Comprehensive characterization, annotation and innovative use of Infinium DNA methylation BeadChip probes

Attenuated sex-related DNA methylation differences in cancer highlight the magnitude bias mediating existing disparities

BACKGROUND

DNA methylation (DNAm) influences both sex differences and cancer development, yet the mechanisms connecting these factors remain unclear.

METHODS

Utilizing data from The Cancer Genome Atlas, we conducted a comprehensive analysis of sex-related DNAm effects in nine non-reproductive cancers, compared to paired normal adjacent tissues (NATs), and validated the results using independent datasets. First, we assessed the extent of sex differential DNAm between cancers and NATs to explore how sex-related DNAm differences change in cancerous tissues. Next, we employed a multivariate adaptive shrinkage approach to model the covariance of cancer-related DNAm effects between sexes, aiming to elucidate how sex impacts aberrant DNAm patterns in cancers. Finally, we investigated correlations between the methylome and transcriptome to identify key signals driving sex-biased DNAm regulation in cancers.

RESULTS

Our analysis revealed a significant attenuation of sex differences in DNAm within cancerous tissues compared to baseline differences in normal tissues. We identified 3,452 CpGs (Pbonf < 0.05) associated with this reduction, with 72% of the linked genes involved in X chromosome inactivation. Through covariance analysis, we demonstrated that sex differences in cancer are predominantly driven by variations in the magnitude of shared DNAm signals, referred to as "amplification." Based on these patterns, we classified cancers into female- and male-biased groups and identified key CpGs exhibiting sex-specific amplification. These CpGs were enriched in binding sites of critical transcription factors, including P53, SOX2, and CTCF. Integrative multi-omics analyses uncovered 48 CpG-gene-cancer trios for females and 380 for males, showing similar magnitude differences in DNAm and gene expression, pointing to a sex-specific regulatory role of DNAm in cancer risk. Notably, several genes regulated by these trios were previously identified as drug targets for cancers, highlighting their potential as sex-specific therapeutic targets.

CONCLUSIONS

These findings advance our understanding of how sex, DNAm, and gene expression interact in cancer, offering insights into the development of sex-specific biomarkers and precision medicine.

Genome-wide DNA methylation and gene expression in human placentas derived from assisted reproductive technology

BACKGROUND

Assisted reproductive technology (ART) has been associated with increased risks for growth disturbance, disrupted imprinting as well as cardiovascular and metabolic disorders. However, the molecular mechanisms and whether they are a result of the ART procedures or the underlying subfertility are unknown.

METHODS

We performed genome-wide DNA methylation (EPIC Illumina microarrays) and gene expression (mRNA sequencing) analyses for a total of 80 ART and 77 control placentas. The separate analyses for placentas from different ART procedures and sexes were performed. To separate the effects of ART procedures and subfertility, 11 placentas from natural conception of subfertile couples and 12 from intrauterine insemination treatments were included.

RESULTS

Here we show that ART-associated changes in the placenta enriche in the pathways of hormonal regulation, insulin secretion, neuronal development, and vascularization. Observed decreased number of stromal cells as well as downregulated TRIM28 and NOTCH3 expressions in ART placentas indicate impaired angiogenesis and growth. DNA methylation changes in the imprinted regions and downregulation of TRIM28 suggest defective stabilization of the imprinting. Furthermore, downregulated expression of imprinted endocrine signaling molecule DLK1 associates with both ART and subfertility.

CONCLUSIONS

Decreased expressions of TRIM28, NOTCH3, and DLK1 bring forth potential mechanisms for several phenotypic features associated with ART. Our results support previous procedure specific findings: the changes associated with growth and metabolism link more prominently to the fresh embryo transfer with smaller placentas and newborns, than to the frozen embryo transfer with larger placentas and newborns. Furthermore, since the observed changes associate also with subfertility, they offer a precious insight to the molecular background of infertility.

Epigenome-wide association study of loneliness in a sample of U.S. middle-aged twins

Loneliness is a complex human trait that is highly polygenic and found to affect gene expression related to inflammatory and immunological functioning. To date, no epigenome-wide association studies of loneliness have tested whether differentially methylated sites are annotated to genes associated with inflammatory and immunological processes. Using 281 individual adult twins' DNA methylation data from the Louisville Twin Study, we performed an epigenome-wide analysis of loneliness to address this gap in the literature. In the discovery analysis, 169 twins were used to prioritize probes and test associations with DNA methylation age acceleration, and 56 independent monozygotic (MZ) twin pairs (112 individuals) were used in a within-family replication analysis. Among the 837,274 sites analyzed, no probe sites were statistically significant at the genome-wide level (p < 5.97 × 10-8), but 25 suggestive sites (p < 5 × 10-5) were annotated to genes related to various biological processes, including inflammatory response and protein-binding functions that extend prior findings. The nominal associations at these suggestive probe sites were highly correlated (r = .72) between the discovery sample and the MZ pair replication sample. Finally, loneliness significantly correlated with the DunedinPACE DNA methylation measure, suggesting that higher levels of loneliness were associated with accelerated epigenetic age as quantified by a measure that indexes longitudinal changes across multiple organ systems.

Methylation patterns associated with C-reactive protein in racially and ethnically diverse populations

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 < 1.2E-7). The downstream pathways affected by DNA methylation included the identification of IFI16 and IRF7 CpG-gene transcript pairs which contributed to the innate immune response gene enrichment pathway along with NLRC5, NOD2, and AIM2. Gene enrichment analysis also identified the nuclear factor-kappaB transcription pathway. Using two-sample Mendelian randomization (MR) we inferred methylation at three CpG sites as causal for CRP levels using both White and Black or African American MR instrument variables. Overall, we identified novel CpG sites and gene transcripts that could be valuable in understanding the specific cellular processes and pathogenic mechanisms involved in inflammation.

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.

Associations of epigenetic age acceleration at birth and age 12 years with adolescent cardiometabolic risk: the HOME study

BACKGROUND

Cardiometabolic risk factors among youth are rising. Epigenetic age acceleration, a biomarker for aging and disease-risk, has been associated with adiposity in children, but its association with other cardiometabolic risk markers remains understudied. We employed data from the Health Outcomes and Measures of the Environment (HOME) study, a prospective pregnancy and birth cohort in the greater Cincinnati metropolitan area, to examine whether accelerated epigenetic age at birth as well as accelerated epigenetic age and faster pace of biological aging at age 12 years were associated with higher cardiometabolic risk in adolescents.

RESULTS

After adjusting for potential confounders, including estimated cell type proportions, epigenetic gestational age acceleration at birth, derived from the Bohlin, Knight, and Haftorn clocks using cord blood DNA methylation data, was not associated with cardiometabolic risk z-scores or individual cardiometabolic risk score components (visceral fat, leptin to adiponectin ratio, HOMA-IR, triglycerides to HDL-C ratio, HbA1c, or systolic blood pressure) at age 12 years. We also did not observe any associations of epigenetic age acceleration, calculated with Horvath's skin and blood, Hannum's, and Wu's epigenetic clocks using peripheral blood at age 12 years, with these same cardiometabolic risk markers. In contrast, faster pace of biological aging was associated with higher cardiometabolic risk [βs (95% CIs)] cardiometabolic risk score 0.25 (0.07, 0.42); visceral fat 0.21 (0.05, 0.38); and hemoglobin A1c 0.23 (0.05, 0.41) per standard deviation increase in pace of biological aging. Faster pace of biological aging was also positively associated with systolic blood pressure, triglycerides to HDL-C ratio, HOMA-IR, and leptin to adiponectin ratio, although these associations were not statistically significant.

CONCLUSIONS

Our findings provide evidence that faster pace of biological aging was associated with higher cardiometabolic risk score, visceral fat, and HbA1c at age 12 years. Further research is needed to determine whether these associations persist from adolescence through adulthood.

Pre-diagnosis blood DNA methylation profiling of twin pairs discordant for breast cancer points to the importance of environmental risk factors

BACKGROUND

Assessment of breast cancer (BC) risk generally relies on mammography, family history, reproductive history, and genotyping of major mutations. However, assessing the impact of environmental factors, such as lifestyle, health-related behavior, or external exposures, is still challenging. DNA methylation (DNAm), capturing both genetic and environmental effects, presents a promising opportunity. Previous studies have identified associations and predicted the risk of BC using DNAm in blood; however, these studies did not distinguish between genetic and environmental contributions to these DNAm sites. In this study, associations between DNAm and BC are assessed using paired twin models, which control for shared genetic and environmental effects, allowing testing for associations between DNAm and non-shared environmental exposures and behavior.

RESULTS

Pre-diagnosis blood samples of 32 monozygotic (MZ) and 76 dizygotic (DZ) female twin pairs discordant for BC were collected at the mean age of 56.0 years, with the mean age at diagnosis 66.8 years and censoring 75.2 years. We identified 212 CpGs (p < 6.4*10-8) and 15 DMRs associated with BC risk across all pairs using paired Cox proportional hazard models. All but one of the BC risks associated with CpGs were hypomethylated, and 198/212 CpGs had their DNAm associated with BC risk independent of genetic effects. According to previous literature, at least five of the top CpGs were related to estrogen signaling. Following a comprehensive two-sample Mendelian randomization analysis, we found evidence supporting a dual causal impact of DNAm at cg20145695 (gene body of NXN, rs480351) with increased risk for estrogen receptor positive BC and decreased risk for estrogen receptor negative BC.

CONCLUSION

While causal effects of DNAm on BC risk are rare, most of the identified CpGs associated with the risk of BC appear to be independent of genetic effects. This suggests that DNAm could serve as a valuable biomarker for environmental risk factors for BC, and may offer potential benefits as a complementary tool to current risk assessment procedures.

MethylCallR : a comprehensive analysis framework for Illumina Methylation Beadchip

DNA methylation is a molecular process that mediates gene-environment interactions. Epigenome-wide association studies (EWAS) using the Illumina Human Methylation BeadChip are powerful tools for quantifying the relationship between DNA methylation and phenotypes. Recently, the Illumina Methylation EPICv2 BeadChip (EPICv2) was released, which includes new features, such as duplicated probes and changed probe names. Several published algorithms have been updated to address these features in EPICv2. However, appropriate EPICv2 preprocessing and integration with previous microarray versions remain complex. Therefore, MethylCallR, an open-source R package designed to provide standard procedures for performing EWAS using Illumina methylation microarrays including EPICv2, was developed. MethylCallR can be used to control duplicated probes in EPICv2, by using pre-set data implemented in MethylCallR or new customized data. MethylCallR includes a straightforward conversion function between different types of Illumina Human Methylation BeadChips. Using MethylCallR, potential outlier sample detection and statistical power estimation were conducted and used to select meaningful probes. Publicly available data was analyzed using MethylCallR and the findings were compared to that of a previous study.

Epigenetic signatures of asthma: a comprehensive study of DNA methylation and clinical markers

BACKGROUND

Asthma, a complex respiratory disease, presents with inflammatory symptoms in the lungs, blood, and other tissues. We investigated the relationship between DNA methylation and 35 clinical markers of asthma.

METHODS

The Illumina Infinium EPIC v1 methylation array was used to evaluate 742,442 CpGs in whole blood from 319 participants from 94 families. They were part of the Netherlands Twin Register from families with at least one member suffering from severe asthma. Repeat blood samples were taken after 10 years from 182 individuals. Principal component analysis on the clinical asthma markers yielded ten principal components (PCs) that explained 92.8% of the total variance. We performed epigenome-wide association studies (EWAS) for each of the ten PCs correcting for familial structure and other covariates.

RESULTS

221 unique CpGs reached genome-wide significance at timepoint 1 after Bonferroni correction. PC7, which correlated with loadings of eosinophil counts and immunoglobulin levels, accounted for the majority of associations (204). Enrichment analysis via the EWAS Atlas identified 190 of these CpGs to be previously identified in EWASs of asthma and asthma-related traits. Proximity assessment to previously identified SNPs associated with asthma identified 17 unique SNPs within 1 MB of two of the 221 CpGs. EWAS in 182 individuals with epigenetic data at a second timepoint identified 49 significant CpGs. EWAS Atlas enrichment analysis indicated that 4 of the 49 were previously associated with asthma or asthma-related traits. Comparing the estimates of all the significant associations identified across the two time points yielded a correlation of 0.81.

CONCLUSION

We identified 270 unique CpGs that were associated with PC scores generated from 35 clinical markers of asthma, either cross-sectionally or 10 years later. A strong correlation was present between effect sizes at the 2 timepoints. Most associations were identified for PC7, which captured blood eosinophil counts and immunoglobulin levels and many of these CpGs have previous associations in earlier studies of asthma and asthma-related traits. The results point to a robust DNA methylation profile as a new, stable biomarker for asthma.

Serotonin Transporter (SLC6A4) and FK506-Binding Protein 5 (FKBP5) Genotype and Methylation Relationships with Response to Meditation in Veterans with PTSD

Meditation-based interventions are novel and effective non-pharmacologic treatments for veterans with PTSD. We examined relationships between treatment response, early life trauma exposure, DNA polymorphisms, and methylation in the serotonin transporter (SLC6A4) and FK506-binding protein 5 (FKBP5) genes. DNA samples and clinical outcomes were examined in 72 veterans with PTSD who received meditation-based therapy in two separate studies of mindfulness-based stress reduction (MBSR) and Transcendental Meditation (TM). The PTSD Checklist was administered to assess symptoms at baseline and after 9 weeks of meditation intervention. We examined the SLC6A4 promoter (5HTTLPR_L/S insertion/deletion + rs25531_A/G) polymorphisms according to previously defined gene expression groups, and the FKBP5 variant rs1360780 previously associated with PTSD disease risk. Methylation for CpG sites of SLC6A4 (28 sites) and FKBP5 (45 sites) genes was quantified in DNA samples collected before and after treatment. The 5HTTLPR LALA high expression genotype was associated with greater symptom improvement in participants exposed to early life trauma (p = 0.015). Separately, pre to post-treatment change of DNA methylation in a group of nine FKBP5 CpG sites was associated with greater symptom improvement (OR = 2.8, 95% CI 1.1-7.1, p = 0.027). These findings build on a wealth of existing knowledge regarding epigenetic and genetic relationships with PTSD disease risk to highlight the potential importance of SLC6A4 and FKBP5 for treatment mechanisms and as biomarkers of symptom improvement.

Glioma immune microenvironment composition calculator (GIMiCC): a method of estimating the proportions of eighteen cell types from DNA methylation microarray data

A scalable platform for cell typing in the glioma microenvironment can improve tumor subtyping and immune landscape detection as successful immunotherapy strategies continue to be sought and evaluated. DNA methylation (DNAm) biomarkers for molecular classification of tumor subtypes have been developed for clinical use. However, tools that predict the cellular landscape of the tumor are not well-defined or readily available. We developed the Glioma Immune Microenvironment Composition Calculator (GIMiCC), an approach for deconvolution of cell types in gliomas using DNAm data. Using data from 17 isolated cell types, we describe the derivation of the deconvolution libraries in the biological context of selected genomic regions and validate deconvolution results using independent datasets. We utilize GIMiCC to illustrate that DNAm-based estimates of immune composition are clinically relevant and scalable for potential clinical implementation. In addition, we utilize GIMiCC to identify composition-independent DNAm alterations that are associated with high immune infiltration. Our future work aims to optimize GIMiCC and advance the clinical evaluation of glioma.

DNA methylation stability in cardiac tissues kept at different temperatures and time intervals

Investigating DNA methylation (DNAm) in cardiac tissues is vital for epigenetic research in cardiovascular diseases (CVDs). During cardiac surgery, biopsies may not be immediately stored due to a lack of human or technical resources at the collection site. Assessing DNAm stability in cardiac samples left in suboptimal conditions is crucial for applying DNAm analysis. We investigated the stability of DNAm in human cardiac tissues kept at 4 °C and 22 °C for periods of 1, 7, 14, and 28 days (exposed samples) using the Illumina Infinium MethylationEPIC v1.0 BeadChip Array. We observed high correlations between samples analysed immediately after tissue collection and exposed ones (R2 > 0.992). Methylation levels were measured as β-values and median absolute β-value differences (|∆β|) ranged from 0.0093 to 0.0119 in all exposed samples. Pairwise differentially methylated position (DMP) analysis revealed no DMPs under 4 °C (fridge temperature) exposure for up to 28 days and 22 °C (room temperature) exposure for one day, while 3,437, 6,918, and 3,824 DMPs were observed for 22 °C samples at 7, 14, and 28 days, respectively. This study provides insights into the stability of genome-wide DNAm, showing that cardiac tissue can be used for reliable DNAm analysis even when stored suboptimally after surgery.

Impact of genomic background and developmental state on signaling pathways and response to therapy in glioblastoma patient-derived cells

Glioblastoma (GBM) tumors represents diverse genomic epigenomic, and transcriptional landscapes, with significant intratumoral heterogeneity that challenges standard of care treatments involving radiation (RT) and the DNA-alkylating agent temozolomide (TMZ). In this study, we employed targeted proteomics to assess the response of a genomically-diverse panel of GBM patient-derived cancer stem cells (CSCs) to astrocytic differentiation, growth factor withdrawal and traditional high fetal bovine serum culture. Our findings revealed a complex crosstalk and co-activation of key oncogenic signaling in CSCs and diverse patterns of response to these external stimuli. Using RNA sequencing and DNA methylation, we observed common adaptations in response to astrocytic differentiation of CSCs across genomically distinct models, including BMP-Smad pathway activation, reduced cholesterol biosynthesis, and upregulation of extracellular matrix components. Notably, we observed that these differentiated CSC progenies retained a subset of stemness genes and the activation of cell survival pathways. We also examined the impact of differentiation state and genomic background on GBM cell sensitivity and transcriptional response to TMZ and RT. Differentiation of CSCs increased resistance to TMZ but not to RT. While transcriptional responses to these treatments were predominantly regulated by p53 in wild-type p53 GBM cells, its transcriptional activity was modulated by the differentiation status and treatment modality. Both mutant and wild-type p53 models exhibited significant activation of a DNA-damage associated interferon response in CSCs and differentiated cells, suggesting this pathway may play a wider role in GBM response to TMZ and RT. Our integrative analysis of the impact of GBM cell developmental states, in the context of genomic and molecular diversity of patient-derived models, provides valuable insights for pre-clinical studies aimed at optimizing treatment strategies.

Technical and biological sources of unreliability of Infinium probes on Illumina methylation microarrays

The Illumina Methylation array platform has facilitated countless epigenetic studies on DNA methylation (DNAme) in health and disease, yet relatively few studies have so studied its reliability, i.e., the consistency of repeated measures. Here we investigate the reliability of both type I and type II Infinium probes. We propose a method for excluding unreliable probes based on dynamic thresholds for mean intensity (MI) and 'unreliability', estimated by probe-level simulation of the influence of technical noise on methylation β values using the background intensities of negative control probes. We validate our method in several datasets, including newly generated Illumina MethylationEPIC BeadChip v1.0 data from paired whole blood samples taken six weeks apart and technical replicates spanning multiple sample types. Our analysis revealed that specifically probes with low MI exhibit higher β value variability between repeated samples. MI was associated with the number of C-bases in the respective probe sequence and correlated negatively with unreliability scores. The unreliability scores were substantiated through validation in a new EPIC v1.0 (blood and cervix) and a publicly available 450k (blood) dataset, as they effectively captured the variability observed in β values between technical replicates. Finally, despite promising higher robustness, the newer version v2.0 of the MethylationEPIC BeadChip retained a substantial number of probes with poor unreliability scores. To enhance current pre-processing pipelines, we developed an R package to calculate MI and unreliability scores and provide guidance on establishing optimal dynamic score thresholds for a given dataset.

Epigenetic programming of host lipid metabolism associated with resistance to TST/IGRA conversion after exposure to Mycobacterium tuberculosis

Mycobacterium tuberculosis (Mtb) exposure leads to a range of outcomes including clearance, latent TB infection (LTBI), and pulmonary tuberculosis (TB). Some heavily exposed individuals resist tuberculin skin test (TST) and interferon-gamma (IFNγ) release assay (IGRA) conversion (RSTR), which suggests that they employ IFNγ-independent mechanisms of Mtb control. Here, we compare monocyte epigenetic profiles of RSTR and LTBI from a Ugandan household contact cohort. Chromatin accessibility did not differ between uninfected RSTR and LTBI monocytes. By contrast, methylation significantly differed at 174 CpG sites and across 63 genomic regions. Consistent with previous transcriptional findings in this cohort, differential methylation was enriched in lipid- and cholesterol-associated pathways including the genes APOC3, KCNQ1, and PLA2G3. In addition, methylation was enriched in Hippo signaling, which is associated with cholesterol homeostasis and includes CIT and SHANK2. Lipid export and Hippo signaling pathways were also associated with gene expression in response to Mtb in RSTR as well as IFN stimulation in monocyte-derived macrophages (MDMs) from an independent healthy donor cohort. Moreover, serum-derived high-density lipoprotein from RSTR had elevated ABCA1-mediated cholesterol efflux capacity (CEC) compared to LTBI. Our findings suggest that resistance to TST/IGRA conversion is linked to regulation of lipid accumulation in monocytes, which could facilitate early Mtb clearance among RSTR subjects through IFNγ-independent mechanisms.IMPORTANCETuberculosis (TB) remains an enduring global health challenge with millions of deaths and new cases each year. Despite recent advances in TB treatment, we lack an effective vaccine or a durable cure. While heavy exposure to Mycobacterium tuberculosis often results in latent TB latent infection (LTBI), subpopulations exist that are either resistant to infection or contain Mtb with interferon-gamma (IFNγ)-independent mechanisms not indicative of LTBI. These resisters provide an opportunity to investigate the mechanisms of TB disease and discover novel therapeutic targets. Here, we compare monocyte epigenetic profiles of RSTR and LTBI from a Ugandan household contact cohort. We identify methylation signatures in host lipid and cholesterol pathways with potential relevance to early TB clearance before the sustained IFN responses indicative of LTBI. This adds to a growing body of literature linking TB disease outcomes to host lipids.

Interactive effect of air pollution and genetic risk of depression on processing speed by resting-state functional connectivity of occipitoparietal network

BACKGROUND

Air pollution, a reversible environmental factor, was significantly associated with the cognitive domains that are impaired in major depressive disorder (MDD), notably processing speed. Limited evidence explores the interactive effect of air pollution and the genetic risk of depression on cognition. This cross-sectional study aims to extend the research by specifically examining how this interaction influences depression-related cognitive impairment and resting-state brain function.

METHODS

Eligible participants were 497 healthy adult volunteers (48.7% males, mean age 24.5) living in Beijing for at least 1 year and exposed to relatively high air pollution from the local community controlling for socioeconomic and genomic. Six months' ambient air pollution exposures were assessed based on residential addresses using monthly averages of fine particulate matter with a diameter of less than or equal to 2.5 μm (PM2.5). A cross-sectional analysis was conducted using functional magnetic resonance imaging (fMRI) and cognitive performance assessments. The polygenic risk score (PRS) of MDD was used to estimate genetic susceptibility.

RESULTS

Using a general linear model and partial least square regression, we observed a negative association between resting-state local connectivity in precuneus and PRS-by-PM2.5 interactive effect (PFWE = 0.028), indicating that PM2.5 exposure reduced the spontaneous activity in precuneus in individuals at high genetic risk for MDD. DNA methylation and gene expression of the SLC30A3 gene, responsible for maintaining zinc-glutamate homeostasis, was suggestively associated with this local connectivity. For the global functional connectivity, the polygenic risk for MDD augmented the neural impact of PM2.5 exposure, especially in the frontal-parietal and frontal-limbic regions of the default mode network (PFDR < 0.05). In those genetically predisposed to MDD, increased PM2.5 exposure positively correlated with resting-state functional connectivity between the left angular gyrus and left cuneus gyrus. This connectivity was negatively associated with processing speed.

CONCLUSIONS

Our cross-sectional study suggests that air pollution may be associated with an increased likelihood of cognitive impairment in individuals genetically predisposed to depression, potentially through alterations in the resting-state function of the occipitoparietal and default mode network.

Schizophrenia is associated with altered DNA methylation variance

Varying combinations of genetic and environmental risk factors are thought to underpin phenotypic heterogeneity between individuals in psychiatric conditions such as schizophrenia. While epigenome-wide association studies in schizophrenia have identified extensive alteration of mean DNA methylation levels, less is known about the location and impact of DNA methylation variance, which could contribute to phenotypic and treatment response heterogeneity. To explore this question, we conducted the largest meta-analysis of blood DNA methylation variance in schizophrenia to date, leveraging three cohorts comprising 1036 individuals with schizophrenia and 954 non-psychiatric controls. Surprisingly, only a small proportion (0.1%) of the 213 variably methylated positions (VMPs) associated with schizophrenia (Benjamini-Hochberg FDR < 0.05) were shared with differentially methylated positions (DMPs; sites with mean changes between cases and controls). These blood-derived VMPs were found to be overrepresented in genes previously associated with schizophrenia and amongst brain-enriched genes, with evidence of concordant changes at VMPs in the cerebellum, hippocampus, prefrontal cortex, or striatum. Epigenetic covariance was also observed with respect to clinically significant metrics including age of onset, cognitive deficits, and symptom severity. We also uncovered a significant VMP in individuals with first-episode psychosis (n = 644) from additional cohorts and a non-psychiatric comparison group (n = 633). Collectively, these findings suggest schizophrenia is associated with significant changes in DNA methylation variance, which may contribute to individual-to-individual heterogeneity.

Developing survival prediction models in colorectal cancer using epigenome-wide DNA methylation data from whole blood

While genome-wide association studies are valuable in identifying CRC survival predictors, the benefit of adding blood DNA methylation (blood-DNAm) to clinical features, including the TNM system, remains unclear. In a multi-site population-based patient cohort study of 2116 CRC patients with baseline blood-DNAm, we analyzed survival predictions using eXtreme Gradient Boosting with a 5-fold nested leave-sites-out cross-validation across four groups: traditional and comprehensive clinical features, blood-DNAm, and their combination. Model performance was assessed using time-dependent ROC curves and calibrations. During a median follow-up of 10.3 years, 1166 patients died. Although blood-DNAm-based predictive signatures achieved moderate performances, predictive signatures based on clinical features outperformed blood-DNAm signatures. The inclusion of blood-DNAm did not improve survival prediction over clinical features. M1 stage, age at blood collection, and N2 stage were the top contributors. Despite some prognostic value, incorporating blood DNA methylation did not enhance survival prediction of CRC patients beyond clinical features.

A comprehensive map of the aging blood methylome in humans

BACKGROUND

During aging, the human methylome undergoes both differential and variable shifts, accompanied by increased entropy. The distinction between variably methylated positions (VMPs) and differentially methylated positions (DMPs), their contribution to epigenetic age, and the role of cell type heterogeneity remain unclear.

RESULTS

We conduct a comprehensive analysis of > 32,000 human blood methylomes from 56 datasets (age range = 6-101 years). We find a significant proportion of the blood methylome that is differentially methylated with age (48% DMPs; FDR < 0.005) and variably methylated with age (37% VMPs; FDR < 0.005), with considerable overlap between the two groups (59% of DMPs are VMPs). Bivalent and Polycomb regions become increasingly methylated and divergent between individuals, while quiescent regions lose methylation more uniformly. Both chronological and biological clocks, but not pace-of-aging clocks, show a strong enrichment for CpGs undergoing both mean and variance changes during aging. The accumulation of DMPs shifting towards a methylation fraction of 50% drives the increase in entropy, smoothening the epigenetic landscape. However, approximately a quarter of DMPs exhibit anti-entropic effects, opposing this direction of change. While changes in cell type composition minimally affect DMPs, VMPs and entropy measurements are moderately sensitive to such alterations.

CONCLUSION

This study represents the largest investigation to date of genome-wide DNA methylation changes and aging in a single tissue, providing valuable insights into primary molecular changes relevant to chronological and biological aging.

A novel method for cell deconvolution using DNA methylation in PCA space

BACKGROUND

In this study, we present a novel method for reference-based cell deconvolution using data from DNA methylation arrays. Different from existing methods like IDOL-Ext, which operate on probe-level data, our approach represents features in the principal component analysis (PCA) space for cell type deconvolution.

RESULTS

Our method's accuracy in estimating cell compositions is validated across various public datasets, including blood samples from glioma patients. It demonstrates precision comparable to IDOL-Ext, with R2 values ranging from 0.73 to 0.99 for most cell types, while offering improved discrimination between similar cell types, particularly T cell subtypes in glioma patient samples (R2 0.42-0.75 vs. 0.36-0.66 for IDOL-Ext). However, both methods showed lower accuracy for certain cell types, such as memory CD8 T cells in glioma patients (R2 0.42 vs. 0.36 for IDOL-Ext), highlighting the challenges in distinguishing closely related cell populations. We have made this method available as an R package "BloodCellDecon" on GitHub.

CONCLUSIONS

Our study confirms the efficacy of cell type deconvolution in PCA space. The results indicate wide-ranging applicability and potential for adaptation to other forms of genomic data.

Epigenetic and genetic risk of Alzheimer disease from autopsied brains in two ethnic groups

Genetic variants and epigenetic features both contribute to the risk of Alzheimer's disease (AD). We studied the AD association of CpG-related single nucleotide polymorphisms (CGS), which act as a hub of both the genetic and epigenetic effects, in Caribbean Hispanics (CH) and generalized the findings to Non-Hispanic Whites (NHW). First, we conducted a genome-wide, sliding-window-based association with AD, in 7,155 CH and 1,283 NHW participants. Next, using data from the dorsolateral prefrontal cortex in 179 CH brains, we tested the cis- and trans-effects of AD-associated CGS on brain DNA methylation to mRNA expression. For the genes with significant cis- and trans-effects, we investigated their enriched pathways. We identified six genetic loci in CH with CGS dosage associated with AD at genome-wide significance levels: ADAM20 (Score = 55.19, P = 4.06 × 10-8), the intergenic region between VRTN and SYNDIG1L (Score = - 37.67, P = 2.25 × 10-9), SPG7 (16q24.3) (Score = 40.51, P = 2.23 × 10-8), PVRL2 (Score = 125.86, P = 1.64 × 10-9), TOMM40 (Score = - 18.58, P = 4.61 × 10-8), and APOE (Score = 75.12, P = 7.26 × 10-26). CGSes in PVRL2 and APOE were also significant in NHW. Except for ADAM20, CGSes in the other five loci were associated with CH brain methylation levels (mQTLs) and CGSes in SPG7, PVRL2, and APOE were also mQTLs in NHW. Except for SYNDIG1L (P = 0.08), brain methylation levels in the other five loci affected downstream mRNA expression in CH (P < 0.05), and methylation at VRTN and TOMM40 were also associated with mRNA expression in NHW. Gene expression in these six loci were also regulated by CpG sites in genes that were enriched in the neuron projection and glutamatergic synapse pathways (FDR < 0.05). DNA methylation at all six loci and mRNA expression of SYNDIG1 and TOMM40 were significantly associated with Braak Stage in CH. In summary, we identified six CpG-related genetic loci associated with AD in CH, harboring both genetic and epigenetic risks. However, their downstream effects on mRNA expression maybe ethnic specific and different from NHW.

Epigenetic patterns, accelerated biological aging, and enhanced epigenetic drift detected 6 months following COVID-19 infection: insights from a genome-wide DNA methylation study

BACKGROUND

The epigenetic status of patients 6-month post-COVID-19 infection remains largely unexplored. The existence of long-COVID, or post-acute sequelae of SARS-CoV-2 infection (PASC), suggests potential long-term changes. Long-COVID includes symptoms like fatigue, neurological issues, and organ-related problems, regardless of initial infection severity. The mechanisms behind long-COVID are unclear, but virus-induced epigenetic changes could play a role.

METHODS AND RESULTS

Our study explores the lasting epigenetic impacts of SARS-CoV-2 infection. We analyzed genome-wide DNA methylation patterns in an Italian cohort of 96 patients 6 months after COVID-19 exposure, comparing them to 191 healthy controls. We identified 42 CpG sites with significant methylation differences (FDR < 0.05), primarily within CpG islands and gene promoters. Dysregulated genes highlighted potential links to glutamate/glutamine metabolism, which may be relevant to PASC symptoms. Key genes with potential significance to COVID-19 infection and long-term effects include GLUD1, ATP1A3, and ARRB2. Furthermore, Horvath's epigenetic clock showed a slight but significant age acceleration in post-COVID-19 patients. We also observed a substantial increase in stochastic epigenetic mutations (SEMs) in the post-COVID-19 group, implying potential epigenetic drift. SEM analysis identified 790 affected genes, indicating dysregulation in pathways related to insulin resistance, VEGF signaling, apoptosis, hypoxia response, T-cell activation, and endothelin signaling.

CONCLUSIONS

Our study provides valuable insights into the epigenetic consequences of COVID-19. Results suggest possible associations with accelerated aging, epigenetic drift, and the disruption of critical biological pathways linked to insulin resistance, immune response, and vascular health. Understanding these epigenetic changes could be crucial for elucidating the complex mechanisms behind long-COVID and developing targeted therapeutic 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.

Maternal smoking DNA methylation risk score associated with health outcomes in offspring of European and South Asian ancestry

Background

Maternal smoking has been linked to adverse health outcomes in newborns but the extent to which it impacts newborn health has not been quantified through an aggregated cord blood DNA methylation (DNAm) score. Here, we examine the feasibility of using cord blood DNAm scores leveraging large external studies as discovery samples to capture the epigenetic signature of maternal smoking and its influence on newborns in White European and South Asian populations.

Methods

We first examined the association between individual CpGs and cigarette smoking during pregnancy, and smoking exposure in two White European birth cohorts (n=744). Leveraging established CpGs for maternal smoking, we constructed a cord blood epigenetic score of maternal smoking that was validated in one of the European-origin cohorts (n=347). This score was then tested for association with smoking status, secondary smoking exposure during pregnancy, and health outcomes in offspring measured after birth in an independent White European (n=397) and a South Asian birth cohort (n=504).

Results

Several previously reported genes for maternal smoking were supported, with the strongest and most consistent association signal from the GFI1 gene (6 CpGs with p<5 × 10-5). The epigenetic maternal smoking score was strongly associated with smoking status during pregnancy (OR = 1.09 [1.07, 1.10], p=5.5 × 10-33) and more hours of self-reported smoking exposure per week (1.93 [1.27, 2.58], p=7.8 × 10-9) in White Europeans. However, it was not associated with self-reported exposure (p>0.05) among South Asians, likely due to a lack of smoking in this group. The same score was consistently associated with a smaller birth size (-0.37±0.12 cm, p=0.0023) in the South Asian cohort and a lower birth weight (-0.043±0.013 kg, p=0.0011) in the combined cohorts.

Conclusions

This cord blood epigenetic score can help identify babies exposed to maternal smoking and assess its long-term impact on growth. Notably, these results indicate a consistent association between the DNAm signature of maternal smoking and a small body size and low birth weight in newborns, in both White European mothers who exhibited some amount of smoking and in South Asian mothers who themselves were not active smokers.

Funding

This study was funded by the Canadian Institutes of Health Research Metabolomics Team Grant: MWG-146332.

Multi-omics Analysis of Umbilical Cord Hematopoietic Stem Cells from a Multi-ethnic Cohort of Hawaii Reveals the Transgenerational Effect of Maternal Pre-Pregnancy Obesity

Background

Maternal obesity is a health concern that may predispose newborns to a high risk of medical problems later in life. To understand the transgenerational effect of maternal obesity, we conducted a multi-omics study, using DNA methylation and gene expression in the CD34+/CD38-/Lin- umbilical cord blood hematopoietic stem cells (uHSCs) and metabolomics of the cord blood, all from a multi-ethnic cohort (n=72) from Kapiolani Medical Center for Women and Children in Honolulu, Hawaii (collected between 2016 and 2018).

Results

Differential methylation (DM) analysis unveiled a global hypermethylation pattern in the maternal pre-pregnancy obese group (BH adjusted p<0.05), after adjusting for major clinical confounders. Comprehensive functional analysis showed hypermethylation in promoters of genes involved in cell cycle, protein synthesis, immune signaling, and lipid metabolism. Utilizing Shannon entropy on uHSCs methylation, we discerned notably higher quiescence of uHSCs impacted by maternal obesity. Additionally, the integration of multi-omics data-including methylation, gene expression, and metabolomics-provided further evidence of dysfunctions in adipogenesis, erythropoietin production, cell differentiation, and DNA repair, aligning with the findings at the epigenetic level. Furthermore, the CpG sites associated with maternal obesity from these pathways also predicted highly accurately (average AUC = 0.8687) between cancer vs. normal tissues in 14 cancer types in The Cancer Genome Atlas (TCGA).

Conclusions

This study revealed the significant correlation between pre-pregnancy maternal obesity and multi-omics level molecular changes in the uHSCs of offspring, particularly in DNA methylation. Moreover, these maternal obesity epigenetic markers in uHSCs may predispose offspring to higher cancer risks.

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.

Sex effects on DNA methylation affect discovery in epigenome-wide association study of schizophrenia

Sex differences in the epidemiology and clinical characteristics of schizophrenia are well-known; however, the molecular mechanisms underlying these differences remain unclear. Further, the potential advantages of sex-stratified meta-analyses of epigenome-wide association studies (EWAS) of schizophrenia have not been investigated. Here, we performed sex-stratified EWAS meta-analyses to investigate whether sex stratification improves discovery, and to identify differentially methylated regions (DMRs) in schizophrenia. Peripheral blood-derived DNA methylation data from 1519 cases of schizophrenia (male n = 989, female n = 530) and 1723 controls (male n = 997, female n = 726) from three publicly available datasets, and the TOP cohort were meta-analyzed to compare sex-specific, sex-stratified, and sex-adjusted EWAS. The predictive power of each model was assessed by polymethylation score (PMS). The number of schizophrenia-associated differentially methylated positions identified was higher for the sex-stratified model than for the sex-adjusted one. We identified 20 schizophrenia-associated DMRs in the sex-stratified analysis. PMS from sex-stratified analysis outperformed that from sex-adjusted analysis in predicting schizophrenia. Notably, PMSs from the sex-stratified and female-only analyses, but not those from sex-adjusted or the male-only analyses, significantly predicted schizophrenia in males. The findings suggest that sex-stratified EWAS meta-analyses improve the identification of schizophrenia-associated epigenetic changes and highlight an interaction between sex and schizophrenia status on DNA methylation. Sex-specific DNA methylation may have potential implications for precision psychiatry and the development of stratified treatments for schizophrenia.

Epigenome-wide association study of prostate cancer in African American men identified differentially methylated genes

INTRODUCTION

Men with African ancestry have the highest incidence and mortality rates of prostate cancer (PCa) worldwide.

METHODS

This study aimed to identify differentially methylated genes between tumor vs. adjacent normal and aggressive vs. indolent PCa in 121 African American patients. Epigenome-wide DNA methylation patterns in tumor DNA were assessed using the human Illumina Methylation EPIC V1 array.

RESULTS

Around 5,139 differentially methylated CpG-sites (q < 0.01, lΔβl > 0.2) were identified when comparing normal vs. tumor, with an overall trend of hypermethylation in prostate tumors.  Multiple representative differentially methylated regions (DMRs), including immune-related genes, such as CD40, Galectin3, OX40L, and STING, were detected in prostate tumors when compared to adjacent normal tissues. Based on an epigenetic clock model, we observed that tumors' total number of stem cell divisions and the stem cell division rate were significantly higher than adjacent normal tissues. Regarding PCa aggressiveness, 2,061 differentially methylated CpG-sites (q < 0.05, lΔβl > .05) were identified when the grade group (GG)1 was compared with GG4/5. Among these 2,061 CpG sites, 155 probes were consistently significant in more than one comparison. Among these genes, several immune system genes, such as COL18A1, S100A2, ITGA4, HLA-C, and ADCYAP1, have previously been linked to tumor progression in PCa.

CONCLUSION

Several differentially methylated genes involved in immune-oncologic pathways associated with disease risk or aggressiveness were identified. In addition, 261 African American-specific differentially methylated genes related to the risk of PCa were identified. These results can shedlight on potential mechanisms contributing to PCa disparities in the African American Population.

Twisting the theory on the origin of human umbilical cord coiling featuring monozygotic twins

The human umbilical cord (hUC) is the lifeline that connects the fetus to the mother. Hypercoiling of the hUC is associated with pre- and perinatal morbidity and mortality. We investigated the origin of hUC hypercoiling using state-of-the-art imaging and omics approaches. Macroscopic inspection of the hUC revealed the helices to originate from the arteries rather than other components of the hUC. Digital reconstruction of the hUC arteries showed the dynamic alignment of two layers of muscle fibers in the tunica media aligning in opposing directions. We observed that genetically identical twins can be discordant for hUC coiling, excluding genetic, many environmental, and parental origins of hUC coiling. Comparing the transcriptomic and DNA methylation profile of the hUC arteries of four twin pairs with discordant cord coiling, we detected 28 differentially expressed genes, but no differentially methylated CpGs. These genes play a role in vascular development, cell-cell interaction, and axis formation and may account for the increased number of hUC helices. When combined, our results provide a novel framework to understand the origin of hUC helices in fetal development.

Epigenetic Signatures of Asthma: A Comprehensive Study of DNA Methylation and Clinical Markers

Background

Asthma, a complex respiratory disease, presents with inflammatory symptoms in the lungs, blood, and other tissues. We investigated the relationship between DNA methylation and 35 clinical markers of asthma. The Illumina Infinium EPIC v1 methylation array was used to evaluate 742,442 CpGs in whole blood samples from 319 participants. They were part of the Netherlands Twin Register from families with at least one member suffering from severe asthma. Repeat blood samples were taken after 10 years from 182 of these individuals. Principal component analysis (PCA) on the clinical markers yielded ten principal components (PCs) that explained 92.8% of the total variance. We performed epigenome-wide association studies (EWAS) for each of the ten PCs correcting for familial structure and other covariates.

Results

221 unique CpGs reached genome-wide significance at timepoint 1 (T1) after Bonferroni correction. PC7 accounted for the majority of associations (204), which correlated with loadings of eosinophil counts and immunoglobulin levels. Enrichment analysis via the EWAS Atlas identified 190 of these CpGs to be previously identified in EWASs of asthma and asthma-related traits. Proximity assessment to previously identified SNPs associated with asthma identified 17 unique SNPs within 1 MB of two of the 221 CpGs. EWAS in 182 individuals with epigenetic data at a second timepoint (T2) identified 49 significant CpGs. EWAS Atlas enrichment analysis indicated that 4 of the 49 were previously associated with asthma or asthma-related traits. Comparing the estimates of all the significant associations identified across the two time points (271 in total) yielded a correlation of 0.81.

Conclusion

We identified 270 unique CpGs that were associated with PC scores generated from 35 clinical markers of asthma, either cross-sectionally or 10 years later. A strong correlation was present between effect sizes at the 2 timepoints. Most associations were identified for PC7, which captured blood eosinophil counts and immunoglobulin levels and many of these CpGs have previous associations in earlier studies of asthma and asthma-related traits. The results point to using this robust DNA methylation profile as a new, stable biomarker for asthma.

DNA Methylation-derived biological age and long-term mortality risk in subjects with type 2 diabetes

BACKGROUND

Individuals with type 2 diabetes (T2D) face an increased mortality risk, not fully captured by canonical risk factors. Biological age estimation through DNA methylation (DNAm), i.e. the epigenetic clocks, is emerging as a possible tool to improve risk stratification for multiple outcomes. However, whether these tools predict mortality independently of canonical risk factors in subjects with T2D is unknown.

METHODS

Among a cohort of 568 T2D patients followed for 16.8 years, we selected a subgroup of 50 subjects, 27 survived and 23 deceased at present, passing the quality check and balanced for all risk factors after propensity score matching. We analyzed DNAm from peripheral blood leukocytes using the Infinium Human MethylationEPIC BeadChip (Illumina) to evaluate biological aging through previously validated epigenetic clocks and assess the DNAm-estimated levels of selected inflammatory proteins and blood cell counts. We tested the associations of these estimates with mortality using two-stage residual-outcome regression analysis, creating a reference model on data from the group of survived patients.

RESULTS

Deceased subjects had higher median epigenetic age expressed with DNAmPhenoAge algorithm (57.49 [54.72; 60.58] years. vs. 53.40 [49.73; 56.75] years; p = 0.012), and accelerated DunedinPoAm pace of aging (1.05 [1.02; 1.11] vs. 1.02 [0.98; 1.06]; p = 0.012). DNAm PhenoAge (HR 1.16, 95% CI 1.05-1.28; p = 0.004) and DunedinPoAm (HR 3.65, 95% CI 1.43-9.35; p = 0.007) showed an association with mortality independently of canonical risk factors. The epigenetic predictors of 3 chronic inflammation-related proteins, i.e. CXCL10, CXCL11 and enRAGE, C-reactive protein methylation risk score and DNAm-based estimates of exhausted CD8 + T cell counts were higher in deceased subjects when compared to survived.

CONCLUSIONS

These findings suggest that biological aging, as estimated through existing epigenetic tools, is associated with mortality risk in individuals with T2D, independently of common risk factors and that increased DNAm-surrogates of inflammatory protein levels characterize deceased T2D patients. Replication in larger cohorts is needed to assess the potential of this approach to refine mortality risk in T2D.

Deconstructing Intratumoral Heterogeneity through Multiomic and Multiscale Analysis of Serial Sections

Tumors may contain billions of cells, including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that are consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.

An Epigenome-Wide Association Study of DNA Methylation and Proliferative Retinopathy over 28 Years in Type 1 Diabetes

Purpose

To perform a prospective epigenome-wide association study of DNA methylation (DNAm) and 28-year proliferative diabetic retinopathy (PDR) incidence in type 1 diabetes (T1D).

Design

Prospective observational cohort study.

Participants

The Pittsburgh Epidemiology of Diabetes Complications (EDC) study of childhood-onset (< 17 years) T1D.

Methods

Stereoscopic fundus photographs were taken in fields 1, 2, and 4 at baseline, 2, 4, 6, 8, 16, 23, and 28 years after DNAm measurements. The photos were graded using the modified Airlie House System. In those free of PDR at baseline (n = 265; mean T1D duration of 18 years at baseline), whole blood DNAm (EPIC array) at 683 597 CpGs was analyzed in Cox models for time to event. Associations between significant CpGs and clinical risk factors were assessed; genetic variants associated with DNAm were identified (methylation quantitative trait loci [meQTLs]). Mendelian randomization was used to examine evidence of causal associations between DNAm and PDR. Post hoc regional and functional analyses were performed.

Main Outcome Measures

Proliferative diabetic retinopathy was defined as the first instance of a grade of ≥ 60 in at least 1 eye or pan-retinal photocoagulation for PDR. Follow-up time was calculated from the study visit at which DNAm data were available (baseline) until PDR incidence or censoring (December 31, 2018 or last follow-up).

Results

PDR incidence was 53% over 28-years' follow-up. Greater DNAm of cg27512687 (KIF16B) was associated with reduced PDR incidence (P = 6.3 × 10-9; false discovery rate [FDR]: < 0.01); 113 cis-meQTLs (P < 5 × 10-8) were identified. Mendelian randomization analysis using the sentinel meQTL as the instrumental variable supported a potentially causal association between cg27512687 and PDR. Cg27512687 was also associated with lower pulse rate and albumin excretion rate and higher estimated glomerular filtration rate, but its association with PDR remained independently significant after adjustment for those factors. In regional analyses, DNAm of FUT4, FKBP1A, and RIN2 was also associated with PDR incidence.

Conclusions

DNA methylation of KIF16B, FUT4, FKBP1A, and RIN2 was associated with PDR incidence, supporting roles for epigenetic regulation of iron clearance, developmental pathways, and autophagy in PDR pathogenesis. Further study of those loci may provide insight into novel targets for interventions to prevent or delay PDR in T1D.

Financial Disclosures

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

mLiftOver: harmonizing data across Infinium DNA methylation platforms

MOTIVATION

Infinium DNA methylation BeadChips are widely used for genome-wide DNA methylation profiling at the population scale. Recent updates to probe content and naming conventions in the EPIC version 2 (EPICv2) arrays have complicated integrating new data with previous Infinium array platforms, such as the MethylationEPIC (EPIC) and the HumanMethylation450 (HM450) BeadChip.

RESULTS

We present mLiftOver, a user-friendly tool that harmonizes probe ID, methylation level, and signal intensity data across different Infinium platforms. It manages probe replicates, missing data imputation, and platform-specific bias for accurate data conversion. We validated the tool by applying HM450-based cancer classifiers to EPICv2 cancer data, achieving high accuracy. Additionally, we successfully integrated EPICv2 healthy tissue data with legacy HM450 data for tissue identity analysis and produced consistent copy number profiles in cancer cells.

AVAILABILITY AND IMPLEMENTATION

mLiftOver is implemented R and available in the Bioconductor package SeSAMe (version 1.21.13+): https://bioconductor.org/packages/release/bioc/html/sesame.html. Analysis of EPIC and EPICv2 platform-specific bias and high-confidence mapping is available at https://github.com/zhou-lab/InfiniumAnnotationV1/raw/main/Anno/EPICv2/EPICv2ToEPIC_conversion.tsv.gz. The source code is available at https://github.com/zwdzwd/sesame/blob/devel/R/mLiftOver.R under the MIT license.

Prediction of DNA methylation-based tumor types from histopathology in central nervous system tumors with deep learning

Precision in the diagnosis of diverse central nervous system (CNS) tumor types is crucial for optimal treatment. DNA methylation profiles, which capture the methylation status of thousands of individual CpG sites, are state-of-the-art data-driven means to enhance diagnostic accuracy but are also time consuming and not widely available. Here, to address these limitations, we developed Deep lEarning from histoPathoLOgy and methYlation (DEPLOY), a deep learning model that classifies CNS tumors to ten major categories from histopathology. DEPLOY integrates three distinct components: the first classifies CNS tumors directly from slide images ('direct model'), the second initially generates predictions for DNA methylation beta values, which are subsequently used for tumor classification ('indirect model'), and the third classifies tumor types directly from routinely available patient demographics. First, we find that DEPLOY accurately predicts beta values from histopathology images. Second, using a ten-class model trained on an internal dataset of 1,796 patients, we predict the tumor categories in three independent external test datasets including 2,156 patients, achieving an overall accuracy of 95% and balanced accuracy of 91% on samples that are predicted with high confidence. These results showcase the potential future use of DEPLOY to assist pathologists in diagnosing CNS tumors within a clinically relevant short time frame.

Gestational exposure to environmental chemicals and epigenetic alterations in the placenta and cord blood mononuclear cells

Background

Exposure to environmental chemicals such as phthalates, phenols, and polycyclic aromatic hydrocarbons (PAHs) during pregnancy can increase the risk of adverse newborn outcomes. We explored the associations between maternal exposure to select environmental chemicals and DNA methylation in cord blood mononuclear cells (CBMC) and placental tissue (maternal and fetal sides) to identify potential mechanisms underlying these associations.

Method

This study included 75 pregnant individuals who planned to give birth at the University of Cincinnati Hospital between 2014 and 2017. Maternal urine samples during the delivery visit were collected and analyzed for 37 biomarkers of phenols (12), phthalates (13), phthalate replacements (4), and PAHs (8). Cord blood and placenta tissue (maternal and fetal sides) were also collected to measure the DNA methylation intensities using the Infinium HumanMethylation450K BeadChip. We used linear regression, adjusting for potential confounders, to assess CpG-specific methylation changes in CBMC (n = 54) and placenta [fetal (n = 67) and maternal (n = 68) sides] associated with gestational chemical exposures (29 of 37 biomarkers measured in this study). To account for multiple testing, we used a false discovery rate q-values < 0.05 and presented results by limiting results with a genomic inflation factor of 1±0.5. Additionally, gene set enrichment analysis was conducted using the Kyoto Encyclopedia of Genes and Genomics pathways.

Results

Among the 29 chemical biomarkers assessed for differential methylation, maternal concentrations of PAH metabolites (1-hydroxynaphthalene, 2-hydroxyfluorene, 4-hydroxyphenanthrene, 1-hydroxypyrene), monocarboxyisononyl phthalate, mono-3-carboxypropyl phthalate, and bisphenol A were associated with altered methylation in placenta (maternal or fetal side). Among exposure biomarkers associated with epigenetic changes, 1-hydroxynaphthalene, and mono-3-carboxypropyl phthalate were consistently associated with differential CpG methylation in the placenta. Gene enrichment analysis indicated that maternal 1-hydroxynaphthalene was associated with lipid metabolism and cellular processes of the placenta. Additionally, mono-3-carboxypropyl phthalate was associated with organismal systems and genetic information processing of the placenta.

Conclusion

Among the 29 chemical biomarkers assessed during delivery, 1-hydroxynaphthalene and mono-3-carboxypropyl phthalate were associated with DNA methylation in the placenta.

Supplementary Information

The online version contains supplementary material available at 10.1186/s43682-024-00027-7.

Imbalance of the von Willebrand Factor - ADAMTS-13 axis in patients with retinal vasculopathy with cerebral leukoencephalopathy and systemic manifestations (RVCL-S)

BACKGROUND

Retinal vasculopathy with cerebral leukoencephalopathy and systemic manifestations (RVCL-S) is an ultra-rare, autosomal-dominant small vessel disease caused by loss-of-function variants in the gene TREX1. Recently, elevated serum levels of von Willebrand Factor Antigen (vWF-Ag) pointed to an underlying endotheliopathy, and microvascular ischemia was suggested to contribute to the neurodegeneration in RVCL-S. Aim of this study was to further elucidate the endotheliopathy in RVCL-S.

METHODS

vWF-Ag and ADAMTS-13 activity were repeatedly measured in two patients with genetically confirmed RVCL-S. Renal biopsy of both RVCL-S patients and autoptic brain, renal, hepatic, and pulmonary specimen of one patient with RVCL-S were examined immunohistochemically in comparison to matched controls. In addition, cerebral methylome analysis was performed in the autoptic brain specimen calculating differentially methylated positions compared to controls.

RESULTS

While vWF-Ag and activity was strongly elevated, ADAMTS-13 activity was low in RVCL-S and further decreased over the course of the disease. Autoptic brain specimen showed signs of thromboinflammation in cerebral small vessels, and vWF-Ag staining was strongly positive in cerebral and renal small vessels in RVCL-S, while only a light to moderate vWF-Ag staining was found in controls. Cerebral methylome analysis yielded 115 differentially methylated CpGs (p < 0.05) in the deceased RVCL-S patient compared to the eight controls without brain pathology. One of the hypomethylated genes coded for ADAMTS-13 (p = 0.00056).

CONCLUSIONS

These findings point to an imbalance of the vWF - ADAMTS-13 axis in patients with RVCL-S, that may finally lead to an accumulation of vWF-Ag in renal and cerebral small vessels. Elevated vWF-Ag levels may serve as an early serum marker reflecting disease activity. If confirmed, therapeutic approaches might aim at an inhibition of vWF-Ag or increase of ADAMTS-13 activity in the future.

Genomic characterization of cervical lymph node metastases in papillary thyroid carcinoma following the Chornobyl accident

Childhood radioactive iodine exposure from the Chornobyl accident increased papillary thyroid carcinoma (PTC) risk. While cervical lymph node metastases (cLNM) are well-recognized in pediatric PTC, the PTC metastatic process and potential radiation association are poorly understood. Here, we analyze cLNM occurrence among 428 PTC with genomic landscape analyses and known drivers (131I-exposed = 349, unexposed = 79; mean age = 27.9 years). We show that cLNM are more frequent in PTC with fusion (55%) versus mutation (30%) drivers, although the proportion varies by specific driver gene (RET-fusion = 71%, BRAF-mutation = 38%, RAS-mutation = 5%). cLNM frequency is not associated with other characteristics, including radiation dose. cLNM molecular profiling (N = 47) demonstrates 100% driver concordance with matched primary PTCs and highly concordant mutational spectra. Transcriptome analysis reveals 17 differentially expressed genes, particularly in the HOXC cluster and BRINP3; the strongest differentially expressed microRNA also is near HOXC10. Our findings underscore the critical role of driver alterations and provide promising candidates for elucidating the biological underpinnings of PTC cLNM.

Development and Validation of a Novel Placental DNA Methylation Biomarker of Maternal Smoking during Pregnancy in the ECHO Program

BACKGROUND

Maternal cigarette smoking during pregnancy (MSDP) is associated with numerous adverse health outcomes in infants and children with potential lifelong consequences. Negative effects of MSDP on placental DNA methylation (DNAm), placental structure, and function are well established.

OBJECTIVE

Our aim was to develop biomarkers of MSDP using DNAm measured in placentas (N = 96 ), collected as part of the Vitamin C to Decrease the Effects of Smoking in Pregnancy on Infant Lung Function double-blind, placebo-controlled randomized clinical trial conducted between 2012 and 2016. We also aimed to develop a digital polymerase chain reaction (PCR) assay for the top ranking cytosine-guanine dinucleotide (CpG) so that large numbers of samples can be screened for exposure at low cost.

METHODS

We compared the ability of four machine learning methods [logistic least absolute shrinkage and selection operator (LASSO) regression, logistic elastic net regression, random forest, and gradient boosting machine] to classify MSDP based on placental DNAm signatures. We developed separate models using the complete EPIC array dataset and on the subset of probes also found on the 450K array so that models exist for both platforms. For comparison, we developed a model using CpGs previously associated with MSDP in placenta. For each final model, we used model coefficients and normalized beta values to calculate placental smoking index (PSI) scores for each sample. Final models were validated in two external datasets: the Extremely Low Gestational Age Newborn observational study, N = 426 ; and the Rhode Island Children's Health Study, N = 237 .

RESULTS

Logistic LASSO regression demonstrated the highest performance in cross-validation testing with the lowest number of input CpGs. Accuracy was greatest in external datasets when using models developed for the same platform. PSI scores in smokers only (n = 72 ) were moderately correlated with maternal plasma cotinine levels. One CpG (cg27402634), with the largest coefficient in two models, was measured accurately by digital PCR compared with measurement by EPIC array (R 2 = 0.98 ).

DISCUSSION

To our knowledge, we have developed the first placental DNAm-based biomarkers of MSDP with broad utility to studies of prenatal disease origins. https://doi.org/10.1289/EHP13838.

Longitudinal analysis of epigenome-wide DNA methylation reveals novel loci associated with BMI change in East Asians

BACKGROUND

Obesity is a global public health concern linked to chronic diseases such as cardiovascular disease and type 2 diabetes (T2D). Emerging evidence suggests that epigenetic modifications, particularly DNA methylation, may contribute to obesity. However, the molecular mechanism underlying the longitudinal change of BMI has not been well-explored, especially in East Asian populations.

METHODS

This study performed a longitudinal epigenome-wide association analysis of DNA methylation to uncover novel loci associated with BMI change in 533 individuals across two Chinese cohorts with repeated DNA methylation and BMI measurements over four years.

RESULTS

We identified three novel CpG sites (cg14671384, cg25540824, and cg10848724) significantly associated with BMI change. Two of the identified CpG sites were located in regions previously associated with body shape and basal metabolic rate. Annotation of the top 20 BMI change-associated CpGs revealed strong connections to obesity and T2D. Notably, these CpGs exhibited active regulatory roles and located in genes with high expression in the liver and digestive tract, suggesting a potential regulatory pathway from genome to phenotypes of energy metabolism and absorption via DNA methylation. Cross-sectional and longitudinal EWAS comparisons indicated different mechanisms between CpGs related to BMI and BMI change.

CONCLUSION

This study enhances our understanding of the epigenetic dynamics underlying BMI change and emphasizes the value of longitudinal analyses in deciphering the complex interplay between epigenetics and obesity.

Improve-RRBS: a novel tool to correct the 3' trimming of reduced representation sequencing reads

Motivation

Reduced Representation Bisulfite Sequencing (RRBS) is a popular approach to determine DNA methylation of the CpG-rich regions of the genome. However, we observed that false positive differentially methylated sites (DMS) are also identified using the standard computational analysis.

Results

During RRBS library preparation the MspI digested DNA undergo end-repair by a cytosine at the 3' end of the fragments. After sequencing, Trim Galore cuts these end-repaired nucleotides. However, Trim Galore fails to detect end-repair when it overlaps with the 3' end of the sequencing reads. We found that these non-trimmed cytosines bias methylation calling, thus, can identify DMS erroneously. To circumvent this problem, we developed improve-RRBS, which efficiently identifies and hides these cytosines from methylation calling with a false positive rate of maximum 0.5%. To test improve-RRBS, we investigated four datasets from four laboratories and two different species. We found non-trimmed 3' cytosines in all datasets analyzed and as much as >50% of false positive DMS under certain conditions. By applying improve-RRBS, these DMS completely disappeared from all comparisons.

Availability and implementation

Improve-RRBS is a freely available python package https://pypi.org/project/iRRBS/ or https://github.com/fothia/improve-RRBS to be implemented in RRBS pipelines.

Semimethylation is a feature of diffuse large B-cell lymphoma, and subgroups with poor prognosis are characterized by global hypomethylation and short telomere length

BACKGROUND

Large B-cell lymphoma (LBCL) is the most common lymphoma and is known to be a biologically heterogeneous disease regarding genetic, phenotypic, and clinical features. Although the prognosis is good, one-third has a primary refractory or relapsing disease which underscores the importance of developing predictive biological markers capable of identifying high- and low-risk patients. DNA methylation (DNAm) and telomere maintenance alterations are hallmarks of cancer and aging. Both these alterations may contribute to the heterogeneity of the disease, and potentially influence the prognosis of LBCL.

RESULTS

We studied the DNAm profiles (Infinium MethylationEPIC BeadChip) and relative telomere lengths (RTL) with qPCR of 93 LBCL cases: Diffuse large B-cell lymphoma not otherwise specified (DLBCL, n = 66), High-grade B-cell lymphoma (n = 7), Primary CNS lymphoma (n = 8), and transformation of indolent B-cell lymphoma (n = 12). There was a substantial methylation heterogeneity in DLBCL and other LBCL entities compared to normal cells and other B-cell neoplasms. LBCL cases had a particularly aberrant semimethylated pattern (0.15 ≤ β ≤ 0.8) with large intertumor variation and overall low hypermethylation (β > 0.8). DNAm patterns could not be used to distinguish between germinal center B-cell-like (GC) and non-GC DLBCL cases. In cases treated with R-CHOP-like regimens, a high percentage of global hypomethylation (β < 0.15) was in multivariable analysis associated with worse disease-specific survival (DSS) (HR 6.920, 95% CI 1.499-31.943) and progression-free survival (PFS) (HR 4.923, 95% CI 1.286-18.849) in DLBCL and with worse DSS (HR 5.147, 95% CI 1.239-21.388) in LBCL. These cases with a high percentage of global hypomethylation also had a higher degree of CpG island methylation, including islands in promoter-associated regions, than the cases with less hypomethylation. Additionally, telomere length was heterogenous in LBCL, with a subset of the DLBCL-GC cases accounting for the longest RTL. Short RTL was independently associated with worse DSS (HR 6.011, 95% CI 1.319-27.397) and PFS (HR 4.689, 95% CI 1.102-19.963) in LBCL treated with R-CHOP-like regimens.

CONCLUSION

We hypothesize that subclones with high global hypomethylation and hypermethylated CpG islands could have advantages in tumor progression, e.g. by inactivating tumor suppressor genes or promoting treatment resistance. Our findings suggest that cases with high global hypomethylation and thus poor prognosis could be candidates for alternative treatment regimens including hypomethylating drugs.

MSA: scalable DNA methylation screening BeadChip for high-throughput trait association studies

The Infinium DNA Methylation BeadChips have significantly contributed to population-scale epigenetics research by enabling epigenome-wide trait association discoveries. Here, we design, describe, and experimentally verify a new iteration of this technology, the Methylation Screening Array (MSA), to focus on human trait screening and discovery. This array utilizes extensive data from previous Infinium platform-based epigenome-wide association studies (EWAS). It incorporates knowledge from the latest single-cell and cell type-resolution whole genome methylome profiles. The MSA is engineered to achieve scalable screening of epigenetics-trait association in an ultra-high sample throughput. Our design encompassed diverse human trait associations, including those with genetic, cellular, environmental, and demographical variables and human diseases such as genetic, neurodegenerative, cardiovascular, infectious, and immune diseases. We comprehensively evaluated this array's reproducibility, accuracy, and capacity for cell-type deconvolution and supporting 5-hydroxymethylation profiling in diverse human tissues. Our first atlas data using this platform uncovered the complex chromatin and tissue contexts of DNA modification variations and genetic variants linked to human phenotypes.

Novel genome-wide DNA methylation profiling reveals distinct epigenetic landscape, prognostic model and cellular composition of early-stage lung adenocarcinoma

BACKGROUND

Lung adenocarcinoma (LUAD) has been a leading cause of cancer-related mortality worldwide. Early intervention can significantly improve prognosis. DNA methylation could occur in the early stage of tumor. Comprehensive understanding the epigenetic landscape of early-stage LUAD is crucial in understanding tumorigenesis.

METHODS

Enzymatic methyl sequencing (EM-seq) was performed on 23 tumors and paired normal tissue to reveal distinct epigenetic landscape, for compared with The Cancer Genome Atlas (TCGA) 450K methylation microarray data. Then, an integrative analysis was performed combined with TCGA LUAD RNA-seq data to identify significant differential methylated and expressed genes. Subsequently, the prognostic risk model was constructed and cellular composition was analyzed.

RESULTS

Methylome analysis of EM-seq comparing tumor and normal tissues identified 25 million cytosine-phosphate-guanine (CpG) sites and 30,187 differentially methylated regions (DMR) with a greater number of untraditional types. EM-seq identified a significantly higher number of CpG sites and DMRs compared to the 450K microarray. By integrating the differentially methylated genes (DMGs) with LUAD-related differentially expressed genes (DEGs) from the TCGA database, we constructed prognostic model based on six differentially methylated-expressed genes (MEGs) and verified our prognostic model in GSE13213 and GSE42127 dataset. Finally, cell deconvolution based on the in-house EM-seq methylation profile was used to estimate cellular composition of early-stage LUAD.

CONCLUSIONS

This study firstly delves into novel pattern of epigenomic DNA methylation and provides a multidimensional analysis of the role of DNA methylation revealed by EM-seq in early-stage LUAD, providing distinctive insights into its potential epigenetic mechanisms.

Associations in cell type-specific hydroxymethylation and transcriptional alterations of pediatric central nervous system tumors

Although intratumoral heterogeneity has been established in pediatric central nervous system tumors, epigenomic alterations at the cell type level have largely remained unresolved. To identify cell type-specific alterations to cytosine modifications in pediatric central nervous system tumors, we utilize a multi-omic approach that integrated bulk DNA cytosine modification data (methylation and hydroxymethylation) with both bulk and single-cell RNA-sequencing data. We demonstrate a large reduction in the scope of significantly differentially modified cytosines in tumors when accounting for tumor cell type composition. In the progenitor-like cell types of tumors, we identify a preponderance differential Cytosine-phosphate-Guanine site hydroxymethylation rather than methylation. Genes with differential hydroxymethylation, like histone deacetylase 4 and insulin-like growth factor 1 receptor, are associated with cell type-specific changes in gene expression in tumors. Our results highlight the importance of epigenomic alterations in the progenitor-like cell types and its role in cell type-specific transcriptional regulation in pediatric central nervous system tumors.

Blood DNA Methylation Analysis Reveals a Distinctive Epigenetic Signature of Vasospasm in Aneurysmal Subarachnoid Hemorrhage

Vasospasm is a potentially preventable cause of poor prognosis in patients with aneurysmal subarachnoid hemorrhage (aSAH). Epigenetics might provide insight on its molecular mechanisms. We aimed to analyze the association between differential DNA methylation (DNAm) and development of vasospasm. We conducted an epigenome-wide association study in 282 patients with aSAH admitted to our hospital. DNAm was assessed with the EPIC Illumina chip (> 850 K CpG sites) in whole-blood samples collected at hospital admission. We identified differentially methylated positions (DMPs) at the CpG level using Cox regression models adjusted for potential confounders, and then we used the DMP results to find differentially methylated regions (DMRs) and enriched biological pathways. A total of 145 patients (51%) experienced vasospasm. In the DMP analysis, we identified 31 CpGs associated with vasospasm at p-value < 10-5. One of them (cg26189827) was significant at the genome-wide level (p-value < 10-8), being hypermethylated in patients with vasospasm and annotated to SUGCT gene, mainly expressed in arteries. Region analysis revealed 13 DMRs, some of them annotated to interesting genes such as POU5F1, HLA-DPA1, RUFY1, and CYP1A1. Functional enrichment analysis showed the involvement of biological processes related to immunity, inflammatory response, oxidative stress, endothelial nitric oxide, and apoptosis. Our findings show, for the first time, a distinctive epigenetic signature of vasospasm in aSAH, establishing novel links with essential biological pathways, including inflammation, immune responses, and oxidative stress. Although further validation is required, our results provide a foundation for future research into the complex pathophysiology of vasospasm.

Donor whole blood DNA methylation is not a strong predictor of acute graft versus host disease in unrelated donor allogeneic haematopoietic cell transplantation

Allogeneic hematopoietic cell transplantation (HCT) is used to treat many blood-based disorders and malignancies, however it can also result in serious adverse events, such as the development of acute graft-versus-host disease (aGVHD). This study aimed to develop a donor-specific epigenetic classifier to reduce incidence of aGVHD by improving donor selection. Genome-wide DNA methylation was assessed in a discovery cohort of 288 HCT donors selected based on recipient aGVHD outcome; this cohort consisted of 144 cases with aGVHD grades III-IV and 144 controls with no aGVHD. We applied a machine learning algorithm to identify CpG sites predictive of aGVHD. Receiver operating characteristic (ROC) curve analysis of these sites resulted in a classifier with an encouraging area under the ROC curve (AUC) of 0.91. To test this classifier, we used an independent validation cohort (n = 288) selected using the same criteria as the discovery cohort. Attempts to validate the classifier failed with the AUC falling to 0.51. These results indicate that donor DNA methylation may not be a suitable predictor of aGVHD in an HCT setting involving unrelated donors, despite the initial promising results in the discovery cohort. Our work highlights the importance of independent validation of machine learning classifiers, particularly when developing classifiers intended for clinical use.

DNA hypomethylation patterns and their impact on the tumor microenvironment in colorectal cancer

BACKGROUND

Recent research underscores the pivotal role of immune checkpoints as biomarkers in colorectal cancer (CRC) therapy, highlighting the dynamics of resistance and response to immune checkpoint inhibitors. The impact of epigenetic alterations in CRC, particularly in relation to immune therapy resistance, is not fully understood.

METHODS

We integrated a comprehensive dataset encompassing TCGA-COAD, TCGA-READ, and multiple GEO series (GSE14333, GSE37892, GSE41258), along with key epigenetic datasets (TCGA-COAD, TCGA-READ, GSE77718). Hierarchical clustering, based on Euclidean distance and Ward's method, was applied to 330 primary tumor samples to identify distinct clusters. The immune microenvironment was assessed using MCPcounter. Machine learning algorithms were employed to predict DNA methylation patterns and their functional enrichment, in addition to transcriptome expression analysis. Genomic mutation profiles and treatment response assessments were also conducted.

RESULTS

Our analysis delineated a specific tumor cluster with CpG Island (CGI) methylation, termed the Demethylated Phenotype (DMP). DMP was associated with metabolic pathways such as oxidative phosphorylation, implicating increased ATP production efficiency in mitochondria, which contributes to tumor aggressiveness. Furthermore, DMP showed activation of the Myc target pathway, known for tumor immune suppression, and exhibited downregulation in key immune-related pathways, suggesting a tumor microenvironment characterized by diminished immunity and increased fibroblast infiltration. Six potential therapeutic agents-lapatinib, RDEA119, WH.4.023, MG.132, PD.0325901, and AZ628-were identified as effective for the DMP subtype.

CONCLUSION

This study unveils a novel epigenetic phenotype in CRC linked to resistance against immune checkpoint inhibitors, presenting a significant step toward personalized medicine by suggesting epigenetic classifications as a means to identify ideal candidates for immunotherapy in CRC. Our findings also highlight potential therapeutic agents for the DMP subtype, offering new avenues for tailored CRC treatment strategies.

Deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial sections

Tumors may contain billions of cells including distinct malignant clones and nonmalignant cell types. Clarifying the evolutionary histories, prevalence, and defining molecular features of these cells is essential for improving clinical outcomes, since intratumoral heterogeneity provides fuel for acquired resistance to targeted therapies. Here we present a statistically motivated strategy for deconstructing intratumoral heterogeneity through multiomic and multiscale analysis of serial tumor sections (MOMA). By combining deep sampling of IDH-mutant astrocytomas with integrative analysis of single-nucleotide variants, copy-number variants, and gene expression, we reconstruct and validate the phylogenies, spatial distributions, and transcriptional profiles of distinct malignant clones. By genotyping nuclei analyzed by single-nucleus RNA-seq for truncal mutations, we further show that commonly used algorithms for identifying cancer cells from single-cell transcriptomes may be inaccurate. We also demonstrate that correlating gene expression with tumor purity in bulk samples can reveal optimal markers of malignant cells and use this approach to identify a core set of genes that is consistently expressed by astrocytoma truncal clones, including AKR1C3, whose expression is associated with poor outcomes in several types of cancer. In summary, MOMA provides a robust and flexible strategy for precisely deconstructing intratumoral heterogeneity and clarifying the core molecular properties of distinct cellular populations in solid tumors.

Characterisation and reproducibility of the HumanMethylationEPIC v2.0 BeadChip for DNA methylation profiling

BACKGROUND

The Illumina family of Infinium Methylation BeadChip microarrays has been widely used over the last 15 years for genome-wide DNA methylation profiling, including large-scale and population-based studies, due to their ease of use and cost effectiveness. Succeeding the popular HumanMethylationEPIC BeadChip (EPICv1), the recently released Infinium MethylationEPIC v2.0 BeadChip (EPICv2) claims to extend genomic coverage to more than 935,000 CpG sites. Here, we comprehensively characterise the reproducibility, reliability and annotation of the EPICv2 array, based on bioinformatic analysis of both manifest data and new EPICv2 data from diverse biological samples.

RESULTS

We find a high degree of reproducibility with EPICv1, evidenced by comparable sensitivity and precision from empirical cross-platform comparison incorporating whole genome bisulphite sequencing (WGBS), and high correlation between technical sample replicates, including between samples with DNA input levels below the manufacturer's recommendation. We provide a full assessment of probe content, evaluating genomic distribution and changes from previous array versions. We characterise EPICv2's new feature of replicated probes and provide recommendations as to the superior probes. In silico analysis of probe sequences demonstrates that probe cross-hybridisation remains a significant problem in EPICv2. By mapping the off-target sites at single nucleotide resolution and comparing with WGBS we show empirical evidence for preferential off-target binding.

CONCLUSIONS

Overall, we find EPICv2 a worthy successor to the previous Infinium methylation microarrays, however some technical issues remain. To support optimal EPICv2 data analysis we provide an expanded version of the EPICv2 manifest to aid researchers in understanding probe design, data processing, choosing appropriate probes for analysis and for integration with methylation datasets from previous versions of the Infinium Methylation BeadChip.