Methylated CpGs Research Articles

Short photoperiod inhibited gonadal growth and elevated hypothalamic Dio3 expression unrelated to promoter DNA methylation in young Brandt's voles.

Photoperiod, the length of daylight, has a significant impact on the physiological characteristics of seasonal breeding animals, including their somatic and gonadal development. In rodents, expression of deiodinase type II (Dio2) and III (Dio3) in the hypothalamus is crucial for responding to photoperiodic signals. However, research on the photoperiodism of hypothalamic gene expression and the corresponding regulatory mechanism in Brandt's voles living in the Mongolian steppes is limited. In this study, we gradually changed day length patterns to simulate spring (increasing long photoperiod, ILP) and autumn (decreasing short photoperiod, DSP). We compared the somatic and gonadal development of voles born under ILP and DSP and the expression patterns of five reproduction-related genes in the hypothalamus of young voles. The results showed that DSP significantly inhibited somatic and gonadal development in both female and male offspring. Compared with ILP, Dio3 expression was significantly upregulated in the hypothalamus under DSP conditions and remained elevated until postnatal week 8 in both males and females. However, there was no significant difference in the methylation levels of the proximal promoter region of Dio3 between ILP and DSP, suggesting that methylation in the proximal promoter region may not be involved in regulating the expression of Dio3. These findings suggest that hypothalamic expression of Dio3 plays a key role in the photoperiodic regulation of gonadal activity in Brandt's voles. However, it appears that CpGs methylation in the promoter region is not the main mechanism regulating Dio3 expression.

The correlation between CpG methylation and gene expression is driven by sequence variants

Gene promoter and enhancer sequences are bound by transcription factors and are depleted of methylated CpG sites (cytosines preceding guanines in DNA). The absence of methylated CpGs in these sequences typically correlates with increased gene expression, indicating a regulatory role for methylation. We used nanopore sequencing to determine haplotype-specific methylation rates of 15.3 million CpG units in 7,179 whole-blood genomes. We identified 189,178 methylation depleted sequences where three or more proximal CpGs were unmethylated on at least one haplotype. A total of 77,789 methylation depleted sequences (~41%) associated with 80,503 cis-acting sequence variants, which we termed allele-specific methylation quantitative trait loci (ASM-QTLs). RNA sequencing of 896 samples from the same blood draws used to perform nanopore sequencing showed that the ASM-QTL, that is, DNA sequence variability, drives most of the correlation found between gene expression and CpG methylation. ASM-QTLs were enriched 40.2-fold (95% confidence interval 32.2, 49.9) among sequence variants associating with hematological traits, demonstrating that ASM-QTLs are important functional units in the noncoding genome.

Droplet digital PCR analysis of CDH13 methylation status in Slovak women with invasive ductal breast cancer

Identifying novel epigenetic biomarkers is a promising way to improve the clinical management of patients with breast cancer. Our study aimed to determine the methylation pattern of 25 tumor suppressor genes (TSG) and select the best methylation biomarker associated with clinicopathological features in the cohort of Slovak patients diagnosed with invasive ductal carcinoma (IDC). Overall, 166 formalin-fixed, paraffin-embedded (FFPE) tissues obtained from patients with IDC were included in the study. The methylation status of the promoter regions of 25 TSG was analyzed using semiquantitative methylation-specific MLPA (MS-MLPA). We identified CDH13 as the most frequently methylated gene in our cohort of patients. Further analysis by ddPCR confirmed an increased level of methylation in the promoter region of CDH13. A significant difference in CDH13 methylation levels was observed between IDC molecular subtypes LUM A versus HER2 (P = 0.0116) and HER2 versus TNBC (P = 0.0234). In addition, significantly higher methylation was detected in HER2+ versus HER2- tumors (P = 0.0004) and PR− versus PR+ tumors (P = 0.0421). Our results provide evidence that alteration in CDH13 methylation is associated with clinicopathological features in the cohort of Slovak patients with IDC. In addition, using ddPCR as a methylation-sensitive method represents a promising approach characterized by higher precision and technical simplicity to measure the methylation of target CpGs in CDH13 compared to other conventional methods such as MS-MLPA.

Role of epigenetic regulation on catecholamine synthesis in pheochromocytoma and paraganglioma.

Pheochromocytomas and paragangliomas (PPGLs) typically secrete catecholamines and their metabolites (metanephrines [MN] and normetanephrine [NMN]). Catecholamines are synthesized by several enzymes: phenylalanine hydroxylase (encoded by PAH), tyrosine hydroxylase (TH), aromatic L-amino acid decarboxylase (DDC), dopamine β-hydroxylase (DBH), and phenylethanolamine N-methyltransferase (PNMT). MN/NMN secretion varies between anatomical and molecular subgroups. The aim of this study was to assess the correlation between DNA methylation of catecholamine synthesis genes and MN/NMN secretion. Gene promoter methylation of PAH, TH, AADC, DBH, and PNMT were extracted and calculated based on publicly available data. Comparisons and correlation analysis were performed between MN±NMN (MN/NMN), NMN only, and neither/unknown secretion patterns. Methylation levels and MN/NMN patterns were compared by three genetic alteration subgroups: pseudohypoxia (PH), kinase signaling (KS), and others. A total of 178 cases were included. Methylation of PAH CpGs negatively correlated with probability for MN/NMN secretion (p<.05 for all CpGs) and positively with NMN-only secretion. NMN-only secreting tumors had significantly higher promoter methylation of PAH, DBH, and PNMT compared with MN/NMN-secreting tumors. MN/NMN-secreting PPGLs had mainly KS alterations (52.1%), whereas NMN-only PPGLs had PH alterations (41.9%). PPGLs in the PH versus KS group had gene promoter hypermethylation of PAH (p=.002), DBH (p=.02), and PNMT (p=.003). Promoter methylation of genes encoding catecholamine synthesis enzymes is strongly and inversely correlated with MN/NMN patterns in PPGLs. KS and PH-related tumors have distinct methylation patterns. These results imply that methylation is a key regulatory mechanism of catecholamine synthesis in PPGLs.

Naive and regulatory B-cell transcription patterns guide the increased risk of papillary thyroid carcinoma in obesity.

A growing number of studies suggest a positive association between obesity and the high incidence of papillary thyroid cancer (PTC), suggesting that the abnormal levels of adipokines associated with obesity may be a risk factor for these aggressive thyroid cancers, but the underlying regulatory mechanisms are not yet clear. We downloaded bulk RNA sequence data for subcutaneous adipose tissue (SAT) in obesity and healthy population and tumor tissues of PTC from GEO database. Through analysis of Differential Expression Genes (DEGs), Gene Set Variation Analysis (GSVA) and Weighted Correlation Network Analysis (WGCNA), we identified co-expressed genes between obesity and PTC, and their pathways were mainly enriched in the regulation of B-cells. Furthermore, through TCGA-THCA (thyroid carcinoma) cohorts analysis, we identified B-cell regulatory-related genes LEF1, TNFRSF13C, SHLD2 and SHLD3 as independent prognostic markers of PTC. Next, we explored the transcriptional regulation mechanism of the increased risk of PTC in obesity through analysis of DNA methylation CpGs data and single-cell RNA sequences (scRNA-seq) from GEO database. PTC-induced hypomethylation of the promoter region may be involved in the transcriptional regulation of these genes, while these genes were further identified in naive and regulatory B-cells of both diseases. Notably, both of the gene expressions in naive and regulatory B-cells showed high similarity in both diseases. Our data reveals the high frequency of PTC in obese populations may be explained by the comparable transcriptional patterns of naive and regulatory B-cells, and offers novel insights for the analysis of critical genes and underlying biological mechanisms for obesity and PTC.

An industrialized diet as a determinant of methylation in the 1F region of the NR3C1 gene promoter.

Dietary composition can modify gene expression, favoring the development of chronic diseases via epigenetic mechanisms. Our study aimed to investigate the relationship between dietary patterns and NR3C1 gene methylation in users of the Brazilian Public Unified Health System (SUS). We recruited 250 adult volunteers and evaluated their socioeconomic status, psychosocial characteristics, lifestyle, and anthropometrics. Peripheral blood was collected and evaluated for cortisol levels, glycemia, lipid profile, and insulin resistance; methylation of CpGs 40-47 of the 1F region of the NR3C1 gene was also measured. Factors associated with degree of methylation were evaluated using generalized linear models (p < 0.05). Lifestyle variables and health variables were included as confounding factors. The findings of our cross-sectional study indicated an association between NR3C1 DNA methylation and intake of processed foods. We also observed relevant associations of average NR3C1 DNA across the segment analyzed, methylation in component 1 (40-43), and methylation in component 2 (44-47) with a pattern of consumption of industrialized products in relation to BMI, serum cortisol levels, and lipid profile. These results may indicate a relationship between methylation and metabolic changes related to the stress response. These findings suggest an association of methylation and metabolic alterations with stress response. In addition, the present study highlights the significant role of diet quality as a stress-inducing factor that influences NR3C1 methylation. This relationship is further linked to changes in psychosocial factors, lifestyle choices, and cardiometabolic variables, including glucose levels, insulin resistance, and hyperlipidemia.

Abstract 974: DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation

Abstract Cell-free DNA (cfDNA) in the bloodstream is increasingly gaining attention as a diagnostic tool for the early detection of cancer. Nevertheless, the characteristics and sources of cfDNA fragmentation in the blood remain poorly understood. In this study, we sought to unravel the impact of DNA methylation and gene expression on the naturally occurring genome-wide fragmentation of cfDNA. We performed a comprehensive analysis of plasma samples from 969 individuals, including 182 individuals diagnosed with cancer (pancreatic, colorectal, ovarian, lung and breast cancer). In healthy individual cfDNA fragmentation patterns like DNA motifs at cfDNA fraqgments ends, recurrent cfDNA fragment start sites, cfDNA coverage and cfDNA fragment size were compared to publicly available data on cfDNA methylation and gene expression from myeloid cells. We discovered that the ends of cfDNA fragments, particularly those containing CGs or CCGs, displayed a distinct pattern of enrichment or depletion, respectively, at methylated CpG positions throughout the genome. This phenomenon is consistent with structural models suggesting an increased interaction of CG fragment ends with nucleosomes. cfDNA fragments were more prevalent (up to 3.7 fold) and of larger sizes (up to 4-5 base larger) when derived from regions of methylated CpGs or transcriptional start sites of genes that were not actively expressed. Differences in cfDNA fragmentation reflected specific biological pathways associated with their tissue of origin (like E2f transcription factors and blood cell metabolism genes in cfDNA from healthy individuals). Through analyses of cfDNA from patients with cancer, we identified a connection between tumor-related hypomethylation, increased gene expression, and a global reduction in cfDNA fragment size. This connection may offer an explanation for the generally smaller cfDNA fragments found in individuals with cancer. We found that cancer-specific methylation at CpG sites from pancreatic cancers were associated with widespread changes in cfDNA fragment ends, particularly for patients with pancreatic (test statistic = Welch two sample t-test; p&amp;lt;2.2e-16) and other cancers. These findings establish a direct link between epigenetic modifications and cfDNA fragmentation that may have implications for non-invasive detection of cancer. Citation Format: Michaël Noë, Akshaya V. Annapragada, Zachariah H. Foda, Jamie E. Medina, Dimitrios Mathios, Stephen Cristiano, Christopher Cherry, Daniel C. Bruhm, Noushin Niknafs, Vilmos Adleff, Leonardo Ferreira, Hari Easwaran, Stephen Baylin, Jillian Phallen, Robert B. Scharpf, Victor E. Velculescu. DNA methylation and gene expression as determinants of genome-wide cell-free DNA fragmentation [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 974.

Abstract 2417: Detection and quantification of site-specific DNA methylation from liquid biopsies as a pharmacodynamic biomarker of OTX-2002, a novel MYC-targeting epigenomic mRNA therapeutic

Abstract Omega Therapeutics has developed a novel platform of programmable epigenomic mRNA medicines capable of modifying chromatin state to specifically tune gene expression at the pre-transcriptional level. Epigenomic controllers (ECs) unlock targets that have been historically considered “undruggable,” with one of the most elusive being the MYC oncogene. A direct MYC-targeting anti-cancer agent has previously remained intangible, largely due to the absence of a drug binding pocket and tight autoregulation. A clinical trial is underway (MYCHELANGELO, NCT05497453) to investigate pre-transcriptional inhibition of MYC with OTX-2002 in patients with hepatocellular carcinoma (HCC). OTX-2002, a first-in-class mRNA therapeutic delivered via lipid nanoparticles (LNP), encodes two proteins that durably modify chromatin, in part, through CpG DNA methylation at the MYC locus. Using both liquid and solid biopsy sampling from in vivo studies, we investigated whether target engagement for OTX-2002 could be assessed by MYC methylation. Detection of DNA methylation has long held promise as an oncology biomarker given its functional roles in various cancer types and the potential signal afforded by methylated CpGs. Indeed, DNA methylation has been shown to serve as a robust analyte in liquid biopsy-derived multi-cancer early detection (MCED) and minimal residual disease (MRD) tests that have recently been utilized in the clinic. Many of these platforms are founded on complex models that leverage methylation signals across &amp;gt;1 million CpGs that can span tens of megabases of genomic space. We faced a distinct challenge when compared to these MCED/MRD tests in developing a pharmacodynamic methylation assay for OTX-2002 as the target region consists of just a few kilobases. With a tissue specific LNP delivery system, ultra-high sensitivity was required to identify rare ctDNA events from the larger cfDNA population. To this end, we designed a minimal hybridization/capture panel that targeted ~50 kb of genomic space, effectively allowing for ultra-deep methylation sequencing of MYC. When this technique was paired with enzymatic (EM) conversion for methylation detection and supported by an analysis pipeline focused on epiallele identification, this assay was able to detect methylation down to the theoretical limit in a dilution series of control genomic DNA, 1 in 104 copies of MYC. This degree of sensitivity translated to successful preclinical detection of on-target methylation by OTX-2002 from DNA extracted from plasma samples collected from mice-bearing human HCC xenografts. Overall, we present a non-invasive and exquisitely sensitive method of assessing target engagement and site-specific pharmacodynamic activity of a novel epigenomic medicine that can be directly translated to the clinical setting. Citation Format: Justin Chen, William Senapedis, Stephen Siecinski, Elmer Figueroa, Adam Katz, Samuel Mildrum, Yaoyu E. Wang, Houda Belaghzal, Kayleigh Gallagher, Graeme Hodgson, Charles W. O'Donnell, Thomas G. McCauley. Detection and quantification of site-specific DNA methylation from liquid biopsies as a pharmacodynamic biomarker of OTX-2002, a novel MYC-targeting epigenomic mRNA therapeutic [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 2417.

The Alpha-Synuclein Gene (SNCA) is a Genomic Target of Methyl-CpG Binding Protein 2 (MeCP2)—Implications for Parkinson’s Disease and Rett Syndrome

Mounting evidence suggests a prominent role for alpha-synuclein (a-syn) in neuronal cell function. Alterations in the levels of cellular a-syn have been hypothesized to play a critical role in the development of Parkinson’s disease (PD); however, mechanisms that control expression of the gene for a-syn (SNCA) in cis and trans as well as turnover of a-syn are not well understood. We analyzed whether methyl-CpG binding protein 2 (MeCP2), a protein that specifically binds methylated DNA, thus regulating transcription, binds at predicted binding sites in intron 1 of the SNCA gene and regulates a-syn protein expression. Chromatin immunoprecipitation (ChIP) and electrophoretic mobility-shift assays (EMSA) were used to confirm binding of MeCP2 to regulatory regions of SNCA. Site-specific methylation and introduction of localized mutations by CRISPR/Cas9 were used to investigate the binding properties of MeCP2 in human SK-N-SH neuroblastoma cells. The significance of MeCP2 for SNCA regulation was further investigated by overexpressing MeCP2 and mutated variants of MeCP2 in MeCP2 knockout cells. We found that methylation-dependent binding of MeCP2 at a restricted region of intron 1 of SNCA had a significant impact on the production of a-syn. A single nucleotide substitution near to CpG1 strongly increased the binding of MeCP2 to intron 1 of SNCA and decreased a-syn protein expression by 60%. In contrast, deletion of a single nucleotide closed to CpG2 led to reduced binding of MeCP2 and significantly increased a-syn levels. In accordance, knockout of MeCP2 in SK-N-SH cells resulted in a significant increase in a-syn production, demonstrating that SNCA is a genomic target for MeCP2 regulation. In addition, the expression of two mutated MeCP2 variants found in Rett syndrome (RTT) showed a loss of their ability to reduce a-syn expression. This study demonstrates that methylation of CpGs and binding of MeCP2 to intron 1 of the SNCA gene plays an important role in the control of a-syn expression. In addition, the changes in SNCA regulation found by expression of MeCP2 variants carrying mutations found in RTT patients may be of importance for the elucidation of a new molecular pathway in RTT, a rare neurological disorder caused by mutations in MECP2.

Abstract A002: In-silico screening of race-specific endometrial cancer methylation markers using machine learning techniques

Abstract Targeted molecular therapy is a promising strategy for cancer treatment. Despite the benefits of these therapies, racial disparities in cancer therapy efficacy persist. To close this racial gap, there is a need to find race-specific biomarkers at the molecular level. Since abnormal DNA methylation has been linked with cancer and has a great potential to transform the diagnosis and treatment of cancer, the main objective of this study was to combine differential DNA methylation and machine learning techniques to identify race-specific methylation signature biomarkers in endometrial tumor samples from White and Black women. We performed genome wide Differentially Methylated CpG (DMCs) analysis in tumors from White patients (TWP) samples compared to tumors from Black patients (TBP) samples using Endometrial Carcinoma (EC) methylation and clinical data from The Cancer Genome Atlas (TCGA). We used supervised and unsupervised machine learning techniques to filter and select signature biomarkers. To evaluate the prognostic capacity of these genes, we performed univariate and multivariate survival analyses using Cox proportional hazards regression model from survival R package. By combining differential methylation CpGs and machine learning techniques, we reduced 704 differentially methylated CpGs to reliable race-specific epigenetic signature genes (ESGs) and Core- epigenetic signature genes (core-ESGs). An area under the curve (AUC) of 0.98 was achieved based on these signature genes. We further found that ESGs showed statistically significant overall survival differences between two racial groups. In addition, comparison of the mutational landscape showed differences in mutation frequencies in the ESGs between the two groups. By combining differential methylation analysis and machine learning techniques, we identified novel race-specific epigenetic signature genes in Black and White women with endometrial cancer. We further showed the potential of these gene in predicting survival differences, mutation, and transcriptomic differences in Black and White women. We propose that combined methylation and somatic mutation profiling of these novel race-specific signature genes can be used to develop potential therapeutic targets for diagnosis and treating endometrial cancer. Citation Format: Huma Asif, Grace Foley, Julie Kim. In-silico screening of race-specific endometrial cancer methylation markers using machine learning techniques [abstract]. In: Proceedings of the AACR Special Conference on Endometrial Cancer: Transforming Care through Science; 2023 Nov 16-18; Boston, Massachusetts. Philadelphia (PA): AACR; Clin Cancer Res 2024;30(5_Suppl):Abstract nr A002.

DNA-methylation variability in normal mucosa: a field cancerization marker in patients with adenomatous polyps.

The phenomenon of field cancerization reflects the transition of normal cells into those predisposed to cancer. Assessing the scope and intensity of this process in the colon may support risk prediction and colorectal cancer prevention. The SWEPIC study, encompassing 1,111 participants for DNA methylation analysis and a subset of 84 for RNA-seq, was employed to detect field cancerization in individuals with adenomatous polyps (AP). Methylation variations were evaluated for their discriminative capability, including in external cohorts, genomic localization, clinical correlations, and associated RNA expression patterns. Normal cecal tissue of individuals harboring an AP in the proximal colon manifested dysregulated DNA methylation compared to tissue from healthy individuals at 558 unique loci. Leveraging these adenoma-related differentially variable and methylated CpGs (aDVMCs), our classifier discerned between healthy and AP-adjacent tissues across SWEPIC datasets (cross-validated ROC AUC [0.63-0.81]), including within age-stratified cohorts. This discriminative capacity was validated in three external sets, differentiating healthy from cancer-adjacent tissue (ROC AUC: [0.82-0.88]). Notably, aDVMC dysregulation correlated with polyp multiplicity. More than 50% of aDVMCs were significantly associated with age. These aDVMCs were enriched in active regions of the genome (p < .001), and associated genes exhibited altered expression in AP-adjacent tissues. Our findings underscore the early onset of field cancerization in the right colon during the neoplastic transformation process. A more extensive validation of aDVMC dysregulation as a stratification tool could pave the way for enhanced surveillance approaches, especially given its linkage to adenoma emergence.

Comprehensive analysis of differentially methylated regions in colorectal cancer (CRC).

73 Background: Epigenetic alterations have been shown to govern many disease states, including cancer. A key epigenetic mark is the DNA methylation of CpGs. Large studies, like The Cancer Genome Atlas, have shown that DNA methylation can differentiate between cancer status and type. Here, differentially methylated genomic patterns were defined between patients with CRC and healthy individuals by utilizing patterns of co-methylation of adjacent CpG loci. Methods: Deep, whole genome bisulfite sequencing (WGBS) was conducted on DNA samples from 100 healthy individuals (median effective coverage of 352x±38x) and from 75 patients with CRC (median effective coverage of 48x±18x). The two cohorts were chosen to be balanced in terms of age (CRC: 58±11 years; healthy: 57±8 years) and to represent major ethnicities in the USA, and the CRC cohort was chosen to represent all stages, histologies and morphologies, and microsatellite instability (MSI, 23%). A novel machine learning model was developed to discover differentially methylated regions between the healthy and CRC cohorts as well as between subpopulations within the CRC cohort, including age, sex, stage, histology, and MSI vs microsatellite stability (MSS). Results: In total, we discovered 132,911 differentially methylated regions between healthy and CRC cohorts, spanning more than 1.14 million CpGs. 76% of all discovered regions were hypermethylated (70% CpG islands, 1.3% CpG shelves, 21% CpG shores) and the rest were hypomethylated (7.3% CpG islands, 8.6% CpG shelves, 25% CpG shores). We also discovered 220 hypermethylated regions that were differentially methylated between CRC MSI samples and CRC MSS samples and healthy cfDNA samples. Furthermore, we discovered subtype-specific differentially methylated regions, such as 62 hyper-methylated regions that were differentially methylated between mucinous adenocarcinoma samples and the rest of the cohort. Conclusions: Based on deep WGBS data from heterogeneous cohorts, representative of the US population eligible for CRC screening, we identified many differentially methylated regions as strong biomarker candidates for the early detection of cancer. Compared to recurrently mutated driver genes in CRC, we find that differential methylation profiles of CRC samples are generally much more homogenous and are therefore ideal biomarkers for targeted sequencing panels with the purpose of early cancer detection. Further, analysis of these patterns based on clinicopathologic factors enabled discovery of subtype specific markers, which can be incorporated to ensure equivalent performance for underrepresented subtypes or subpopulations.

Age prediction using DNA methylation of Y-chromosomal CpGs in semen samples

In cases of sexual assault, the evidence often exists as a mixture of female and male body fluids, and in many cases, contains a higher proportion of female body fluids than males. In these cases, Y-STR, rather than autosomal STRs, can provide useful information. It becomes very difficult to identify the true suspect if there is no match among known suspects or if a match exists for two or more suspects, e.g. two suspects from the same paternal lineage. However, age prediction using the DNA methylation of Y-chromosomal CpGs can help narrow the search for unknown suspects and discriminate between older and younger suspects. Therefore, the DNA methylation profiles of semen samples from 56 healthy Korean males were generated using Illumina’s Infinium MethylationEPIC BeadChip Array. Among the ten identified age-associated CpG markers located in the Y-chromosome, nine were used to construct age prediction models. The identified markers were further investigated in the MPS analysis of 147 semen samples, and the multiplex assay was validated with the reliability, reproducibility and sensitivity tests. Several age prediction models were constructed using the MPS data with the multiple linear regression, stepwise linear regression, ridge linear regression, lasso regression, elastic net linear regression and support vector machine analyses, and all showed MAEs of 5 to 7 years in the test set samples. Six single-source female samples were also subjected to MPS analysis but showed very low coverage that could not affect the analysis of the mixed samples. Therefore, the age prediction models of the present study are expected to provide useful investigative leads, especially in mixed male and female samples from sexual assault cases.

Defining high confidence targets of differential CpG methylation in response to in utero arsenic exposure and implications for cancer risk

Arsenic is a relatively abundant metalloid that impacts DNA methylation and has been implicated in various adverse health outcomes including several cancers and diabetes. However, uncertainty remains about the identity of genomic CpGs that are sensitive to arsenic exposure, in utero or otherwise. Here we identified a high confidence set of CpG sites whose methylation is sensitive to in utero arsenic exposure. To do so, we analyzed methylation of infant CpGs as a function of maternal urinary arsenic in cord blood and placenta from geographically and ancestrally distinct human populations. Independent analyses of these distinct populations were followed by combination of results across sexes and populations/tissue types. Following these analyses, we concluded that both sex and tissue type are important drivers of heterogeneity in methylation response at several CpGs. We also identified 17 high confidence CpGs that were hypermethylated across sex, tissue type and population; 11 of these were located within protein coding genes. This pattern is consistent with hypotheses that arsenic increases cancer risk by inducing the hypermethylation of genic regions. This study represents an opportunity to understand consistent, reproducible patterns of epigenomic responses after in utero arsenic exposure and may aid towards novel biomarkers or signatures of arsenic exposure. Identifying arsenic-responsive sites can also contribute to our understanding of the biological mechanisms by which arsenic exposure can affect biological function and increase risk of cancer and other age-related diseases.

Maternal adverse childhood experiences (ACEs) and DNA methylation of newborns in cord blood

BackgroundAdverse childhood experiences (ACEs) increase the risk of poor health outcomes later in life. Psychosocial stressors may also have intergenerational health effects by which parental ACEs are associated with mental and physical health of children. Epigenetic programming may be one mechanism linking parental ACEs to child health. This study aimed to investigate epigenome-wide associations of maternal preconception ACEs with DNA methylation patterns of children. In the Center for the Health Assessment of Mothers and Children of Salinas study, cord blood DNA methylation was measured using the Illumina HumanMethylation450 BeadChip. Preconception ACEs, which occurred during the mothers’ childhoods, were collected using a standard ACE questionnaire including 10 ACE indicators. Maternal ACE exposures were defined in this study as (1) the total number of ACEs; (2) the total number of ACEs categorized as 0, 1–3, and > 4; and (3) individual ACEs. Associations of ACE exposures with differential methylated positions, regions, and CpG modules determined using weighted gene co-expression network analysis were evaluated adjusting for covariates.ResultsData on maternal ACEs and cord blood DNA methylation were available for 196 mother/newborn pairs. One differential methylated position was associated with maternal experience of emotional abuse (cg05486260/FAM135B gene; q value < 0.05). Five differential methylated regions were significantly associated with the total number of ACEs, and 36 unique differential methylated regions were associated with individual ACEs (Šidák p value < 0.05). Fifteen CpG modules were significantly correlated with the total number of ACEs or individual ACEs, of which 8 remained significant in fully adjusted models (p value < 0.05). Significant modules were enriched for pathways related to neurological and immune development and function.ConclusionsMaternal ACEs prior to conception were associated with cord blood DNA methylation of offspring at birth. Although there was limited overlap between differential methylated regions and CpGs in modules associated with ACE exposures, statistically significant regions and networks were related to genes involved in neurological and immune function. Findings may provide insights to pathways linking psychosocial stressors to health. Further research is needed to understand the relationship between changes in DNA methylation and child health.

Mediating effects of DNA methylation in the association between sleep quality and infertility among women of childbearing age

BackgroundThis study aims to investigate the association between sleep quality and infertility among women and to explore the mediating effects of DNA methylation in this association.MethodsThis study is a population-based case–control study. The relationship between sleep quality and infertility was investigated in women with anovulatory infertility (n = 43) and healthy controls (n = 43). Genome-wide DNA methylation was profiled from peripheral blood samples using the Illumina Infinium Human Methylation 850k BeadChip. Differentially methylated CpGs between cases and controls were identified using the ChAMP R package. The mediating effect of DNA methylation between sleep quality and infertility among women was investigated using the Bayesian estimation method provided by the R package “mediation”.ResultsThe survey included 86 women of reproductive age, with 43 participants each in the case and control groups. The average age of the women was 27.6 ± 2.8 years (case group: 27.8 ± 3.0 years, control group: 27.4 ± 2.7 years). A total of 262 differentially methylated CpGs corresponding to 185 genes were identified. Difficulty falling asleep was a risk factor for infertility in women (OR = 3.69, 95%CI = 1.14, 11.99), and a causal mediation effect of DNA methylation CpGs was found. The mediating effect coefficient for cg08298632 was 0.10 (95%CI = 0.01–0.22), and the proportion of the total effect mediated by this methylation site increased to 64.3%.ConclusionThese results suggest that DNA methylation CpGs (cg08298632) play a significant role in the relationship between difficulty falling asleep and infertility in females. These findings contribute to our understanding of the underlying mechanisms that connect difficulty falling asleep and infertility in women. Further studies are necessary to fully understand the biological significance and potential therapeutic applications of these findings. The identified DNA methylation sites provide new and valuable insights and potential targets for future studies aiming to prevent and treat female infertility.

DAT1 5'-Un-Translated-Region Methylation Patterns as Bio-Markers of ADHD Psycho-Pathology: Contribution to Disease Prognosis and to Monitoring of a Successful Therapy.

Epigenetic modifications, such as changes in DNA methylation, have been linked to several diseases in recent years. The purpose of our study was to search for biomarkers that (using non-invasive techniques) could assist the clinician in the prognosis of infant/adolescent psychopathology. We previously showed that changes in methylation of the 5'-UTR in the DAT1/SLC6A3 gene can be used as a biomarker for the prognosis of initial severe ADHD: treatment-resistant severe ADHD children were characterized by methylated CpG 1 in particular, while methylated CpGs 2 and 6 were then found in children who improved after the therapy. Further, we confirmed these outcomes and provided the hypothesis that symptomatology might be influenced by the children's genotype and family environment. In particular, levels of CpG 3 methylation in the heterozygous ADHD children were associated with high paternal own risk or stress. Eventually, we found that the same biomarkers are more broadly useful in the field of internalizing or externalizing symptoms (when a certain vulnerability is already present in the child). In particular, it was seen how inheriting specific 9-repeat or 10-repeat VNTR alleles from the mother or from the father could modify the pattern of methylation at the 5'-UTR of the DAT1 gene. A specific pattern of methylations (with CpG 2 following either CpGs 1 + 3 or CpG 6 at the DAT1 5'-UTR) has been associated, therefore, with the likelihood of an internalizing or externalizing developmental trajectory entailing ADHD-like psycho-pathological characteristics. Since each individual responds differently to a specific treatment, we suggest that these methylation patterns may be used as biomarkers to monitor the outcome and/or predict the success of a given therapy (personalized medicine).

Integrated epigenome, whole genome sequence and metabolome analyses identify novel multi-omics pathways in type 2 diabetes: a Middle Eastern study

BackgroundT2D is of high prevalence in the middle east and thus studying its mechanisms is of a significant importance. Using 1026 Qatar BioBank samples, epigenetics, whole genome sequencing and metabolomics were combined to further elucidate the biological mechanisms of T2D in a population with a high prevalence of T2D.MethodsAn epigenome-wide association study (EWAS) with T2D was performed using the Infinium 850K EPIC array, followed by whole genome-wide sequencing SNP-CpG association analysis (> 5.5 million SNPs) and a methylome-metabolome (CpG-metabolite) analysis of the identified T2D sites.ResultsA total of 66 T2D-CpG associations were identified, including 63 novel sites in pathways of fructose and mannose metabolism, insulin signaling, galactose, starch and sucrose metabolism, and carbohydrate absorption and digestion. Whole genome SNP associations with the 66 CpGs resulted in 688 significant CpG-SNP associations comprising 22 unique CpGs (33% of the 66 CPGs) and included 181 novel pairs or pairs in novel loci. Fourteen of the loci overlapped published GWAS loci for diabetes related traits and were used to identify causal associations of HK1 and PFKFB2 with HbA1c. Methylome-metabolome analysis identified 66 significant CpG-metabolite pairs among which 61 pairs were novel. Using the identified methylome-metabolome associations, methylation QTLs, and metabolic networks, a multi-omics network was constructed which suggested a number of metabolic mechanisms underlying T2D methylated genes. 1-palmitoyl-2-oleoyl-GPE (16:0/18:1) – a triglyceride-associated metabolite, shared a common network with 13 methylated CpGs, including TXNIP, PFKFB2, OCIAD1, and BLCAP. Mannonate – a food component/plant shared a common network with 6 methylated genes, including TXNIP, BLCAP, THBS4 and PEF1, pointing to a common possible cause of methylation in those genes. A subnetwork with alanine, glutamine, urea cycle (citrulline, arginine), and 1-carboxyethylvaline linked to PFKFB2 and TXNIP revealed associations with kidney function, hypertension and triglyceride metabolism. The pathway containing STYXL1-POR was associated with a sphingosine-ceramides subnetwork associated with HDL-C and LDL-C and point to steroid perturbations in T2D.ConclusionsThis study revealed several novel methylated genes in T2D, with their genomic variants and associated metabolic pathways with several implications for future clinical use of multi-omics associations in disease and for studying therapeutic targets.

GraphCpG: imputation of single-cell methylomes based on locus-aware neighboring subgraphs.

Single-cell DNA methylation sequencing can assay DNA methylation at single-cell resolution. However, incomplete coverage compromises related downstream analyses, outlining the importance of imputation techniques. With a rising number of cell samples in recent large datasets, scalable and efficient imputation models are critical to addressing the sparsity for genome-wide analyses. We proposed a novel graph-based deep learning approach to impute methylation matrices based on locus-aware neighboring subgraphs with locus-aware encoding orienting on one cell type. Merely using the CpGs methylation matrix, the obtained GraphCpG outperforms previous methods on datasets containing more than hundreds of cells and achieves competitive performance on smaller datasets, with subgraphs of predicted sites visualized by retrievable bipartite graphs. Besides better imputation performance with increasing cell number, it significantly reduces computation time and demonstrates improvement in downstream analysis. The source code is freely available at https://github.com/yuzhong-deng/graphcpg.git.

The methylation profile of IL4, IL5, IL10, IFNG and FOXP3 associated with environmental exposures differed between Polish infants with the food allergy and/or atopic dermatitis and without the disease.

Epigenetic dynamics has been indicated to play a role in allergy development. The environmental stimuli have been shown to influence the methylation processes. This study investigated the differences in CpGs methylation rate of immune-attached genes between healthy and allergic infants. The research was aimed at finding evidence for the impact of environmental factors on methylation-based regulation of immunological processes in early childhood. The analysis of methylation level of CpGs in the IL4, IL5, IL10, IFNG and FOXP3 genes was performed using high resolution melt real time PCR technology. DNA was isolated from whole blood of Polish healthy and allergic infants, with food allergy and/or atopic dermatitis, aged under six months. The significantly lower methylation level of FOXP3 among allergic infants compared to healthy ones was reported. Additional differences in methylation rates were found, when combining with environmental factors. In different studied groups, negative correlations between age and the IL10 and FOXP3 methylation were detected, and positive - in the case of IL4. Among infants with different allergy symptoms, the decrease in methylation level of IFNG, IL10, IL4 and FOXP3 associated with passive smoke exposure was observed. Complications during pregnancy were linked to different pattern of the IFNG, IL5, IL4 and IL10 methylation depending on allergy status. The IFNG and IL5 methylation rates were higher among exclusively breastfed infants with atopic dermatitis compared to the non-breastfed. A decrease in the IFNG methylation was noted among allergic patients fed exclusively with milk formula. In different study groups, a negative correlation between IFNG, IL5 methylation and maternal BMI or IL5 methylation and weight was noted. Some positive correlations between methylation rate of IL10 and child's weight were found. A higher methylation of IL4 was positively correlated with the number of family members with allergy. The FOXP3 methylation in allergic infants was lower than in the healthy ones. The methylation profile of IL4, IL5, IL10, IFNG and FOXP3 associated with environmental exposures differed between the studied groups. The results offer insights into epigenetic regulation of immunological response in early childhood.