also results in loss of CTCF binding, accompanied by changes in chromatin interactions involving key transcription factors. In conclusion, epigenetic dysregulation, and not genetic lesions, explains the mixed phenotype of this group of leukemias with ambiguous lineage. The data collected here constitute a useful and comprehensive epigenomic reference for subsequent studies of acute myeloid leukemias, T-cell acute lymphoblastic leukemias and mixed-phenotype leukemias.

Rockfish: A transformer-based model for accurate 5-methylcytosine prediction from nanopore sequencing.

DNA methylation plays an important role in various biological processes, including cell differentiation, ageing, and cancer development. The most important methylation in mammals is 5-methylcytosine mostly occurring in the context of CpG dinucleotides. Sequencing methods such as whole-genome bisulfite sequencing successfully detect 5-methylcytosine DNA modifications. However, they suffer from the serious drawbacks of short read lengths and might introduce an amplification bias. Here we present Rockfish, a deep learning algorithm that significantly improves read-level 5-methylcytosine detection by using Nanopore sequencing. Rockfish is compared with other methods based on Nanopore sequencing on R9.4.1 and R10.4.1 datasets. There is an increase in the single-base accuracy and the F1 measure of up to 5 percentage points on R.9.4.1 datasets, and up to 0.82 percentage points on R10.4.1 datasets. Moreover, Rockfish shows a high correlation with whole-genome bisulfite sequencing, requires lower read depth, and achieves higher confidence in biologically important regions such as CpG-rich promoters while being computationally efficient. Its superior performance in human and mouse samples highlights its versatility for studying 5-methylcytosine methylation across varied organisms and diseases. Finally, its adaptable architecture ensures compatibility with new versions of pores and chemistry as well as modification types.

A systematic review on the contribution of DNA methylation to hearing loss.

BACKGROUND: DNA methylation may have a regulatory role in monogenic sensorineural hearing loss and complex, polygenic phenotypic forms of hearing loss, including age-related hearing impairment or Meniere disease. The purpose of this systematic review is to critically assess the evidence supporting a functional role of DNA methylation in phenotypes associated with hearing loss. RESULTS: The search strategy yielded a total of 661 articles. After quality assessment, 25 records were selected (12 human DNA methylation studies, 5 experimental animal studies and 8 studies reporting mutations in the DNMT1 gene). Although some methylation studies reported significant differences in CpG methylation in diverse gene promoters associated with complex hearing loss phenotypes (ARHI, otosclerosis, MD), only one study included a replication cohort that supported a regulatory role for CpG methylation in the genes TCF25 and POLE in ARHI. Conversely, several studies have independently confirmed pathogenic mutations within exon 21 of the DNMT1 gene, which encodes the DNA (cytosine-5)-methyltransferase 1 enzyme. This methylation enzyme is strongly associated with a rare disease defined by autosomal dominant cerebellar ataxia, deafness and narcolepsy (ADCA-DN). Of note, rare variants in DNMT1 and DNMT3A genes have also been reported in noise-induced hearing loss. CONCLUSIONS: Evidence supporting a functional role for DNA methylation in hearing loss is limited to few genes in complex disorders such as ARHI. Mutations in the DNMT1 gene are associated with ADCA-DN, suggesting the CpG methylation in hearing loss genes deserves further attention in hearing research.

Impact of genomic and epigenomic alterations of multigene on a multicancer pedigree.

BACKGROUND: Germline mutations have been identified in a small number of hereditary cancers, but the genetic predisposition for many familial cancers remains to be elucidated. METHODS: This study identified a Chinese pedigree that presented different cancers (breast cancer, BRCA; adenocarcinoma of the esophagogastric junction, AEG; and B-cell acute lymphoblastic leukemia, B-ALL) in each of the three generations. Whole-genome sequencing and whole-exome sequencing were performed on peripheral blood or bone marrow and cancer biopsy samples. Whole-genome bisulfite sequencing was conducted on the monozygotic twin brothers, one of whom developed B-ALL. RESULTS: According to the ACMG guidelines, bioinformatic analysis of the genome sequencing revealed 20 germline mutations, particularly mutations in the DNAH11 (c.9463G > A) and CFH (c.2314G > A) genes that were documented in the COSMIC database and validated by Sanger sequencing. Forty-one common somatic mutated genes were identified in the cancer samples, displaying the same type of single nucleotide substitution Signature 5. Meanwhile, hypomethylation of PLEK2, MRAS, and RXRA as well as hypermethylation of CpG island associated with WT1 was shown in the twin with B-ALL. CONCLUSIONS: These findings reveal genomic alterations in a pedigree with multiple cancers. Mutations found in the DNAH11, CFH genes, and other genes predispose to malignancies in this family. Dysregulated methylation of WT1, PLEK2, MRAS, and RXRA in the twin with B-ALL increases cancer susceptibility. The similarity of the somatic genetic changes among the three cancers indicates a hereditary impact on the pedigree. These familial cancers with germline and somatic mutations, as well as epigenomic alterations, represent a common molecular basis for many multiple cancer pedigrees.

DNA methylation profile of inflammatory breast cancer and its impact on prognosis and outcome.

BACKGROUND: Inflammatory breast cancer (IBC) is a rare disease characterized by rapid progression, early metastasis, and a high mortality rate. METHODS: Genome-wide DNA methylation analysis (EPIC BeadChip platform, Illumina) and somatic gene variants (105 cancer-related genes) were performed in 24 IBCs selected from a cohort of 140 cases. RESULTS: We identified 46,908 DMPs (differentially methylated positions) (66% hypomethylated); CpG islands were predominantly hypermethylated (39.9%). Unsupervised clustering analysis revealed three clusters of DMPs characterized by an enrichment of specific gene mutations and hormone receptor status. The comparison among DNA methylation findings and external datasets (TCGA-BRCA stages III-IV) resulted in 385 shared DMPs mapped in 333 genes (264 hypermethylated). 151 DMPs were associated with 110 genes previously detected as differentially expressed in IBC (GSE45581), and 68 DMPs were negatively correlated with gene expression. We also identified 4369 DMRs (differentially methylated regions) mapped on known genes (2392 hypomethylated). BCAT1, CXCL12, and TBX15 loci were selected and evaluated by bisulfite pyrosequencing in 31 IBC samples. BCAT1 and TBX15 had higher methylation levels in triple-negative compared to non-triple-negative, while CXCL12 had lower methylation levels in triple-negative than non-triple-negative IBC cases. TBX15 methylation level was associated with obesity. CONCLUSIONS: Our findings revealed a heterogeneous DNA methylation profile with potentially functional DMPs and DMRs. The DNA methylation data provided valuable insights for prognostic stratification and therapy selection to improve patient outcomes.

Tumor detection by analysis of both symmetric- and hemi-methylation of plasma cell-free DNA.

Aberrant DNA methylation patterns have been used for cancer detection. However, DNA hemi-methylation, present at about 10% CpG dinucleotides, has been less well studied. Here we show that a majority of differentially hemi-methylated regions (DHMRs) in liver tumor DNA or plasma cells free (cf) DNA do not overlap with differentially methylated regions (DMRs) of the same samples, indicating that DHMRs could serve as independent biomarkers. Furthermore, we analyzed the cfDNA methylomes of 215 samples from individuals with liver or brain cancer and individuals without cancer (controls), and trained machine learning models using DMRs, DHMRs or both. The models incorporated with both DMRs and DHMRs show a superior performance compared to models trained with DMRs or DHMRs, with AUROC being 0.978, 0.990, and 0.983 in distinguishing control, liver and brain cancer, respectively, in a validation cohort. This study supports the potential of utilizing both DMRs and DHMRs for multi-cancer detection.

Integrating muti-omics data to identify tissue-specific DNA methylation biomarkers for cancer risk.

The relationship between tissue-specific DNA methylation and cancer risk remains inadequately elucidated. Leveraging resources from the Genotype-Tissue Expression consortium, here we develop genetic models to predict DNA methylation at CpG sites across the genome for seven tissues and apply these models to genome-wide association study data of corresponding cancers, namely breast, colorectal, renal cell, lung, ovarian, prostate, and testicular germ cell cancers. At Bonferroni-corrected P < 0.05, we identify 4248 CpGs that are significantly associated with cancer risk, of which 95.4% (4052) are specific to a particular cancer type. Notably, 92 CpGs within 55 putative novel loci retain significant associations with cancer risk after conditioning on proximal signals identified by genome-wide association studies. Integrative multi-omics analyses reveal 854 CpG-gene-cancer trios, suggesting that DNA methylation at 309 distinct CpGs might influence cancer risk through regulating the expression of 205 unique cis-genes. These findings substantially advance our understanding of the interplay between genetics, epigenetics, and gene expression in cancer etiology.

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/.