Assessment Of DNA Methylation Research Articles

Assessing DNA Methylation of ATG 5 and MAP1LC3Av1 Gene In Oral Squamous Cell Carcinoma And Oral Leukoplakia- A Cross Sectional Study

BackgroundThe progression and pathogenesis of oral cancer is greatly impacted by epigenetic modifications, such as DNA methylation. Autophagy, is an adaptive mechanism used to maintain the survival and integrity of cells. Oral squamous cell carcinoma is linked to a number of autophagy indicators, although it is yet unknown if DNA methylation of autophagy-related genes promotes the development of oral leukoplakia (OL), oral squamous cell carcinoma (OSCC). AimOur study was aimed to assess, compare and evaluate the DNA methylation of ATG5 and MAP1LC3Av1 genes in oral leukoplakia, oral squamous cell carcinoma. Materials and methodsThis cross-sectional study was designed with sample size of 48 tissues which was clinically and histopathologically diagnosed as OL, OSCC and normal tissue. The samples were divided into three groups (Group A, Group B, and Group C; (n = 16 each). Following histopathological confirmation, the tissue was stored in the RNA reagent, then subjected to DNA extraction, methylation-sensitive polymerase chain reaction (MS-PCR). DNA methylation of the ATG5 and MAP1LC3Av1 genes were assessed. ResultsShapiro-Wilk and Kolmogorov-Smirnov tests showed that the values were normally distributed. Both the ATG5 and MAP1LC3Av1 genes were methylated in OSCC, OL tissues compared to normal tissues. A statistically significant results was seen among the three study groups. ConclusionA significant difference was noted in the hypermethylation status of the promoter regions of the ATG5 and MAP1LC3Av1 genes. This provides some insight into their crucial role in the development of tumors. Future research with larger sample is needed to assess its potential clinical implications in oral carcinoma.

Evaluation of DNAmAge in paired fresh, frozen, and formalin-fixed paraffin-embedded heart tissues.

The continued development in methylome analysis has enabled a more precise assessment of DNA methylation, but treatment of target tissue prior to analysis may affect DNA analysis. Prediction of age based on methylation levels in the genome (DNAmAge) has gained much interest in disease predisposition (biological age estimation), but also in chronological donor age estimation in crime case samples. Various epigenetic clocks were designed to predict the age. However, it remains unknown how the storage of the tissues affects the DNAmAge estimation. In this study, we investigated the storage method impact of DNAmAge by the comparing the DNAmAge of the two commonly used storage methods, freezing and formalin-fixation and paraffin-embedding (FFPE) to DNAmAge of fresh tissue. This was carried out by comparing paired heart tissue samples of fresh tissue, samples stored by freezing and FFPE to chronological age and whole blood samples from the same individuals. Illumina EPIC beadchip array was used for methylation analysis and the DNAmAge was evaluated with the following epigenetic clocks: Horvath, Hannum, Levine, Horvath skin+blood clock (Horvath2), PedBE, Wu, BLUP, EN, and TL. We observed differences in DNAmAge among the storage conditions. FFPE samples showed a lower DNAmAge compared to that of frozen and fresh samples. Additionally, the DNAmAge of the heart tissue was lower than that of the whole blood and the chronological age. This highlights caution when evaluating DNAmAge for FFPE samples as the results were underestimated compared with fresh and frozen tissue samples. Furthermore, the study also emphasizes the need for a DNAmAge model based on heart tissue samples for an accurate age estimation.

Uncovering DNA methylation landscapes to decipher evolutionary footprints of phenotypic diversity in chickpea.

Genetic diversity and environmental factors are long believed to be the dominant contributors to phenotypic diversity in crop plants. However, it has been recently established that, besides genetic variation, epigenetic variation, especially variation in DNA methylation, plays a significant role in determining phenotypic diversity in crop plants. Therefore, assessing DNA methylation diversity in crop plants becomes vital, especially in the case of crops like chickpea, which has a narrow genetic base. Thus, in the present study, we employed whole-genome bisulfite sequencing to assess DNA methylation diversity in wild and cultivated (desi and kabuli) chickpea. This revealed extensive DNA methylation diversity in both wild and cultivated chickpea. Interestingly, the methylation diversity was found to be significantly higher than genetic diversity, suggesting its potential role in providing vital phenotypic diversity for the evolution and domestication of the Cicer gene pool. The phylogeny based on DNA methylation variation also indicates a potential complementary role of DNA methylation variation in addition to DNA sequence variation in shaping chickpea evolution. Besides, the study also identified diverse epi-alleles of many previously known genes of agronomic importance. The Cicer MethVarMap database developed in this study enables researchers to readily visualize methylation variation within the genes and genomic regions of their interest (http://223.31.159.7/cicer/public/). Therefore, epigenetic variation like DNA methylation variation can potentially explain the paradox of high phenotypic diversity despite the narrow genetic base in chickpea and can potentially be employed for crop improvement.

Exploring the epigenetic profile of ID4 in breast cancer: bioinformatic insights into methylation patterns and chromatin accessibility dynamics.

Inhibitor of differentiation 4 (ID4) is a dominant-negative regulator of basic helix-loop-helix (bHLH) transcription factors. The expression of ID4 is dysregulated in various breast cancer subtypes, indicating a potential role for ID4 in subtype-specific breast cancer development. This study aims to elucidate the epigenetic regulation of ID4 within breast cancer subtypes, with a particular focus on DNA methylation and chromatin accessibility. Bioinformatic analyses were conducted to assess DNA methylation and chromatin accessibility in ID4 regulatory regions across breast cancer subtypes. Gene Set Enrichment Analysis (GSEA) was conducted to identify related gene sets. Transcription factor binding within ID4 enhancer and promoter regions was explored. In vitro experiments involved ER+ breast cancer cell lines treated with estradiol (E2) and Tamoxifen. Distinct epigenetic profiles of ID4 were observed, revealing increased methylation and reduced chromatin accessibility in luminal subtypes compared to the basal subtype. Gene Set Enrichment Analysis (GSEA) implicated estrogen-related pathways, suggesting a potential link between estrogen signaling and the regulation of ID4 expression. Transcription factor analysis identified ER and FOXA1 as regulators of ID4 enhancer regions. In vitro experiments confirmed the role of ER, demonstrating reduced ID4 expression and increased methylation with estradiol treatment. Conversely, Tamoxifen treatment increased ID4 expression, indicating the potential involvement of ER signaling through ERα in the epigenetic regulation of ID4 in breast cancer cells. This study shows the intricate epigenetic regulation of ID4 in breast cancer, highlighting subtype-specific differences in DNA methylation and chromatin accessibility.

Age Prediction Using DNA Methylation Heterogeneity Metrics.

Dynamic changes in genomic DNA methylation patterns govern the epigenetic developmental programs and accompany the organism's aging. Epigenetic clock (eAge) algorithms utilize DNA methylation to estimate the age and risk factors for diseases as well as analyze the impact of various interventions. High-throughput bisulfite sequencing methods, such as reduced-representation bisulfite sequencing (RRBS) or whole genome bisulfite sequencing (WGBS), provide an opportunity to identify the genomic regions of disordered or heterogeneous DNA methylation, which might be associated with cell-type heterogeneity, DNA methylation erosion, and allele-specific methylation. We systematically evaluated the applicability of five scores assessing the variability of methylation patterns by evaluating within-sample heterogeneity (WSH) to construct human blood epigenetic clock models using RRBS data. The best performance was demonstrated by the model based on a metric designed to assess DNA methylation erosion with an MAE of 3.686 years. We also trained a prediction model that uses the average methylation level over genomic regions. Although this region-based model was relatively more efficient than the WSH-based model, the latter required the analysis of just a few short genomic regions and, therefore, could be a useful tool to design a reduced epigenetic clock that is analyzed by targeted next-generation sequencing.

Green space exposure and blood DNA methylation at birth and in childhood – A multi-cohort study

Green space exposure has been associated with improved mental, physical and general health. However, the underlying biological mechanisms remain largely unknown. The aim of this study was to investigate the association between green space exposure and cord and child blood DNA methylation.Data from eight European birth cohorts with a total of 2,988 newborns and 1,849 children were used. Two indicators of residential green space exposure were assessed: (i) surrounding greenness (satellite-based Normalized Difference Vegetation Index (NDVI) in buffers of 100 m and 300 m) and (ii) proximity to green space (having a green space ≥ 5,000 m2 within a distance of 300 m). For these indicators we assessed two exposure windows: (i) pregnancy, and (ii) the period from pregnancy to child blood DNA methylation assessment, named as cumulative exposure. DNA methylation was measured with the Illumina 450K or EPIC arrays. To identify differentially methylated positions (DMPs) we fitted robust linear regression models between pregnancy green space exposure and cord blood DNA methylation and between cumulative green space exposure and child blood DNA methylation. Two sensitivity analyses were conducted: (i) without adjusting for cellular composition, and (ii) adjusting for air pollution. Cohort results were combined through fixed-effect inverse variance weighted meta-analyses. Differentially methylated regions (DMRs) were identified from meta-analysed results using the Enmix-combp and DMRcate methods.There was no statistical evidence of pregnancy or cumulative exposures associating with any DMP (False Discovery Rate, FDR, p-value < 0.05). However, surrounding greenness exposure was inversely associated with four DMRs (three in cord blood and one in child blood) annotated to ADAMTS2, KCNQ1DN, SLC6A12 and SDK1 genes. Results did not change substantially in the sensitivity analyses.Overall, we found little evidence of the association between green space exposure and blood DNA methylation. Although we identified associations between surrounding greenness exposure with four DMRs, these findings require replication.

Abstract LB193: Enhanced single cell DNA methylation analysis using combinatorial indexing

Abstract The epigenetic landscape of the human brain undergoes a plethora of changes during malignant transformation. In recent years, DNA methylation-based epigenetic modifications have been widely studied using traditional techniques like bisulfite sequencing and enzymatic methyl sequencing (EM-seq). However, these methods analyze bulk cell populations and lack the granularity of single-cell analysis. Although advances in single-cell analysis have revolutionized our understanding of cellular heterogeneity and functional diversity within complex biological systems, they are still costly, low throughput, and laborious. To address these challenges, ScaleBio has pioneered combinatorial indexing technology, enabling a significant increase in cell throughput. This method utilizes the cell itself as a compartment to perform 2-3 rounds of sequential barcoding in a plate-based workflow, eliminating the need for complex instrumentation. This technology has been successfully adapted to assess DNA methylation at the single-cell level offering a robust, affordable, high-throughput protocol that enhances yield, diversity, and coverage. In this study we used ScaleBio's single-cell methylation kit to investigate DNA methylation patterns during oncogenesis using cancer cells with widespread DNA methylation changes, such as human isocitrate dehydrogenase (IDH) mutant glioma cells at the single-cell level. The IDH gene family, comprising of IDH1, IDH2, and IDH3, encodes enzymes involved in the tricarboxylic acid (TCA) cycle. IDH1/2 mutations are present in over 80% of low-grade gliomas while IDH-mutant gliomas constitute about 1/5th of all adult diffuse gliomas, thus making them one of the most common brain tumor subtypes. As such, IDH mutations have emerged as attractive therapeutic targets for glioma treatment. By uncovering DNA methylation patterns at the single cell level, we provide here an epigenetic map to better understand this complex disease and better inform clinical discoveries. We achieved high cell recovery and robust cytosine coverage throughout our analysis of single cell methylomes isolated from human glioma tumor tissue. Using this data we generated a ranked list of the top hypo- and hypermethylated genomic regions and identified cell type specific clusters seen in different pathological states by looking at Differentially Methylated Regions (DMR) uncovering unique single-cell methylation profiles that may be obscured by bulk or pseudo-bulk analysis. These data show that the ScaleBio single-cell methylation workflow offers increased sensitivity, specificity, and accuracy in identifying DNA methylation sites when compared to other techniques while offering a comprehensive view of methylomes and providing insights into cellular heterogeneity and trajectories. Citation Format: Sanika Khare, Dominic Skinner, Maggie Nakamoto, Hosu Sin, Ashley Woodfin, Eric Pu, Lin Lin, Jason Koth, Beth Walczak. Enhanced single cell DNA methylation analysis using combinatorial indexing [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(7_Suppl):Abstract nr LB193.

Optimizing Droplet Digital PCR Assay for Precise Assessment of MEIS1 Gene Promoter Methylation

Abstract DNA methylation is characterized as a gene regulatory mechanism that involves the methylation of the 5-carbon (C5) position of cytosine, resulting in the formation of 5-methylcytosine. The analysis of aberrantly methylated cytosine-phosphate-guanine (CpG) dinucleotides, primarily in the promoter regions of tumor suppressor genes, can serve as promising prognostic and predictive markers of cancer development. Meis homeobox 1 (MEIS1) gene, crucial for cell growth and differentiation, exhibits dysregulation linked to various cancer types, acting as both a positive and negative regulator. The selection of an appropriate method for the evaluation of gene promoter methylation status is important for clinical implementation without biases regarding false positive and false negative outcomes. The study focuses on the optimization of a novel droplet digital PCR (ddPCR) assay for identifying the methylation status of MEIS1. Compared to traditional methods, ddPCR offers an increased sensitivity and specificity, presenting a promising tool for precise DNA methylation assessment with potential implications for cancer diagnostics and prognostics.

Building Minimized Epigenetic Clock by iPlex MassARRAY Platform.

Epigenetic clocks are valuable tools for estimating both chronological and biological age by assessing DNA methylation levels at specific CpG dinucleotides. While conventional epigenetic clocks rely on genome-wide methylation data, targeted approaches offer a more efficient alternative. In this study, we explored the feasibility of constructing a minimized epigenetic clock utilizing data acquired through the iPlex MassARRAY technology. The study enrolled a cohort of relatively healthy individuals, and their methylation levels of eight specific CpG dinucleotides in genes SLC12A5, LDB2, FIGN, ACSS3, FHL2, and EPHX3 were evaluated using the iPlex MassARRAY system and the Illumina EPIC array. The methylation level of five studied CpG sites demonstrated significant correlations with chronological age and an acceptable convergence of data obtained by the iPlex MassARRAY and Illumina EPIC array. At the same time, the methylation level of three CpG sites showed a weak relationship with age and exhibited a low concordance between the data obtained from the two technologies. The construction of the epigenetic clock involved the utilization of different machine-learning models, including linear models, deep neural networks (DNN), and gradient-boosted decision trees (GBDT). The results obtained from these models were compared with each other and with the outcomes generated by other well-established epigenetic clocks. In our study, the TabNet architecture (deep tabular data learning architecture) exhibited the best performance (best MAE = 5.99). Although our minimized epigenetic clock yielded slightly higher age prediction errors compared to other epigenetic clocks, it still represents a viable alternative to the genome-wide epigenotyping array.

Abstract 7030: Reference materials for analysis of DNA methylation in cell-free circulating tumor DNA

Abstract Aberrant DNA methylation is associated with many cancers including breast, liver, bone, and colon and has been identified as a biomarker for early cancer screening. Liquid biopsies are beginning to screen for DNA methylation in cancer-derived DNA, but accurate assessment of methylation is not trivial, and methods like bisulfite sequencing can result in biased data. Reference materials for establishing the analytical validity of measurements of CpG methylation are not widely available. In order to prepare such reference materials, genomic DNA (gDNA) was extracted from the well characterized human reference cell line GM24385 and fragmented to a circulating tumor DNA (ctDNA)-like size distribution. This DNA was processed further to prepare CpG-methylated and unmethylated versions. The size distribution was determined by using the Bioanalyzer High Sensitivity DNA Kit (Agilent, Santa Clara, CA). Methylation status in the reference materials was confirmed by both digital PCR (dPCR) and NGS based methods. A digital PCR method was developed to analyze heterozygous single nucleotide polymorphisms (SNPs) using the Bio-Rad QX200™ Droplet Digital PCR (ddPCR) System. To determine methylation levels by NGS, the NEBNext™ Enzymatic Methyl-seq Kit was used (EM-seq). Paired-end sequencing of the libraries was performed on a NextSeq™ 2000 (Illumina, San Diego, CA). Data alignment to hg19 was done with the bwa-meth (Pedersen, BS., et al.) aligner, and assessment of methylation in the aligned data was done with MethylDackel (Ryan, D.). Each reference material had an average peak size of ~160 bp in length, similar to patient cfDNA. By dPCR, the unmethylated reference material had an average of 0.73% DNA methylation, while the methylated reference material had an average of 100.10% DNA methylation. Values can be above 100% by dPCR due to unequal representation of both alleles. By NGS, the unmethylated reference material had an average of 0.93 % CpG methylation, which was similar to the background of 1.13 % and 1.31 % for CHG and CHH methylation, respectively. The methylated reference material had an average of 93.95 % CpG methylation, with a background of 0.69 % and 0.74 % for CHG and CHH methylation, respectively. Because EM-seq relies on enzymatic protection and conversion steps, it may be that these reactions did not allow for full protection and full conversion, which led to values above 0 % for unmethylated and below 100 % for methylated materials. We have developed reference materials for the assessment of DNA methylation in ctDNA. One unmethylated and one methylated reference material was created. These reference materials can be mixed together to the level of methylation required to help aid in assay design, optimization, and validation. Citation Format: Alysha Higgs, Angelique Ryan, Jayanthi Ramprakash, Dana Ruminski Lowe, Yves Konigshofer, Catherine Huang, Andrew Anfora, Russell Garlick, Bharathi Anekella. Reference materials for analysis of DNA methylation in cell-free circulating tumor DNA [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 7030.

(060) Epigenetic and Gene Expression Profiles in Non-Plaque Tissues from Men with Peyronie’s Disease

Abstract Introduction Peyronie’s Disease (PD) can significantly impact sexual function. A hereditary predisposition to PD suggests that genetic variants may exist, and gene expression may modulate the penetrance of the disease. Identification of changes in epigenetic and gene expression profiles will facilitate a deeper understanding of the disease and provide insight for more targeted therapies. Objective Our objective is to determine if PD is correlated with epigenetic variations and/or gene expression changes, as indicated by DNA methylation assessment and RNA sequencing. Methods Penile tunica albuginea samples (not from fibrotic plaques) were obtained from men with PD undergoing penile prosthesis placement. Control samples were collected from men with erectile dysfunction (ED) without PD undergoing penile prosthesis placement. DNA methylation analyses were performed on homogenized penile tissue samples via an Illumina Human MethylationEPIC BeadChip v2 array. Using the minfi package in R, beta values were produced for all 936,990 CpG sites for each sample and SWAN normalization was applied. Differentially methylated regions (DMR) were found via USEQ with a threshold Wilcoxon FDR score of 40. Gene expression levels were examined in PD and ED samples via RNA-sequencing. Gene expression data was compared against epigenetic data to determine if any epigenetics changes identified affected gene expression profiles. Results A total of 24 tissue samples were collected: 12 ED and 12 PD. USEQ yielded 36 total DMRs with an FDR score of 40 or greater (p-value&amp;lt;0.0001). Of these 36 DMRs, a Stanford GREAT analysis revealed 60 total gene-region associations and five implicated biological processes: anterior/posterior pattern specification, chordate embryonic development, embryo development (ending in birth or egg hatching), somitogenesis, and pattern specification process. Furthermore, differential gene expression analysis identified 76 genes with significant expression changes between PD and ED groups, of which 17 genes were upregulated while 59 were downregulated. Long noncoding RNAs and the keratocan gene showed notable expression differences between PD and ED groups. GO enrichment analysis revealed significant terms related to DNA binding and protein binding. None of the differentially regulated genes overlapped with identified DMRs. Conclusions This study identified distinct gene expression and DNA methylation patterns between PD and ED groups, despite PD samples not being taken from plaque regions, suggesting that more systemic changes may be present. Upregulated genes in PD included long noncoding RNAs and the keratocan gene, suggesting their involvement in disease pathogenesis. Long noncoding RNA overexpression may serve a regulatory function in gene expression or cell processes while overexpression of the keratocan gene may promote collagen accumulation and remodeling, leading to fibrous plaque formation. Likewise, DMRs and their region-gene associations suggest a role in early embryonic development for pathogenesis. Although RNA-seq did not indicate any significant differentially expressed genes that matched with gene-region associations correlated with DMRs, the significance and quantity of DMRs between ED and PD sample groups is indicative of affected biological processes that manifest in distinct pathophysiologies. Further research is needed to investigate if differentially regulated genes exist in DMRs that exhibited changes but did not meet the criteria threshold for inclusion here. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Contraline, Techfields Inc, Alto Neurosciences, Curebase.

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

ABSTRACT 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.

Strengths and limitations of reduced representation bisulfite sequencing (RRBS) in the perspective of DNA methylation analysis in fish: a case-study on rainbow trout spermatozoa.

DNA methylation in CpG dinucleotides is an important epigenetic mark in fish spermatozoa since it has been shown that some sperm methylome features are transmitted to the offspring. Reduced representation bisulfite sequencing (RRBS) is one genome-scale methods developed to assess DNA methylation at CpG sites. It allows the sequencing of a reduced fraction of the genome expected to be enriched in CpGs. The aim of this study is to characterize the extent of the CpG sites that can be identified in the RRBS-reduced sequenced fraction of rainbow trout spermatozoa, in order to evaluate the potential of RRBS for sperm DNA methylation studies. We observed that RRBS did provide a reduced amount of genomic data, the sum of the CpGs analyzed on 12 males spanning 9% of the total genomic CpGs. CpGs were only slightly enriched in the RRBS data (×1.7 times the sequenced nucleotides), the possible causes being linked to trout genome structure and sequenced fragments size. All genomic functional features were represented in our CpG dataset, with a noticeable enrichment in exons but, strikingly, not in promoters. The number of CpGs shared between biological replicates was low, but this proportion reached workable values from six biological replicates (46% of the analyzed cytosines) on. The choices that are to be made regarding fragment size selection and the options during bioinformatic data processing are discussed. In all, RRBS is a relevant first-approach method to scan the CpG DNA methylation status of spermatozoa along rainbow trout genome, although in a very reduced pattern among biological replicates.

Epigenetic Effects of Resveratrol on Oncogenic Signaling in Breast Cancer.

The crosstalk between oncogenic signaling pathways plays a crucial role in driving cancer development. We previously demonstrated that dietary polyphenols, specifically resveratrol (RSV) and other stilbenoids, epigenetically target oncogenes for silencing via DNA hypermethylation in breast cancer. In the present study, we identify signal transduction regulators among RSV-hypermethylated targets and investigate the functional role of RSV-mediated DNA hypermethylation in the regulation of Hedgehog and Wnt signaling. Non-invasive ER-positive MCF-7 and highly invasive triple-negative MCF10CA1a human breast cancer cell lines were used as experimental models. Upon 9-day exposure to 15 µM RSV, pyrosequencing and qRT-PCR were performed to assess DNA methylation and expression of GLI2 and WNT4, which are upstream regulators of the Hedgehog and Wnt pathways, respectively. Our results showed that RSV led to a DNA methylation increase within GLI2 and WNT4 enhancers, which was accompanied by decreases in gene expression. Consistently, we observed the downregulation of genes downstream of the Hedgehog and Wnt signaling, including common targets shared by both pathways, CCND1 and CYR61. Further analysis using chromatin immunoprecipitation identified increased H3K27 trimethylation and decreased H3K9 and H3K27 acetylation, along with abolishing OCT1 transcription factor binding. Those changes indicate a transcriptionally silent chromatin state at GLI2 and WNT4 enhancers. The inhibition of the Wnt signal transduction was confirmed using a phospho-antibody array that demonstrated suppression of positive and stimulation of negative Wnt regulators. In conclusion, our results provide scientific evidence for dietary polyphenols as epigenetics-modulating agents that act to re-methylate and silence oncogenes, reducing the oncogenic signal transduction. Targeting such an action could be an effective strategy in breast cancer prevention and/or adjuvant therapy.

Novel MEI1 mutations cause chromosomal and DNA methylation abnormalities leading to embryonicarrest and implantation failure.

This study presents a case of a female infertile patient suffering from embryonic arrest and recurrent implantation failure. The primary objective was to assess the copy number variations (CNVs) and DNA methylation of her embryos. Genetic diagnosis was conducted by whole-exome sequencing and validated through Sanger sequencing. CNV evaluation of two cleavage stage embryos was performed using whole-genome sequencing, while DNA methylation and CNV assessment of two blastocysts were carried out using whole-genome bisulfite sequencing. We identified two novel pathogenic frameshift variants in the MEI1 gene (NM_152513.3, c.3002delC, c.2264_2268 + 11delGTGAGGTATGGACCAC) in the proband. These two variants were inherited from her heterozygous parents, consistent with autosomal recessive genetic transmission. Notably, two Day 3 embryos and two Day 6 blastocysts were all aneuploid, with numerous monosomy and trisomy events. Moreover, global methylation levels greatly deviated from the optimized window of 0.25-0.27, measuring 0.344 and 0.168 for the respective blastocysts. This study expands the mutational spectrum of MEI1 and is the first to document both aneuploidy and abnormal methylation levels in embryos from a MEI1-affected female patient presenting with embryonic arrest. Given that females affected by MEI1 mutations might experience either embryonic arrest or monospermic androgenetic hydatidiform moles due to the extrusion of all maternal chromosomes, the genetic makeup of the arrested embryos of MEI1 patients provides important clues for understanding the different disease mechanisms of the two phenotypes.

Reduced representative methylome profiling of cell-free DNA for breast cancer detection.

Whole-genome methylation sequencing of cfDNA is not cost-effective for tumor detection. Here, we introduce reduced representative methylome profiling (RRMP), which employs restriction enzyme for depletion of AT-rich sequence to achieve enrichment and deep sequencing of CG-rich sequences. We first verified the ability of RRMP to enrich CG-rich sequences using tumor cell genomic DNA and analyzed differential methylation regions between tumor cells and normal whole blood cells. We then analyzed cfDNA from 29 breast cancer patients and 27 non-breast cancer individuals to detect breast cancer by building machine learning models. RRMP captured 81.9% CpG islands and 75.2% gene promoters when sequenced to 10 billion base pairs, with an enrichment efficiency being comparable to RRBS. RRMP allowed us to assess DNA methylation changes between tumor cells and whole blood cells. Applying our approach to cfDNA from 29 breast cancer patients and 27 non-breast cancer individuals, we developed machine learning models that could discriminate between breast cancer and non-breast cancer controls (AUC = 0.85), suggesting possibilities for truly non-invasive cancer detection. We developed a new method to achieve reduced representative methylome profiling of cell-free DNA for tumor detection.

The impact of parental and developmental stress on DNA methylation in the avian hypothalamic-pituitary-adrenal axis.

The hypothalamic-pituitary-adrenal (HPA) axis coordinates an organism's response to environmental stress. The responsiveness and sensitivity of an offspring's stress response may be shaped not only by stressors encountered in their early post-natal environment but also by stressors in their parent's environment. Yet, few studies have considered how stressors encountered in both of these early life environments may function together to impact the developing HPA axis. Here, we manipulated stressors in the parental and post-natal environments in a population of house sparrows (Passer domesticus) to assess their impact on changes in DNA methylation (and corresponding gene expression) in a suite of genes within the HPA axis. We found that nestlings that experienced early life stress across both life-history periods had higher DNA methylation in a critical HPA axis gene, the glucocorticoid receptor (NR3C1). In addition, we found that the life-history stage when stress was encountered impacted some genes (HSD11B1, NR3C1 and NR3C2) differently. We also found evidence for the mitigation of parental stress by post-natal stress (in HSD11B1 and NR3C2). Finally, by assessing DNA methylation in both the brain and blood, we were able to evaluate cross-tissue patterns. While some differentially methylated regions were tissue-specific, we found cross-tissue changes in NR3C2 and NR3C1, suggesting that blood is a suitable tissue for assessing DNA methylation as a biomarker of early life stress. Our results provide a crucial first step in understanding the mechanisms by which early life stress in different life-history periods contributes to changes in the epigenome of the HPA axis.

(059) Epigenetic Profiles of Men with Peyronie’s Disease

Abstract Introduction Peyronie’s Disease (PD) can significantly impact sexual function. A hereditary predisposition to PD suggests that genetic variants may exist, and gene expression may modulate the penetrance of the disease. Identification of changes in epigenetic or gene expression profiles would facilitate a deeper understanding of the disease and provide insight for more targeted therapies. Objective Our objective is to determine if predisposition to PD is correlated with epigenetic variations and/or gene expression changes, as indicated by DNA methylation assessment and RNA sequencing. Methods Penile tunica albuginea samples were obtained from men with PD undergoing penile prosthesis placement. Penile sample from these men were not from fibrotic plaques. Control samples were collected from men with erectile dysfunction (ED) without PD undergoing penile prosthesis placement. DNA methylation analyses were performed on homogenized penile tissue samples via an Illumina Human MethylationEPIC BeadChip v2 array. Using the minfi package in R, beta values were produced for all 936,990 CpG sites for each sample and SWAN normalization was applied. Differentially methylated regions (DMR) were found via USEQ with a threshold Wilcoxon FDR score of 40. Gene expression levels were examined in PD and ED samples via RNA-sequencing. Gene expression data was compared against epigenetic data to determine if any epigenetics changes identified affected gene expression profiles. Results A total of 24 tissue samples were collected: 12 ED and 12 PD. USEQ yielded 36 total DMRs with a FDR score of 40 or greater (p-value&amp;lt;0.0001). Of these 36 DMRs, a Stanford GREAT analysis revealed 60 total gene-region associations and five implicated biological processes: anterior/posterior pattern specification, chordate embryonic development, embryo development (ending in birth or egg hatching), somitogenesis, and pattern specification process. Furthermore, differential gene expression analysis identified 76 genes with significant expression changes between PD and ED groups, of which 17 genes were upregulated while 59 were downregulated. Long noncoding RNAs and the keratocan gene showed notable expression differences between PD and ED groups. GO enrichment analysis revealed significant terms related to DNA binding and protein binding. None of the differentially regulated genes overlapped with identified DMRs. Conclusions This study identified distinct gene expression and DNA methylation patterns between PD and ED groups, despite PD samples not being taken from plaque regions. Upregulated genes in PD included long noncoding RNAs and the keratocan gene, suggesting their involvement in disease pathogenesis. Long noncoding RNA overexpression may serve a regulatory function in gene expression or cell processes while overexpression of the keratocan gene may promote collagen accumulation and remodeling, leading to fibrous plaque formation in the affected area. Likewise, DMRs and their region-gene associations suggest a role in early embryonic development for pathogenesis. Although RNA-seq did not indicate any significant differentially expressed genes that matched with gene-region associations correlated with DMRs, the significance and quantity of DMRs between ED and PD sample groups is indicative of affected biological processes that manifest in distinct pathophysiologies. Further research is needed to investigate if differentially regulated genes exist in DMRs that exhibited changes but did not meet the criteria threshold for inclusion here. Disclosure Any of the authors act as a consultant, employee or shareholder of an industry for: Paterna bio, Firmtech, Turtle health, Maximus, Carrot, Contraline, endo pharmaceuticals, inherent biosciences, techfields inc, macro trials, alto neurosciences, curebase, vivify medical.

Maternally derived avian corticosterone affects offspring genome-wide DNA methylation in a passerine species.

Avian embryos develop in an egg composition which reflects both maternal condition and the recent environment of their mother. In birds, yolk corticosterone (CORT) influences development by impacting pre- and postnatal growth, as well as nestling stress responses and development. One possible mechanism through which maternal CORT may affect offspring development is via changes to offspring DNA methylation. We sought to investigate this, for the first time in birds, by quantifying the impact of manipulations to maternal CORT on offspring DNA methylation. We non-invasively manipulated plasma CORT concentrations of egg-laying female zebra finches (Taeniopygia castanotis) with an acute dose of CORT administered around the time of ovulation and collected their eggs. We then assessed DNA methylation in the resulting embryonic tissue and in their associated vitelline membrane blood vessels, during early development (5 days after lay), using two established methods - liquid chromatography-mass spectrometry (LC-MS) and methylation-sensitive amplification fragment length polymorphism (MS-AFLP). LC-MS analysis showed that global DNA methylation was lower in embryos from CORT-treated mothers, compared to control embryos. In contrast, blood vessel DNA from eggs from CORT-treated mothers showed global methylation increases, compared to control samples. There was a higher proportion of global DNA methylation in the embryonic DNA of second clutches, compared to first clutches. Locus-specific analyses using MS-AFLP did not reveal a treatment effect. Our results indicate that an acute elevation of maternal CORT around ovulation impacts DNA methylation patterns in their offspring. This could provide a mechanistic understanding of how a mother's experience can affect her offspring's phenotype.

MethScore as a new comprehensive DNA methylation-based value refining the prognosis in acute myeloid leukemia.

Changes in DNA methylation are common events in the pathogenesis of acute myeloid leukemia (AML) and have been repeatedly reported as associated with prognosis. However, studies integrating these numerous and potentially prognostically relevant DNA methylation changes are lacking. Therefore, we aimed for an overall evaluation of these epigenetic aberrations to provide a comprehensive NGS-based approach of DNA methylation assessment for AML prognostication. We designed a sequencing panel targeting 239 regions (approx. 573kb of total size) described in the literature as having a prognostic impact or being associated with AML pathogenesis. Diagnostic whole-blood DNA samples of adult AML patients divided into a training (n = 128) and a testing cohort (n = 50) were examined. The libraries were prepared using SeqCap Epi Enrichments System (Roche) and sequenced on MiSeq instrument (Illumina). Altogether, 1935 CpGs affecting the survival (p < 0.05) were revealed in the training cohort. A summarizing value MethScore was then calculated from these significant CpGs. Patients with lower MethScore had markedly longer overall survival (OS) and event-free survival (EFS) than those with higher MethScore (p < 0.001). The predictive ability of MethScore was verified on the independent testing cohort for OS (p = 0.01). Moreover, the proof-of-principle validation was performed using the TCGA dataset. We showed that comprehensive NGS-based approach of DNA methylation assessment revealed a robust epigenetic signature relevant to AML outcome. We called this signature MethScore and showed it might serve as a strong prognostic marker able to refine survival probability of AML patients.