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PubMed2026

eQTM (expression quantitative trait methylation) Atlas: a comprehensive resource of over 11 million DNA methylation-gene expression associations through across 11 tissues and 4 diseases.

MOTIVATION: Epigenome-wide association studies (EWAS) have identified numerous DNA methylation (DNAm) CpG sites associated with complex traits and diseases, but interpretation of those CpG sites remains challenging because in EWAS, CpGs are mostly linked to nearby genes based only on genomic proximity. Expression quantitative trait methylation (eQTM) analyses connect DNAm CpGs with statistically associated gene expression levels. However, a comprehensive, searchable resource integrating eQTMs across diverse tissues and disease contexts has been lacking. RESULTS: We developed the eQTM Atlas, a web-based resource that manually curates more than 11 million DNAm-gene expression associations from eight cohorts, covering 11 tissue types, four broad disease contexts, 173,886 unique CpG probes and 20,231 unique genes. The Atlas supports gene- or CpG- searches by tissue or disease type and finding associated CpG or genes, visualization of cis- and trans-eQTMs through genome browser, heatmap interfaces across various tissues, and cohort-level data downloads. By integrating eQTM results with EWAS resources, the eQTM Atlas enables users to connect disease- or trait-associated CpGs to statistically associated genes rather than relying solely on proximity-based gene annotation, supporting functional interpretation of EWAS findings and generation of disease-specific regulatory hypotheses. AVAILABILITY AND IMPLEMENTATION: The eQTM Atlas is freely available at https://shiny.crc.pitt.edu/eqtm_browser/. The web interface is implemented in R Shiny and hosted through the University of Pittsburgh Center for Research Computing (CRC). Source code is available at https://github.com/ads303/eQTM-Atlas.

DNA methylation↗

PubMed2026

DNA hypomethylation of the OLFM1 gene in patients with depression.

OBJECTIVE: Depression is a heterogeneous psychiatric disorder and a growing public health concern, characterized by its high prevalence, recurrence rate, and association with suicide. There is evidence suggesting that both genetic susceptibility and environmental factors can regulate gene expression through DNA methylation, thereby influencing the occurrence and development of depression. The olfactory sensory neuropeptide 1 (OLFM1) protein is a risk factor for mental disorders. However, there are no reports yet regarding the correlation between the OLFM1 gene and depression, nor have there been any studies on the association between OLFM1 gene DNA methylation and depression. METHODS: Genomic DNA was extracted from peripheral blood samples of patients with depression (n = 100) and healthy controls (n = 100) using the QIAamp DNA Blood Mini Kit. Subsequently, the extracted genomic DNA was subjected to bisulfite treatment using the EZ DNA Methylation-Gold™ kit. DNA methylation levels of 107 CpG sites in six fragments of OLFM1 exon 1 and its downstream were detected by the Illumina HiSeq platform using MethylTarget™ technology. RESULTS: Methylation levels across the overall OLFM1 CpG island and its six fragments (OLFM1-1 to OLFM1-6) were significantly reduced in the depression group relative to controls. Analysis of the OLFM1 gene fragments revealed that 84 of 107 CpG sites were significantly hypomethylated in depressed individuals. When patients were divided by sex, male patients displayed hypomethylation at 65 CpG sites, substantially more than the 37 sites found in females. CONCLUSION: OLFM1 hypomethylation is associated with depression and may serve as a potential epigenetic biomarker.

Humans↗

PubMed2025

Development and validation of a machine learning prognostic model based on an epigenomic signature in patients with pancreatic ductal adenocarcinoma.

BACKGROUND: In Pancreatic Ductal Adenocarcinoma (PDAC), current prognostic scores are unable to fully capture the biological heterogeneity of the disease. While some approaches investigating the role of multi-omics in PDAC are emerging, the analysis of methylation data is under exploited. MATERIALS AND METHODS: We analyzed CpG sites from two publicly available datasets, the TCGA-PAAD used as discovery set and the CPTAC-PDA as external test set. Single mutations and co-mutation of KRAS and TP53 genes were identified as targets, and differentially methylated CpG sites (DMC) were detected accordingly. We trained and validated Random Forest (RF) models to predict each target. Area Under the Receiver Operating Characteristic curve (AUROC) and Area Under the Precision-Recall curve (AUPRC) were used as performance metrics. Then, we performed consensus clustering from the DMCs to identify novel patients' profiles. Finally, we trained and validated a combination of eXtreme Gradient Boosting (XGB) and tree models to select an epigenomic prognostic determinant. RESULTS: From 598 DMCs extracted, an RF model predicted KRAS and TP53 co-mutation on the external test set with AUROC of 0.77 and AUPRC of 0.87. The consensus clustering allowed us to identify 4 clusters (C1, C2, C3, and C4) of patients. The C4 cluster captured a subgroup of patients with favorable Overall Survival (OS) with respect to others. The XGB model perfectly predicted C4 vs other clusters on the discovery set. In both cohorts, patients were stratified into two risk groups according to methylation levels of cg16854533, individuated as the most important CpG site. CONCLUSION: We analyzed methylation data to develop a classifier for the TP53 and KRAS mutational status. Four prognostic clusters were pointed out and a prognostic model using a CpG site was validated in an independent cohort. Our results evidence that the proposed use of methylation data facilitates risk stratification for PDAC.

Humans↗

PubMed2026

Plasma cfDNA hypermethylation at SNCA intron 1 as a potential blood-based epigenetic signal in Parkinson's disease and multiple system atrophy.

BACKGROUND: The accumulation of α-synuclein (SNCA) in the central nervous system is a hallmark of Parkinson's disease (PD) and multiple system atrophy (MSA). SNCA intron 1 methylation is implicated in SNCA transcriptional regulation and may serve as a peripheral epigenetic signal in synucleinopathies. However, studies of SNCA methylation in leukocyte-derived DNA have yielded inconsistent results. We aimed to evaluate whether cell-free DNA (cfDNA)-based SNCA intron 1 methylation differs in PD or MSA compared with normal controls (NC). METHODS: Plasma cfDNA was collected from 105 patients with PD, 50 with MSA, and 114 NC. DNA methylation at CpG sites 10-17 was quantified by bisulfite pyrosequencing. Multivariable linear and logistic regression models, adjusted for age, sex, and education, were used to compare methylation levels and estimate odds ratios (ORs). RESULTS: Patients with PD exhibited hypermethylation at CpG site 14 and higher mean methylation across CpG sites 10-17 compared with NC. Patients with MSA showed hypermethylation at CpG sites 10, 12, 13, and 17 and elevated mean methylation. Elevated mean methylation was also observed in drug-naïve de novo PD and early-stage PD patients. Compared with the lowest tertile, the highest mean methylation tertile was associated with increased odds of PD (OR, 2.49; 95% CI, 1.08-5.92) and MSA (OR, 5.02; 95% CI, 1.58-18.00). CONCLUSION: Plasma cfDNA SNCA intron 1 hypermethylation is associated with PD and MSA and detectable in drug-naïve and early-stage PD. It may represent a peripheral epigenetic alteration and warrants evaluation as an adjunctive signal for early screening.

Humans↗

PubMed2024

Epigenetic signature of very low birth weight in young adult life.

BACKGROUND: Globally, one in ten babies is born preterm (<37 weeks), and 1-2% preterm at very low birth weight (VLBW, <1500 g). As adults, they are at increased risk for a plethora of health conditions, e.g., cardiometabolic disease, which may partly be mediated by epigenetic regulation. We compared blood DNA methylation between young adults born at VLBW and controls. METHODS: 157 subjects born at VLBW and 161 controls born at term, from the Helsinki Study of Very Low Birth Weight Adults, were assessed for peripheral venous blood DNA methylation levels at mean age of 22 years. Significant CpG-sites (5'-C-phosphate-G-3') were meta-analyzed against continuous birth weight in four independent cohorts (pooled n = 2235) with cohort mean ages varying from 0 to 31 years. RESULTS: In the discovery cohort, 66 CpG-sites were differentially methylated between VLBW adults and controls. Top hits were located in HIF3A, EBF4, and an intergenic region nearest to GLI2 (distance 57,533 bp). Five CpG-sites, all in proximity to GLI2, were hypermethylated in VLBW and associated with lower birth weight in the meta-analysis. CONCLUSION: We identified differentially methylated CpG-sites suggesting an epigenetic signature of preterm birth at VLBW present in adult life. IMPACT: Being born preterm at very low birth weight has major implications for later health and chronic disease risk factors. The mechanism linking preterm birth to later outcomes remains unknown. Our cohort study of 157 very low birth weight adults and 161 controls found 66 differentially methylated sites at mean age of 22 years. Our findings suggest an epigenetic mark of preterm birth present in adulthood, which opens up opportunities for mechanistic studies.

Humans↗

PubMed2024

A methylation risk score for chronic kidney disease: a HyperGEN study.

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

Humans↗

PubMed2022

Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study.

BACKGROUND: The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking. RESULTS: We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%. CONCLUSIONS: Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.

Humans↗

PubMed2025

Estimating population structure using epigenome-wide methylation data.

INTRODUCTION: In epigenome-wide association analysis (EWAS), unaddressed population stratification often leads to inflation. We aimed to compute methylation population scores (MPSs) that predict genetic principal components (GPCs) using a feature selection and regression approach. METHODS: We used multi-ethnic methylation data (Illumina 450K/EPIC array) from unrelated MESA (n=929), CARDIA (n=1123), JHS (n=1365), ARIC (n=2338), and HCHS/SOL (n=1475) individuals, randomly assigning 85% of participants from each cohort to a training dataset and the remaining 15% to a test dataset. First, we estimated the associations of GPCs with each available CpG methylation site using linear regression within each cohort, adjusting for age, sex, smoking status, race/ethnic background (as a proxy for background information associated with lifestyle and other environmental exposures that may impact methylation), alcohol use status, body mass index, and cell type proportions. We meta-analyzed the associations across cohorts and selected CpG sites with association FDR-adjusted q-value <0.05. We next aggregated individuallevel data across the cohort-specific training datasets, and applied two-stage weighted least squares Lasso regression, with the GPCs as the outcomes and the selected CpG sites as penalized predictors, adjusting for the aforementioned covariates. The developed MPSs are the weighted sum of selected CpG sites from the Lasso. To evaluate the developed MPSs, we constructed them in the test dataset, and compared them with GPCs, and with MPSs constructed based on a previously-published paper. Comparison was based on correlation analysis and data visualization. We demonstrate the use of the MPSs in EWAS. RESULTS: In the test dataset, the MPSs were highly correlated with GPCs, with correlation decreasing, though not monotonically, for later components. Specifically, MPS1 and GPC1 had R2= 0.99, while MPS7 and GPC7 had R2=0.27 (the lowest observed correlation). In data visualization, MPSs had similar patterns as GPCs in differentiating self-reported White, Black, and Hispanic/Latino groups, while outperforming MPC constructed using alternative published methods. MPSs showed comparable performance to GPCs in reducing some of the inflation in EWAS. CONCLUSIONS: Methylation-based population scores provide a reliable estimate of population structure in the data and can complement GPCs when genetic data are absent. Unlike previous methods based on unsupervised methylation PCA, MPSs uses supervised learning with covariate adjustment to capture genetic structure across diverse populations. The weights for each GPCs derived in our study can be applied to generate MPSs in other studies.

Journal Article↗

PubMed2026

Genetic-epigenetic interactions (meQTLs) in orofacial clefts etiology.

Understanding how genetic variants influence disease risk through molecular mechanisms remains a central challenge in complex disease genetics. Nonsyndromic orofacial clefts (OFCs) exemplify this challenge, with most risk loci residing in non-coding regions. We hypothesized that common genetic variants influence OFC risk by modulating DNA methylation at regulatory elements through methylation quantitative trait loci (meQTLs). We analyzed 10 OFC-associated SNPs against genome-wide DNA methylation profiles in 409 cases and 456 controls, identifying 23 potential meQTLs. Findings were validated using 358 cleft-discordant sibling pairs with MethyLight assays. We performed formal mediation analysis, genotype-tissue interaction and cross-referenced with the mQTL Database to assess developmental timing. Nine meQTLs were validated, including rs987525 (8q24)-cg16561172 (MYC) (P = 9.6 × 10⁻⁶), which mapped to a mesendoderm-active enhancer upstream of MYC. Genotype × tissue interaction confirmed tissue-specificity (P = 1.00 × 10- 3), with stronger effects in oral-derived tissue (saliva). Additional validated SNP-CpG associations involved MAFB-PLCG1, NOG-PPM1E, FOXE1-FRZB, and SPRY2-LGR4. While effect sizes correlated between tissues (r = 0.81), formal mediation analysis indicated individual CpG sites do not fully mediate SNP-phenotype relationships, suggesting coordinated epigenetic mechanisms. Most associations showed peak effects during childhood, while 8q24 showed unique adult-specific patterns. We identified genetic variants influencing methylation at craniofacial regulatory elements, and provided a mechanistic link for a major risk locus, 8q24, with tissue-specific effects in saliva. While individual CpG sites did not fully mediate the genetic risk, our findings identified specific regulatory regions where coordinated epigenetic changes may contribute to OFC susceptibility.

Humans↗

PubMed2026

Non-parametric differential methylation analysis characterizes histotype-specific promoter regions in epithelial ovarian cancer.

Epithelial ovarian cancer (EOC) is a heterogenous disease with frequent late-stage diagnosis and high mortality rates, for which no reliable screening tests exist. In recent years, epigenetic biomarkers in the form of DNA methylation in CpG-rich regions have gained increased attention in the scientific community due to their robust nature and accessibility, allowing for diagnosis without the need for invasive surgery. In this study, we investigated the aberrant methylation of promoter regions in early stage EOC through non-parametric methods, with the purpose of characterizing candidate epigenetic biomarkers. The approach was used on a cohort of early stage EOC samples, and results were compared to existing programs for differential methylation. Significant regions were then used to construct a CpG panel for stratifying EOC histotypes through predictive classification in external data. Identified promoter regions were highly reproducible across cohorts, and the constructed CpG model stratified histotypes in external cohorts through predictive classification. Comparisons against other DMP and DMR callers showed a degree of homogeneity between results but also revealed promoter regions that were overlooked despite clear signs of aberrant methylation. Finally, EOC histotypes were found to differ in their methylation distribution types, and results indicate that methods sensitive to non-normally distributed data may be poorly suited to compare groups with different distribution types. The non-parametric approach identified aberrantly methylated promoter regions that were highly reproducible across cohorts. Results from predictive classification indicate that these regions may be useful for the purpose of EOC histotype stratification.

Humans↗

PubMed2026

Interplay between the role of DNA methylation in regulating gene expression and TE-silencing in a reptilian methylome.

DNA methylation is a major component of eukaryotic genomes with an important role in the defence against transposable elements, to transcriptionally silence their activity and prevent transposition. DNA methylation also plays a major role in the regulation of gene expression. This dual role can come into conflict, where DNA methylation in gene regulatory regions becomes perturbed due to transposable element transposition, leading to disruption of gene expression. Here, we describe how this conflict is reflected in DNA methylation patterns in the sand lizard genome where there is recent transposable element activity. Using long-read sequencing technology we show that CpG islands in gene transcriptional start sites are typically hypomethylated and associated with higher gene expression. Outside transcriptional start sites, a majority of CpG islands overlapped transposable elements and were associated with hypermethylation, consistent with a host-defence role in suppressing transposition activity. We identify 605 instances where transcriptional start sites were associated with transposable elements (4.3% of all genes). These instances were far rarer in conjunction with a CpG island, when methylation signatures would be in conflict. Transposable elements were found to be closer to and at higher density the more hypermethylated a transcriptional start site was, suggesting strong selection against selfish genetic elements transposing into hypomethylated transcriptional start sites.

CpG islands↗

PubMed2025

Sex-Chromosome-Dependent Ageing in Female Heterogametic Methylomes.

Recent research in humans and both model and non-model animals has shown that DNA methylation (DNAm), an epigenetic modification, is one of the mechanisms underlying the ageing process. DNAm-based indices predict mortality and provide valuable insights into biological ageing mechanisms. Although sex-dependent differences in lifespan are ubiquitous and sex chromosomes are thought to play an important role in sex-specific ageing, they have been largely ignored in epigenetic ageing studies. We characterised the genome-wide distribution of age-related CpG (Cytosine-phosphate-Guanine) sites from longitudinal samples in two avian species (zebra finch and jackdaw), including for the first time the avian sex chromosomes (Z and the female-specific, haploid W). In both species, we find a small fraction of the CpG sites to show age-related changes in DNAm with the majority of them being located on the haploid, female-specific W chromosome, where DNAm levels predominantly decrease with age. Age-related CpG sites were over-represented on the zebra finch but under-represented on the jackdaw Z chromosome. Our results highlight distinct age-related changes in sex chromosome DNAm compared to the rest of the genome in two avian species, suggesting this previously understudied feature of sex chromosomes may be instrumental in sex-dependent ageing. Moreover, studying the DNAm of sex chromosomes might be particularly useful in ageing research, facilitating the identification of shared (sex-dependent) age-related pathways and processes between phylogenetically diverse organisms.

Animals↗

PubMed2026

Sex-specific differences in liver DNA methylation patterns and epigenetic aging in mice.

Biological sex has been shown to influence aging outcomes, contributing to distinct trajectories in disease susceptibility and lifespan. DNA methylation patterns provide a quantitative measure of biological aging. This study investigated whether aged male and female mice display distinct liver DNA methylation patterns and differences in epigenetic aging. Liver samples were collected from 17 aged c57BL/6 mice (6 males, 11 females). Genomic DNA was extracted and bisulfite-converted before targeted enrichment of 2,045 murine age-associated CpG loci. Biological age (DNAge) was estimated using a previously developed DNA methylation-based predictor generated through elastic net regression. The difference (ΔDNAge) between DNAge and chronological age was computed. Sex-specific differences were assessed by comparing site-specific methylation ratios, ΔDNAge values, and through principal component analysis (PCA) and multiple linear regression. Twelve CpG sites across six genes (Fam84b, Zswim6, Hsf4, Mn1, Qprt, and Rapgefl1) showed significant sex-associated differences in methylation. Fam84b demonstrated the largest and most consistent sex-associated effect, with all three associated CpG sites showing higher methylation in males (regression coefficients: -0.204, -0.281, and -0.294). Zswim6 exhibited consistent lower methylation ratios in females, whereas the other genes showed higher methylation in females. There were no sex differences in biological age or ΔDNAge (P = 0.596). Although the epigenetic clock did not reveal differences between sexes in aging, aged mice did exhibit sex-specific liver methylation patterns different from those reported in younger mice, suggesting that sex-dependent epigenetic changes may emerge later in life and may reflect sexual dimorphism in liver function with age.NEW & NOTEWORTHY Males and females are known to age differently and develop certain diseases at different rates. Here, we examined the livers of aged male and female mice to see if they show different DNA methylation patterns. We found that aged male and female mice had distinct DNA methylation patterns at specific genes. Interestingly, most of these methylation differences were not present in younger mice, suggesting that sex differences in the genome may change with age.

Animals↗

PubMed2026

Epigenetic and immunological alterations in umbilical cord blood of overweight/obese women with gestational diabetes mellitus: insights into DNA methylation signatures and immune cell dysregulation.

BACKGROUND: Gestational diabetes mellitus (GDM) is a common pregnancy complication associated with adverse maternal and neonatal outcomes. Epigenetic modifications may reflect intrauterine metabolic exposure and contribute to immune and metabolic alterations. This study aimed to explore DNA methylation profiles in umbilical cord blood from overweight and obese women with and without GDM. METHODS: Umbilical cord blood samples from 30 overweight/obese pregnant women (with and without GDM) were analyzed using the Illumina 850 K methylation array to identify differentially methylated positions (DMPs) and regions (DMRs). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to assess the functional relevance of methylation changes. Immune cell composition was estimated using deconvolution analysis and further examined in an independent single-cell RNA sequencing (scRNA-seq) cohort. Lasso regression was applied to identify CpG sites associated with GDM status and construct a preliminary methylation-based classification model. RESULTS: A total of 23,331 hypermethylated and 29,501 hypomethylated DMPs were identified between women with and without GDM, with hypomethylation predominating. Enrichment analyses indicated associations with neurodevelopmental pathways, metabolic processes, immune regulation, and epigenetic modification. Immune deconvolution analysis suggested reduced proportions of CD4+ T cells (p < 0.05) and a trend toward decreased NK cells in the GDM group, alongside increased CD8+ T cells and neutrophils. Seven CpG sites were selected for model construction and demonstrated strong discriminatory performance within this cohort. CONCLUSION: This exploratory study identifies distinct cord blood DNA methylation patterns associated with GDM in overweight/obese pregnancies. The findings suggest potential links between epigenetic alterations and immune cell composition in GDM-exposed offspring. The identified CpG signature warrants further validation in larger, prospective cohorts to determine its clinical applicability.

Humans↗

PubMed2025

A SuperLearner-based pipeline for the development of DNA methylation-derived predictors of phenotypic traits.

BACKGROUND: DNA methylation (DNAm) provides a window to characterize the impacts of environmental exposures and the biological aging process. Epigenetic clocks are often trained on DNAm using penalized regression of CpG sites, but recent evidence suggests potential benefits of training epigenetic predictors on principal components. METHODOLOGY/FINDINGS: We developed a pipeline to simultaneously train three epigenetic predictors; a traditional CpG Clock, a PCA Clock, and a SuperLearner PCA Clock (SL PCA). We gathered publicly available DNAm datasets to generate i) a novel childhood epigenetic clock, ii) a reconstructed Hannum adult blood clock, and iii) as a proof of concept, a predictor of polybrominated biphenyl exposure using the three developmental methodologies. We used correlation coefficients and median absolute error to assess fit between predicted and observed measures, as well as agreement between duplicates. The SL PCA clocks improved fit with observed phenotypes relative to the PCA clocks or CpG clocks across several datasets. We found evidence for higher agreement between duplicate samples run on alternate DNAm arrays when using SL PCA clocks relative to traditional methods. Analyses examining associations between relevant exposures and epigenetic age acceleration (EAA) produced more precise effect estimates when using predictions derived from SL PCA clocks. CONCLUSIONS: We introduce a novel method for the development of DNAm-based predictors that combines the improved reliability conferred by training on principal components with advanced ensemble-based machine learning. Coupling SuperLearner with PCA in the predictor development process may be especially relevant for studies with longitudinal designs utilizing multiple array types, as well as for the development of predictors of more complex phenotypic traits.

DNA Methylation↗

PubMed2026

Multi-omics integrative analysis provides insight into potential molecular responses to sustained high water flow in common carp (Cyprinus carpio) cultured in recirculating aquaculture.

To investigate the potential molecular responses by which water flow intensity affects the growth of common carp (Cyprinus carpio) in a recirculating aquaculture system (RAS), a control group (CG, actual water velocity 0.3 cm/s) and three sustained flow treatment groups were established, including a low-flow group (LF, 1 body length per second, bl/s), a medium-flow group (MF, 2 bl/s), and a high-flow group (HF, 3 bl/s). After 12 weeks of culture in the RAS, growth performance was compared among groups under different flow intensities. The best-performing group and the control group were then selected for the determination of intestinal digestive enzyme activities, as well as transcriptomic and whole-genome bisulfite sequencing analyses of muscle tissue. The results showed that the specific growth rate and feed intake of the HF group were significantly higher than those of the other groups (P < 0.05), whereas no significant difference in feed conversion ratio was observed among groups. Compared with the CG group, lipase activity was significantly higher in the HF group (P < 0.05), while α-amylase and trypsin activities showed increasing trends without significant differences. RNA-seq identified a total of 273 differentially expressed genes, including 72 upregulated genes and 201 downregulated genes in the HF group relative to the CG group. These genes were mainly enriched in glycolysis, pyruvate metabolism, ATP metabolism, the pentose phosphate pathway, the insulin signaling pathway, the PPAR signaling pathway, and the adipocytokine signaling pathway, indicating that sustained high water flow induced a muscle transcriptional response characterized by remodeling of energy metabolism and substrate utilization. Whole-genome bisulfite sequencing analysis showed that DNA methylation in common carp muscle occurred predominantly in the CpG context. Differentially methylated regions between the HF and CG groups were mainly distributed in transcription-related regulatory regions, including promoters, CpG islands, and CpG island shores. In promoter regions, the number of hypermethylated regions in the HF group relative to the CG group was markedly higher than that of hypomethylated regions. Integrated analysis further identified two candidate genes showing both promoter differential methylation and differential expression, namely LOC109094644 and bcorl1, suggesting that adaptation to high water flow may involve IGF-related growth regulation and remodeling of upstream transcriptional programs. The qPCR results were consistent with the transcriptomic data. Taken together, within the tested range, a sustained water flow of 3 bl/s was more conducive to the growth of common carp in the RAS, which may be associated with enhanced lipid digestion and utilization, remodeling of the muscle energy metabolic network, changes in promoter methylation, and the coordinated regulation of key candidate genes. This study provides a theoretical basis for clarifying the exercise adaptation mechanism of common carp in recirculating aquaculture and for optimizing flow velocity parameters.

Animals↗

PubMed2026

Mapping Protein Occupancy on DNA with an Unnatural Cytosine Modification.

The epigenome provides a dynamic layer of gene regulatory control above the static genetic sequence. DNA base modifications are key epigenetic regulators, predominantly found within CpG contexts in mammalian genomes. Working in tandem with these DNA modifications, chromatin-associated proteins and transcription factors further control gene expression. Given the interplay of these factors, concurrent mapping of DNA base modifications with protein-DNA occupancy can greatly aid in interpreting the epigenome. Existing multimodal mapping methods include the use of DNA methyltransferases to mark accessible, protein-unbound DNA in non-CpG contexts. However, such approaches can either confound readouts with native DNA modifications or constrain users to third-generation sequencing approaches. To circumvent these limitations, we explored the possibility of introducing an unnatural DNA base modification, 5-carboxymethylcytosine, as an alternative label for protein occupancy. Here, we report our efforts to rationally engineer non-CpG-specific DNA methyltransferases to take on neomorphic DNA carboxymethyltransferase (CxMTase) activities. We find that DNA carboxymethylation of cytosines in GpC contexts shows broad compatibility with the most widely used epigenetic detection methods and can be used to reliably report on protein occupancy states. Using this approach, we reveal the single-molecule binding patterns of LexA, a master repressor in the bacterial DNA damage (SOS) response, at its self-regulated and endogenously methylated promoter. We thus show that unnatural DNA modifications can uncover novel biological insights and potentiate new approaches to multimodal epigenetic profiling.

DNA↗

PubMed2026

Multi-omics Mendelian Randomization Prioritizes Neutrophil Extracellular Trap-related Genes Associated with Atrial Fibrillation Risk.

BACKGROUND: Neutrophil extracellular traps (NETs) participate in thrombosis, inflammation, and cardiovascular remodeling, yet whether NET-related genes (NRGs) are associated with atrial fibrillation (AF) risk across multiple molecular layers remains unclear. This study used a multiomics Mendelian randomization framework to prioritize NRGs supported by methylation, expression, and protein quantitative trait loci (QTL) data. METHODS: Genome-wide significant cis instruments (P < 5 × 10-8) were obtained for 90 methylation QTLs (mQTLs), 100 expression QTLs (eQTLs), and 38 protein QTLs (pQTLs) mapped to 137 literature- curated NRG entries. Summary-data-based Mendelian randomization (SMR) coupled with the heterogeneity in dependent instruments (HEIDI) test was applied using whole-blood mQTL data (n = 1,980), eQTLGen blood eQTL data (n = 31,684), and deCODE plasma pQTL data (n = 35,559). AF outcome data were obtained from a meta-analysis including 60,620 cases and 970,216 controls of European ancestry. RESULTS: At the methylation level, 21 CpG-feature associations across 13 genes remained significant after HEIDI filtering and false discovery rate (FDR) correction. Expression-level analysis identified eight significant gene-AF associations, whereas protein-level analysis identified seven significant features representing five unique proteins. Cross-omics integration prioritized C3, MAPK3, and STAT3 as Tier 1 genes, CTSC, LPAR3, and THBD as Tier 2 genes, and fourteen additional genes as Tier 3 candidates. C3 showed risk-increasing protein-level associations together with multiple significant CpG signals, whereas MAPK3 and STAT3 showed directionally protective expression/protein or methylation/protein patterns. DISCUSSION: The cross-omics convergence on C3, MAPK3, and STAT3 is consistent with complement activation, immune-fibrotic signaling, and cytokine-regulatory pathways implicated in AF biology, but the findings should be interpreted as genetic prioritization rather than definitive intervention-ready causality. CpG-level heterogeneity at the C3 locus and the blood/plasma origin of the QTL resources further support a cautious interpretation. Modest colocalization support and the unresolved possibility of pQTL sample overlap further support this cautious, hypothesis-generating interpretation. CONCLUSION: Multi-omics SMR prioritizes C3, MAPK3, and STAT3 as the most consistently supported NET-related genes associated with AF risk. These findings provide a framework for atrialtissue replication and mechanistic validation of NET-related pathways in AF.

Atrial fibrillation↗