Differentially Methylated Sites Research Articles

Somatic Super-Enhancer Epigenetic Signature for Overall Survival Prediction in Patients with Breast Invasive Carcinoma.

To analyze genome-wide super-enhancers (SEs) methylation signature of breast invasive carcinoma (BRCA) and its clinical value. Differential methylation sites (DMS) between BRCA and adjacent tissues from The Cancer Genome Atlas (TCGA) database were identified by using ChAMP package in R software. Super-enhancers were identified sing ROSE software. Overlap analysis was used to assess the potential DMS in SEs region. Feature selection was performed by Cox regression and least absolute shrinkage and selection operator (LASSO) algorithm based on TCGA training cohort. Prognosis model validation was performed in TCGA training cohort, TCGA validation cohort, and gene expression omnibus (GEO) test cohort. The gene ontology and KEGG analysis revealed that SEs target genes were significantly enriched in cell-migration-associated processes and pathways. A total of 83 654 DMS were identified between BRCA and adjacent tissues. Around 2397 DMS in SEs region were identified by overlap study and used to feature selection. By using Cox regression and LASSO algorithm, 42 features were selected to develop a clinical prediction model (CPM). Both training (TCGA) and validation cohorts (TCGA and GEO) show that the CPM has ideal discrimination and calibration. The CPM based on DMS at SE regions has ideal discrimination and calibration, which combined with tumor node metastasis (TNM) stage could improve prognostication, and thus contribute to individualized medicine.

Prenatal maternal anxiety promotes atopic dermatitis in offspring via placental DNA methylation changes.

Maternal anxiety during pregnancy has been previously reported to be associated with atopic dermatitis (AD) in offspring. The potential mechanism is not yet proven but epigenetic change may be suggested. We examined whether maternal anxiety during pregnancy may alter placental DNA methylation, then develop AD in the offspring. We evaluated maternal anxiety at 36 weeks of gestation by self-reported questionnaires, the State-Trait Anxiety Inventory-Trait subscale (STAI-T), in the Cohort for Childhood Origin of Asthma and Allergic Diseases (COCOA) study. AD was diagnosed at 6 months of age by pediatric allergists. We stratified the subjects into four groups according to the STAI score of mothers and diagnosis of AD in children. Placental genome-wide methylation microarray was analyzed using Infinium 450K BeadChip and selected genes were validated by pyrosequencing. From microarray, several differential methylation sites were identified in AD and healthy subjects and in total subjects, regarding to the STAI scores. Among differential methylation sites in microarray, six sites were selected for pyrosequencing. And site of matrix metalloproteinases 27 (MMP27) among 6 sites showed decreased methylation in AD infants with high STAI mothers compared to healthy infants with low STAI mothers. Epigenetic change in placenta can be a suggesting mechanism for the development of AD in offspring at 6 months of age associated with maternal anxiety during pregnancy and MMP27 may be a candidate gene.

Identification of prognostic values of the transcription factor-CpG-gene triplets in lung adenocarcinoma: A narrative review

Abnormal DNA methylation can regulate carcinogenesis in lung adenocarcinoma (LUAD), while transcription factors (TFs) mediate methylation in a site-specific manner to affect downstream transcriptional regulation and tumor progression. Therefore, this study aimed to explore the TF-methylation-gene regulatory relationships that influence LUAD prognosis. Differential analyses of methylation sites and genes were generated by integrating transcriptome and methylome profiles from public databases. Through target gene identification, motif enrichment in the promoter region, and TF prediction, TF-methylation and methylation-gene relation pairs were obtained. Then, the prognostic TF-methylation-gene network was constructed using univariate Cox regression analysis. Prognostic models were constructed based on the key regulatory axes. Finally, Kaplan-Meier curves were created to evaluate the model efficacy and the relationship between candidate genes and prognosis. A total of 1878 differential expressed genes and 1233 differential methylation sites were screened between LUAD and normal samples. Then 10 TFs were predicted to bind 144 enriched motifs. After integrating TF-methylation and methylation-gene relations, a prognostic TF-methylation-gene network containing 4 TFs, 111 methylation sites, and 177 genes was constructed. In this network, ERG-cg27071152-MTURN and FOXM1-cg19212949-PTPR regulatory axes were selected to construct the prognostic models, which showed robust abilities in predicting 1-, 3-, and 5-year survival probabilities. Finally, ERG and MTURN were downregulated in LUAD samples, whereas FOXM1 and PTPR were upregulated. Their expression levels were related to LUAD prognosis. ERG-cg27071152-MTURN and FOXM1-cg19212949-PTPR regulatory axes were proposed as potential biomarkers for predicting the prognosis of LUAD.

Genome-wide DNA methylation of Munro's microabscess reveals the epigenetic regulation in the pathogenesis of psoriasis.

Munro's microabscess is a typical pathological feature in the early psoriatic lesion, mainly characterized by the accumulation of neutrophils in the epidermis. DNA methylation microenvironment of Munro's microabscess and the crosstalk with transcription and its effect on neutrophils have not yet been revealed. Performed genome-wide DNA methylation analysis and further differential methylation analysis of psoriatic skin lesions with and without Munro's microabscess from two batch samples consisting of 114 former samples in the discovery stage and 21 newly-collected samples in the validation stage. Utilized GO, MEME, and other tools to conduct downstream analysis on differentially methylated sites (DMSs). Correlation analysis of methylation level and transcriptome data was also conducted. We observed 647 overlapping DMSs associated with Munro's microabscess. Subsequently, GO pathway analysis revealed that DNA methylation might affect the physical properties associated with skin cells through focal adhesion and cellsubstrate junction and was likely to recruit neutrophils in the epidermis. Via the MEME tool, used to investigate the possible binding transcription factors (TFs) of 20 motifs around the 647 DMSs, it was found that DNA methylation regulated the binding of AP1 family members and the recruitment of neutrophils in the epidermis through the TGF-beta pathway and the TH17 pathway. Meanwhile, combined with our earlier transcriptome data, we found DNA methylation would regulate the expressions of CFDP, SIRT6, SMG6, TRAPPC9, HSD17B7, and KIAA0415, indicating these genes would potentially promote the process of Munro's microabscess. In conclusion, DNA methylation may affect the course of psoriasis by regulating the progression of Munro's microabscess in psoriatic skin lesions.

Genome-wide differential DNA methylation analysis of MDA-MB-231 breast cancer cells treated with curcumin derivatives, ST08 and ST09

ST08 and ST09 are potent curcumin derivatives with antiproliferative, apoptotic, and migrastatic properties. Both ST08 and ST09 exhibit in vitro and in vivo anticancer properties. As reported earlier, these derivatives were highly cytotoxic towards MDA-MB-231 triple-negative breast cancer cells with IC50 values in the nanomolar (40-80nM) range.In this study,we performed whole-genome bisulfite sequencing(WGBS) of untreated (control), ST08 and ST09 (treated) triple-negative breast cancer cell line MDA-MB-231 to unravel epigenetic changes induced by the drug. We identified differentially methylated sites (DMSs) enriched in promoter regions across the genome. Analysis of the CpG island promoter methylation identified 12 genes common to both drugs, and 50% of them are known to be methylated in patient samples that were hypomethylated by drugs belonging to the homeobox family transcription factors.Methylation analysis of the gene body revealed 910 and 952 genes to be hypermethylatedin ST08 and ST09 treated MDA-MB-231 cells respectively. Correlation of the gene body hypermethylation with expression revealed CACNAH1 to be upregulated in ST08 treatment and CDH23 upregulation in ST09.Further, integrated analysis of the WGBS with RNA-seq identified uniquely altered pathways - ST08 altered ECM pathway, and ST09 cell cycle, indicating drug-specific signatures.

An integrated systems‐level analysis of the molecular changes resulting from systemic infections in Alzheimer’s disease

AbstractBackgroundTo fully understand the molecular consequences of neuroinflammation and systemic infection in Alzheimer’s disease (AD), it is important to scrutinise molecular changes occurring in the brain in individuals with AD after they have had a systemic infection. Recently, several epigenome‐wide association studies (EWAS) have identified robust and reproducible alterations in AD brain samples compared to controls. In the current study we have performed an EWAS comparing bulk brain tissue in individuals with AD and non‐demented controls with or without a systemic infection.MethodDNA methylation arrays were employed for quantification of DNA methylation in extracted DNA from 276 prefrontal cortex brain tissue samples (controls, n = 72; AD‐diagnosed, n = 86; cognitively normal with infection, n = 48; AD‐diagnosed with infection, n = 70). Methylation values were quality checked and normalised before Analysis of Variance was performed to identify sites of significant differential methylation across all groups. Probes that were significant to AD‐only patients and infection‐only patients, when compared to controls, were removed, leaving only probes that were specifically differentially methylated in infection‐AD cases.ResultsOverall, more significant changes in methylation across the genome can be observed in AD patients who also suffered from systemic infection compared to AD‐only patients and infection‐only patients. By removing probes that are significantly associated with either systemic infections or AD, the remaining significant probes are therefore more likely to be associated with the consequences of infections, specifically within AD patients. Identified genes include AUTS2, a gene implicated in developmental disorders, and ADAR, a protein‐coding gene involved in the control of the innate immune response and controlling the function of certain neurotransmitters.ConclusionThe exact pathways affected by systemic infection are yet to be scrutinised, however this initial data provides evidence that unique changes to the methylome occur in AD‐diagnosed patients who additionally suffer from a systemic infection. The next steps of this project include isolating microglia to observe methylation changes specific to these cells, as well as incorporating more sample data sets to improve power.

Dissecting the epigenomic differences between smoking and nicotine dependence in a veteran cohort.

Smoking is a serious public health issue linked to more than 8 million deaths per year worldwide and may lead to nicotine dependence (ND). Although the epigenomic literature on smoking is well established, studies evaluating the role of epigenetics in ND are limited. In this study, we examined the epigenomic signatures of ND and how these differ from smoking exposure to identify biomarkers specific to ND. We investigated the peripheral epigenetic profile of smoking status (SS) and ND in a US male veteran cohort. DNA from saliva was collected from 1135 European American (EA) male US military veterans. DNAm was assessed using the Illumina Infinium Human MethylationEPIC BeadChip array. SS was evaluated as current smokers (n = 137; 12.1%) and non-current smokers (never and former; n = 998; 87.9%). NDFTND was assessed as a continuous variable using the Fagerström Test for ND (FTND; n= 1135; mean = 2.54 ± 2.29). Epigenome-wide association studies (EWAS) and co-methylation analyses were conducted for SS and NDFTND . A total of 450 and 22 genome-wide significant differentially methylated sites (DMS) were associated with SS and NDFTND , respectively (15 overlapped DMS). We identified 97 DMS (43 genes) in SS-EWAS previously reported in the literature, including AHRR and F2RL3 genes (p-value: 1.95 × 10-83 to 4.55 × 10-33 ). NDFTND novel DMS mapped to NEUROG1, ANPEP, and SLC29A1. Co-methylation analysis identified 386 modules (11 SS-related and 19 NDFTND -related). SS-related modules showed enrichment for alcoholism, while NDFTND -related modules were enriched for nicotine addiction. This study confirms previous findings associated with SS and identifies novel and-potentially specific-epigenetic biomarkers of ND that may inform prognosis and novel treatment strategies.

Association between placental DNA methylation and fetal congenital heart disease.

Congenital heart disease (CHD) is a worldwide problem with high morbidity and mortality. Early diagnosis of congenital heart disease is still a challenge in clinical work. In recent years, few studies indicated that placental methylation may be predictors of CHD. More studies are needed to confirm the association between placental methylation and CHD. The aim of this study was to investigate the association between prenatal placental DNA methylation and CHD. Placental tissues were obtained from four fetuses during the second trimester with isolated, non-syndromic congenital heart disease, including three cases with double outlet right ventricle (DORV) and one case with tetralogy of Fallot (TOF), and four unaffected fetuses as controls. The Illumina Infinium Human Methylation 850K BeadChip assay was employed to identify differential methylation sites (DMSs) and differential methylation regions (DMRs). Differential methylation was evaluated by comparing the β-values for individual CpG loci in cases vs. controls. In addition, the function of genes was assessed through KEGG enrichment analysis, Gene Ontology (GO) analysis and KEGG pathway analysis. Compared with the control group, we identified 9625 differential methylation genes on 26,202 DMSs (p < 0.05), of which 6997 were hyper-methylation and 2628 were hypo-methylation. The top 30 terms of GO biological process and KEGG enrichment analysis of DMSs were connected with multiple important pathways of heart development and disease. Ten differentially methylated regions and the genes related to DMRs, such as TLL1, CRABP1, FDFT1, and PCK2, were identified. The deformity caused by the loss of function of these genes is remarkably consistent with the clinical phenotype of our cases. The DNA methylation level of placental tissue is closely associated with fetal congenital heart disease.

Screening of Differential DNA Methylation Sites and Signal Pathway Analysis of Juvenile Myelomonocytic Leukemia in Children before and after Decitabine Treatment

Enrolled subjects were 7 children diagnosed with JMML in Nanfang Chunfu Children's Institute Hematology & Oncology Research according to the 2016 WHO standard from January 2019 to July 2020. Bone marrow samples were collected from all 7 children before and after the decitabine treatment. DNA extraction was successfully performed in all 7 cases of before group. And DNA extraction was successfully performed in only 4 cases of after group, while was failed in the rest of 3 cases. 11 DNA samples that were successfully extracted and qualified for quality control (7 cases before treatment, 4 cases after treatment) were subjected to chip experiments according to the Illumina Infinium Methylation EPIC 850K BeadChip manufacture protocol. The BMIQ algorithm is used to standardize methylation level β value. The enrolled cases were divided into two groups before and after treatment with decitabine, and the difference in β value before and after treatment was compared. The criteria for differential screening are: ∣Δβ∣≥0.1, P<0.01. Then through the visualization of DMP display, GO and KEGG function enrichment and related signal pathways, explore the mechanism of demethylation of decitabine in the treatment of JMML. Public database JMML gene expression dataset and independent JMML validation cohort was used for mechanism validation. 1. From the β value density curve and box plot, it can be seen that the β value of JMML children has a "bimodal" pattern, but the density of high methylation sites is significantly higher than that of low methylation sites. Screening for differential methylation sites through the champ. DMP function, a total of 2310 differentially methylated positions that meet the screening criteria were obtained, accounting for 0.26% of the methylation coverage of 850K chip, indicating that demethylation drugs have an effect on the overall high methylation level loci, but number of points does not affected much. Through DMP scatter plots, volcano plots and cluster analysis, it is found that each enrolled child with JMML has a specific abnormally hypermethylation pattern, and demethylation treatment is to reduce the degree of methylation of certain CpG sites under the specific hypermethylation pattern of each patient. 2. Perform GO and KEGG function enrichment analysis on the genes adjacent to the 2310 differentially methylated sites that have been screened out. In the GO enrichment analysis, it is found that the activity of PI3K/AKT pathway showed the highest adjacent gene enrichment with significant P value(Figure 1.A). In the KEGG enrichment analysis(Figure 1.B), it is found that DMP has the highest degree of enrichment in genes that affect signal transduction, indicating that demethylation therapy has the greatest impact on the signal transduction process within/between the signal pathway. Combined with the results of GSEA, it is suggested that decitabine may reduce the methylation of some related genes in the PI3K/AKT signaling pathway near the CpG site, thereby inhibiting the abnormal activation of the PI3K/AKT signaling pathway, so as to achieve the effect of treating JMML. In the validation cohort, it was confirmed that the expression of phosphorylated PI3K/AKT protein was significantly decreased after decitabine treatment compared with before treatment. 3. A total of 5 motifs were obtained by motif analysis, and these motifs correspond to a total of 22 transcription factors, namely INSM1, SP1, T, EBF1, Egr1, EWSR1-FLI1, FEV Hand1::Tcfe2a, IRF1, Klf4, Myf , NFATC2, NFE2L2, NHLH1, PPARG::RXRA, RXR::RAR_DR5, SPI1, Spz1, Stat3, Tal1::Gata1, TFAP2A, Zfp423; the upstream transcription factors of the target genes DNMT1, DNMT3A and DNMT3B of decitabine. The 165 possible transcription factors were intersected with the transcription factors corresponding to the motif analysis, and the common transcription factor was the RXRA gene. GSE71935 dataset in the GEO contains gene expression data of 38 JMML patients and 9 normal healthy controls, confirming that JMML patients have decreased RXRA gene expression and increased DNMT3A and DNMT3B expression relative to healthy donors group(Figure 1.C/D). Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

DNA Hyper-methylation Associated With Schizophrenia May Lead to Increased Levels of Autoantibodies.

Environmental stressors may influence immune surveillance in B lymphocytes and stimulate autoimmune responses via epigenetic DNA methylation modifications in schizophrenia (SCZ). A total of 2722, Chinese Han origin subjects were recruited in this study (2005-2011), which included a discovery follow-up cohort with 40 remitters of SCZ (RSCZ), 40 nonremitters of SCZ (NRSCZ), and 40 controls (CTL), and a replication follow-up cohort (64 RSCZ, 16 NRSCZ, and 84 CTL), as well as a case-control validation cohort (1230 SCZ and 1208 CTL). Genomic DNA methylation, target gene mRNA transcripts, and plasma autoantibody levels were measured across cohorts. We found extensive differences in global DNA methylation profiles between RSCZ and NRSCZ groups, wherein differential methylation sites (DMS) were enriched with immune cell maturation and activation in the RSCZ group. Out of 2722 participants, the foremost DMS cg14341177 was hyper-methylated in the SCZ group and it inhibited the alternative splicing of its target gene BICD2 and may have increased its autoantigen exposure, leading to an increase in plasma anti-BICD2 IgG antibody levels. The levels of cg14341177 methylation and anti-BICD2 IgG decreased significantly in RSCZ endpoint samples but not in NRSCZ endpoint samples. There are strong positive correlations between cg14341177 methylation, anti-BICD2 IgG, and positive and negative syndrome scale (PANSS) scores in the RSCZ groups, but not in the NRSCZ groups. These data suggest that abnormal DNA methylation could affect autoreactive responses in SCZ, and that cg14341177 methylation and anti-BICD2 IgG levels may potentially serve as useful biomarkers.

Comprehensive Analysis of GDF10 Methylation Site-Associated Genes as Prognostic Markers for Endometrial Cancer.

Growth differentiation factor-10 (GDF10) with its methylation trait has recently been found to play a crucial regulatory and communication role in cancers. This investigation aims to identify GDF10 methylation site-associated genes that are closely associated with endometrial cancer (EC) patients' survival based on normal and UCEC samples from the UCSC Xena database. Our study revealed for the first time that EC exhibited significantly higher levels of GDF10 promoter methylation in comparison with normal tissues. Multiple differentiated methylation sites, which have prognostic value due to their apparent survival differences, were found in the GDF10 promoter region. We performed weighted gene coexpression network analysis (WGCNA) on EC tissues and paraneoplastic tissues while using these differentially methylated sites as phenotypes for selecting the most correlated key modules and their internal genes. To obtain a gene set, the key module genes and differentially expressed genes (DEGs) of EC were intersected. The least absolute shrinkage and selection operator (LASSO) regression along with multivariate Cox regression were performed from the gene set and we screened out the key genes B4GALNT3, DNAJC22, and GREB1. Finally, a prognostic model was validated for effectiveness based on these genes. Additionally, Kaplan-Meier analysis and time-dependent receiver operating characteristics (ROC) were applied to assess and verify the model, and they showed good prognosis prediction. Moreover, the differences in risk scores were statistically significant with age, tumor stage, and grade. They may be related to the immune infiltration of tumors as well. In conclusion, based on the methylation-related genes associated with GDF10, we developed a prognosis model for EC patients. It might provide a fresh view for further research and treatment of EC.

Profiling Genome-Wide DNA Methylation in Children with Autism Spectrum Disorder and in Children with Fragile X Syndrome.

Autism spectrum disorder (ASD) is an early onset, developmental disorder whose genetic cause is heterogeneous and complex. In total, 70% of ASD cases are due to an unknown etiology. Among the monogenic causes of ASD, fragile X syndrome (FXS) accounts for 2–4% of ASD cases, and 60% of individuals with FXS present with ASD. Epigenetic changes, specifically DNA methylation, which modulates gene expression levels, play a significant role in the pathogenesis of both disorders. Thus, in this study, using the Human Methylation EPIC Bead Chip, we examined the global DNA methylation profiles of biological samples derived from 57 age-matched male participants (2–6 years old), including 23 subjects with ASD, 23 subjects with FXS with ASD (FXSA) and 11 typical developing (TD) children. After controlling for technical variation and white blood cell composition, using the conservatory threshold of the false discovery rate (FDR ≤ 0.05), in the three comparison groups, TD vs. AD, TD vs. FXSA and ASD vs. FXSA, we identified 156, 79 and 3100 differentially methylated sites (DMS), and 14, 13 and 263 differential methylation regions (DMRs). Interestingly, several genes differentially methylated among the three groups were among those listed in the SFARI Gene database, including the PAK2, GTF2I and FOXP1 genes important for brain development. Further, enrichment analyses identified pathways involved in several functions, including synaptic plasticity. Our preliminary study identified a significant role of altered DNA methylation in the pathology of ASD and FXS, suggesting that the characterization of a DNA methylation signature may help to unravel the pathogenicity of FXS and ASD and may help the development of an improved diagnostic classification of children with ASD and FXSA. In addition, it may pave the way for developing therapeutic interventions that could reverse the altered methylome profile in children with neurodevelopmental disorders.

DNA methylation markers in peripheral blood for psoriatic arthritis

BackgroundThe clinical manifestations of psoriatic arthritis (PsA) are highly heterogeneous and no reliable diagnostic biomarkers exist. ObjectiveWe explored the role of DNA methylation CpG markers in the diagnosis of PsA. MethodsDNA methylation array was used to screen for differentially methylated sites (DMSs) in the discovery phase (PsA, n = 25; healthy controls [HCs], n = 19; psoriasis vulgaris [PsV], n = 20). In the validation phase, pyrosequencing was used to identify the DMSs in an expanded cohort (PsA, n = 60; HCs, n = 91; PsV, n = 48; rheumatoid arthritis [RA], n = 60). Logistic regression prediction models were established based on the identified DMSs for the diagnosis of PsA. ResultsA total of 17 DMSs differentiating PsA and HCs as well as 11 DMSs differentiating PsA and PsV were screened in the discovery phase. A total of six DMSs (chr14: cg07940072, chr14: 38061320, chr9: cg15734589, chr6: cg12800266, chr3: cg12992827, chr6: cg24500972) differentiating PsA and HCs and two DMSs (chr12: cg16459382, chr2: cg16348668) differentiating PsA and PsV were identified using pyrosequencing. Three logistic regression prediction models were established based on the identified DMSs, which distinguished PsA, RA, PsV, and HCs (P < 0.001). The models performed well in differentiating PsA from HCs, RA, and PsV (AUC: 0.858, 0.851, and 0.976, respectively). ConclusionsThe models based on methylated CpG sites are useful for distinguishing patients with PsA from HCs and those with RA or PsV and are a highly sensitive and specific diagnostic biomarker for PsA.

Epigenome-wide association studies of occupational exposure to benzene and formaldehyde

ABSTRACT Sufficient evidence supports a relationship between certain myeloid neoplasms and exposure to benzene or formaldehyde. DNA methylation could underlie benzene- and formaldehyde-induced health outcomes, but data in exposed human populations are limited. We conducted two cross-sectional epigenome-wide association studies (EWAS), one in workers exposed to benzene and another in workers exposed to formaldehyde. Using HumanMethylation450 BeadChips, we investigated differences in blood cell DNA methylation among 50 benzene-exposed subjects and 48 controls, and among 31 formaldehyde-exposed subjects and 40 controls. We performed CpG-level and regional-level analyses. In the benzene EWAS, we found genome-wide significant alterations, i.e., FWER-controlled P-values <0.05, in the mean and variance of methylation at 22 and 318 CpG sites, respectively, and in mean methylation of a large genomic region. Pathway analysis of genes corresponding to benzene-associated differential methylation sites revealed an impact on the AMPK signalling pathway. In formaldehyde-exposed subjects compared to controls, 9 CpGs in the DUSP22 gene promoter had genome-wide significant decreased methylation variability and a large region of the HOXA5 promoter with 44 CpGs was hypomethylated. Our findings suggest that DNA methylation may contribute to the pathogenesis of diseases related to benzene and formaldehyde exposure. Aberrant expression and methylation of HOXA5 previously has been shown to be clinically significant in myeloid leukaemias. The tumour suppressor gene DUSP22 is a potential biomarker of exposure to formaldehyde, and irregularities have been associated with multiple exposures and diseases.

Associations of Heavy Metals with Activities of Daily Living Disability: An Epigenome-Wide View of DNA Methylation and Mediation Analysis.

Background:Exposure to heavy metals has been reported to be associated with multiple diseases. However, direct associations and potential mechanisms of heavy metals with physical disability remain unclear.Objectives:We aimed to quantify associations of heavy metals with physical disability and further explore the potential mechanisms of DNA methylation on the genome scale.Methods:A cross-sectional study of 4,391 older adults was conducted and activities of daily living (ADL) disability were identified using a 14-item scale questionnaire including basic and instrumental activities to assess the presence of disability (yes or no) rated on a scale of dependence. Odds ratios (ORs) and 95% confidence intervals (CI) were estimated to quantify associations between heavy metals and ADL disability prevalence using multivariate logistic regression and Bayesian kernel machine regression (BKMR) models. Whole blood–derived DNA methylation was measured using the HumanMethylationEPIC BeadChip array. An ADL disability-related epigenome-wide DNA methylation association study (EWAS) was performed among 212 sex-matched ADL disability cases and controls, and mediation analysis was further applied to explore potential mediators of DNA methylation.Results:Each 1-standard deviation (SD) higher difference in -transformed manganese, copper, arsenic, and cadmium level was significantly associated with a 14% (95% CI: 1.05, 1.24), 16% (95% CI:1.07, 1.26), 22% (95% CI:1.13, 1.33), and 15% (95% CI:1.06, 1.26) higher odds of ADL disability, which remained significant in the multiple-metal and BKMR models. A total of 85 differential DNA methylation sites were identified to be associated with ADL disability prevalence, among which methylation level at cg220000984 and cg23012519 (annotated to IRGM and PKP3) mediated 31.0% and 31.2% of manganese-associated ADL disability prevalence, cg06723863 (annotated to ESRP2) mediated 32.4% of copper-associated ADL disability prevalence, cg24433124 (nearest to IER3) mediated 15.8% of arsenic-associated ADL disability prevalence, and cg07905190 and cg17485717 (annotated to FREM1 and TCP11L1) mediated 21.5% and 30.5% of cadmium-associated ADL disability prevalence (all ).Discussion:Our findings suggested that heavy metals contributed to higher prevalence of ADL disability and that locus-specific DNA methylation are partial mediators, providing potential biomarkers for further cellular mechanism studies. https://doi.org/10.1289/EHP10602

Hypomethylation of the opioid receptor delta 1 gene combined with high opioid receptor delta 1 protein levels indicates increased risk of gout.

BackgroundThe purpose of this study was to identify biomarkers for the diagnosis of gout in Chinese Han males using methylation microarray profiling.MethodsWe screened for differentially methylated genes (DMGs) in gout using a methylation microarray and analyzed the functions of the DMGs using gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. We verified gene methylation levels by pyrosequencing and protein levels by enzyme‐linked immunosorbent assays (ELISAs). Statistical analyses were performed using SPSS. Two‐sided p values <0.05 were deemed to be statistically significant for all analyses.ResultsWe identified 20,426 significant differential methylation sites (5719 high‐methylation sites and 14,707 low‐methylation sites). Bioinformatics analysis showed that the DMGs were mainly involved in 43 biological functions, 13 cellular components, 18 molecular functions, and 35 KEGG pathways. We selected opioid receptor delta 1 (OPRD1) for verification of methylation levels between 50 gout patients and 50 controls. The methylation levels of OPRD1 (Chr1:29,139,121) were significantly lower in the gout group (p < 0.05), while OPRD1 protein levels were significantly higher in the gout group (p < 0.05). In addition, the AUC of the combination of OPRD1 (Chr1:29,139,121) methylation and OPRD1 protein levels was 0.796 (0.710, 0.883) with a high sensitivity of 82% and a specificity of 68% (p < 0.001).ConclusionsThe combination of OPRD1 (Chr1:29,139,121) hypomethylation and high levels of OPRD1 protein is a potential biomarker for gout diagnosis.

Machine Learning-Based Epigenetic Classifiers for Axillary Staging of Patients with ER-Positive Early-Stage Breast Cancer.

In the era of molecular stratification and effective multimodality therapies, surgical staging of the axilla is becoming less relevant for patients with estrogen receptor (ER)-positive early-stage breast cancer (EBC). Therefore, a nonsurgical method for accurately predicting lymph node disease is the next step in the de-escalation of axillary surgery. This study sought to identify epigenetic signatures in the primary tumor that accurately predict lymph node status. We selected a cohort of patients in The Cancer Genome Atlas (TCGA) with ER-positive, HER2-negative invasive ductal carcinomas, and clinically-negative axillae (n = 127). Clinicopathological nomograms from the Memorial Sloan Kettering Cancer Center (MSKCC) and the MD Anderson Cancer Center (MDACC) were calculated. DNA methylation (DNAm) patterns from primary tumor specimens were compared between patients with pN0 and those with > pN0. The cohort was divided into training (n = 85) and validation (n = 42) sets. Random forest was employed to obtain the combinations of DNAm features with the highest accuracy for stratifying patients with > pN0. The most efficient combinations were selected according to the area under the curve (AUC). Clinicopathological models displayed a modest predictive potential for identifying > pN0 disease (MSKCC AUC 0.76, MDACC AUC 0.69, p = 0.15). Differentially methylated sites (DMS) between patients with pN0 and those with > pN0were identified (n = 1656). DMS showed a similar performance to the MSKCC model (AUC = 0.76, p = 0.83). Machine learning approaches generated five epigenetic classifiers, which showed higher discriminative potential than the clinicopathological variables tested (AUC > 0.88, p < 0.05). Epigenetic classifiers based on primary tumor characteristics can efficiently stratify patients with no lymph node involvement from those with axillary lymph node disease, thereby providing an accurate method of staging the axilla.

Uncovering of potential molecular markers for cervical squamous cell carcinoma (CESC) based on analysis of methylated-differentially expressed genes

ObjectiveCervical squamous cell carcinoma (CESC) is a cancer with high mortality caused by human papillomavirus. The aim of this study was to uncover potential CESC biomarkers to help early diagnosis and treatment. Materials and methodsThe mRNA transcriptome data and DNA methylation data were downloaded from database for the identification of differentially expressed mRNAs (DEmRNAs) and DNA methylation analysis. Functional analysis was used to reveal the molecular functions. Then, the association between differential methylation and DEmRNA was analyzed. Protein–protein interaction (PPI) network analysis was performed on the selected differentially methylated genes (DEGs). Subsequently, we analyzed the prognosis and constructed a prognostic risk model. We also performed diagnostic analyses of risk model genes. In addition, we verified the protein expression level of identified DEGs. Results1438 DEmRNAs, 1669 differentially methylated sites (DMSs), 46 differentially methylated CpG islands and 53 differential methylation genes (DMGs) were obtained. In PPI, the highest interaction scores were MX2 and IRF8, and their interaction score was 0.928. Interestingly, 5 DMGs were found to be associated with CESC prognosis. In addition, our results demonstrated that high risk score was associated with poor prognosis of CESC. Furthermore, it was found that ZIK1, ZNRF2, HHEX, VCAM1 could be diagnostic molecular markers for CESC. ConclusionAnalysis of methylated-differentially expressed genes may contribute to the identification of early diagnosis and therapeutic targets of CESC. In addition, a prognostic model based on 5 DMGs can be used to predict the prognosis of CESC.

Embryonic heat conditioning in chicks induces transgenerational heat/immunological resilience via methylation on regulatory elements

The question of whether behavioral traits are heritable is under debate. An obstacle in demonstrating transgenerational inheritance in mammals originates from the maternal environment's effect on offspring phenotype. Here, we used in ovo embryonic heat conditioning (EHC) of first-generation chicks, demonstrating heredity of both heat and immunological resilience, confirmed by a reduced fibril response in their untreated offspring to either heat or LPS challenge. Concordantly, transcriptome analysis confirmed that EHC induces changes in gene expression in the anterior preoptic hypothalamus (APH) that contribute to these phenotypes in the offspring. To study the association between epigenetic mechanisms and trait heritability, DNA-methylation patterns in the APH of offspring of control versus EHC fathers were evaluated. Genome-wide analysis revealed thousands of differentially methylated sites (DMSs), which were highly enriched in enhancers and CCCTC-binding factor (CTCF) sites. Overlap analysis revealed 110 differentially expressed genes that were associated with altered methylation, predominantly on enhancers. Gene-ontology analysis shows pathways associated with immune response, chaperone-mediated protein folding, and stress response. For the proof of concept, we focused on HSP25 and SOCS3, modulators of heat and immune responses, respectively. Chromosome conformational capture (3C) assay identified interactions between their promoters and methylated enhancers, with the strongest frequency on CTCF binding sites. Furthermore, gene expression corresponded with the differential methylation patterns, and presented increased CTCF binding in both hyper- and hypomethylated DMSs. Collectively, we demonstrate that EHC induces transgenerational thermal and immunological resilience traits. We propose that one of the mechanisms underlying inheritance depends on three-dimensional (3D) chromatin reorganization.

DNA Methylation Difference between Female and Male Ussuri Catfish (Pseudobagrus ussuriensis) in Brain and Gonad Tissues.

DNA methylation has been found to be involved in sex determination and differentiation in many aquaculture species. The Ussuri catfish (Pseudobagrus ussuriensis) is a popular aquaculture fish in China with high economic value in which male-biased sex dimorphism was observed in terms of body size and body weight. In this study, DNA methylation-sensitive RAD sequencing (Methyl-RAD) was used to explore the epigenetic difference between adult male and female samples in brain and gonad tissues. In brain tissues, 5,442,496 methylated cytosine sites were found and 9.94% of these sites were from symmetric CCGG or CCWGG sites. Among these sites, 321 differential DNA methylation sites (DMSs) in 171 genes were identified, while in gonad tissues, 4,043,053 methylated cytosines sites were found in total and 11.70% of them were from CCGG or CCWGG. Among these sites, 78 differential DNA methylation sites were found which were located in 64 genes. We also found several sex-determination genes among these differential methylated genes, such as amh, gsdf and hsd11b2 in brain tissues and slco3a1, socs2 and trim47 in gonad tissues. These results provided evidence for understanding the function of DNA methylation in the sex differentiation in Pseudobagrus ussuriensis, which further deepens the relationship between gene regulation and epigenetics.