CpG Sites Research Articles

Genomic architecture in social insects is more strongly associated with phylogeny than social behavior

Abstract The evolution of sociality in insects has been predicted to reduce effective population sizes, in turn leading to changes in genome architecture, including higher recombination rates, larger genomes, increased GC-biased gene conversion (gBGC), and greater intragenomic variation in GC content to maintain castes through differential methylation. As the number of sequenced insect genomes continues to grow, it remains an open question which, if any, of these genomic features are consistent across social insect genomes. A major challenge to determining such commonalities has been the lack of phylogenetically controlled analyses across independent origins of sociality. Of the 15 Hymenoptera species for which recombination rate was available, social species had higher rates of recombination. Next, we conducted a broader analysis of genome architecture by analyzing genome assemblies for 435 species of Hymenoptera and 8 species of Blattodea to test if GC content, genome size, distribution of CpG sites or codon bias repeatedly differed between social and nonsocial species. Overall, there was little support for predictable changes in genome architecture associated with sociality across Hymenoptera, after accounting for phylogenetic relationships. However, we found a significant negative relationship between sociality and GC content within the family Apidae and a significant negative relationship between sociality and genome size within the family Halictidae. In all, these results suggest that unique origins of social behavior may produce unique trends in genomic architecture. Our study highlights the need to examine genome architecture across independent origins of social behavior.

BS-clock, advancing epigenetic age prediction with high-resolution DNA methylation bisulfite sequencing data.

DNA methylation patterns provide precise and accurate estimates of biological age due to their robustness and predictable changes associated with aging processes. Although several methylation aging clocks have been developed in recent years, they are primarily designed for DNA methylation array data, which has limited CpG coverage and detection sensitivity compared to bisulfite sequencing data. Here, we present BS-clock, a novel DNA methylation clock for human aging based on bisulfite sequencing data. Using BS-seq data from 529 samples retrieved from four tissues, our BS-clock achieves higher correlations with chronological age in multiple tissue types compared to existing array-based clocks. Our study revealed age-dependent aging rates across different age stages and disease conditions, and overall low cross-tissue prediction capability by applying the model trained on one tissue type to others. In summary, BS-clock overcomes limitations of array-based techniques, offering genome-wide CpG site coverage and more robust and accurate aging quantification. This research paves the way for advanced epigenetic studies of aging and holds promise for developing targeted interventions to promote healthy aging. All analysis codes for reproducing the results of the study are publicly available at https://github.com/hucongcong97/BS-clock. Supplementary data are available at Bioinformatics online.

The study of Alzheimer's disease risk diagnosis based on natural killer cell marker genes in the multi-omics data.

Alzheimer's disease (AD) is a common neurodegenerative disorder, currently lacking effective early diagnostic methods. However, natural killer (NK) cells may play a potential role in AD pathogenesis. This study aims to identify AD-related feature genes from NK cell markers to construct a diagnostic model and explore their potential biological mechanisms in AD. Single-cell RNA sequencing data was used to identify NK cell markers. A novel feature selection algorithm, adaptive dynamic graph convolutional network (ADGCN), was proposed to extract AD-related feature genes and construct a diagnostic model. Differential, correlation and enrichment analyses were performed to understand the biological mechanisms of these genes. Immune infiltration analysis compared the immune microenvironment between AD and controls. Two regulatory networks explored interactions between feature genes, transcription factors and microRNAs. The association between SNPs and feature genes' expression was examined through expression quantitative trait loci analysis. Differential CpG sites were identified to analyze their association with the NK cell markers' expression. We developed an optimal diagnostic model (ADGCN-XGBoost) with 17 feature genes, demonstrating high diagnostic effectiveness across datasets. These genes were primarily related to macromolecule biosynthesis, cytoplasmic translation biological processes and ribosome pathway, and potentially modulated immune infiltration of AD patients. We predicted 27 target miRNAs and 21 transcription factors influencing these genes. Multimodal analysis identified 57 significant SNP-gene associations and seven CpG-gene pairs. This study proposed a novel feature selection algorithm and developed a diagnostic model based on 17 feature genes, providing new potential biomarkers for AD diagnosis.

Noninvasive, epigenetic age estimation in an elasmobranch, the cownose ray (Rhinoptera bonasus)

Age data are essential for estimating life history parameters and are thus critical for population assessment, management, and conservation. Traditional vertebrae-based age estimation in elasmobranchs can be costly, time intensive, of low accuracy, and is by necessity lethal. Herein, epigenetic clocks were developed for an elasmobranch, the cownose ray (Rhinoptera bonasus), using aquarium-born individuals (n = 42) with known dates of birth (age range: 7−7,878 days or 0−21 years) and two tissue types (fin clips and whole blood) that can be sampled in a relatively non-invasive manner. Enzymatically-converted restriction site-associated DNA sequencing (ECrad-seq) was used to identify CpG sites that exhibited age-correlated DNA methylation. The epigenetic clocks developed were highly accurate (mean absolute error, MAE, < 0.75 years) and precise (R2 > 0.98). Age-associated CpG sites were identified across tissues, and a multi-tissue clock was also highly accurate (MAE < 1 year) and precise (R2 = 0.97). Using the developed fin clip clock, three wild-caught individuals of unknown age but managed in aquariums for > 22 years were predicted to be 22.10−23.49 years old. Overall, the results have important implications for future epigenetic clock development and noninvasive age estimation in elasmobranchs.

Features of influenza virus hemagglutinin genes and their recoding possibilities

The world has already entered the stage of increasing odds for a new pandemic, which prompts to seek out for new flu vaccines, because existing vaccines demonstrate only suboptimal effectiveness. With the Covid-19 pandemic, the possibility of using mRNA vaccines has been opened up, and a prospect of finding hemagglutinin (HA) gene mRNA-based new influenza vaccines seems very attractive. As a rule, the mRNA vaccine is a product of recoding, which ensures the mRNA stability. However, the results of mRNA recoding can be ambiguous. The purpose of this report is to analyze the features of genes and proteins and to consider opportunities and limitations in their recoding. Primary structures of NA proteins and relevant genes were retrieved from Internet publicly available databases. The amino acid composition and frequency of dipeptides, nucleotide and dinucleotide compositions, %GC, translational code and compositions of neighboring di- and tricodones, distribution along primary structure for explicit and synonymous mutations were determined. H1N1 and H3N2 subtypes have both specific and general features (limitations) in their genes, differing not only in the number of protein substitutions, but also in the number and distribution of gene synonymous codons, which do not manifest in the protein primary structure, but appear, apparently, as a hidden factor, which causes the low effectiveness of classical influenza vaccines. The identification of several limitations in gene structure suggests that its any modification (in any gene) must not contradict each of the restrictions established by nature. The frequency of CpG dinucleotides in all studied strains is low, but a potential for optimizing it in H1N1 strains due to the prohibition of the quartet in the gene for arginine-encoding codons is especially limited and can be implemented through synonymous codons of other amino acids (alanine, proline, threonine or serine). Compared to the H1N1 subtype, the H3N2 subtype can be expected to have more possibilities in constructing stable NA gene mRNA.

Universal prediction of vertebrate species age at maturity

Animal age at maturity can be used as a universal and simple predictor of species extinction risk. At present, methods to estimate age at maturity are typically species-specific, limiting comparisons among species, or are infeasible due to practical constraints. To overcome this, here we develop a universal predictor of species-level age at maturity for vertebrates. We show that modelling the frequency of ‘CG’ sequences (CpG sites) in gene promoter regions yields rapid predictions of vertebrate age at maturity. Our models predict age at maturity with remarkable accuracy and generalisability, with median error rates of 30% (less than 1 year) and are robust to genome assemblies of varying quality. We generate predictions for 1912 vertebrate species for which age at maturity estimates were previously absent from public databases. The predictions can be used to help to inform management decisions for the many species for which more detailed population information is currently unavailable.

ZC3HAV1 facilitates STING activation and enhances inflammation

Stimulator of interferon genes (STING) is vital in the cytosolic DNA-sensing process and critical for initiating the innate immune response, which has important functions in host defense and contributes to the pathogenesis of inflammatory diseases. Zinc finger CCCH-type antiviral protein 1 (ZC3HAV1) specifically binds the CpG dinucleotides in the viral RNAs of multiple viruses and promotes their degradation. ZAPS (ZC3HAV1 short isoform) is a potent stimulator of retinoid acid-inducible gene I (RIG-I) signaling during the antiviral response. However, how ZC3HAV1 controls STING signaling is unclear. Here, we show that ZC3HAV1 specifically potentiates STING activation by associating with STING to promote its oligomerization and translocation from the endoplasmic reticulum (ER) to the Golgi, which facilitates activation of IRF3 and NF-κB pathway. Accordingly, Zc3hav1 deficiency protects mice against herpes simplex virus-1 (HSV-1) infection- or 5,6-dimethylxanthenone-4-acetic acid (DMXAA)-induced inflammation in a STING-dependent manner. These results indicate that ZC3HAV1 is a key regulator of STING signaling, which suggests its possible use as a therapeutic target for STING-dependent inflammation.

Causal Mediation Analysis for Integrating Exposure, Genomic, and Phenotype Data

Causal mediation analysis provides an attractive framework for integrating diverse types of exposure, genomic, and phenotype data. Recently, this field has seen a surge of interest, largely driven by the increasing need for causal mediation analyses in health and social sciences. This article aims to provide a review of recent developments in mediation analysis, encompassing mediation analysis of a single mediator and a large number of mediators, as well as mediation analysis with multiple exposures and mediators. Our review focuses on the recent advancements in statistical inference for causal mediation analysis, especially in the context of high-dimensional mediation analysis. We delve into the complexities of testing mediation effects, especially addressing the challenge of testing a large number of composite null hypotheses. Through extensive simulation studies, we compare the existing methods across a range of scenarios. We also include an analysis of data from the Normative Aging Study, which examines DNA methylation CpG sites as potential mediators of the effect of smoking status on lung function. We discuss the pros and cons of these methods and future research directions.

Methylation levels in the 5' region of the &lt;i&gt;TBX20&lt;/i&gt; gene in the ascending aorta change in opposite direction in atherosclerosis and aneurysm

We found hypomethylation of 5 CpG sites in the 5’region of TBX20 gene (7p14.2) in the tissues of atherosclerotic aortic plaque compared to dilated part of aorta in patients with ascending aortic aneurysm. Using GEO database, we found that the DNA methylation level in the chr7:35253926-35262250 region changes in opposite direction in aortic dissection and aortic atherosclerosis. The results suggest an alteration in epigenetic regulation both in aortic atherosclerosis andaortic aneurysm.

Comprehensive Analysis of Codon Usage Bias in Human Papillomavirus Type 51.

Human papillomavirus type 51 (HPV-51) is associated with various cancers, including cervical cancer. Examining the codon usage bias of the organism can offer valuable insights into its evolutionary patterns and its relationship with the host. This study comprehensively analyzed codon usage bias in HPV-51 by examining 64 complete genome sequences sourced from the NCBI GenBank database. Our analysis revealed no noteworthy preference for codon usage in HPV-51 overall. However, there was a noticeable bias towards A/T-ending codons, accompanied by GC3s below 32%. Dinucleotide frequency analysis revealed reduced frequencies for ApA, CpG, and TpC dinucleotides, while CpA and TpG dinucleotides were more frequent than others. Relative Synonymous Codon Usage analysis revealed 30 favored codons, primarily concluding with A/T nucleotides. Further analysis using Parity Rule 2, Effective Number of Codons plot, and neutrality plot indicated a balance between mutational pressure and natural selection, with natural selection being the primary force shaping codon usage bias. The Isoacceptor tRNA Pool analysis indicates that HPV-51 has a higher translation efficiency within the human cellular translational system. Moreover, the Codon Adaptation Index and Relative Codon Deoptimization Index analyses suggested a moderate adaptation of HPV-51 to human codon preferences. Our discoveries offer valuable perspectives on how HPV-51 evolves and uses genetic codes, contributing to a deeper comprehension of its endurance and disease-causing potential.

Changes in Gut Microbial Composition and DNA Methylation in Obese Patients with NAFLD After Bariatric Surgery

This study investigates the effects of bariatric surgery on non-alcoholic fatty liver disease (NAFLD) by examining the interplay between gut microbiota, epigenetics, and metabolic health. A cohort of 22 patients undergoing sleeve gastrectomy (SG) was analyzed for changes in gut microbial composition and DNA methylation profiles before and six months after surgery. Correlations between gut microbial abundance and clinical markers at baseline revealed that certain genera were associated with worse metabolic health and liver markers. Following SG, significant improvements were observed in the clinical, anthropometric, and biochemical parameters of the NAFLD patients. Although alpha-diversity indices (i.e., Chao1, Simpson, Shannon) did not show significant changes, beta-diversity analysis revealed a slight shift in microbial composition (PERMANOVA, p = 0.036). Differential abundance analysis identified significant changes in specific bacterial taxa, including an increase in beneficial Lactobacillus species such as Lactobacillus crispatus and Lactobacillus iners and a decrease in harmful taxa like Erysipelotrichia. Additionally, DNA methylation analysis revealed 609 significant differentially methylated CpG sites between the baseline values and six months post-surgery, with notable enrichment in genes related to the autophagy pathway, such as IRS4 and ATG4B. The results highlight the individualized responses to bariatric surgery and underscore the potential for personalized treatment strategies. In conclusion, integrating gut microbiota and epigenetic factors into NAFLD management could enhance treatment outcomes, suggesting that future research should explore microbiome-targeted therapies and long-term follow-ups on liver health post-surgery.

A DNA Polymerase Variant Senses the Epigenetic Marker 5-Methylcytosine by Increased Misincorporation.

Dysregulation of DNA methylation is associated with human disease, particularly cancer, and the assessment of aberrant methylation patterns holds great promise for clinical diagnostics. However, DNA polymerases do not effectively discriminate between processing 5-methylcytosine (5 mC) and unmethylated cytosine, resulting in the silencing of methylation information during amplification or sequencing. As a result, current detection methods require multi-step DNA conversion treatments or careful analysis of sequencing data to decipher individual 5 mC bases. To overcome these challenges, we propose a novel DNA polymerase-mediated 5 mC detection approach. Here, we describe the engineering of a thermostable DNA polymerase variant derived from Thermus aquaticus with altered fidelity towards 5 mC. Using a screening-based evolutionary approach, we have identified a DNA polymerase that exhibits increased misincorporation towards 5 mC during DNA synthesis. This DNA polymerase generates mutation signatures at methylated CpG sites, allowing direct detection of 5 mC by reading an increased error rate after sequencing without prior treatment of the sample DNA.

Association between maternal perinatal stress and depression and infant DNA methylation in the first year of life

Maternal stress and depression during pregnancy and the first year of the infant’s life affect a large percentage of mothers. Maternal stress and depression have been associated with adverse fetal and childhood outcomes as well as differential child DNA methylation (DNAm). However, the biological mechanisms connecting maternal stress and depression to poor health outcomes in children are still largely unknown. Here we aim to determine whether prenatal stress and depression are associated with differences in cord blood mononuclear cell DNAm (CBMC-DNAm) in newborns (n = 119) and whether postnatal stress and depression are associated with differences in peripheral blood mononuclear cell DNAm (PBMC-DNAm) in children of 12 months of age (n = 113) from the Canadian Healthy Infant Longitudinal Development (CHILD) cohort. Stress was measured using the 10-item Perceived Stress Scale (PSS) and depression was measured using the 20-item Center for Epidemiologic Studies Depression Questionnaire (CESD). Both stress and depression were measured longitudinally at 18 weeks and 36 weeks of pregnancy and six months and 12 months postpartum. We conducted epigenome-wide association studies (EWAS) using robust linear regression followed by a sensitivity analysis in which we bias-adjusted for inflation and unmeasured confounding using the bacon and cate methods. To quantify the cumulative effect of maternal stress and depression, we created composite prenatal and postnatal adversity scores. We identified a significant association between prenatal stress and differential CBMC-DNAm at 8 CpG sites and between prenatal depression and differential CBMC-DNAm at 2 CpG sites. Additionally, we identified a significant association between postnatal stress and differential PBMC-DNAm at 8 CpG sites and between postnatal depression and differential PBMC-DNAm at 11 CpG sites. Using our composite scores, we further identified 2 CpG sites significantly associated with prenatal adversity and 7 CpG sites significantly associated with postnatal adversity. Several of the associated genes, including PLAGL1, HYMAI, BRD2, and ERC2 have been implicated in adverse fetal outcomes and neuropsychiatric disorders. These data further support the finding that differential DNAm may play a role in the relationship between maternal mental health and child health.

ABCG2 Gene Expression in Non-Small Cell Lung Cancer.

Background/Objectives: ATP-binding cassette subfamily G member 2 [ABCG2/breast cancer resistance protein (BCRP)] contributes to mechanisms of multidrug resistance (MDR) and is a marker of side population (SP) cells in human cancers. The primary objective of this study was to investigate the impact of ABCG2 gene expression on the non-small cell lung cancer (NSCLC) development, course of cancer disease, and patient prognosis using publicly available data. Obtained results were supplemented with assessment of ABCG2 expression in blood of NSCLC patients. Methods: The dataset of lung cancer was analyzed utilizing the TIMER 2.0, UALCAN, TNMplot, MEXPRESS, cBioPortal, MethSurv, KM Plotter, STRING, and ShinyGO 0.80 databases. Blood samples from 50 patients were assessed using the real-time PCR method. Results: The ABCG2 gene was expressed at a low level in NSCLC, and did not correlate with clinical aggressiveness of lung cancer. Higher ABCG2 expression improved overall survival, but only in LUAD. In addition, CpG sites located on the CpG island affecting the NSCLC patient's prognosis were indicated. In the case of our own laboratory results, the study did not reveal any changes in the ABCG2 expression levels in blood collected from patients at different time points during the diagnostic-therapeutic procedure. In the in silico analysis, most ABCG2 protein interactors were associated with the development of drug resistance. Conclusions: ABCG2 appears to have a particularly significant impact on the survival of patients with lung cancer and on the effect of immunotherapy related to immune cell infiltration. Presented findings may support personalized medicine strategies based on bioinformatics findings.

Decoding the Methylation Patterns of ABC Transporters in Colorectal Cancer

Colorectal cancer (CRC) is a significant global health concern, posing a major threat to morbidity and mortality rates. The molecular mechanisms that drive CRC, particularly the DNA methylation patterns in ATP-binding cassette (ABC) genes, have attracted considerable attention because of their potential roles in CRC drug resistance, initiation, and progression. This study aimed to investigate the methylation patterns of ABC genes in CRC using a high-throughput microarray technology. Microarray methylation data from CRC and adjacent normal tissues were subjected to preprocessing, differential methylation analysis, and correlation analysis using the MethSurv tool for a detailed study of methylation patterns. The study revealed global hypomethylation of 43 ABC transporters and two pseudogenes in CRC compared to normal tissues. Receiver operating characteristic curve analysis identified 369 CpG sites as potential biomarkers for CRC diagnosis, with area under the curve values ranging from acceptable to outstanding. Survival analysis demonstrated the correlation between DNA methylation of individual CpG sites and patient survival probability in colon and rectal adenocarcinoma datasets from The Cancer Genome Atlas. The study provides insights into the epigenetic landscape of ABC genes in CRC, highlighting their potential roles in drug resistance, disease initiation, and progression. The findings offer opportunities for developing innovative therapeutic approaches and improving patient outcomes in the fight against CRC. Further research is needed to validate these results and investigate the functional implications of ABC gene methylation in CRC pathogenesis and treatment response.

Mapping the epigenomic landscape of post-traumatic stress disorder in human cortical neurons.

The study conducted a comprehensive genome-wide analysis of differential 5mC and 5hmC modifications at both CpG and non-CpG sites in postmortem orbitofrontal neurons from 25 PTSD cases and 13 healthy controls. It was observed that PTSD patients exhibit a greater number of differential 5hmC sites compared to 5mC sites. Specifically, individuals with PTSD tend to show hyper-5mC/5hmC at CpG sites, particularly within CpG islands and promoter regions, and hypo-5mC/5hmC at non-CpG sites, especially within intragenic regions. Functional enrichment analysis indicated distinct yet interconnected roles for 5mC and 5hmC in PTSD. The 5mC marks primarily regulate cell-cell adhesion processes, whereas 5hmC marks are involved in embryonic morphogenesis and cell fate commitment. By integrating published PTSD findings from central and peripheral tissues through multi-omics approaches, several biological mechanisms were prioritized, including developmental processes, HPA axis regulation, and immune responses. Based on the consistent enrichment in developmental processes, we hypothesize that if epigenetic changes occur during early developmental stages, they may increase the risk of developing PTSD following trauma exposure. Conversely, if these epigenetic changes occur in adulthood, they may influence neuronal apoptosis and survival mechanisms.

Methylomic signature of current cannabis use in two first-episode psychosis cohorts.

The rising prevalence and legalisation of cannabis worldwide have underscored the need for a comprehensive understanding of its biological impact, particularly on mental health. Epigenetic mechanisms, specifically DNA methylation, have gained increasing recognition as vital factors in the interplay between risk factors and mental health. This study aimed to explore the effects of current cannabis use and high-potency cannabis on DNA methylation in two independent cohorts of individuals experiencing first-episode psychosis (FEP) compared to control subjects. The combined sample consisted of 682 participants (188 current cannabis users and 494 never users). DNA methylation profiles were generated on blood-derived DNA samples using the Illumina DNA methylation array platform. A meta-analysis across cohorts identified one CpG site (cg11669285) in the CAVIN1 gene that showed differential methylation with current cannabis use, surpassing the array-wide significance threshold, and independent of the tobacco-related epigenetic signature. Furthermore, a CpG site localised in the MCU gene (cg11669285) achieved array-wide significance in an analysis of the effect of high-potency (THC = > 10%) current cannabis use. Pathway and regional analyses identified cannabis-related epigenetic variation proximal to genes linked to immune and mitochondrial function, both of which are known to be influenced by cannabinoids. Interestingly, a model including an interaction term between cannabis use and FEP status identified two sites that were significantly associated with current cannabis use with a nominally significant interaction suggesting that FEP status might moderate how cannabis use affects DNA methylation. Overall, these findings contribute to our understanding of the epigenetic impact of current cannabis use and highlight potential molecular pathways affected by cannabis exposure.

Maternal e-cigarette exposure alters DNA methylome, site-specific CpG and CH methylation, and transcriptomic signatures in the neonatal brain

Maternal use of e-cigarette (e-cig) aerosols poses significant risks to fetal brain development, potentially increasing susceptibility to neurodevelopmental disorders in later life. However, the underlying mechanisms remain incompletely understood. This study aimed to understand the effects of fetal e-cig exposure on DNA methylome and transcriptomic changes in the neonatal brain. Pregnant rats were exposed to e-cig aerosols, and neonatal brains (5 males and 5 females/group) from both control and e-cig-exposed groups were used for experimental analysis. Results indicated that prenatal e-cig exposure altered site-specific DNA methylation patterns at both CpG and CH (non-CpG) sites, predominantly in intergenic and intronic regions, with sex dimorphism in methylation and gene expression changes. Gene ontology analysis revealed that e-cig exposure not only affected neuron projection development and axonogenesis but also altered pathways related to neurodegeneration and long-term depression. These findings provide novel insights into the dynamic changes of CpG and CH methylation induced by e-cig exposure, underscoring the susceptibility of the developing brain to maternal e-cig exposure and its potential implications for developmental disorders and neurodegenerative diseases later in life.

Developing a DNA Methylation Signature to Differentiate High-Grade Serous Ovarian Carcinomas from Benign Ovarian Tumors.

Epithelial ovarian cancer (EOC) represents a significant health challenge, with high-grade serous ovarian cancer (HGSOC) being the most common subtype. Early detection is hindered by nonspecific symptoms, leading to late-stage diagnoses and poor survival rates. Biomarkers are crucial for early diagnosis and personalized treatment OBJECTIVE: Our goal was to develop a robust statistical procedure to identify a set of differentially methylated probes (DMPs) that would allow differentiation between HGSOC and benign ovarian tumors. Using the Infinium EPIC Methylation array, we analyzed the methylation profiles of 48 ovarian samples diagnosed with HGSOC, borderline ovarian tumors, or benign ovarian disease. Through a multi-step statistical procedure combining univariate and multivariate logistic regression models, we aimed to identify CpG sites of interest. We discovered 21 DMPs and developed a predictive model validated in two independent cohorts. Our model, using a distance-to-centroid approach, accurately distinguished between benign and malignant disease. This model can potentially be used in other types of sample material. Moreover, the strategy of the model development and validation can also be used in other disease contexts for diagnostic purposes.

Effects of Differentially Methylated CpG Sites in Enhancer and Promoter Regions on the Chromatin Structures of Target LncRNAs in Breast Cancer.

Aberrant DNA methylation plays a crucial role in breast cancer progression by regulating gene expression. However, the regulatory pattern of DNA methylation in long noncoding RNAs (lncRNAs) for breast cancer remains unclear. In this study, we integrated gene expression, DNA methylation, and clinical data from breast cancer patients included in The Cancer Genome Atlas (TCGA) database. We examined DNA methylation distribution across various lncRNA categories, revealing distinct methylation characteristics. Through genome-wide correlation analysis, we identified the CpG sites located in lncRNAs and the distally associated CpG sites of lncRNAs. Functional genome enrichment analysis, conducted through the integration of ENCODE ChIP-seq data, revealed that differentially methylated CpG sites (DMCs) in lncRNAs were mostly located in promoter regions, while distally associated DMCs primarily acted on enhancer regions. By integrating Hi-C data, we found that DMCs in enhancer and promoter regions were closely associated with the changes in three-dimensional chromatin structures by affecting the formation of enhancer-promoter loops. Furthermore, through Cox regression analysis and three machine learning models, we identified 11 key methylation-driven lncRNAs (DIO3OS, ELOVL2-AS1, MIAT, LINC00536, C9orf163, AC105398.1, LINC02178, MILIP, HID1-AS1, KCNH1-IT1, and TMEM220-AS1) that were associated with the survival of breast cancer patients and constructed a prognostic risk scoring model, which demonstrated strong prognostic performance. These findings enhance our understanding of DNA methylation's role in lncRNA regulation in breast cancer and provide potential biomarkers for diagnosis.