Calling differentially methylated regions from whole genome bisulphite sequencing with DMRcate

Isolating the effects of HIV infection and HIV exposure on epigenetic profiles in infants using historical data from the Mothers and Infants Cohort Study

BACKGROUND

Epigenetics offers insight into the mechanisms by which early life HIV infection and HIV exposure in utero affects offspring health. However, due to the widespread use of antiretroviral therapy (ART) during pregnancy/infancy, contemporary studies are unable to disentangle effects of HIV from ART exposure on epigenetic profiles.

METHODS

Using historical specimens collected before widespread use of ART (1985-1991), we compared DNA methylation (DNAm) profiles among infants with perinatally-acquired HIV (PHIV), HIV-exposed but uninfected (HEU), and HIV-unexposed uninfected (HUU). DNAm in peripheral blood mononuclear cells collected at 3 and 12 months of age (36 PHIV, 33 HEU, and 33 HUU) was profiled using the Illumina Infinium MethylationEPIC BeadChip. We tested for differentially methylated (DM) CpG sites between groups at 3 and 12 months, adjusting for sex, race/ethnicity, and cell type proportions. Biological pathway enrichment analyses were conducted.

FINDINGS

Comparing PHIV to HEU, there were 2 DM sites at 3 months and 11 at 12 months. Comparing PHIV to HUU, there was 1 DM CpG site at 3 months and 6 at 12 months. Immune-related pathways, including interferon-mediated signalling pathways were enriched. HIV exposure was not associated with any variation in DNA methylation, as no differences were detected between HEU vs. HUU at 3 or 12 months.

INTERPRETATION

HIV infection (in the absence of ART during pregnancy/infancy) was associated with DNA methylation changes at 3 and 12 months of life in infants. Differential methylation in PHIV is related to immune processes and HIV exposure in the absence of infection does not contribute to differential methylation.

FUNDING

This study was supported by funding from the National Institutes of Health (R21HD104558 to SS, K01DA053157 to SS, P30ES019776 to CJM, and P30ES005022 to ESB.

Systems epigenetic approach towards non-invasive breast cancer detection

No study has systematically compared the suitability of DNA methylation (DNAme) profiles in non-invasive samples for the detection of breast cancer (BC). We assess non-tumour DNAme in 1,100 cervical, buccal, and blood samples from BC cases and controls and find that cervical samples exhibit the largest nuber of differentially methylated sites, followed by buccal samples. No sites were significant in blood after FDR adjustment. Deriving DNAme-based classifiers for BC detection in each sample type (WID-buccal-, cervical-, or blood-BC), we achieve validation AUCs of 0.75, 0.66, and 0.51, respectively. Buccal and cervical BC-associated DNAme alterations distinguish between BC cases and controls in both surrogate and breast tissue (AUC > 0.88), yet individual sites and the directionality of methylation changes are not identical between these two sample types, and buccal sample DNAme aligns with breast methylation changes more closely. Pending additional validation, these insights may have the potential to improve non-invasive personalized BC prevention.

Using Residual Newborn Blood Spots to Investigate CpG Methylation in Relation to Air Pollution and Congenital Heart Defects

BACKGROUND

The prevalence of tetralogy of Fallot (TOF), a common congenital heart defect, has increased over the last two decades.

METHODS

Genome-wide CpG methylation patterns were assessed and analyzed in relation to gestational air pollution exposure among 24 infants with TOF and 24 sex-matched control infants without a birth defect from a North Carolina population-based, case-control study of major structural birth defects (2006-2011). Air pollution exposure during obstetric weeks 3-8 was assigned based on self-reported residence. DNA was extracted from residual newborn blood spots, and DNA methylation levels were measured using the Illumina EPIC Array.

RESULTS

Cases had higher exposure to both PM2 .5 and O3 compared to controls. No specific CpG loci were statistically significantly associated with TOF status or air pollution exposure; however, we observed associations between TOF case status and DNA methylation at specific genomic regions with genes enriched for functions in metabolism. Additionally, there were significant regions that displayed differential DNA methylation in relation to air pollution exposure within genes involved in apoptosis, necrosis, inflammation, and immune response pathways.

CONCLUSIONS

Generally, air pollution exposure and TOF were associated with differential DNA methylation in distinct genes. These results highlight suggestive links between the environment, epigenome, and TOF to be further investigated in larger studies.

Strong nuclear expression of HOXB13 is a reliable surrogate marker for DNA methylome profiling to distinguish myxopapillary ependymoma from spinal ependymoma

Spinal ependymoma and myxopapillary ependymoma are the two most common spinal ependymal tumor types that feature distinct histological characteristics, genetic alterations and DNA methylation profiles. Their histological distinction may be difficult in individual cases and molecular diagnostic assessment, in particular DNA methylome profiling, may then be required to assign the correct diagnosis. Expression of the homeobox gene HOXB13 at the mRNA and protein levels has been reported as a frequent finding in myxopapillary ependymoma that may serve as a diagnostic marker for these tumors. Here, we evaluated the diagnostic role of HOXB13 immunostaining in 143 spinal neoplasms, comprising 54 histologically classified myxopapillary ependymomas, 46 histologically classified spinal ependymomas, and various other tumor types. Immunohistochemical results for HOXB13 protein were compared to molecular findings obtained by bead array-based DNA methylation and DNA copy number profiling, as well as next generation gene panel sequencing-based mutational analysis. Our findings indicate strong nuclear HOXB13 expression as a reliable diagnostic marker for molecularly confirmed myxopapillary ependymoma. Moreover, we provide evidence that differential HOXB13 protein expression is related to differential HOXB13-associated CpG site methylation in myxopapillary vs. spinal ependymomas, which can be assessed by targeted DNA methylation analysis. Taken together, immunohistochemistry for HOXB13 protein expression and targeted DNA methylation analysis of HOXB13 represent useful surrogate approaches that may substitute for DNA methylome profiling in routine diagnostics and facilitate precise classification of spinal ependymal tumors. In particular, strong nuclear HOXB13 immunoreactivity may serve as a novel diagnostic criterion for the classification of myxopapillary ependymoma.

Multi-omic analysis of SDHB-deficient pheochromocytomas and paragangliomas identifies metastasis and treatment-related molecular profiles

Hereditary SDHB-mutant pheochromocytomas (PC) and paragangliomas (PG) are rare tumours with a high propensity to metastasize although their clinical behaviour is unpredictable. To characterize the genomic landscape of these tumours and identify metastasis biomarkers, we perform multi-omic analysis on 94 tumours from 79 patients using seven molecular methods. Sympathetic (chromaffin cell) and parasympathetic (non-chromaffin cell) PCPG have distinct molecular profiles reflecting their cell-of-origin and biochemical profile. TERT and ATRX-alterations are associated with metastatic PCPG and these tumours have an increased mutation load, and distinct transcriptional and telomeric features. Most PCPG have quiet genomes with some rare co-operative driver events, including EPAS1/HIF-2α mutations. Two mechanisms of acquired resistance to DNA alkylating chemotherapies are identifiable; MGMT overexpression and mismatch repair-deficiency causing hypermutation. Our comprehensive multi-omic analysis of SDHB-mutant PCPG therefore identifies features of metastatic disease and treatment response, expanding our understanding of these rare neuroendocrine tumours.

Epigenome-wide analysis reveals potential biomarkers for radiation-induced toxicity risk in prostate cancer

BACKGROUND

Prostate cancer is the second most common cancer globally, with radiation therapy (RT) being a key treatment for clinically localized and locally advanced cases. Given high survival rates, addressing long-term side effects of RT is crucial for preserving quality-of-life. Radiogenomics, the study of genetic variations affecting response to radiation, has primarily focussed on genomic biomarkers, while DNA methylation studies offer insights into RT responses. Although most research has centred on tumours, no epigenome-wide association studies have explored peripheral blood biomarkers of RT-induced toxicities in prostate cancer patients. Identifying such biomarkers could reveal molecular mechanisms underlying RT response and enable personalized treatment.

METHODS

We analysed 105 prostate cancer patients (52 cases and 53 controls). Cases developed grade ≥ 2 genitourinary and/or gastrointestinal late toxicity after 12 months of starting RT, whereas controls did not. An epigenome-wide association study of post-RT toxicities was performed using the Illumina MethylationEPIC BeadChip, adjusting for age and cell type composition. We constructed two methylation risk scores-one using differentially methylated positions (MRSsites) and another using differentially methylated regions (MRSregions)-as well as a Support Vector Machine-based methylation signature (SVMsites). We evaluated RT effects on biological age and stochastic epigenetic mutations within established radiation response pathways. Gene Ontology and pathway enrichment analyses were also performed.

RESULTS

Pre-RT methylation analysis identified 56 differentially methylated positions (adjusted p-value ≤ 0.05), and 6 differentially methylated regions (p-value ≤ 0.05) associated with the genes NTM, ACAP1, IL1RL2, VOOP1, AKR1E2, and an intergenic region on chromosome 13 related to Short/Long Interspersed Nuclear Elements. Both Methylation Risk Scores (MRSsites AUC = 0.87; MRSregions AUC = 0.89) and the 8-CpG Support Vector Machine signature (SVMsites AUC = 0.98) exhibited strong discriminatory accuracy in classifying patients in the discovery cohort. Gene ontology analysis revealed significant enrichment (adjusted p-value ≤ 0.05) of genes involved in DNA repair, inflammatory response, tissue repair, and oxidative stress response pathways.

CONCLUSIONS

Epigenetic biomarkers show potential for predicting severe long-term adverse effects of RT in prostate cancer patients. The identified methylation patterns provide valuable insights into toxicity mechanisms and may aid personalized treatment strategies. However, validation in independent cohorts is essential to confirm their predictive value and clinical applicability.

easyEWAS: a flexible and user-friendly R package for epigenome-wide association study

Motivation

Rapid advancements in high-throughput sequencing technologies especially the Illumina DNA methylation Beadchip greatly fuelled the surge in epigenome-wide association study (EWAS), providing crucial insights into intrinsic DNA methylation modifications associated with environmental exposure, diseases, and health traits. However, current tools are complex and less user-friendly to accommodate appropriate EWAS designs and make downstream analyses and result interpretations complicated, especially for clinicians and public health professionals with limited bioinformatic skills.

Results

We integrated the current state-of-the-art EWAS analysis methods and tools to develop a flexible and user-friendly R package easyEWAS for conducting DNA methylation-based research using Illumina DNA methylation Beadchips. With easyEWAS, we provide a battery of statistical methods to support differential methylation position analysis across various scenarios, as well as differential methylation region analysis based on the DMRcate method. To facilitate result interpretation, we provide comprehensive functional annotation and result visualization functionalities. Additionally, a bootstrap-based internal validation was incorporated into easyEWAS to ensure the robustness of EWAS results. Evaluation in asthma patients as the example demonstrated that easyEWAS could simplify and streamline the conduction of EWAS and corresponding downstream analyses, thus effectively advancing DNA methylation research in public health and clinical settings.

Availability and implementation

easyEWAS is implemented as an R package and is available at https://github.com/ytwangZero/easyEWAS.

Age-related changes in DNA methylation in a sample of elderly Brazilians

BACKGROUND

Age-related changes in DNA methylation (DNAm) play a critical role in regulating gene expression. However, most epigenome-wide association studies have predominantly focused on individuals of European descent. This study aims to characterize longitudinal changes in DNAm patterns in a cohort of elderly Brazilian participants.

METHODS

DNAm profiles were collected approximately nine years apart from 23 elderly Brazilian individuals using the Illumina Infinium MethyationEPIC BeadChip. Using mixed-effects models, we examined changes in DNAm patterns using both quantitative age and binary timepoint (e.g., baseline vs. follow-up) as predictors of interest to identify differentially methylated positions (DMPs). Significant DMPs were compared with a list of previously identified age-related DMPs. Differentially methylated regions (DMRs) were also identified using DMRcate. Gene ontology (GO) pathway enrichment analyses were performed to explore the functional significance of identified DMPs and DMRs.

RESULTS

Of the 586,229 autosomal probes included in the differential methylation analyses, 2768 significant (FDR < 0.05) age-associated DMPs (aDMPs) and 2757 significant (FDR < 0.05) timepoint-associated DMPs (tpDMPs) were identified. Of the 2768 aDMPs, 1471 were replicated from previous studies. Of the 1297 non-replicated CpGs, 77.4% were exclusive to the EPIC array. The DMR analyses identified 305 age-associated DMRs (aDMRs) and 372 timepoint-associated DMRs (tpDMRs). Both aDMPs and aDMRs exhibited age-related hypermethylation within CpG islands and promoter regions of the genome, whereas hypomethylation predominantly occurred in interCGI and intergenic regions and introns. The GO enrichment analyses identified several neurological and cognition-related pathways enriched for hypermethylated CpG islands, many of which were mapped near transcription start sites and first exon regions.

CONCLUSIONS

This longitudinal study identified age-associated and timepoint-associated DMPs and DMRs in a sample of elderly Brazilians. Most of the non-replicated CpGs were found to be on the new EPIC array, suggesting that more age-related studies using the EPIC array are required to validate these CpGs. The GO pathway enrichment analyses identified age-related enrichment of several gene sets related to cognitive and physical decline in elderly populations. The enrichment of these sites could provide evidence for age-related neurodegeneration and cognitive decline in elderly populations.

Identification of DNA methylation signatures in follicular-patterned thyroid tumors

BACKGROUND AND AIMS

Follicular-patterned thyroid tumors (FPTTs) are frequently encountered in thyroid pathology, encompassing follicular adenoma (FA), follicular thyroid carcinoma (FTC), noninvasive follicular thyroid neoplasm with papillary-like nuclear features (NIFTP), and follicular variant of papillary thyroid carcinoma (fvPTC). Recently, a distinct entity termed differentiated high-grade thyroid carcinoma has been described by the 5th edition of the WHO classification of the thyroid tumors, categorized as either high-grade fvPTC, high-grade FTC or high-grade oncocytic carcinoma of the thyroid (OCA). Accurate differentiation among these lesions, particular between the benign (FA), borderline (NIFTP) and malignant neoplasms (FTC and fvPTC), remains a challenge in both histopathological and cytological diagnoses. This study aimed to develop a novel molecular diagnostic approach utilizing DNA methylation to distinguish between these thyroid tumors.

MATERIALS AND METHODS

DNA methylation signatures and machine learning were employed to construct classification models for FPTTs. A total of 178 thyroid samples from the Gene Expression Omnibus were analyzed. The models were validated using two independent cohorts.

RESULTS

13 cytosine-guanine dinucleotides (CpGs) exhibited significant differences in methylation levels among FA, FTC, NIFTP and fvPTC. Notably, NIFTP showed hypomethylation compared to other subtypes. A Random Forest classifier, based on the methylation status of these 13 CpGs, effectively categorized the four tumor subtypes (AUC = 0.86, accuracy = 0.70 for internal data, and AUC approximately 0.80 for validation data). The selected CpGs were significantly associated with the tumor progression pathway.

CONCLUSION

This study established a robust method for categorizing FPTTs based on DNA methylation patterns. The identified DNA methylation approach holds clinical promise for efficiently diagnosing thyroid neoplasms.

Causality-driven candidate identification for reliable DNA methylation biomarker discovery

Despite vast data support in DNA methylation (DNAm) biomarker discovery to facilitate health-care research, this field faces huge resource barriers due to preliminary unreliable candidates and the consequent compensations using expensive experiments. The underlying challenges lie in the confounding factors, especially measurement noise and individual characteristics. To achieve reliable identification of a candidate pool for DNAm biomarker discovery, we propose a Causality-driven Deep Regularization framework to reinforce correlations that are suggestive of causality with disease. It integrates causal thinking, deep learning, and biological priors to handle non-causal confounding factors, through a contrastive scheme and a spatial-relation regularization that reduces interferences from individual characteristics and noises, respectively. The comprehensive reliability of the proposed method was verified by simulations and applications involving various human diseases, sample origins, and sequencing technologies, highlighting its universal biomedical significance. Overall, this study offers a causal-deep-learning-based perspective with a compatible tool to identify reliable DNAm biomarker candidates, promoting resource-efficient biomarker discovery.

edgeR v4: powerful differential analysis of sequencing data with expanded functionality and improved support for small counts and larger datasets

edgeR is an R/Bioconductor software package for differential analyses of sequencing data in the form of read counts for genes or genomic features. Over the past 15 years, edgeR has been a popular choice for statistical analysis of data from sequencing technologies such as RNA-seq or ChIP-seq. edgeR pioneered the use of the negative binomial distribution to model read count data with replicates and the use of generalized linear models to analyze complex experimental designs. edgeR implements empirical Bayes moderation methods to allow reliable inference when the number of replicates is small. This article announces edgeR version 4, which includes new developments across a range of application areas. Infrastructure improvements include support for fractional counts, implementation of model fitting in C and a new statistical treatment of the quasi-likelihood pipeline that improves accuracy for small counts. The revised package has new functionality for differential methylation analysis, differential transcript expression, differential transcript and exon usage, testing relative to a fold-change threshold and pathway analysis. This article reviews the statistical framework and computational implementation of edgeR, briefly summarizing all the existing features and functionalities but with special attention to new features and those that have not been described previously.

Mitotic block and epigenetic repression underlie neurodevelopmental defects and neurobehavioral deficits in congenital heart disease

Hypoplastic left heart syndrome (HLHS) is a severe congenital heart disease associated with microcephaly and poor neurodevelopmental outcomes. Here we show that the Ohia HLHS mouse model, with mutations in Sap130, a chromatin modifier, and Pcdha9, a cell adhesion protein, also exhibits microcephaly associated with mitotic block and increased apoptosis leading to impaired cortical neurogenesis. Transcriptome profiling, DNA methylation, and Sap130 ChIPseq analyses all demonstrate dysregulation of genes associated with autism and cognitive impairment. This includes perturbation of REST transcriptional regulation of neurogenesis, disruption of CREB signaling regulating synaptic plasticity, and defects in neurovascular coupling mediating cerebral blood flow. Adult mice harboring either the Pcdha9 mutation, which show normal brain anatomy, or forebrain-specific Sap130 deletion via Emx1-Cre, which show microcephaly, both demonstrate learning and memory deficits and autism-like behavior. These findings provide mechanistic insights indicating the adverse neurodevelopment in HLHS may involve cell autonomous/nonautonomous defects and epigenetic dysregulation.

Proximal and Classic Epithelioid Sarcomas are Distinct Molecular Entities Defined by MYC/GATA3 and SOX17/Endothelial Markers, Respectively

Epithelioid sarcoma (ES) is a rare tumor hallmarked by the loss of INI1/SMARCB1 expression. Apart from this alteration, little is known about the biology of ES. Despite recent advances in treatment, the prognosis of ES remains unsatisfactory. To elucidate the molecular underpinnings of ES, and to identify diagnostic biomarkers and potential therapeutic vulnerabilities, we performed an integrated omics profiling (RNA sequencing and methylation array) of 24 primary, untreated ESs. Transcriptome and methylome analysis identified 2 distinct molecular clusters that essentially corresponded to the morphologic variants of ES, classic ES (C-ES) and the more aggressive proximal ES (P-ES). The P-ES group was characterized by hyperactivation of GATA3 and MYC pathways, with extensive epigenetic rewiring associated with EZH2 overexpression. Both DNA methylation and gene expression analysis indicated a striking similarity with the "MYC subgroup" of atypical teratoid/rhabdoid tumor, another SMARCB1-deficient tumor, implying a shared molecular background and potential therapeutic vulnerabilities. Conversely, the C-ES group exhibited an endothelial-like molecular profile, with expression of vascular genes and elevated proangiogenic SOX17 signaling. Immunohistochemistry validated the overexpression of the chromatin regulators GATA3 (9/12 vs 0/16) and EZH2 (7/7 vs 2/6) in P-ESs, and of the vascular factors SOX17 (8/8 vs 1/10) and N-cadherin (5/9 vs 0/10) in C-ESs. Therefore, these molecules emerge as potential diagnostic tools to fill the gap represented by the lack of ES subtype-specific biomarkers. In summary, our study shows that P-ES and C-ES represent distinct molecular entities defined by MYC/GATA3 and SOX17/endothelial molecular traits, respectively. Besides providing insights into the biology of ES, our study pinpoints subtype-specific biomarkers and potential therapeutic vulnerabilities.

Impact of combined exercise on blood DNA methylation and physical health in older women with obesity

This study examined the effects of a 14-week combined exercise program on blood DNA methylation (DNAm) and its potential biological pathways in normal-weight, overweight, and obese older women. A total of 41 participants were assessed at baseline, 7 weeks, and 14 weeks into the training. Their whole-blood DNAm profiles were measured using the Infinitum MethylationEPIC BeadChip, alongside physical and biochemical health evaluations. The results showed notable health improvements, with decreases in blood pressure and cholesterol levels in the overweight and obese groups. Blood triglycerides were reduced only in the overweight group. Physical performance also improved across all groups. At 14 weeks, 1,043 differentially methylated positions (DMPs) were identified, affecting 744 genes. The genes were linked to biological processes, such as cellular metabolism, with significant pathway enrichment related to oxidative phosphorylation and chemical carcinogenesis. Additionally, the overweight group experienced significant reductions in methylation levels at eight lipogenesis-related genes. Protein EpiScore analysis revealed decreased levels of CCL11, VEGFA, and NTRK3 proteins at 14 weeks compared to baseline. Despite these significant molecular changes, there was no observable difference in DNAm age after the intervention. This study highlights how combined exercise can modify DNAm patterns in older women, particularly in lipogenesis-related genes, but suggests that further research is needed to understand the full implications for biological ageing.

DNA Methylation Profiling of Salivary Gland Tumors Supports and Expands Conventional Classification

Tumors of the major and minor salivary glands histologically encompass a diverse and partly overlapping spectrum of frequent diagnostically challenging neoplasms. Despite recent advances in molecular testing and the identification of tumor-specific mutations or gene fusions, there is an unmet need to identify additional diagnostic biomarkers for entities lacking specific alterations. In this study, we collected a comprehensive cohort of 363 cases encompassing 20 different salivary gland tumor entities and explored the potential of DNA methylation to classify these tumors. We were able to show that most entities show specific epigenetic signatures and present a machine learning algorithm that achieved a mean balanced accuracy of 0.991. Of note, we showed that cribriform adenocarcinoma is epigenetically distinct from classical polymorphous adenocarcinoma, which could support risk stratification of these tumors. Myoepithelioma and pleomorphic adenoma form a uniform epigenetic class, supporting the theory of a single entity with a broad but continuous morphologic spectrum. Furthermore, we identified a histomorphologically heterogeneous but epigenetically distinct class that could represent a novel tumor entity. In conclusion, our study provides a comprehensive resource of the DNA methylation landscape of salivary gland tumors. Our data provide novel insight into disputed entities and show the potential of DNA methylation to identify new tumor classes. Furthermore, in future, our machine learning classifier could support the histopathologic diagnosis of salivary gland tumors.

MethyLasso: a segmentation approach to analyze DNA methylation patterns and identify differentially methylated regions from whole-genome datasets

DNA methylation is an epigenetic mark involved in the regulation of gene expression, and patterns of DNA methylation anticorrelate with chromatin accessibility and transcription factor binding. DNA methylation can be profiled at the single cytosine resolution in the whole genome and has been performed in many cell types and conditions. Computational approaches are then essential to study DNA methylation patterns in a single condition or capture dynamic changes of DNA methylation levels across conditions. Toward this goal, we developed MethyLasso, a new approach to segment DNA methylation data. We use it as an all-in-one tool to perform the identification of low-methylated regions, unmethylated regions, DNA methylation valleys and partially methylated domains in a single condition as well as differentially methylated regions between two conditions. We performed a rigorous benchmarking comparing existing approaches by evaluating the agreement of the regions across tools, their number, size, level of DNA methylation, boundaries, cytosine-guanine content and coverage using several real datasets as well as the sensitivity and precision of the approaches using simulated data and show that MethyLasso performs best overall. MethyLasso is freely available at https://github.com/bardetlab/methylasso.

Methylation changes and INS-IGF2 expression predict progression in early-stage Wilms tumor

Wilms tumor, the most common pediatric kidney cancer, accounts for 5% of childhood cancers and is classified by stage and histological subtype. Despite high survival rates (80-85%), approximately 15% of patients experience relapse, reducing survival to around 50%. Epigenetic changes, particularly DNA methylation, play a critical role in Wilms tumor pathogenesis. This study investigates the prognostic potential of DNA methylation in stage I and II patients with favorable histology, aiming to identify early relapse biomarkers. Genome-wide methylation was assessed using methylation microarrays in tumor tissues from relapsed patients (n = 9) and those with complete responses (n = 9), alongside normal tissues (n = 3 each). Differentially methylated probes and regions were analyzed, with additional ROC and survival analyses. Real-time PCR was used to measure IGF2 and INS-IGF2 gene expression. The analysis revealed hypomethylation in intergenic regions in remission patients, identifying 14 differentially methylated positions as potential biomarkers. Increased INS-IGF2 expression was associated with relapse, suggesting its role in disease progression. While the study concentrated on stages I and II patients, where relapse rates are lower, this focus inherently led to a smaller sample size. Despite this, the findings provide valuable insights into the potential role of DNA methylation markers for monitoring disease progression and guiding personalized treatment in Wilms tumor patients.

Exploring the impact of intra-tumoural heterogeneity on liquid biopsy cell-free DNA methylation and copy number in head and neck squamous cell carcinoma

Liquid biopsy profiling is gaining increasing promise towards biomarker-led identification and disease stratification of tumours, particularly for tumours displaying significant intra-tumoural heterogeneity (ITH). For head and neck squamous cell carcinoma (HNSCC), which display high levels of genetic ITH, identification of epigenetic modifications and methylation signatures has shown multiple uses in stratification of HNSCC for prognosis, treatment, and HPV status. In this study, we investigated the potential of liquid biopsy methylomics and genomic copy number to profile HNSCC. We conducted multi-region sampling of tumour core, tumour margin and normal adjacent mucosa, as well as plasma cell-free DNA (cfDNA) across 9 HNSCC patients. Collectively, our work highlights the prevalence of methylomic ITH in HNSCC, and demonstrates the potential of cfDNA methylation as a tool for ITH assessment and serial sampling.

PCBS: an R package for fast and accurate analysis of bisulfite sequencing data

MOTIVATION

Whole-genome bisulfite sequencing is a powerful tool for analyzing chromatin methylation genome-wide, but analysis of whole-genome bisulfite data is slow, inflexible, and often inaccurate.

RESULTS

We developed PCBS (Principal Component BiSulfite), a computationally efficient R package for Whole Genome Bisulfite Sequencing analysis that demonstrates remarkable accuracy and flexibility compared to current tools. PCBS identifies differentially methylated loci, differentially methylated regions, and offers novel functionality that allows for more targeted methylation analyses. PCBS uses minimal computational resources; a complete pipeline in mouse can run on a local RStudio instance in a matter of minutes.

AVAILABILITY AND IMPLEMENTATION

PCBS is an R package available under a GNU GPLv3 license on GitHub: https://github.com/katlande/PCBS and CRAN: https://CRAN.R-project.org/package=PCBS. Instructions for use are available at: https://katlande.github.io/PCBS/.

Early moderate prenatal alcohol exposure and maternal diet impact offspring DNA methylation across species

Alcohol consumption in pregnancy can affect genome regulation in the developing offspring but results have been contradictory. We employed a physiologically relevant murine model of short-term moderate prenatal alcohol exposure (PAE) resembling common patterns of alcohol consumption in pregnancy in humans. Early moderate PAE was sufficient to affect site-specific DNA methylation in newborn pups without altering behavioural outcomes in adult littermates. Whole-genome bisulfite sequencing of neonatal brain and liver revealed stochastic influence on DNA methylation that was mostly tissue-specific, with some perturbations likely originating as early as gastrulation. DNA methylation differences were enriched in non-coding genomic regions with regulatory potential indicative of broad effects of alcohol on genome regulation. Replication studies in human cohorts with fetal alcohol spectrum disorder suggested some effects were metastable at genes linked to disease-relevant traits including facial morphology, intelligence, educational attainment, autism, and schizophrenia. In our murine model, a maternal diet high in folate and choline protected against some of the damaging effects of early moderate PAE on DNA methylation. Our studies demonstrate that early moderate exposure is sufficient to affect fetal genome regulation even in the absence of overt phenotypic changes and highlight a role for preventative maternal dietary interventions.

Sexually dimorphic DNA methylation and gene expression patterns in human first trimester placenta

BACKGROUND

Fetal sex and placental development impact pregnancy outcomes and fetal-maternal health, but the critical timepoint of placenta establishment in first trimester is understudied in human pregnancies.

METHODS

Pregnant subjects were recruited in late first trimester (weeks 10-14) at time of chorionic villus sampling, a prenatal diagnostic test. Leftover placenta tissue was collected and stored until birth outcomes were known, then DNA and RNA were isolated from singleton, normal karyotype pregnancies resulting in live births. DNA methylation was measured with the Illumina Infinium MethylationEPIC BeadChip array (n = 56). Differential methylation analysis compared 25 females versus 31 males using a generalized linear model on 743,461 autosomal probes. Gene expression sex differences were analyzed with RNA-sequencing (n = 74). An integrated analysis was performed using linear regression to correlate gene expression and DNA methylation in 51 overlapping placentas.

RESULTS

Methylation analysis identified 151 differentially methylated probes (DMPs) significant at false discovery rate < 0.05, including 89 (59%) hypermethylated in females. Probe cg17612569 (GABPA, ATP5J) was the most significant CpG site, hypermethylated in males. There were 11 differentially methylated regions affected by fetal sex, with transcription factors ZNF300 and ZNF311 most significantly hypermethylated in males and females, respectively. RNA-sequencing identified 152 genes significantly sexually dimorphic at false discovery rate < 0.05. The 151 DMPs were associated with 18 genes with gene downregulation (P < 0.05) in the direction of hypermethylation, including 2 genes significant at false discovery rate < 0.05 (ZNF300 and CUB and Sushi multiple domains 1, CSMD1). Both genes, as well as Family With Sequence Similarity 228 Member A (FAM228A), showed significant correlation between DNA methylation and sexually dimorphic gene expression, though FAM228A DNA methylation was less sexually dimorphic. Comparison with other sex differences studies found that cg17612569 is male-hypermethylated across gestation in placenta and in human blood up to adulthood.

CONCLUSIONS

Overall, sex dimorphic differential methylation with associated differential gene expression in the first trimester placenta is small, but there remain significant genes that may be regulated through methylation leading to differences in the first trimester placenta.

Diagnostic utility of DNA methylation analysis in genetically unsolved pediatric epilepsies and CHD2 episignature refinement

Sequence-based genetic testing identifies causative variants in ~ 50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. We interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 582 individuals with genetically unsolved DEEs. We identify rare differentially methylated regions (DMRs) and explanatory episignatures to uncover causative and candidate genetic etiologies in 12 individuals. Using long-read sequencing, we identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and four copy number variants. We also identify pathogenic variants associated with episignatures. Finally, we refine the CHD2 episignature using an 850 K methylation array and bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate variants as 2% (12/582) for unsolved DEE cases.

DNA Methylation in the Anti-Mullerian Hormone Gene and the Risk of Disease Activity in Multiple Sclerosis

OBJECTIVE

Multiple sclerosis (MS) has a complex pathobiology, with genetic and environmental factors being crucial players. Understanding the mechanisms underlying heterogeneity in disease activity is crucial for tailored treatment. We explored the impact of DNA methylation, a key mechanism in the genetics-environment interplay, on disease activity in MS.

METHODS

Peripheral immune methylome profiling using Illumina Infinium MethylationEPIC BeadChips was conducted on 249 untreated relapsing-remitting MS patients, sampled at the start of disease-modifying treatment (DMT). A differential methylation analysis compared patients with evidence of disease activity (EDA) to those with no evidence of disease activity (NEDA) over 2 years from DMT start. Utilizing causal inference testing (CIT) and Mendelian randomization (MR), we sought to elucidate the relationships between DNA methylation, gene expression, genetic variation, and disease activity.

RESULTS

Four differentially methylated regions (DMRs) were identified between EDA and NEDA. Examining the influence of single nucleotide polymorphisms (SNPs), 923 variants were found to account for the observed differences in the 4 DMRs. Importantly, 3 out of the 923 SNPs, affecting DNA methylation in a DMR linked to the anti-Mullerian hormone (AMH) gene, were associated with disease activity risk in an independent cohort of 1,408 MS patients. CIT and MR demonstrated that DNA methylation in AMH acts as a mediator for the genetic risk of disease activity.

INTERPRETATION

This study uncovered a novel molecular pathway implicating the interaction between DNA methylation and genetic variation in the risk of disease activity in MS, emphasizing the role of sex hormones, particularly the AMH, in MS pathobiology. ANN NEUROL 2024;96:289-301.

Multi-omic analysis of SDHB-deficient pheochromocytomas and paragangliomas identifies metastasis and treatment-related molecular profiles

Hereditary SDHB-mutant pheochromocytomas (PC) and paragangliomas (PG) are rare tumours with a high propensity to metastasize although their clinical behaviour is unpredictable. To characterize the genomic landscape of these tumours and identify metastasis biomarkers, we performed multi-omic analysis on 94 tumours from 79 patients using seven molecular methods. Sympathetic (chromaffin cell) and parasympathetic (non-chromaffin cell) PCPG had distinct molecular profiles reflecting their cell-of-origin and biochemical profile. TERT and ATRX-alterations were associated with metastatic PCPG and these tumours had an increased mutation load, and distinct transcriptional and telomeric features. Most PCPG had quiet genomes with some rare co-operative driver events observed, including EPAS1/HIF-2α mutations. Two mechanisms of acquired resistance to DNA alkylating chemotherapies were also detected - MGMT overexpression and mismatch repair-deficiency causing hypermutation. Our comprehensive multi-omic analysis of SDHB-mutant PCPG therefore identified features of metastatic disease and treatment response, expanding our understanding of these rare neuroendocrine tumours.

Epigenetic Regulation of DLK1-DIO3 Region in Thyroid Carcinoma

Non-coding RNAs (ncRNAs) have emerged as pivotal regulators in cellular biology, dispelling their former perception as 'junk transcripts'. Notably, the DLK1-DIO3 region harbors numerous ncRNAs, including long non-coding RNAs (lncRNAs) and over 50 microRNA genes. While papillary thyroid cancer showcases a pervasive decrease in DLK1-DIO3-derived ncRNA expression, the precise mechanisms driving this alteration remain elusive. We hypothesized that epigenetic alterations underlie shifts in ncRNA expression during thyroid cancer initiation and progression. This study aimed to elucidate the epigenetic mechanisms governing DLK1-DIO3 region expression in this malignancy. We have combined the analysis of DNA methylation by bisulfite sequencing together with that of histone modifications through ChIP-qPCR to gain insights into the epigenetic contribution to thyroid cancer in cell lines representing malignancies with different genetic backgrounds. Our findings characterize the region's epigenetic signature in thyroid cancer, uncovering distinctive DNA methylation patterns, particularly within CpG islands on the lncRNA MEG3-DMR, which potentially account for its downregulation in tumors. Pharmacological intervention targeting DNA methylation combined with histone deacetylation restored ncRNA expression. These results contribute to the understanding of the epigenetic mechanisms controlling the DLK1-DIO3 region in thyroid cancer, highlighting the combined role of DNA methylation and histone marks in regulating the locus' expression.

Alterations in Blood Methylome as Potential Epigenetic Biomarker in Sporadic Parkinson's Disease

OBJECTIVE

To characterize DNA methylation (DNAm) differences between sporadic Parkinson's disease (PD) and healthy control (HC) individuals enrolled in the Parkinson's Progression Markers Initiative (PPMI).

METHODS

Using whole blood, we characterized longitudinal differences in DNAm between sporadic PD patients (n = 196) and HCs (n = 86) enrolled in PPMI. RNA sequencing (RNAseq) was used to conduct gene expression analyses for genes mapped to differentially methylated cytosine-guanine sites (CpGs).

RESULTS

At the time of patient enrollment, 5,178 CpGs were differentially methylated (2,683 hypermethylated and 2,495 hypomethylated) in PD compared to HC. Of these, 579 CpGs underwent significant methylation changes over 3 years. Several differentially methylated CpGs were found near the cytochrome P450 family 2 subfamily E member 1 (CYP2E1) gene. Additionally, multiple hypermethylated CpGs were associated with the N-myc downregulated gene family member 4 (NDRG4) gene. RNA-Seq analyses showed 75 differentially expressed genes in PD patients compared to controls. An integrative analysis of both differentially methylated sites and differentially expressed genes revealed 20 genes that exhibited hypomethylation concomitant with overexpression. Additionally, 1 gene, cathepsin H (CTSH), displayed hypermethylation that was associated with its decreased expression.

INTERPRETATION

We provide initial evidence of alterations in DNAm in blood of PD patients that may serve as potential epigenetic biomarker of disease. To evaluate the significance of these changes throughout the progression of PD, additional profiling at longer intervals and during the prodromal stages of disease will be necessary. ANN NEUROL 2024;95:1162-1172.

PCBS: an R package for fast and accurate analysis of bisulfite sequencing data

Motivation

Whole-genome bisulfite sequencing is a powerful tool for analyzing chromatin methylation genome-wide, but analysis of whole-genome bisulfite data is hampered by slow, inaccurate, and inflexible pipelines.

Results

We developed PCBS, a computationally efficient R package for Whole Genome Bisulfite Sequencing analysis that demonstrates remarkable accuracy and flexibility compared to current tools. PCBS identifies differentially methylated loci and differentially methylated regions and offers novel functionality that allows for more targeted methylation analyses. PCBS uses minimal computational resources; a complete pipeline in mouse can run on a local RStudio instance in a matter of minutes.

Availability and Implementation

PCBS is an R package available under a GNU GPLv3 license at: https://github.com/katlande/PCBS and from CRAN: https://CRAN.R-project.org/package=PCBS. Instructions for use are available at: https://katlande.github.io/PCBS/.

Novel DNA methylation-based epigenetic signatures in colorectal cancer from peripheral blood leukocytes

Colorectal cancer (CRC) is a multifactorial disease characterized by accumulation of multiple genetic and epigenetic alterations, transforming colonic epithelial cells into adenocarcinomas. Alteration of DNA methylation (DNAm) is a promising biomarker for predicting cancer risk and prognosis, but its role in CRC tumorigenesis is inconclusive. Notably, few DNAm studies have used pre-diagnostic peripheral blood (PB) DNA, causing difficulty in postulating the underlying biologic mechanism of CRC initiation. We conducted epigenome-wide association (EWA) scans in postmenopausal women from Women's Health Initiative (WHI) with their pre-diagnostic DNAm in PB leukocytes (PBLs) to prospectively evaluate CRC development. Our site-specific DNAm analyses across the genome adjusted for DNAm-age, leukocyte heterogeneities, as well as body mass index, diabetes, and insulin resistance. We validated 20 top EWA-CpGs in 2 independent CRC tissue datasets. Also, we detected differentially methylated regions (DMRs) associated with CRC, further mapped to transcriptomic profile, and finally conducted a Gene Set Enrichment Analysis. We detected multiple novel CpGs validated across WHI and tissue datasets. In particular, 2 CpGs (B4GALNT4cg10321339, SV2Bcg18144285) had the strongest effect on CRC risk. Results from our DMR scans contained MIR663cg06007966, which was also validated in EWA analyses. Also, we detected 1 methylome region in PEG10 of Chr7 shared across datasets. Our findings reflect both novel and well-established epigenomic and transcriptomic sites in CRC, warranting further functional validations. Our study contributes to better understanding of the complex interrelated mechanisms on the methylome underlying CRC tumorigenesis and suggests novel preventive DNAm-targets in PBLs for detecting at-risk individuals for CRC development.

Cancer predisposition signaling in Beckwith-Wiedemann Syndrome drives Wilms tumor development

BACKGROUND

Wilms tumor (WT) exhibits structural and epigenetic changes at chromosome 11p15, which also cause Beckwith-Wiedemann Syndrome (BWS). Children diagnosed with BWS have increased risk for WT. The aim of this study is to identify the molecular signaling signatures in BWS driving these tumors.

METHODS

We performed whole exome sequencing, methylation array analysis, and gene expression analysis on BWS-WT samples. Our data were compared to publicly available nonBWS data. We categorized WT from BWS and nonBWS patients by assessment of 11p15 methylation status and defined 5 groups- control kidney, BWS-nontumor kidney, BWS-WT, normal-11p15 nonBWS-WT, altered-11p15 nonBWS-WT.

RESULTS

BWS-WT samples showed single nucleotide variants in BCORL1, ASXL1, ATM and AXL but absence of recurrent gene mutations associated with sporadic WT. We defined a narrow methylation range stratifying nonBWS-WT samples. BWS-WT and altered-11p15 nonBWS-WT showed enrichment of common and unique molecular signatures based on global differential methylation and gene expression analysis. CTNNB1 overexpression and broad range of interactions were seen in the BWS-WT interactome study.

CONCLUSION

While WT predisposition in BWS is well-established, as are 11p15 alterations in nonBWS-WT, this study focused on stratifying tumor genomics by 11p15 status. Further investigation of our findings may identify novel therapeutic targets in WT oncogenesis.

Improvements in lung function following vitamin C supplementation to pregnant smokers are associated with buccal DNA methylation at 5 years of age

BACKGROUND

We previously reported in the "Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function" randomized clinical trial (RCT) that vitamin C (500 mg/day) supplementation to pregnant smokers is associated with improved respiratory outcomes that persist through 5 years of age. The objective of this study was to assess whether buccal cell DNA methylation (DNAm), as a surrogate for airway epithelium, is associated with vitamin C supplementation, improved lung function, and decreased occurrence of wheeze.

METHODS

We conducted epigenome-wide association studies (EWAS) using Infinium MethylationEPIC arrays and buccal DNAm from 158 subjects (80 placebo; 78 vitamin C) with pulmonary function testing (PFT) performed at the 5-year visit. EWAS were performed on (1) vitamin C treatment, (2) forced expiratory flow between 25 and 75% of expired volume (FEF25-75), and (3) offspring wheeze. Models were adjusted for sex, race, study site, gestational age at randomization (≤ OR > 18 weeks), proportion of epithelial cells, and latent covariates in addition to child length at PFT in EWAS for FEF25-75. We considered FDR p < 0.05 as genome-wide significant and nominal p < 0.001 as candidates for downstream analyses. Buccal DNAm measured in a subset of subjects at birth and near 1 year of age was used to determine whether DNAm signatures originated in utero, or emerged with age.

RESULTS

Vitamin C treatment was associated with 457 FDR significant (q < 0.05) differentially methylated CpGs (DMCs; 236 hypermethylated; 221 hypomethylated) and 53 differentially methylated regions (DMRs; 26 hyper; 27 hypo) at 5 years of age. FEF25-75 was associated with one FDR significant DMC (cg05814800), 1,468 candidate DMCs (p < 0.001), and 44 DMRs. Current wheeze was associated with 0 FDR-DMCs, 782 candidate DMCs, and 19 DMRs (p < 0.001). In 365/457 vitamin C FDR significant DMCs at 5 years of age, there was no significant interaction between time and treatment.

CONCLUSIONS

Vitamin C supplementation to pregnant smokers is associated with buccal DNA methylation in offspring at 5 years of age, and most methylation signatures appear to be persistent from the prenatal period. Buccal methylation at 5 years was also associated with current lung function and occurrence of wheeze, and these functionally associated loci are enriched for vitamin C associated loci. Clinical trial registration ClinicalTrials.gov, NCT01723696 and NCT03203603.

Effect of parental adverse childhood experiences on intergenerational DNA methylation signatures from peripheral blood mononuclear cells and buccal mucosa

In this study, the effect of cumulative ACEs experienced on human maternal DNA methylation (DNAm) was estimated while accounting for interaction with domains of ACEs in prenatal peripheral blood mononuclear cell samples from the Maternal and Developmental Risks from Environmental Stressors (MADRES) pregnancy cohort. The intergenerational transmission of ACE-associated DNAm was also explored used paired maternal (N = 120) and neonatal cord blood (N = 69) samples. Replication in buccal samples was explored in the Children's Health Study (CHS) among adult parental (N = 31) and pediatric (N = 114) samples. We used a four-level categorical indicator variable for ACEs exposure: none (0 ACEs), low (1-3 ACEs), moderate (4-6 ACEs), and high (>6 ACEs). Effects of ACEs on maternal DNAm (N = 240) were estimated using linear models. To evaluate evidence for intergenerational transmission, mediation analysis (N = 60 mother-child pairs) was used. Analysis of maternal samples displayed some shared but mostly distinct effects of ACEs on DNAm across low, moderate, and high ACEs categories. CLCN7 and PTPRN2 was associated with maternal DNAm in the low ACE group and this association replicated in the CHS. CLCN7 was also nominally significant in the gene expression correlation analysis among maternal profiles (N = 35), along with 11 other genes. ACE-associated methylation was observed in maternal and neonatal profiles in the COMT promoter region, with some evidence of mediation by maternal COMT methylation. Specific genomic loci exhibited mutually exclusive maternal ACE effects on DNAm in either maternal or neonatal population. There is some evidence for an intergenerational effect of ACEs, supported by shared DNAm signatures in the COMT gene across maternal-neonatal paired samples.

Epigenome-wide association study on short-, intermediate- and long-term ozone exposure in Han Chinese, the NSPT study

Epidemiological and epigenetic studies have acknowledged ambient ozone exposure associated with inflammatory and cardiovascular disease. However, the molecular mechanisms still remained unclear, and epigenome-wide analysis in cohort were lacking, especially in Chinese. We included blood-derived DNA methylation for 3365 Chinese participants from the NSPT cohort and estimated individual ozone exposure level of short-, intermediate- and long-term, based on a validated prediction model. We performed epigenome-wide association studies which identified 59 CpGs and 30 DMRs at a strict genome-wide significance (P < 5 ×10-8). We also conducted comparison on the DNA methylation alteration corresponding to different time windows, and observed an enhanced differentiated methylation trend for intermediate- and long-term exposure, while the short-term exposure associated methylation changes did not retain. The targeted genes of methylation alteration were involved in mechanism related to aging, inflammation disease, metabolic syndrome, neurodevelopmental disorders, and oncogenesis. Underlying pathways were enriched in biological activities including telomere maintenance process, DNA damage response and megakaryocyte differentiation. In conclusion, our study is the first EWAS on ozone exposure conducted in large-scale Han Chinese cohort and identified associated DNA methylation change on CpGs and regions, as well as related gene functions and pathways.

Branched-chain amino acid transaminase 1 regulates glioblastoma cell plasticity and contributes to immunosuppression

BACKGROUND

Glioblastoma is the most common malignant brain tumor in adults. Cellular plasticity and the poorly differentiated features result in a fast relapse of the tumors following treatment. Moreover, the immunosuppressive microenvironment proved to be a major obstacle to immunotherapeutic approaches. Branched-chain amino acid transaminase 1 (BCAT1) was shown to drive the growth of glioblastoma and other cancers;however, its oncogenic mechanism remains poorly understood.

METHODS

Using human tumor data, cell line models and orthotopic immuno-competent and -deficient mouse models, we investigated the phenotypic and mechanistic effects of BCAT1 on glioblastoma cell state and immunomodulation.

RESULTS

Here, we show that BCAT1 is crucial for maintaining the poorly differentiated state of glioblastoma cells and that its low expression correlates with a more differentiated glioblastoma phenotype. Furthermore, orthotopic tumor injection into immunocompetent mice demonstrated that the brain microenvironment is sufficient to induce differentiation of Bcat1-KO tumors in vivo. We link the transition to a differentiated cell state to the increased activity of ten-eleven translocation demethylases and the hypomethylation and activation of neuronal differentiation genes. In addition, the knockout of Bcat1 attenuated immunosuppression, allowing for an extensive infiltration of CD8+ cytotoxic T-cells and complete abrogation of tumor growth. Further analysis in immunodeficient mice revealed that both tumor cell differentiation and immunomodulation following BCAT1-KO contribute to the long-term suppression of tumor growth.

CONCLUSIONS

Our study unveils BCAT1's pivotal role in promoting glioblastoma growth by inhibiting tumor cell differentiation and sustaining an immunosuppressive milieu. These findings offer a novel therapeutic avenue for targeting glioblastoma through the inhibition of BCAT1.

A novel approach toward optimal workflow selection for DNA methylation biomarker discovery

DNA methylation is a major epigenetic modification involved in many physiological processes. Normal methylation patterns are disrupted in many diseases and methylation-based biomarkers have shown promise in several contexts. Marker discovery typically involves the analysis of publicly available DNA methylation data from high-throughput assays. Numerous methods for identification of differentially methylated biomarkers have been developed, making the need for best practices guidelines and context-specific analyses workflows exceedingly high. To this end, here we propose TASA, a novel method for simulating methylation array data in various scenarios. We then comprehensively assess different data analysis workflows using real and simulated data and suggest optimal start-to-finish analysis workflows. Our study demonstrates that the choice of analysis pipeline for DNA methylation-based marker discovery is crucial and different across different contexts.

Comprehensive DNA Methylation Profiling of Medullary Thyroid Carcinoma: Molecular Classification, Potential Therapeutic Target, and Classifier System

PURPOSE

Medullary thyroid carcinoma (MTC) presents a distinct biological context from other thyroid cancers due to its specific cellular origin. This heterogeneous and rare tumor has a high prevalence of advanced diseases, making it crucial to address the limited therapeutic options and enhance complex clinical management. Given the high clinical accessibility of methylation information, we construct the largest MTC methylation cohort to date.

EXPERIMENTAL DESIGN

Seventy-eight fresh-frozen MTC samples constituted our methylation cohort. The comprehensive study process incorporated machine learning, statistical analysis, and in vitro experiments.

RESULTS

Our study pioneered the identification of a three-class clustering system for risk stratification, exhibiting pronounced epigenomic heterogeneity. The elevated overall methylation status in MTC-B, combined with the "mutual exclusivity" of hypomethylated sites displayed by MTC-A and MTC-C, distinctively characterized the MTC-specific methylation pattern. Integrating with the transcriptome, we further depicted the features of these three clusters to scrutinize biological properties. Several MTC-specific aberrant DNA methylation events were emphasized in our study. NNAT expression was found to be notably reduced in poor-prognostic MTC-C, with its promoter region overlapping with an upregulated differentially methylated region. In vitro experiments further affirmed NNAT's therapeutic potential. Moreover, we built an elastic-net logistic regression model with a relatively high AUC encompassing 68 probes, intended for future validation and systematic clinical application.

CONCLUSIONS

Conducting research on diseases with low incidence poses significant challenges, and we provide a robust resource and comprehensive research framework to assist in ongoing MTC case inclusion and facilitate in-depth dissection of its molecular biological features.

DNA methylation of insulin signaling pathways is associated with HOMA2-IR in primary myoblasts from older adults

BACKGROUND

While ageing is associated with increased insulin resistance (IR), the molecular mechanisms underlying increased IR in the muscle, the primary organ for glucose clearance, have yet to be elucidated in older individuals. As epigenetic processes are suggested to contribute to the development of ageing-associated diseases, we investigated whether differential DNA methylation was associated with IR in human primary muscle stem cells (myoblasts) from community-dwelling older individuals.

METHODS

We measured DNA methylation (Infinium HumanMethylationEPIC BeadChip) in myoblast cultures from vastus lateralis biopsies (119 males/females, mean age 78.24 years) from the Hertfordshire Sarcopenia Study extension (HSSe) and examined differentially methylated cytosine phosphate guanine (CpG) sites (dmCpG), regions (DMRs) and gene pathways associated with HOMA2-IR, an index for the assessment of insulin resistance, and levels of glycated hemoglobin HbA1c.

RESULTS

Thirty-eight dmCpGs (false discovery rate (FDR) < 0.05) were associated with HOMA2-IR, with dmCpGs enriched in genes linked with JNK, AMPK and insulin signaling. The methylation signal associated with HOMA2-IR was attenuated after the addition of either BMI (6 dmCpGs), appendicular lean mass index (ALMi) (7 dmCpGs), grip strength (15 dmCpGs) or gait speed (23 dmCpGs) as covariates in the model. There were 8 DMRs (Stouffer < 0.05) associated with HOMA2-IR, including DMRs within T-box transcription factor (TBX1) and nuclear receptor subfamily-2 group F member-2 (NR2F2); the DMRs within TBX1 and NR2F2 remained associated with HOMA2-IR after adjustment for BMI, ALMi, grip strength or gait speed. Forty-nine dmCpGs and 21 DMRs were associated with HbA1c, with cg13451048, located within exoribonuclease family member 3 (ERI3) associated with both HOMA2-IR and HbA1c. HOMA2-IR and HbA1c were not associated with accelerated epigenetic ageing.

CONCLUSIONS

These findings suggest that insulin resistance is associated with differential DNA methylation in human primary myoblasts with both muscle mass and body composition making a significant contribution to the methylation changes associated with IR.

Validation of hypermethylated DNA regions found in colorectal cancers as potential aging-independent biomarkers of precancerous colorectal lesions

BACKGROUND

We previously identified 16,772 colorectal cancer-associated hypermethylated DNA regions that were also detectable in precancerous colorectal lesions (preCRCs) and unrelated to normal mucosal aging. We have now conducted a study to validate 990 of these differentially methylated DNA regions (DMRs) in a new series of preCRCs.

METHODS

We used targeted bisulfite sequencing to validate these 990 potential biomarkers in 59 preCRC tissue samples (41 conventional adenomas, 18 sessile serrated lesions), each with a patient-matched normal mucosal sample. Based on differential DNA methylation tests, a panel of candidate DMRs was chosen on a subset of our cohort and then validated on the remaining part of our cohort and two publicly available datasets with respect to their stratifying potential between preCRCs and normal mucosa.

RESULTS

Strong statistical significance for the difference in methylation levels was observed across the full set of 990 investigated DMRs. From these, a selected candidate panel of 30 DMRs correctly identified 58/59 tumors (area under the receiver operating curve: 0.998).

CONCLUSIONS

These validated DNA hypermethylation markers can be exploited to develop more accurate noninvasive colorectal tumor screening assays.

Diagnostic Utility of Genome-wide DNA Methylation Analysis in Genetically Unsolved Developmental and Epileptic Encephalopathies and Refinement of a CHD2 Episignature

Sequence-based genetic testing currently identifies causative genetic variants in ∼50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. Rare epigenetic variations ("epivariants") can drive disease by modulating gene expression at single loci, whereas genome-wide DNA methylation changes can result in distinct "episignature" biomarkers for monogenic disorders in a growing number of rare diseases. Here, we interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 516 individuals with genetically unsolved DEEs who had previously undergone extensive genetic testing. We identified rare differentially methylated regions (DMRs) and explanatory episignatures to discover causative and candidate genetic etiologies in 10 individuals. We then used long-read sequencing to identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and two copy number variants. We also identify pathogenic sequence variants associated with episignatures; some had been missed by previous exome sequencing. Although most DEE genes lack known episignatures, the increase in diagnostic yield for DNA methylation analysis in DEEs is comparable to the added yield of genome sequencing. Finally, we refine an episignature for CHD2 using an 850K methylation array which was further refined at higher CpG resolution using bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate genetic causes as ∼2% (10/516) for unsolved DEE cases.

Associations between epigenome-wide DNA methylation and height-related traits among Sub-Saharan Africans: the RODAM study

Human height and related traits are highly complex, and extensively research has shown that these traits are determined by both genetic and environmental factors. Such factors may partially affect these traits through epigenetic programing. Epigenetic programing is dynamic and plays an important role in controlling gene expression and cell differentiation during (early) development. DNA methylation (DNAm) is the most commonly studied epigenetic feature. In this study we conducted an epigenome-wide DNAm association analysis on height-related traits in a Sub-Saharan African population, in order to detect DNAm biomarkers across four height-related traits. DNAm profiles were acquired in whole blood samples of 704 Ghanaians, sourced from the Research on Obesity and Diabetes among African Migrants study, using the Illumina Infinium HumanMethylation450 BeadChip. Linear models were fitted to detect differentially methylated positions (DMPs) and regions (DMRs) associated with height, leg-to-height ratio (LHR), leg length, and sitting height. No epigenome-wide significant DMPs were recorded. However we did observe among our top DMPs five informative probes associated with the height-related traits: cg26905768 (leg length), cg13268132 (leg length), cg19776793 (height), cg23072383 (LHR), and cg24625894 (sitting height). All five DMPs are annotated to genes whose functions were linked to bone cell regulation and development. DMR analysis identified overlapping DMRs within the gene body of HLA-DPB1 gene, and the HOXA gene cluster. In this first epigenome-wide association studies of these traits, our findings suggest DNAm associations with height-related heights, and might influence development and maintenance of these traits. Further studies are needed to replicate our findings, and to elucidate the molecular mechanism underlying human height-related traits.

Integrated multi-omics analysis identifies epigenetic alteration related to neurodegeneration development in post-traumatic stress disorder patients

INTRODUCTION

Post-traumatic stress disorder (PTSD), is associated with an elevated risk of neurodegenerative disorders, but the molecular mechanism was not wholly identified. Aberrant methylation status and miRNA expression pattern have been identified to be associated with PTSD, but their complex regulatory networks remain largely unexplored.

METHODS

The purpose of this study was to identify the key genes/pathways related to neurodegenerative disorder development in PTSD by evaluating epigenetic regulatory signature (DNA methylation and miRNA) using an integrative bioinformatic analysis. We integrated DNA expression array data with miRNA and DNA methylation array data - obtained from the GEO database- to evaluate the epigenetic regulatory mechanisms.

RESULTS

Our results indicated that target genes of dysregulated miRNAs were significantly related to several neurodegenerative diseases. Several dysregulated genes in the neurodegeneration pathways interacted with some members of the miR-17 and miR-15/107 families. Our analysis indicated that APP/CaN/NFATs signaling pathway was dysregulated in the peripheral blood samples of PTSD. Besides, the DNMT3a and KMT2D genes, as the encoding DNA and histone methyltransferase enzymes, were upregulated, and DNA methylation and miRNA regulators were proposed as critical molecular mechanisms. Our study found dysregulation of circadian rhythm as the CLOCK gene was upregulated and hypomethylated at TSS1500 CpGs S_shores and was also a target of several dysregulated miRNAs.

CONCLUSION

In conclusion, we found evidence of a negative feedback loop between stress oxidative, circadian rhythm dysregulation, miR-17 and miR-15/107 families, some essential genes involved in neuronal and brain cell health, and KMT2D/DNMT3a in the peripheral blood samples of PTSD.

Comparative computational analysis to distinguish mesenchymal stem cells from fibroblasts

Introduction

Mesenchymal stem cells (MSCs) are considered to be the most promising stem cell type for cell-based therapies in regenerative medicine. Based on their potential to home to diseased body sites following a therapeutically application, these cells could (i) differentiate then into organ-specific cell types to locally restore injured cells or, most prominently, (ii) foster tissue regeneration including immune modulations more indirectly by secretion of protective growth factors and cytokines. As tissue-resident stem cells of mesenchymal origin, these cells are morphologically and even molecularly- at least concerning the classical marker genes- indistinguishable from similar lineage cells, particularly fibroblasts.

Methods

Here we used microarray-based gene expression and global DNA methylation analyses as well as accompanying computational tools in order to specify differences between MSCs and fibroblasts, to further unravel potential identity genes and to highlight MSC signaling pathways with regard to their trophic and immunosuppressive action.

Results

We identified 1352 differentially expressed genes, of which in the MSCs there is a strong signature for e.g., KRAS signaling, known to play essential role in stemness maintenance, regulation of coagulation and complement being decisive for resolving inflammatory processes, as well as of wound healing particularly important for their regenerative capacity. Genes upregulated in fibroblasts addressed predominately transcription and biosynthetic processes and mapped morphological features of the tissue. Concerning the cellular identity, we specified the already known HOX code for MSCs, established a potential HOX code for fibroblasts, and linked certain HOX genes to functional cell-type-specific properties. Accompanied methylation profiles revealed numerous regions, especially in HOX genes, being differentially methylated, which might provide additional biomarker potential.

Discussion

Conclusively, transcriptomic together with epigenetic signatures can be successfully be used for the definition (cellular identity) of MSCs versus fibroblasts as well as for the determination of the superior functional properties of MSCs, such as their immunomodulatory potential.

DNA methylation variations and epigenetic aging in telomere biology disorders

Telomere Biology Disorders (TBDs) are characterized by mutations in telomere-related genes leading to short telomeres and premature aging but with no strict correlation between telomere length and disease severity. Epigenetic alterations are also markers of aging and we aimed to evaluate whether DNA methylation (DNAm) could be part of the pathogenesis of TBDs. In blood from 35 TBD cases, genome-wide DNAm were analyzed and the cases were grouped based on relative telomere length (RTL): short (S), with RTL close to normal controls, and extremely short (ES). TBD cases had increased epigenetic age and DNAm alterations were most prominent in the ES-RTL group. Thus, the differentially methylated (DM) CpG sites could be markers of short telomeres but could also be one of the mechanisms contributing to disease phenotype since DNAm alterations were observed in symptomatic, but not asymptomatic, cases with S-RTL. Furthermore, two or more DM-CpGs were identified in four genes previously linked to TBD or telomere length (PRDM8, SMC4, VARS, and WNT6) and in three genes that were novel in telomere biology (MAS1L, NAV2, and TM4FS1). The DM-CpGs in these genes could be markers of aging in hematological cells, but they could also be of relevance for the progression of TBD.

DNA Methylation Landscapes of Prostate Cancer Brain Metastasis Are Shaped by Early Driver Genetic Alterations

Metastases from primary prostate cancers to rare locations, such as the brain, are becoming more common due to longer life expectancy resulting from improved treatments. Epigenetic dysregulation is a feature of primary prostate cancer, and distinct DNA methylation profiles have been shown to be associated with the mutually exclusive SPOP-mutant or TMPRSS2-ERG fusion genetic backgrounds. Using a cohort of prostate cancer brain metastases (PCBM) from 42 patients, with matched primary tumors for 17 patients, we carried out a DNA methylation analysis to examine the epigenetic distinction between primary prostate cancer and PCBM, the association between epigenetic alterations and mutational background, and particular epigenetic alterations that may be associated with PCBM. Multiregion sampling of PCBM revealed epigenetic stability within metastases. Aberrant methylation in PCBM was associated with mutational background and PRC2 complex activity, an effect that is particularly pronounced in SPOP-mutant PCBM. While PCBM displayed a CpG island hypermethylator phenotype, hypomethylation at the promoters of genes involved in neuroactive ligand-receptor interaction and cell adhesion molecules such as GABRB3, CLDN8, and CLDN4 was also observed, suggesting that cells from primary tumors may require specific reprogramming to form brain metastasis. This study revealed the DNA methylation landscapes of PCBM and the potential mechanisms and effects of PCBM-associated aberrant DNA methylation.

SIGNIFICANCE

DNA methylation analysis reveals the molecular characteristics of PCBM and may serve as a starting point for efforts to identify and target susceptibilities of these rare metastases.

Atypical teratoid/rhabdoid tumoroids reveal subgroup-specific drug vulnerabilities

Atypical teratoid/rhabdoid tumors (ATRTs) represent a rare, but aggressive pediatric brain tumor entity. They are genetically defined by alterations in the SWI/SNF chromatin remodeling complex members SMARCB1 or SMARCA4. ATRTs can be further classified in different molecular subgroups based on their epigenetic profiles. Although recent studies suggest that the different subgroups have distinct clinical features, subgroup-specific treatment regimens have not been developed thus far. This is hampered by the lack of pre-clinical in vitro models representative of the different molecular subgroups. Here, we describe the establishment of ATRT tumoroid models from the ATRT-MYC and ATRT-SHH subgroups. We demonstrate that ATRT tumoroids retain subgroup-specific epigenetic and gene expression profiles. High throughput drug screens on our ATRT tumoroids revealed distinct drug sensitivities between and within ATRT-MYC and ATRT-SHH subgroups. Whereas ATRT-MYC universally displayed high sensitivity to multi-targeted tyrosine kinase inhibitors, ATRT-SHH showed a more heterogeneous response with a subset showing high sensitivity to NOTCH inhibitors, which corresponded to high expression of NOTCH receptors. Our ATRT tumoroids represent the first pediatric brain tumor organoid model, providing a representative pre-clinical model which enables the development of subgroup-specific therapies.

DNA Methylation Changes in Autologous Hematopoietic Stem Cell Transplant Patients

BACKGROUND

Blood cancers may be potentially cured with hematopoietic stem cell transplantation (HCT); however, standard pre-assessments for transplant eligibility do not capture all contributing factors for transplant outcomes. Epigenetic biomarkers predict outcomes in various diseases. This pilot study aims to explore epigenetic changes (epigenetic age and differentially methylated genes) in patients before and after autologous HCT, that can serve as potential biomarkers to better predict HCT outcomes.

METHODS

This study used a prospective longitudinal study design to compare genome wide DNA methylation changes in 36 autologous HCT eligible patients recruited from the Cellular Immunotherapies and Transplant clinic at a designated National Cancer Center.

RESULTS

Genome-wide DNA methylation, measured by the Illumina Infinium Human Methylation 850K BeadChip, showed a significant difference in DNA methylation patterns post-HCT compared to pre-HCT. Compared to baseline levels of DNA methylation pre-HCT, 3358 CpG sites were hypo-methylated and 3687 were hyper-methylated. Identified differentially methylated positions overlapped with genes involved in hematopoiesis, blood cancers, inflammation and immune responses. Enrichment analyses showed significant alterations in biological processes such as immune response and cell structure organization, however no significant pathways were noted. Though participants had an advanced epigenetic age compared to chronologic age before and after HCT, both epigenetic age and accelerated age decreased post-HCT.

CONCLUSION

Epigenetic changes, both in epigenetic age and differentially methylated genes were observed in autologous HCT recipients, and should be explored as biomarkers to predict transplant outcomes after autologous HCT in larger, longitudinal studies.

A Preliminary Comparison of the Methylome and Transcriptome from the Prefrontal Cortex Across Alzheimer’s Disease and Lewy Body Dementia

Background: Pathological amyloid-β and α-synuclein are associated with a spectrum of related dementias, ranging from Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), to Parkinson disease dementia (PDD). While these diseases share clinical and pathological features, they also have unique patterns of pathology. However, epigenetic factors that contribute to these pathological differences remain unknown. Objective: In this preliminary study, we explore differences in DNA methylation and transcription in five neuropathologically defined groups: cognitively unimpaired controls, AD, pure DLB, DLB with concomitant AD (DLBAD), and PDD. Methods: We employed an Illumina Infinium 850k array and RNA-seq to quantify these differences in DNA methylation and transcription, respectively. We then used Weighted Gene Co-Network Expression Analysis (WGCNA) to determine transcriptional modules and correlated these with DNA methylation. Results: We found that PDD was transcriptionally unique and correlated with an unexpected hypomethylation pattern compared to the other dementias and controls. Surprisingly, differences between PDD and DLB were especially notable with 197 differentially methylated regions. WGCNA yielded numerous modules associated with controls and the four dementias: one module was associated with transcriptional differences between controls and all the dementias as well as having significant overlap with differentially methylated probes. Functional enrichment demonstrated that this module was associated with responses to oxidative stress. Conclusion: Future work that extends these joint DNA methylation and transcription analyses will be critical to better understanding of differences that contribute to varying clinical presentation across dementias.

Principal component analysis- and tensor decomposition-based unsupervised feature extraction to select more suitable differentially methylated cytosines: Optimization of standard deviation versus state-of-the-art methods

In contrast to RNA-seq analysis, which has various standard methods, no standard methods for identifying differentially methylated cytosines (DMCs) exist. To identify DMCs, we tested principal component analysis and tensor decomposition-based unsupervised feature extraction with optimized standard deviation, which has been shown to be effective for differentially expressed gene (DEG) identification. The proposed method outperformed certain conventional methods, including those that assume beta-binomial distribution for methylation as the proposed method does not require this, especially when applied to methylation profiles measured using high throughput sequencing. DMCs identified by the proposed method also significantly overlapped with various functional sites, including known differentially methylated regions, enhancers, and DNase I hypersensitive sites. The proposed method was applied to data sets retrieved from The Cancer Genome Atlas to identify DMCs using American Joint Committee on Cancer staging system edition labels. This suggests that the proposed method is a promising standard method for identifying DMCs.

epialleleR: an R/Bioconductor package for sensitive allele-specific methylation analysis in NGS data

Low-level mosaic epimutations within the BRCA1 gene promoter occur in 5-8% of healthy individuals and are associated with a significantly elevated risk of breast and ovarian cancer. Similar events may also affect other tumor suppressor genes, potentially being a significant contributor to cancer burden. While this opens a new area for translational research, detection of low-level mosaic epigenetic events requires highly sensitive and robust methodology for methylation analysis. We here present epialleleR, a computational framework for sensitive detection, quantification, and visualization of mosaic epimutations in methylation sequencing data. Analyzing simulated and real data sets, we provide in-depth assessments of epialleleR performance and show that linkage to epihaplotype data is necessary to detect low-level methylation events. The epialleleR is freely available at https://github.com/BBCG/epialleleR and https://bioconductor.org/packages/epialleleR/ as an open-source R/Bioconductor package.

Integrated Molecular Analysis Reveals 2 Distinct Subtypes of Pure Seminoma of the Testis

Objective

Testicular germ cell tumors (TGCT) are the most common solid malignancy in adolescent and young men, with a rising incidence over the past 20 years. Overall, TGCTs are second in terms of the average life years lost per person dying of cancer, and clinical therapeutics without adverse long-term side effects are lacking. Platinum-based regimens for TGCTs have heterogeneous outcomes even within the same histotype that frequently leads to under- and over-treatment. Understanding of molecular differences that lead to diverse outcomes of TGCT patients may improve current treatment approaches. Seminoma is the most common subtype of TGCTs, which can either be pure or present in combination with other histotypes.

Methods

Here we conducted a computational study of 64 pure seminoma samples from The Cancer Genome Atlas, applied consensus clustering approach to their transcriptomic data and revealed 2 clinically relevant seminoma subtypes: seminoma subtype 1 and 2.

Results

Our analysis identified significant differences in pluripotency stage, activity of double stranded DNA breaks repair mechanisms, rates of loss of heterozygosity, and expression of lncRNA responsible for cisplatin resistance between the subtypes. Seminoma subtype 1 is characterized by higher pluripotency state, while subtype 2 showed attributes of reprograming into non-seminomatous TGCT. The seminoma subtypes we identified may provide a molecular underpinning for variable responses to chemotherapy and radiation.

Conclusion

Translating our findings into clinical care may help improve risk stratification of seminoma, decrease overtreatment rates, and increase long-term quality of life for TGCT survivors.

Activation of stably silenced genes by recruitment of a synthetic de-methylating module

Stably silenced genes that display a high level of CpG dinucleotide methylation are refractory to the current generation of dCas9-based activation systems. To counter this, we create an improved activation system by coupling the catalytic domain of DNA demethylating enzyme TET1 with transcriptional activators (TETact). We show that TETact demethylation-coupled activation is able to induce transcription of suppressed genes, both individually and simultaneously in cells, and has utility across a number of cell types. Furthermore, we show that TETact can effectively reactivate embryonic haemoglobin genes in non-erythroid cells. We anticipate that TETact will expand the existing CRISPR toolbox and be valuable for functional studies, genetic screens and potential therapeutics.

Stably silenced genes with methylated CpG at the promoter are refractory to current CRISPR activation systems. Here the authors create a more robust activation system, TETact that recruits DNA-demethylating TET1 with transcriptional activators.