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Systemic low-grade inflammation is a feature of chronic disease. C-reactive protein (CRP) is a common biomarker of inflammation and used as an indicator of disease risk; however, the role of inflammation in disease is not completely understood. Methylation is an epigenetic modification in the DNA which plays a pivotal role in gene expression. In this study we evaluated differential DNA methylation patterns associated with blood CRP level to elucidate biological pathways and genetic regulatory mechanisms to improve the understanding of chronic inflammation. The racially and ethnically diverse participants in this study were included as 50% White, 41% Black or African American, 7% Hispanic or Latino/a, and 2% Native Hawaiian, Asian American, American Indian, or Alaska Native (total n = 13,433) individuals. We replicated 113 CpG sites from 87 unique loci, of which five were novel (CADM3, NALCN, NLRC5, ZNF792, and cg03282312), across a discovery set of 1,150 CpG sites associated with CRP level (p

Children born via cesarean delivery have a higher risk of metabolic, immunological, and neurodevelopmental disorders compared to those born via vaginal delivery, although mechanisms remain unclear. We conducted a meta-analysis of epigenome-wide association studies to examine the associations between delivery mode and blood DNA methylation at birth and its persistence in early childhood. Participants were from 19 pregnancy cohorts (9833 term newborns) and 6 pediatric cohorts (2429 children aged 6 to 10 years). We identified six CpGs in cord blood associated with cesarean delivery (effect size range: 0.4 to 0.7%, P < 1.0 × 10-7): MAP2K2 (cg19423175), LIM2 (cg01500140), CNP (cg13917614), BLM (cg18247172), RASA3 (cg22348356), and RUNX3 (cg20674490), independent of cell proportions and other confounders. In childhood, none of these CpGs were associated with cesarean delivery, and no additional CpGs were identified. Delivery mode was associated with cell proportions at birth but not in childhood. Further research is needed to elucidate cesarean deliverys molecular influence on offspring health.

Somatic hypermutation in cancer has gained momentum with the increased use of tumour mutation burden as a biomarker for immune checkpoint inhibitors. Spontaneous deamination of 5-methylcytosine to thymine at CpG dinucleotides is one of the most ubiquitous endogenous mutational processes in normal and cancer cells. Here, we performed a systematic investigation of somatic CpG hypermutation at a pan-cancer level. We studied 30,191 cancer patients and 103 cancer types and developed an algorithm to identify somatic CpG hypermutation. Across cancer types, we observed the highest prevalence in paediatric leukaemia (3.5%), paediatric high-grade glioma (1.7%), and colorectal cancer (1%). We discovered germline variants and somatic mutations in the mismatch repair complex MutSα (MSH2-MSH6) as genetic drivers of somatic CpG hypermutation in cancer, which frequently converged on CpG sites and TP53 driver mutations. We further observe an association between somatic CpG hypermutation and response to immune checkpoint inhibitors. Overall, our study identified novel cancer types that display somatic CpG hypermutation, strong association with MutSα-deficiency, and potential utility in cancer immunotherapy.

Worldwide trends to delay childbearing have increased parental ages at birth. Older parental age may harm offspring health, but mechanisms remain unclear. Alterations in offspring DNA methylation (DNAm) patterns could play a role as aging has been associated with methylation changes in gametes of older individuals. We meta-analyzed epigenome-wide associations of parental age with offspring blood DNAm of over 9500 newborns and 2000 children (5-10 years old) from the Pregnancy and Childhood Epigenetics consortium. In newborns, we identified 33 CpG sites in 13 loci with DNAm associated with maternal age (PFDR

Whole-genome bisulfite sequencing (BS-Seq) measures cytosine methylation changes at single-base resolution and can be used to profile cell-free DNA (cfDNA). In plasma, ultrashort single-stranded cfDNA (uscfDNA, ∼50 nt) has been identified together with 167 bp double-stranded mononucleosomal cell-free DNA (mncfDNA). However, the methylation profile of uscfDNA has not been described. Conventional BS-Seq workflows may not be helpful because bisulfite conversion degrades larger DNA into smaller fragments, leading to erroneous categorization as uscfDNA. We describe the '5mCAdpBS-Seq' workflow in which pre-methylated 5mC (5-methylcytosine) single-stranded adapters are ligated to heat-denatured cfDNA before bisulfite conversion. This method retains only DNA fragments that are unaltered by bisulfite treatment, resulting in less biased uscfDNA methylation analysis. Using 5mCAdpBS-Seq, uscfDNA had lower levels of DNA methylation (∼15%) compared to mncfDNA and was enriched in promoters and CpG islands. Hypomethylated uscfDNA fragments were enriched in upstream transcription start sites (TSSs), and the intensity of enrichment was correlated with expressed genes of hemopoietic cells. Using tissue-of-origin deconvolution, we inferred that uscfDNA is derived primarily from eosinophils, neutrophils, and monocytes. As proof-of-principle, we show that characteristics of the methylation profile of uscfDNA can distinguish non-small cell lung carcinoma from non-cancer samples. The 5mCAdpBS-Seq workflow is recommended for any cfDNA methylation-based investigations.

Previous research has found that living in a disadvantaged neighborhood is associated with poor health outcomes. Living in disadvantaged neighborhoods may alter inflammation and immune response in the body, which could be reflected in epigenetic mechanisms such as DNA methylation (DNAm). We used robust linear regression models to conduct an epigenome-wide association study examining the association between neighborhood deprivation (Area Deprivation Index; ADI), and DNAm in brain tissue from 159 donors enrolled in the Emory Goizueta Alzheimers Disease Research Center (Georgia, USA). We found one CpG site (cg26514961, gene PLXNC1) significantly associated with ADI after controlling for covariates and multiple testing (p-value=5.0e-8). Effect modification by APOE ε4 was statistically significant for the top ten CpG sites from the EWAS of ADI, indicating that the observed associations between ADI and DNAm were mainly driven by donors who carried at least one APOE ε4 allele. Four of the top ten CpG sites showed a significant concordance between brain tissue and tissues that are easily accessible in living individuals (blood, buccal cells, saliva), including DNAm in cg26514961 (PLXNC1). Our study identified one CpG site (cg26514961, PLXNC1 gene) that was significantly associated with neighborhood deprivation in brain tissue. PLXNC1 is related to immune response, which may be one biological pathway how neighborhood conditions affect health. The concordance between brain and other tissues for our top CpG sites could make them potential candidates for biomarkers in living individuals.

Purpose: Renal cell carcinoma (RCC) is a common malignancy, with patients frequently diagnosed at an advanced stage due to the absence of sufficiently sensitive detection technologies, significantly compromising patient survival and quality of life. Advances in cell-free DNA (cfDNA) methylation profiling using liquid biopsies offer a promising non-invasive diagnostic option, but robust biomarkers for early detection are current not available. This study aimed to identify methylation biomarkers for RCC and establish a DNA methylation signature-based prognostic model for this disease. Methods: High-throughput methylation sequencing was performed on peripheral blood samples obtained from 49 primarily Stage I RCC patients and 44 healthy controls. Comparative analysis and Least Absolute Shrinkage and Selection Operator (LASSO) regression methods were employed to identify RCC methylation signatures.Subsequently, methylation markers-based diagnostic and prognostic models for RCC were independently trained and validated using random forest and Cox regression methodologies, respectively. Results: Comparative analysis revealed 864 differentially methylated CpG islands (DMCGIs), 96.3% of which were hypermethylated. Using a training set from The Cancer Genome Atlas (TCGA) dataset of 443 early-stage RCC tumors and matched normal tissues, we applied LASSO regression and identified 23 methylation signatures. We then constructed a random forest-based diagnostic model for early-stage RCC and validated the model using two independent datasets: a TCGA set of 460 RCC tumors and controls, and a blood sample set from our study of 15 RCC cases and 29 healthy controls. For Stage I RCC tissue, the model showed excellent discrimination (AUC-ROC: 0.999, sensitivity: 98.5%, specificity: 100%). Blood sample validation also yielded commendable results (AUC-ROC: 0.852, sensitivity: 73.9%, specificity: 89.7%). Further analysis using Cox regression identified 7 of the 23 DMCGIs as prognostic markers for RCC, allowing the development of a prognostic model with strong predictive power for 1-, 3-, and 5-year survival (AUC-ROC > 0.7). Conclusions: Our findings highlight the critical role of hypermethylation in RCC etiology and progression, and present these identified biomarkers as promising candidates for diagnostic and prognostic applications. [ABSTRACT FROM AUTHOR]

This study aimed to investigate whether genes with different modes of inheritance differ in the presence of promoter-enriched CGI loci. For each autosomal chromosome, the author searched for variations in the total number of diseases' phenotypes with autosomal dominant (AD) and recessive (AR) inheritance for a list of promoter-poor CGI (CGI−) and promoter-enriched CGI (CGI+) genes using the OMIM database. Then, the CGI− and CGI+ genes displaying random allelic or bi-allelic expression were examined. The author evaluated whether there was a distinct distribution of AD and AR diseases in the groups of chromosomes based on their SNP hotspot density. The same analysis was conducted for the X chromosome. The SPSS statistical package was utilized. The distribution of AD and AR diseases between CGI− and CGI+ bi-allelic genes significantly differed in autosomal chromosomes 6 and 17, which show intermediate SNP hotspot density. Additionally, a statistically significant difference was observed in AD and AR diseases in the remaining autosomal chromosomes with low SNP hotspots between their randomly allelic expressed CGI− and CGI+ genes. Specifically, AD diseases were related to CGI− genes, while AR diseases were associated with CGI+ genes. In the X chromosome, X-linked dominant (XLD) diseases were mainly found in CGI+ genes, and X-linked recessive (XLR) diseases were found in CGI− genes, regardless of the X-inactivation process. It is essential to study inheritance and classify genetic variants in a more stochastic way than the terms "Dominant" and "Recessive," and their derivatives, such as "Codominant" and "Incomplete Dominant," are applied in Mendelian and non-Mendelian inheritance. This concept may further explain the "Reduced Penetrance" and "Variable Expressivity" in certain human diseases. All the above suggests a need to reassess how genetic and epigenetic data are studied and utilized for genetic counseling or precision medicine. [ABSTRACT FROM AUTHOR]

Background: Tooth movement induced orofacial pain is the most cited negative effect during orthodontic treatment, while treatment options without side effects are limited. The differential expression of pain-related genes due to DNA methylation and demethylation is instrumental in pain. The purpose of the study was to evaluate the DNA methylation profiling of CpG islands (CGI) and CGI shores in promoter regions in trigeminal ganglions (TG) of tooth movement induced orofacial pain rats, thus to further insight the DNA methylation regulation in orofacial pain. Materials and methods: An orofacial pain rat model was constructed by ligating coil springs between the incisor and first maxillary molar with 40 g of force. The Rat Grimace Score (RGS) was used for pain evaluation. The genome methylation status was analyzed by the reduced representation bisulfite sequencing (RRBS) technique. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses were conducted in the differentially methylated regions (DMRs). Moreover, a protein-protein interaction (PPI) network was established to detect annotated genes associated with pain. Results: RGS was significantly higher in orofacial pain rats than in sham rats. RRBS showed widespread methylation changes in CGI and CGI shores in TG promoter regions. Both 902 hypermethylated DMRs and 862 hypomethylated DMRs were found in the CGIs of promoter regions. KEGG analysis revealed that annotated genes are participated in endocrine, nervous, immune, and sensory systems. Moreover, the "Calcium signaling pathway", "Wnt signaling pathway" and "Neuroactive ligand-receptor interaction" were significantly enriched pathways. Furthermore, PPI network showed several genes (Ctnnb1, Dlg4, Creb1, Camk2g, Bmp2, etc.) with different methylation statuses were reported to be associated with pain. Conclusions: This study demonstrated methylation changes were existed in CGI and CGI shores in TG promoter regions when pain occurs, thus providing a basis for further study on the mechanism of DNA methylation in orofacial pain. [ABSTRACT FROM AUTHOR]

Abstract Background Tooth movement induced orofacial pain is the most cited negative effect during orthodontic treatment, while treatment options without side effects are limited. The differential expression of pain-related genes due to DNA methylation and demethylation is instrumental in pain. The purpose of the study was to evaluate the DNA methylation profiling of CpG islands (CGI) and CGI shores in promoter regions in trigeminal ganglions (TG) of tooth movement induced orofacial pain rats, thus to further insight the DNA methylation regulation in orofacial pain. Materials and methods An orofacial pain rat model was constructed by ligating coil springs between the incisor and first maxillary molar with 40 g of force. The Rat Grimace Score (RGS) was used for pain evaluation. The genome methylation status was analyzed by the reduced representation bisulfite sequencing (RRBS) technique. Gene ontology (GO) and kyoto encyclopedia of genes and genomes (KEGG) analyses were conducted in the differentially methylated regions (DMRs). Moreover, a protein-protein interaction (PPI) network was established to detect annotated genes associated with pain. Results RGS was significantly higher in orofacial pain rats than in sham rats. RRBS showed widespread methylation changes in CGI and CGI shores in TG promoter regions. Both 902 hypermethylated DMRs and 862 hypomethylated DMRs were found in the CGIs of promoter regions. KEGG analysis revealed that annotated genes are participated in endocrine, nervous, immune, and sensory systems. Moreover, the “Calcium signaling pathway”, “Wnt signaling pathway” and “Neuroactive ligand-receptor interaction” were significantly enriched pathways. Furthermore, PPI network showed several genes (Ctnnb1, Dlg4, Creb1, Camk2g, Bmp2, etc.) with different methylation statuses were reported to be associated with pain. Conclusions This study demonstrated methylation changes were existed in CGI and CGI shores in TG promoter regions when pain occurs, thus providing a basis for further study on the mechanism of DNA methylation in orofacial pain.

BackgroundSystemic lupus erythematosus (SLE) has numerous symptoms across organs and an unpredictable flare-remittance pattern. This has made it challenging to understand drivers of long-term SLE outcomes. Our objective was to identify whether changes in DNA methylation over time, in an actively flaring SLE cohort, were associated with remission and whether these changes meaningfully subtype SLE patients.MethodsFifty-nine multi-ethnic SLE patients had clinical visits and DNA methylation profiles at a flare and approximately 3 months later. Methylation was measured using the Illumina EPIC array. We identified sites where methylation change between visits was associated with remission at the follow-up visit using limma package and a time x remission interaction term. Models adjusted for batch, age at diagnosis, time between visits, age at flare, sex, medications, and cell-type proportions. Separately, a paired T-test identified Bonferroni significant methylation sites with ≥ 3% change between visits (n = 546). Methylation changes at these sites were used for unsupervised consensus hierarchical clustering. Associations between clusters and patient features were assessed.ResultsNineteen patients fully remitted at the follow-up visit. For 1,953 CpG sites, methylation changed differently for remitters vs. non-remitters (Bonferroni p

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

BackgroundEpigenome-wide association studies have identified multiple DNA methylation sites (CpGs) associated with alcohol consumption, an important lifestyle risk factor for cardiovascular diseases. This study aimed to test the hypothesis that an alcohol consumption epigenetic risk score (ERS) is associated with blood pressure (BP) traits.ResultsWe implemented an ERS based on a previously reported epigenetic signature of 144 alcohol-associated CpGs in meta-analysis of participants of European ancestry. We found a one-unit increment of ERS was associated with eleven drinks of alcohol consumed per day, on average, across several cohorts (p

Chronic kidney disease (CKD) impacts about 1 in 7 adults in the United States, but African Americans (AAs) carry a disproportionately higher burden of disease. Epigenetic modifications, such as DNA methylation at cytosine-phosphate-guanine (CpG) sites, have been linked to kidney function and may have clinical utility in predicting the risk of CKD. Given the dynamic relationship between the epigenome, environment, and disease, AAs may be especially sensitive to environment-driven methylation alterations. Moreover, risk models incorporating CpG methylation have been shown to predict disease across multiple racial groups. In this study, we developed a methylation risk score (MRS) for CKD in cohorts of AAs. We selected nine CpG sites that were previously reported to be associated with estimated glomerular filtration rate (eGFR) in epigenome-wide association studies to construct a MRS in the Hypertension Genetic Epidemiology Network (HyperGEN). In logistic mixed models, the MRS was significantly associated with prevalent CKD and was robust to multiple sensitivity analyses, including CKD risk factors. There was modest replication in validation cohorts. In summary, we demonstrated that an eGFR-based CpG score is an independent predictor of prevalent CKD, suggesting that MRS should be further investigated for clinical utility in evaluating CKD risk and progression.

DNA methylation is an essential component of transposable element (TE) silencing, yet the mechanism by which methylation causes transcriptional repression remains poorly understood1-5. Here we study the Arabidopsis thaliana Methyl-CpG Binding Domain (MBD) proteins MBD1, MBD2 and MBD4 and show that MBD2 acts as a TE repressor during male gametogenesis. MBD2 bound chromatin regions containing high levels of CG methylation, and MBD2 was capable of silencing the FWA gene when tethered to its promoter. MBD2 loss caused activation at a small subset of TEs in the vegetative cell of mature pollen without affecting DNA methylation levels, demonstrating that MBD2-mediated silencing acts strictly downstream of DNA methylation. TE activation in mbd2 became more significant in the mbd5 mbd6 and adcp1 mutant backgrounds, suggesting that MBD2 acts redundantly with other silencing pathways to repress TEs. Overall, our study identifies MBD2 as a methyl reader that acts downstream of DNA methylation to silence TEs during male gametogenesis.

Age-associated changes in DNA methylation have been characterized across various animals, but not yet in amphibians, which are of particular interest because they include widely studied model organisms. In this study, we present clear evidence that the aquatic vertebrate species Xenopus tropicalis displays patterns of age-associated changes in DNA methylation. We have generated whole-genome bisulfite sequencing (WGBS) profiles from skin samples of nine frogs representing young, mature, and old adults and characterized the gene- and chromosome-scale DNA methylation changes with age. Many of the methylation features and changes we observe are consistent with what is known in mammalian species, suggesting that the mechanism of age-related changes is conserved. Moreover, we selected a few thousand age-associated CpG sites to build an assay based on targeted DNA methylation analysis (TBSseq) to expand our findings in future studies involving larger cohorts of individuals. Preliminary results of a pilot TBSeq experiment recapitulate the findings obtained with WGBS setting the basis for the development of an epigenetic clock assay. The results of this study will allow us to leverage the unique resources available for Xenopus to study how DNA methylation relates to other hallmarks of ageing.

In this study, we analyzed the regulatory properties of 26 (twenty-six) genes associated with nonsyndromic male infertility. We applied an in silico analysis in order to determine the number and distribution of promoters and identify relevant promoter consensus sequences and potential transcription factors. Underlining the concept of alternative transcriptional initiation (ATI), we have found that 65.4% of genes associated with nonsyndromic male infertility have 1 (one) to 6 (six) promoters, located in the region 1 kb upstream of the TSS, and 41% of them are located at a position below −500 bp. Although the TATA box consensus sequence TAWAAA, such as W is A or T, appears at a common location in all genes, it is shifted for at least 10 bp in the EFCAB9 gene. The C2H2 zinc finger is found to be the most significant common transcription factor, binding genes' promoters GLIS1, ZSCAN21, GLIS3, GLIS1, ZNF770, ZNF780A, ZNF81, and ZNF264. On the other hand, basic leucine zipper factors (bZIPs) bind the JUNB gene promoter specifically, exhibiting unique regulatory properties of all genes associated with nonsyndromic male infertility. Two genes, NANOS1 and ZMYND15, are expected to be less susceptible to DNA methylation, due to the high density of CpG content found in their promoter regions. [ABSTRACT FROM AUTHOR]

Single-nucleotide variants (SNVs) in segmental duplications (SDs) have not been systematically assessed because of the limitations of mapping short-read sequencing data1,2. Here we constructed 1:1 unambiguous alignments spanning high-identity SDs across 102 human haplotypes and compared the pattern of SNVs between unique and duplicated regions3,4. We find that human SNVs are elevated 60% in SDs compared to unique regions and estimate that at least 23% of this increase is due to interlocus gene conversion (IGC) with up to 4.3 megabase pairs of SD sequence converted on average per human haplotype. We develop a genome-wide map of IGC donors and acceptors, including 498 acceptor and 454 donor hotspots affecting the exons of about 800 protein-coding genes. These include 171 genes that have 'relocated' on average 1.61 megabase pairs in a subset of human haplotypes. Using a coalescent framework, we show that SD regions are slightly evolutionarily older when compared to unique sequences, probably owing to IGC. SNVs in SDs, however, show a distinct mutational spectrum: a 27.1% increase in transversions that convert cytosine to guanine or the reverse across all triplet contexts and a 7.6% reduction in the frequency of CpG-associated mutations when compared to unique DNA. We reason that these distinct mutational properties help to maintain an overall higher GC content of SD DNA compared to that of unique DNA, probably driven by GC-biased conversion between paralogous sequences5,6.

BACKGROUND: Fibrinogen plays an essential role in blood coagulation and inflammation. Circulating fibrinogen levels may be determined based on interindividual differences in DNA methylation at cytosine-phosphate-guanine (CpG) sites and vice versa. OBJECTIVES: To perform an EWAS to examine an association between blood DNA methylation levels and circulating fibrinogen levels to better understand its biological and pathophysiological actions. METHODS: We performed an epigenome-wide association study of circulating fibrinogen levels in 18 037 White, Black, American Indian, and Hispanic participants, representing 14 studies from the Cohorts for Heart and Aging Research in Genomic Epidemiology consortium. Circulating leukocyte DNA methylation was measured using the Illumina 450K array in 12 904 participants and using the EPIC array in 5133 participants. In each study, an epigenome-wide association study of fibrinogen was performed using linear mixed models adjusted for potential confounders. Study-specific results were combined using array-specific meta-analysis, followed by cross-replication of epigenome-wide significant associations. We compared models with and without CRP adjustment to examine the role of inflammation. RESULTS: We identified 208 and 87 significant CpG sites associated with fibrinogen levels from the 450K (p < 1.03 × 10-7) and EPIC arrays (p < 5.78 × 10-8), respectively. There were 78 associations from the 450K array that replicated in the EPIC array and 26 vice versa. After accounting for overlapping sites, there were 83 replicated CpG sites located in 61 loci, of which only 4 have been previously reported for fibrinogen. The examples of genes located near these CpG sites were SOCS3 and AIM2, which are involved in inflammatory pathways. The associations of all 83 replicated CpG sites were attenuated after CRP adjustment, although many remained significant. CONCLUSION: We identified 83 CpG sites associated with circulating fibrinogen levels. These associations are partially driven by inflammatory pathways shared by both fibrinogen and CRP.

This study sought to examine the association between DNA methylation and body mass index (BMI) and the potential of BMI-associated cytosine-phosphate-guanine (CpG) sites to provide information about metabolic health. We pooled summary statistics from six trans-ethnic epigenome-wide association studies (EWASs) of BMI representing nine cohorts (n = 17,034), replicated these findings in the Womens Health Initiative (WHI, n = 4,822), and developed an epigenetic prediction score of BMI. In the pooled EWASs, 1,265 CpG sites were associated with BMI (p

Despite the prognostic value of arterial stiffness (AS) and pulsatile hemodynamics (PH) for cardiovascular morbidity and mortality, epigenetic modifications that contribute to AS/PH remain unknown. To gain a better understanding of the link between epigenetics (DNA methylation) and AS/PH, we examined the relationship of eight measures of AS/PH with CpG sites and co-methylated regions using multi-ancestry participants from Trans-Omics for Precision Medicine (TOPMed) Multi-Ethnic Study of Atherosclerosis (MESA) with sample sizes ranging from 438 to 874. Epigenome-wide association analysis identified one genome-wide significant CpG (cg20711926-CYP1B1) associated with aortic augmentation index (AIx). Follow-up analyses, including gene set enrichment analysis, expression quantitative trait methylation analysis, and functional enrichment analysis on differentially methylated positions and regions, further prioritized three CpGs and their annotated genes (cg23800023-ETS1, cg08426368-TGFB3, and cg17350632-HLA-DPB1) for AIx. Among these, ETS1 and TGFB3 have been previously prioritized as candidate genes. Furthermore, both ETS1 and HLA-DPB1 have significant tissue correlations between Whole Blood and Aorta in GTEx, which suggests ETS1 and HLA-DPB1 could be potential biomarkers in understanding pathophysiology of AS/PH. Overall, our findings support the possible role of epigenetic regulation via DNA methylation of specific genes associated with AIx as well as identifying potential targets for regulation of AS/PH.

BackgroundCongenital heart defects (CHDs) affect approximately half of individuals with Down syndrome (DS), but the molecular reasons for incomplete penetrance are unknown. Previous studies have largely focused on identifying genetic risk factors associated with CHDs in individuals with DS, but comprehensive studies of the contribution of epigenetic marks are lacking. We aimed to identify and characterize DNA methylation differences from newborn dried blood spots (NDBS) of DS individuals with major CHDs compared to DS individuals without CHDs.MethodsWe used the Illumina EPIC array and whole-genome bisulfite sequencing (WGBS) to quantitate DNA methylation for 86 NDBS samples from the California Biobank Program: (1) 45 DS-CHD (27 female, 18 male) and (2) 41 DS non-CHD (27 female, 14 male). We analyzed global CpG methylation and identified differentially methylated regions (DMRs) in DS-CHD versus DS non-CHD comparisons (both sex-combined and sex-stratified) corrected for sex, age of blood collection, and cell-type proportions. CHD DMRs were analyzed for enrichment in CpG and genic contexts, chromatin states, and histone modifications by genomic coordinates and for gene ontology enrichment by gene mapping. DMRs were also tested in a replication dataset and compared to methylation levels in DS versus typical development (TD) WGBS NDBS samples.ResultsWe found global CpG hypomethylation in DS-CHD males compared to DS non-CHD males, which was attributable to elevated levels of nucleated red blood cells and not seen in females. At a regional level, we identified 58, 341, and 3938 CHD-associated DMRs in the Sex Combined, Females Only, and Males Only groups, respectively, and used machine learning algorithms to select 19 Males Only loci that could distinguish CHD from non-CHD. DMRs in all comparisons were enriched for gene exons, CpG islands, and bivalent chromatin and mapped to genes enriched for terms related to cardiac and immune functions. Lastly, a greater percentage of CHD-associated DMRs than background regions were differentially methylated in DS versus TD samples.ConclusionsA sex-specific signature of DNA methylation was detected in NDBS of DS-CHD compared to DS non-CHD individuals. This supports the hypothesis that epigenetics can reflect the variability of phenotypes in DS, particularly CHDs.

BackgroundGenetic variants can modulate phenotypic outcomes via epigenetic intermediates, for example at methylation quantitative trait loci (mQTL). We present the first large-scale assessment of mQTL at human genomic regions selected for interindividual variation in CpG methylation, which we call correlated regions of systemic interindividual variation (CoRSIVs). These can be assayed in blood DNA and do not reflect interindividual variation in cellular composition.ResultsWe use target-capture bisulfite sequencing to assess DNA methylation at 4086 CoRSIVs in multiple tissues from each of 188 donors in the NIH Gene-Tissue Expression (GTEx) program. At CoRSIVs, DNA methylation in peripheral blood correlates with methylation and gene expression in internal organs. We also discover unprecedented mQTL at these regions. Genetic influences on CoRSIV methylation are extremely strong (median R2=0.76), cumulatively comprising over 70-fold more human mQTL than detected in the most powerful previous study. Moreover, mQTL beta coefficients at CoRSIVs are highly skewed (i.e., the major allele predicts higher methylation). Both surprising findings are independently validated in a cohort of 47 non-GTEx individuals. Genomic regions flanking CoRSIVs show long-range enrichments for LINE-1 and LTR transposable elements; the skewed beta coefficients may therefore reflect evolutionary selection of genetic variants that promote their methylation and silencing. Analyses of GWAS summary statistics show that mQTL polymorphisms at CoRSIVs are associated with metabolic and other classes of disease.ConclusionsA focus on systemic interindividual epigenetic variants, clearly enhanced in mQTL content, should likewise benefit studies attempting to link human epigenetic variation to the risk of disease.

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

Epigenome-wide association studies (EWAS) are widely implemented in epidemiology, and the Illumina HumanMethylationEPIC BeadChip (EPIC) DNA microarray is the most-used technology. Recently, next-generation sequencing (NGS)-based methods, which assess DNA methylation at single-base resolution, have become more affordable and technically feasible. While the content of microarray technology is fixed, NGS-based approaches, such as the Roche Nimblegen, SeqCap Epi Enrichment System (SeqCap), offer the flexibility of targeting most CpGs in a gene. With the current usage of microarrays and emerging NGS-based technologies, it is important to establish whether data generated from the two platforms are comparable. We harnessed 112 samples from the Center for the Health Assessment of Mothers and Children of Salinas (CHAMACOS) birth cohort study and compared DNA methylation between the EPIC microarray and SeqCap for PON1 and nine additional candidate genes, by evaluating epigenomic coverage and correlations. We conducted multivariable linear regression and principal component analyses to assess the ability of the EPIC array and SeqCap to detect biological differences in gene methylation by the PON1-108 single nucleotide polymorphism. We found an overall high concordance (r = 0.84) between SeqCap and EPIC DNA methylation, among highly methylated and minimally methylated regions. However, substantial disagreement was present between the two methods in moderately methylated regions, with SeqCap measurements exhibiting greater within-site variation. Additionally, SeqCap did not capture PON1 SNP associated differences in DNA methylation that were evident with the EPIC array. Our findings indicate that microarrays perform well for analysing DNA methylation in large cohort studies but with limited coverage.

Aim: To identify differential methylation related to prescribed opioid use. Methods: This study examined whether blood DNA methylation, measured using Illumina arrays, differs by recent opioid medication use in four population-based cohorts. We meta-analyzed results (282 users; 10,560 nonusers) using inverse-variance weighting. Results: Differential methylation (false discovery rate

BackgroundIdentifying blood-based DNA methylation patterns is a minimally invasive way to detect biomarkers in predicting age, characteristics of certain diseases and conditions, as well as responses to immunotherapies. As microarray platforms continue to evolve and increase the scope of CpGs measured, new discoveries based on the most recent platform version and how they compare to available data from the previous versions of the platform are unknown. The neutrophil dexamethasone methylation index (NDMI 850) is a blood-based DNA methylation biomarker built on the Illumina MethylationEPIC (850K) array that measures epigenetic responses to dexamethasone (DEX), a synthetic glucocorticoid often administered for inflammation. Here, we compare the NDMI 850 to one we built using data from the Illumina Methylation 450K (NDMI 450).ResultsThe NDMI 450 consisted of 22 loci, 15 of which were present on the NDMI 850. In adult whole blood samples, the linear composite scores from NDMI 450 and NDMI 850 were highly correlated and had equivalent predictive accuracy for detecting DEX exposure among adult glioma patients and non-glioma adult controls. However, the NDMI 450 scores of newborn cord blood were significantly lower than NDMI 850 in samples measured with both assays.ConclusionsWe developed an algorithm that reproduces the DNA methylation glucocorticoid response score using 450K data, increasing the accessibility for researchers to assess this biomarker in archived or publicly available datasets that use the 450K version of the Illumina BeadChip array. However, the NDMI850 and NDMI450 do not give similar results in cord blood, and due to data availability limitations, results from sample types of newborn cord blood should be interpreted with care.

BackgroundMyeloid-derived suppressor cells (MDSCs), which include monocytic (mMDSCs) and granulocytic (gMDSCs) cells, are an immunosuppressive, heterogeneous population of cells upregulated in cancer and other pathologic conditions, in addition to normal conditions of stress. The origin of MDSCs is debated, and the regulatory pattern responsible for gMDSC differentiation remains unknown. Since DNA methylation (DNAm) contributes to lineage differentiation, we have investigated whether it contributes to the acquisition of the gMDSC phenotype.ResultsUsing the Illumina EPIC array to measure DNAm of gMDSCs and neutrophils from diverse neonatal and adult blood sources, we found 189 differentially methylated CpGs between gMDSCs and neutrophils with a core of ten differentially methylated CpGs that were consistent across both sources of cells. Genes associated with these loci that are involved in immune responses include VCL, FATS, YAP1, KREMEN2, UBTF, MCC-1, and EFCC1. In two cancer patient groups that reflected those used to develop the methylation markers (head and neck squamous cell carcinoma (HNSCC) and glioma), all of the CpG loci were differentially methylated, reaching statistical significance in glioma cases and controls, while one was significantly different in the smaller HNSCC group.ConclusionsOur findings indicate that gMDSCs have a core of distinct DNAm alterations, informing future research on gMDSC differentiation and function.

ObjectiveFindings from cross-sectional studies have revealed associations between DNA methylation and systemic lupus erythematosus (SLE) outcomes. This study was undertaken to investigate the dynamics of DNA methylation by examining participants from an SLE longitudinal cohort using samples collected at 2 time points.MethodsA total of 101 participants from the California Lupus Epidemiology Study were included in our analysis. DNA was extracted from blood samples collected at the time of enrolment in the cohort and samples collected after 2 years and was analyzed using Illumina EPIC BeadChip kit. Paired t-tests were used to identify genome-wide changes which included 256 CpG sites previously found to be associated with SLE subtypes. Linear mixed models were developed to understand the relationship between DNA methylation and disease activity, medication use, and sample cell-type proportions, adjusted for age, sex, and genetic principal components.ResultsThe majority of CpGs that were previously determined to be associated with SLE subtypes remained stable over 2 years (185 CpGs [72.3%]; t-test false discovery rate >0.05). Compared to background genome-wide methylation, there was an enrichment of SLE subtype-associated CpGs that changed over time (27.7% versus 0.34%). Changes in cell-type proportions were associated with changes at 67 CpGs (P

Background: Methylation plays a crucial role in genome regulation, serving as an essential epigenetic mechanism. CpG islands, which are regions of DNA rich in CpG dinucleotides, are ubiquitous epigenetic regulatory features that can modulate the functional dynamics of genes, thereby influencing the pathophysiology of pathogenic organisms within a host. Objectives: In this study, we aimed to investigate the distribution of CpG islands on Papillomavirus genomes and assess their potential impact on the neoplastic progression of different Alphapapillomavirus genera within host cells. Methods: We conducted an analysis of dinucleotide frequencies in DNA sequences from various Alphapapillomavirus genera. The sequences for our analysis were sourced from the specialized HPV (human papillomavirus) database (pave.niaid.nih.gov). Following a comprehensive comparative examination of entire genomes from different HPV species, we specifically focused on 63 genomes belonging to the Alphapapillomavirus genus to identify internal CpG island profiles. These investigations were conducted using online bioinformatics software (DBCAT), and statistical analysis was performed using GraphPad Prism v. 8.0.1. Results: Our preliminary findings revealed that 76.1% of the viruses in our study had fewer than 3 CpG islands but multiple CpG sites, while fewer than 25% of the viruses possessed at least 3 CpG islands. High-risk viruses were identified in 68.42% of genotypes with fewer than 3 CpG islands, whereas low-risk genotypes were observed in 15.7% of cases. Notably, some oncogenic viruses lacked CpG islands entirely, and this pattern was also observed in viruses with a single CpG island, occurring in 50% of cases. Based on the absence of CpG islands, genotypes such as HPV 67, HPV 97, and HPV 34 could potentially be classified as carcinogenic. Additionally, the distribution of CpG islands across HPV genes did not appear to be random. Genes like L2 and E2 contained a CpG island in 50% of cases, whereas oncogenes E6 and E7 consistently had a CpG island in 100% of cases in high-risk genotypes. Conclusions: Our findings suggest that the loss of 1 or more CpG islands could potentially transform an HPV genotype into a high-risk genotype. This process may be accelerated in the presence of host-related risk factors. Further research is required to validate whether CpG island distribution can aid in identifying oncogenic viruses. [ABSTRACT FROM AUTHOR]

Initially described as a triad of immunodeficiency, congenital heart defects and hypoparathyroidism, 22q11.2 deletion syndrome (22q11.2DS) now encompasses a great amount of abnormalities involving different systems. Approximately 85% of patients share a 3 Mb 22q11.2 region of hemizygous deletion in which 46 protein-coding genes are included. However, the hemizygosity of the genes of this region cannot fully explain the clinical phenotype and the phenotypic variability observed among patients. Additional mutations in genes located outside the deleted region, leading to "dual diagnosis", have been described in 1% of patients. In some cases, the hemizygosity of the 22q11.2 region unmasks autosomal recessive conditions due to additional mutations on the non-deleted allele. Some of the deleted genes play a crucial role in gene expression regulation pathways, involving the whole genome. Typical miRNA expression patterns have been identified in 22q11.2DS, due to an alteration in miRNA biogenesis, affecting the expression of several target genes. Also, a methylation epi-signature in CpG islands differentiating patients from controls has been defined. Herein, we summarize the evidence on the genetic and epigenetic mechanisms implicated in the pathogenesis of the clinical manifestations of 22q11.2 DS. The review of the literature confirms the hypothesis that the 22q11.2DS phenotype results from a network of interactions between deleted protein-coding genes and altered epigenetic regulation. [ABSTRACT FROM AUTHOR]

In the context of infectious diseases, the dynamic interplay between ever-changing host populations and viral biology demands a more flexible modeling approach than common fixed correlations. Embracing random-effects regression models allows for a nuanced understanding of the intricate ecological and evolutionary dynamics underlying complex phenomena, offering valuable insights into disease progression and transmission patterns. In this article, we employed a random-effects regression to model an observed decreasing median plasma viral load (pVL) among individuals with HIV in Mexico City during 2019–2021. We identified how these functional slope changes (i.e. random slopes by year) improved predictions of the observed pVL median changes between 2019 and 2021, leading us to hypothesize underlying ecological and evolutionary factors. Our analysis involved a dataset of pVL values from 7325 ART-naïve individuals living with HIV, accompanied by their associated clinical and viral molecular predictors. A conventional fixed-effects linear model revealed significant correlations between pVL and predictors that evolved over time. However, this fixed-effects model could not fully explain the reduction in median pVL; thus, prompting us to adopt random-effects models. After applying a random effects regression model—with random slopes and intercepts by year—, we observed potential ''functional changes'' within the local HIV viral population, highlighting the importance of ecological and evolutionary considerations in HIV dynamics: A notably stronger negative correlation emerged between HIV pVL and the CpG content in the pol gene, suggesting a changing immune landscape influenced by CpG-induced innate immune responses that could impact viral load dynamics. Our study underscores the significance of random effects models in capturing dynamic correlations and the crucial role of molecular characteristics like CpG content. By enriching our understanding of changing host-virus interactions and HIV progression, our findings contribute to the broader relevance of such models in infectious disease research. They shed light on the changing interplay between host and pathogen, driving us closer to more effective strategies for managing infectious diseases. Significance of the study: This study highlights a decreasing trend in median plasma viral loads among ART-naïve individuals living with HIV in Mexico City between 2019 and 2021. It uncovers various predictors significantly correlated with pVL, shedding light on the complex interplay between host-virus interactions and disease progression. By employing a random-slopes model, the researchers move beyond traditional fixed-effects models to better capture dynamic correlations and evolutionary changes in HIV dynamics. The discovery of a stronger negative correlation between pVL and CpG content in HIV-pol sequences suggests potential changes in the immune landscape and innate immune responses, opening avenues for further research into adaptive changes and responses to environmental shifts in the context of HIV infection. The study's emphasis on molecular characteristics as predictors of pVL adds valuable insights to epidemiological and evolutionary studies of viruses, providing new avenues for understanding and managing HIV infection at the population level.

BackgroundLRIG1, the founding member of the LRIG (leucine-rich repeat and immunoglobulin-like domain) family of transmembrane proteins, is a negative regulator of receptor tyrosine kinases and a tumour suppressor. Decreased LRIG1 expression is consistently observed in cancer, across diverse tumour types, and is linked to poor patient prognosis. However, mechanisms by which LRIG1 is repressed are not fully understood. Silencing of LRIG1 through promoter CpG island methylation has been reported in colorectal and cervical cancer but studies in breast cancer remain limited.MethodsIn silico analysis of human breast cancer patient data were used to demonstrate a correlation between DNA methylation and LRIG1 silencing in basal/triple-negative breast cancer, and its impact on patient survival. LRIG1 gene expression, protein abundance, and methylation enrichment were examined by quantitative reverse-transcription PCR, immunoblotting, and methylation immunoprecipitation, respectively, in breast cancer cell lines in vitro. We examined the impact of global demethylation on LRIG1 expression and methylation enrichment using 5-aza-2'-deoxycytidine. We also examined the effects of targeted demethylation of the LRIG1 CpG island, and transcriptional activation of LRIG1 expression, using the RNA guided deadCas9 transactivation system.ResultsAcross breast cancer subtypes, LRIG1 expression is lowest in the basal/triple-negative subtype so we investigated whether differential methylation may contribute to this. Indeed, we find that LRIG1 CpG island methylation is most prominent in basal/triple-negative cell lines and patient samples. Use of the global demethylating agent 5-aza-2'-deoxycytidine decreases methylation leading to increased LRIG1 transcript expression in basal/triple-negative cell lines, while having no effect on LRIG1 expression in luminal/ER-positive cell lines. Using a CRISPR/deadCas9 (dCas9)-based targeting approach, we demonstrate that TET1-mediated demethylation (Tet1-dCas9) along with VP64-mediated transcriptional activation (VP64-dCas9) at the CpG island, increased endogenous LRIG1 expression in basal/triple-negative breast cancer cells, without transcriptional upregulation at predicted off-target sites. Activation of LRIG1 by the dCas9 transactivation system significantly increased LRIG1 protein abundance, reduced site-specific methylation, and reduced cancer cell viability. Our findings suggest that CRISPR-mediated targeted activation may be a feasible way to restore LRIG1 expression in cancer.ConclusionsOur study contributes novel insight into mechanisms which repress LRIG1 in triple-negative breast cancer and demonstrates for the first time that targeted de-repression of LRIG1 in cancer cells is possible. Understanding the epigenetic mechanisms associated with repression of tumour suppressor genes holds potential for the advancement of therapeutic approaches.

Offspring generated by in vitro fertilization (IVF) are believed to be healthy but display a possible predisposition to chronic diseases, like hypertension and glucose intolerance. Since epigenetic changes are believed to underlie such phenotype, this study aimed at describing global DNA methylation changes in the liver of adult mice generated by natural mating (FB group) or by IVF. Embryos were generated by IVF or natural mating. At 30 weeks of age, mice were sacrificed. The liver was removed, and global DNA methylation was assessed using whole-genome bisulfite sequencing (WGBS). Genomic Regions for Enrichment Analysis Tool (GREAT) and G:Profilerβ were used to identify differentially methylated regions (DMRs) and for functional enrichment analysis. Overrepresented gene ontology terms were summarized with REVIGO, while canonical pathways (CPs) were identified with Ingenuity® Pathway Analysis. Overall, 2692 DMRs (4.91%) were different between the groups. The majority of DMRs (84.92%) were hypomethylated in the IVF group. Surprisingly, only 0.16% of CpG islands were differentially methylated and only a few DMRs were located on known gene promoters (n = 283) or enhancers (n = 190). Notably, the long-interspersed element (LINE), short-interspersed element (SINE), and long terminal repeat (LTR1) transposable elements showed reduced methylation (P < 0.05) in IVF livers. Cellular metabolic process, hepatic fibrosis, and insulin receptor signaling were some of the principal biological processes and CPs modified by IVF. In summary, IVF modifies the DNA methylation signature in the adult liver, resulting in hypomethylation of genes involved in metabolism and gene transcription regulation. These findings may shed light on the mechanisms underlying the developmental origin of health and disease.

Although male-female differences in placental structure and function have been observed, little is understood about their molecular underpinnings. Here, we present a mega-analysis of 14 publicly available placenta DNA methylation (DNAm) microarray datasets to identify individual CpGs and regions associated with fetal sex. In the discovery dataset of placentas from full term pregnancies (N = 532 samples), 5212 CpGs met genome-wide significance (p

BackgroundAltered DNA methylation may be an intermediate phenotype between breast cancer risk factors and disease. Mammographic density is a strong risk factor for breast cancer. However, no studies to date have identified an epigenetic signature of mammographic density. We performed an epigenome-wide association study of mammographic density.MethodsWhite blood cell DNA methylation was measured for 385 postmenopausal women using the Illumina Infinium MethylationEPIC BeadChip array. Differential methylation was assessed using genome-wide, probe-level, and regional analyses. We implemented a resampling-based approach to improve the stability of our findings.ResultsOn average, women with elevated mammographic density exhibited DNA hypermethylation within CpG islands and gene promoters compared to women with lower mammographic density. We identified 250 CpG sites for which DNA methylation was significantly associated with mammographic density. The top sites were located within genes associated with cancer, including HDLBP, TGFB2, CCT4, and PAX8, and were more likely to be located in regulatory regions of the genome. We also identified differential DNA methylation in 37 regions, including within the promoters of PAX8 and PF4, a gene involved in the regulation of angiogenesis. Overall, our results paint a picture of epigenetic dysregulation associated with mammographic density.ConclusionMammographic density is associated with differential DNA methylation throughout the genome, including within genes associated with cancer. Our results suggest the potential involvement of several genes in the biological mechanisms behind differences in breast density between women. Further studies are warranted to explore these potential mechanisms and potential links to breast cancer risk.

Gene body methylation (GBM) is an ancestral mode of DNA methylation whose role in development has been obscured by the more prominent roles of promoter and CpG island methylation. The wasp Nasonia vitripennis has little promoter and CpG island methylation, yet retains strong GBM, making it an excellent model for elucidating the roles of GBM. Here we show that N. vitripennis DNA methyltransferase 1a (Nv-Dnmt1a) knockdown leads to failures in cellularization and gastrulation of the embryo. Both of these disrupted events are hallmarks of the maternal-zygotic transition (MZT) in insects. Analysis of the embryonic transcriptome and methylome revealed strong reduction of GBM and widespread disruption of gene expression during embryogenesis after Nv-Dnmt1a knockdown. Strikingly, there was a strong correlation between loss of GBM and reduced gene expression in thousands of methylated loci, consistent with the hypothesis that GBM directly facilitates high levels of transcription. We propose that lower expression levels of methylated genes due to reduced GBM is the crucial direct effect of Nv-Dnmt1 knockdown. Subsequently, the disruption of methylated genes leads to downstream dysregulation of the MZT, culminating in developmental failure at gastrulation.

DNA methylation is a labile modification associated with gene expression control and environmental adaptations. High throughput, scalable and quantitative assessments of specific DNA methylation modifications in complex genomic regions for use in large population studies are needed. The performance of Droplet Digital™ PCR (ddPCR™) was investigated for DNA methylation detection against next-generation bisulfite sequencing (NGS) to demonstrate the ability of ddPCR to detect and validate DNA methylation levels and complex patterns among neighboring CpGs in regions associated with prenatal tobacco exposure. While both techniques are reproducible, ddPCR demonstrates a unique advantage for high-throughput DNA methylation analysis in large-scale population studies and provides the specificity to accurately measure DNA methylation of target CpGs in complex regions.

The completion of a telomere-to-telomere human reference genome, T2T-CHM13, has resolved complex regions of the genome, including repetitive and homologous regions. Here, we present a high-resolution epigenetic study of previously unresolved sequences, representing entire acrocentric chromosome short arms, gene family expansions, and a diverse collection of repeat classes. This resource precisely maps CpG methylation (32.28 million CpGs), DNA accessibility, and short-read datasets (166,058 previously unresolved chromatin immunoprecipitation sequencing peaks) to provide evidence of activity across previously unidentified or corrected genes and reveals clinically relevant paralog-specific regulation. Probing CpG methylation across human centromeres from six diverse individuals generated an estimate of variability in kinetochore localization. This analysis provides a framework with which to investigate the most elusive regions of the human genome, granting insights into epigenetic regulation.

Cognitive skills are a strong predictor of a wide range of later life outcomes. Genetic and epigenetic associations across the genome explain some of the variation in general cognitive abilities in the general population and it is plausible that epigenetic associations might arise from prenatal environmental exposures and/or genetic variation early in life. We investigated the association between cord blood DNA methylation at birth and cognitive skills assessed in children from eight pregnancy cohorts within the Pregnancy And Childhood Epigenetics (PACE) Consortium across overall (total N = 2196), verbal (total N = 2206) and non-verbal cognitive scores (total N = 3300). The associations at single CpG sites were weak for all of the cognitive domains investigated. One region near DUSP22 on chromosome 6 was associated with non-verbal cognition in a model adjusted for maternal IQ. We conclude that there is little evidence to support the idea that variation in cord blood DNA methylation at single CpG sites is associated with cognitive skills and further studies are needed to confirm the association at DUSP22.

Health outcomes are frequently shaped by difficult to dissect inter-relationships between biological, behavioral, social and environmental factors. DNA methylation patterns reflect such multivariate intersections, providing a rich source of novel biomarkers and insight into disease etiologies. Recent advances in whole-genome bisulfite sequencing enable investigation of DNA methylation over all genomic CpGs, but existing bioinformatic approaches lack accessible system-level tools. Here, we develop the R package Comethyl, for weighted gene correlation network analysis of user-defined genomic regions that generates modules of comethylated regions, which are then tested for correlations with multivariate sample traits. First, regions are defined by CpG genomic location or regulatory annotation and filtered based on CpG count, sequencing depth and variability. Next, correlation networks are used to find modules of interconnected nodes using methylation values within the selected regions. Each module containing multiple comethylated regions is reduced in complexity to a single eigennode value, which is then tested for correlations with experimental metadata. Comethyl has the ability to cover the noncoding regulatory regions of the genome with high relevance to interpretation of genome-wide association studies and integration with other types of epigenomic data. We demonstrate the utility of Comethyl on a dataset of male cord blood samples from newborns later diagnosed with autism spectrum disorder (ASD) versus typical development. Comethyl successfully identified an ASD-associated module containing regions mapped to genes enriched for brain glial functions. Comethyl is expected to be useful in uncovering the multivariate nature of health disparities for a variety of common disorders. Comethyl is available at github.com/cemordaunt/comethyl with complete documentation and example analyses.

Type 1 diabetes affects over nine million individuals globally, with approximately 40% developing diabetic kidney disease. Emerging evidence suggests that epigenetic alterations, such as DNA methylation, are involved in diabetic kidney disease. Here we assess differences in blood-derived genome-wide DNA methylation associated with diabetic kidney disease in 1304 carefully characterised individuals with type 1 diabetes and known renal status from two cohorts in the United Kingdom-Republic of Ireland and Finland. In the meta-analysis, we identify 32 differentially methylated CpGs in diabetic kidney disease in type 1 diabetes, 18 of which are located within genes differentially expressed in kidneys or correlated with pathological traits in diabetic kidney disease. We show that methylation at 21 of the 32 CpGs predict the development of kidney failure, extending the knowledge and potentially identifying individuals at greater risk for diabetic kidney disease in type 1 diabetes.

BackgroundOvarian clear cell carcinoma (OCCC) is a rare ovarian cancer histotype that tends to be resistant to standard platinum-based chemotherapeutics. We sought to better understand the role of DNA methylation in clinical and biological subclassification of OCCC.MethodsWe interrogated genome-wide methylation using DNA from fresh frozen tumors from 271 cases, applied nonsmooth nonnegative matrix factorization (nsNMF) clustering, and evaluated clinical associations and biological pathways.ResultsTwo approximately equally sized clusters that associated with several clinical features were identified. Compared with Cluster 2 (N = 137), Cluster 1 cases (N = 134) presented at a more advanced stage, were less likely to be of Asian ancestry, and tended to have poorer outcomes including macroscopic residual disease following primary debulking surgery (P < 0.10). Subset analyses of targeted tumor sequencing and IHC data revealed that Cluster 1 tumors showed TP53 mutation and abnormal p53 expression, and Cluster 2 tumors showed aneuploidy and ARID1A/PIK3CA mutation (P < 0.05). Cluster-defining CpGs included 1,388 CpGs residing within 200 bp of the transcription start sites of 977 genes; 38% of these genes (N = 369 genes) were differentially expressed across cluster in transcriptomic subset analysis (P < 10-4). Differentially expressed genes were enriched for six immune-related pathways, including IFNα and IFNγ responses (P < 10-6).ConclusionsDNA methylation clusters in OCCC correlate with disease features and gene expression patterns among immune pathways.ImpactThis work serves as a foundation for integrative analyses that better understand the complex biology of OCCC in an effort to improve potential for development of targeted therapeutics.

BackgroundBeef tenderness is a complex trait of economic importance for the beef industry. Understanding the epigenetic mechanisms underlying this trait may help improve the accuracy of breeding programs. However, little is known about epigenetic effects on Bos taurus muscle and their implications in tenderness, and no studies have been conducted in Bos indicus.ResultsComparing methylation profile of Bos indicus skeletal muscle with contrasting beef tenderness at 14 days after slaughter, we identified differentially methylated cytosines and regions associated with this trait. Interestingly, muscle that became tender beef had higher levels of hypermethylation compared to the tough group. Enrichment analysis of predicted target genes suggested that differences in methylation between tender and tough beef may affect signal transduction pathways, among which G protein signaling was a key pathway. In addition, different methylation levels were found associated with expression levels of GNAS, PDE4B, EPCAM and EBF3 genes. The differentially methylated elements correlated with EBF3 and GNAS genes overlapped CpG islands and regulatory elements. GNAS, a complex imprinted gene, has a key role on G protein signaling pathways. Moreover, both G protein signaling pathway and the EBF3 gene regulate muscle homeostasis, relaxation, and muscle cell-specificity.ConclusionsWe present differentially methylated loci that may be of interest to decipher the epigenetic mechanisms affecting tenderness. Supported by the previous knowledge about regulatory elements and gene function, the methylation data suggests EBF3 and GNAS as potential candidate genes and G protein signaling as potential candidate pathway associated with beef tenderness via methylation.

DNA methylation microarrays can be employed to interrogate cell-type composition in complex tissues. Here, we expand reference-based deconvolution of blood DNA methylation to include 12 leukocyte subtypes (neutrophils, eosinophils, basophils, monocytes, naïve and memory B cells, naïve and memory CD4 + and CD8 + T cells, natural killer, and T regulatory cells). Including derived variables, our method provides 56 immune profile variables. The IDOL (IDentifying Optimal Libraries) algorithm was used to identify libraries for deconvolution of DNA methylation data for current and previous platforms. The accuracy of deconvolution estimates obtained using our enhanced libraries was validated using artificial mixtures and whole-blood DNA methylation with known cellular composition from flow cytometry. We applied our libraries to deconvolve cancer, aging, and autoimmune disease datasets. In conclusion, these libraries enable a detailed representation of immune-cell profiles in blood using only DNA and facilitate a standardized, thorough investigation of immune profiles in human health and disease.

Infinium methylation arrays are not available for the vast majority of non-human mammals. Moreover, even if species-specific arrays were available, probe differences between them would confound cross-species comparisons. To address these challenges, we developed the mammalian methylation array, a single custom array that measures up to 36k CpGs per species that are well conserved across many mammalian species. We designed a set of probes that can tolerate specific cross-species mutations. We annotate the array in over 200 species and report CpG island status and chromatin states in select species. Calibration experiments demonstrate the high fidelity in humans, rats, and mice. The mammalian methylation array has several strengths: it applies to all mammalian species even those that have not yet been sequenced, it provides deep coverage of conserved cytosines facilitating the development of epigenetic biomarkers, and it increases the probability that biological insights gained in one species will translate to others.

BackgroundFew studies have examined prognostic outcomes-associated molecular signatures other than overall survival (OS) for gastric cancer (GC). We aimed to identify DNA methylation biomarkers associated with multiple prognostic outcomes of GC in an epigenome-wide association study.MethodsBased on the Cancer Genome Atlas (TCGA), DNA methylation loci associated with OS (n = 381), disease-specific survival (DSS, n = 372), and progression-free interval (PFI, n = 383) were discovered in training set subjects (false discovery rates