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Results for “DNA methylation profiling”

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PubMed2026

Genome-wide DNA methylation profiling during metabolic dysfunction-associated steatohepatitis-related hepatocarcinogenesis in patients in Japan and the United States.

This study aimed to compare ethnicity-related differences in DNA methylation profiles during metabolic dysfunction-associated steatohepatitis (MASH)-related hepatocarcinogenesis in patients from Japan and the United States (US). Genome-wide DNA methylation analysis using the Infinium assay was performed in 36, 148 and 36 samples of normal liver tissue (NLT), non-cancerous liver tissue showing MASH, and MASH-related hepatocellular carcinoma (HCC), respectively (220 samples in total), from the Japan and US cohorts. Principal component analysis revealed that MASH had a distinct DNA methylation profile differing from that of NLT, and that the MASH profiles in the two cohorts differed from each other. DNA methylation alterations of cancer-related genes in MASH were inherited by or strengthened in MASH-related HCC itself, resulting in expression alterations. DNA methylation alterations of FGFR2, FUT4, B3GNT5 and MOSC1 in the precancerous MASH stage were shared by the two cohorts, suggesting that such genes are commonly associated with MASH-related hepatocarcinogenesis. On the other hand, it was suggested that DNA methylation alterations of ZNF611 and SAMD10, and those of SHC1, are involved specifically in MASH-related hepatocarcinogenesis in the Japan and the US cohorts, respectively. These findings suggest that DNA methylation alterations, which may reflect race and lifestyle, are associated with MASH-related hepatocarcinogenesis.

Humans↗
PubMed2026

DNA Methylation Profiling of Pediatric Ectomesenchymoma Supports Embryonal Rhabdomyosarcoma-Like Epigenetic Identity.

Ectomesenchymoma is a rare, biphenotypic pediatric tumor combining rhabdomyoblastic and neuroectodermal differentiation. We characterize two novel cases through integrated genomics and the first report of genome-wide DNA methylation profiling. Both tumors harbored RAS-pathway mutations (HRAS p.Gly13Arg; NRAS p.Gln61His). Methylation analysis, including microdissected components, consistently aligned ectomesenchymoma with the embryonal rhabdomyosarcoma superfamily, revealing a shared myogenic epigenetic program despite neural differentiation. Shared copy-number profiles across distinct histological regions supported a monoclonal origin. Overall, our data support a close biological relationship between ectomesenchymoma and embryonal rhabdomyosarcoma and indicate that RAS-pathway testing and methylation profiling can significantly refine diagnostic precision.

Humans↗
PubMed2026

DNA methylation profiles of quail blood cells by whole-genome bisulfite and Oxford Nanopore sequencing.

Whole Genome Bisulfite Sequencing (WGBS) has been the gold standard DNA methylation mapping and quantification for over a decade. Oxford Nanopore Technologies (ONT) sequencing directly measures nucleotide modifications. In this study, we have compared DNA methylation levels (5-methylcytosine) at CpG sites in the quail genome using WGBS and ONT. Samples were collected to investigate transgenerational DNA methylation changes in Japanese quail following ancestral exposure to a phytoestrogen. Blood samples from 24 third-generation (G3) individuals-descendants of either treated or untreated ancestors-were sequenced after bisulfite conversion. Both methods revealed broadly consistent methylation patterns. ONT reads covered more CpG sites and detected a higher number of differentially methylated cytosines (DMCs). Principal component analyses showed that both sex and ancestral treatment groups accounted for a portion of the observed epigenetic variation, for both technologies. Strong concordance between WGBS and ONT results supports the reliability of ONT sequencing for epigenomic research, including in quails. These data pave the way for further investigation into whether genistein induces epigenetic changes for several generations.

Animals↗
PubMed2026

Epigenetic safety of in vitro maturation in PCOS: genome-wide DNA methylation profiling of cord blood from a randomized controlled trial.

BACKGROUND: In vitro maturation (IVM) provides a safer alternative to conventional in vitro fertilization (IVF) for women with polycystic ovary syndrome (PCOS) by mitigating the risk of ovarian hyperstimulation. However, concerns persist regarding whether IVM perturbs epigenetic reprogramming in the offspring. Current evidence is constrained by candidate-gene approaches or a lack of parental controls. This study aimed to evaluate the genome-wide DNA methylation safety of IVM compared with conventional IVF using a rigorous trio-based design. METHODS: This secondary epigenetic analysis was nested within a randomized controlled trial (RCT) (ClinicalTrials.gov: NCT03463772). We included 10 nuclear families (trios), comprising five IVM-conceived and five IVF-conceived singleton offspring alongside their biological parents. Both groups utilized a uniform freeze-only single-blastocyst transfer strategy to minimize hormonal confounding. Genomic DNA from umbilical cord blood (UCB) and parental peripheral blood was analyzed using reduced representation bisulfite sequencing (RRBS). Genome-wide methylation patterns and differentially methylated regions (DMRs) were subsequently compared between the groups. RESULTS: Clinical characteristics were comparable between the IVM and IVF groups. Genome-wide analyses demonstrated high concordance in UCB methylation patterns, revealing no significant differences in global CpG methylation levels or distributions across key genomic features (promoters, CpG islands, and gene bodies). Only three rare DMRs were identified in UCB (representing ~ 0.0001% of the genome), none of which mapped to imprinted or developmentally critical loci. Furthermore, methylation variability remained consistent between the groups. CONCLUSIONS: Our findings provide robust mechanistic evidence supporting the epigenetic safety of IVM. The remarkable stability of the neonatal methylome confirms that specific IVM conditions do not compromise early developmental programming, thereby endorsing IVM as a safe and viable alternative for women with PCOS. TRIAL REGISTRATION: ClinicalTrials.gov registry, NCT03463772. Registered on March 13, 2018.

Humans↗
PubMed2025

Enhancing the sensitivity of non-invasive cervical cancer detection using CpG methylation haplotype profiling.

DNA methylation is a critical epigenetic modification that regulates gene expression and plays a significant role in cancer development. This methylation signature can be detected in cancer-derived DNA from non-invasive samples, such as plasma, urine or Pap smears. However, in early-stage cancers-when detection is most critical-the concentration of cancer DNA is often low, limiting the sensitivity of current detection methods. Traditional DNA methylation detection techniques, which rely on methylation ratio-based measurements, may obscure subtle variations in methylation patterns, further reducing detection sensitivity. In this study, we analyzed cervical scraping specimens and examined whether detecting cancer-specific methylation patterns in cervical cancer could be enhanced using a Highly Methylated Haplotype (HMH) approach. This novel approach captures highly methylated haplotypes at single-molecule resolution using next-generation sequencing, providing greater detail than conventional methods. HMHs in specific DNA regions are a hallmark of cancer and stand out in contrast to sporadic methylation commonly observed in non-cancerous tissues. We applied HMH profiling to a gene panel of four biomarkers (CA10, DPP10, FMN2, and HAS1) previously validated in cervical cancer studies. At pre-specified cutoffs (99th percentile of normals), haplotype-based scoring achieved 89.9% sensitivity for invasive cancer at high specificity (~ 94-98%), outperforming median (78.0%) and single-CpG (71.6%) methods. For clinically relevant endpoints, the combined panel detected 51-52% of CIN2 + and 66-67% of CIN3 + cases, again exceeding the performance of median- and single-CpG-based scoring methods.These findings demonstrate the potential of HMH to substantially enhance sensitivity in cervical cancer detection, offering a promising approach for non-invasive diagnostics.

Humans↗
PubMed2026

Changes of DNA methylation and gene expression profile in placental villi and chorioamniotic membranes under preeclampsia.

BACKGROUND: Preeclampsia (PE) is a serious pregnancy complication with elusive pathogenesis. Although epigenetic dysregulation is implicated, its layer-specific placental roles are poorly defined. This study aimed to identify shared and layer-specific epigenetic alterations in PE by profiling DNA methylation and gene expression in placental villi (PV) and chorioamniotic membranes (CAM). RESEARCH DESIGN AND METHODS: PV and CAM samples were collected from 7 normal and 8 PE pregnancies, and three public DNA methylation datasets (GSE98224, GSE44667, GSE75196) were integrated. Differentially methylated genes (DMGs) and differentially expressed genes (DEGs) were identified based on whole-genome methylation and transcriptome sequencing. Layer-specific and shared gene sets were identified by cross-analysis, with functional annotation using Gene Ontology (GO). RESULTS: EM-seq revealed a hypermethylation-dominant, tissue-specific methylation landscape in PE placentas. Cross-tissue comparison identified shared DMGs between the two layers, including nine key genes consistently altered in public datasets. Integrated analysis in PV further identified 22 co-dysregulated genes, enriched in thermoregulation, maternal-fetal immunity, signal transduction, and cell differentiation. CONCLUSIONS: This study elucidates the shared and layer-specific dysregulation of gene networks at methylomic and transcriptomic levels in PE placenta. Comparing PV and CAM highlights placental epigenetic heterogeneity and dysfunction, offering novel clues for mechanistic research and layer-targeted therapies.

Humans↗
PubMed2022

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

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

Child↗
PubMed2026

Integrated Clinicopathologic and Multiomic Profiling Reveals MEIS1-Rearranged Sarcoma as a Distinct Entity With 2 Prognostic Subgroups.

Sarcomas with MEIS1 fusions represent a rare, recently recognized group of mesenchymal neoplasms with a predilection for genitourinary and gynecologic sites. A subset exhibits skeletal muscle differentiation resembling spindle cell rhabdomyosarcoma. Existing literature is limited to case reports and small series, with scant comprehensive clinicopathologic, molecular, and outcome data. In this study, we analyzed a multi-institutional cohort of 20 MEIS1-rearranged sarcomas using integrated clinicopathologic review, genomic profiling, and DNA methylation analysis. The tumors occurred in 17 females and 3 males (median age, 41 years; range, 6-58 years), arising mainly in the uterus/vagina (n = 12), vulva/perineum (n = 4), bone (n = 2), and kidney (n = 2), with a median size of 9 cm (range, 2.5-20 cm). Histology showed mostly bland spindle cells in fascicles/storiform patterns, alternating cellularity, fibromyxoid stroma, prominent vascularity, and adipose metaplasia (45%). A subset of cases featured high-grade morphology with epithelioid cells and increased mitotic activity. Skeletal muscle markers were variably positive in 9 cases. Fusions involved MEIS1 with NCOA2 (16/20), NCOA1 (3/20), or FOXO1 (1/20). Recurrent additional genomic alterations included CTNNB1 mutations (31.6%) and MDM2 amplification (15%). DNA methylation profiling showed that MEIS1-rearranged sarcomas formed a unifying cluster comprising 2 subgroups, regardless of rhabdomyosarcomatous phenotype, clearly separated from other mesenchymal neoplasms, including various rhabdomyosarcoma subtypes and uterine sarcomas. The 2 DNA methylation (Meth) subgroups correlated with differences in genome-wide copy number variation (CNV) status (Meth-CNV high vs Meth-CNV low), with Meth-CNV high tumors characterized by high mitotic rate, frequent tumor necrosis, recurrent co-occurring CTNNB1 and MDM2 alterations, and recurrent chromosomal arm-level changes. Most importantly, this subgroup exhibited significantly worse overall survival (P = .027) and disease-free survival (median, 5 vs 99 months; P = .017). This study establishes MEIS1-rearranged sarcoma as a distinct entity with generally indolent but potentially aggressive behavior. The 2 methylation/CNV subgroups provide potential utility for prognostic stratification and highlight actionable molecular targets in high-risk cases.

Humans↗
PubMed2025

Whole-Genome Bisulfite Sequencing with a Small Amount of DNA.

Whole-genome bisulfite sequencing (WGBS) is the most widely used method to study DNA methylation profiles across the genome. Since the bisulfite reaction causes DNA degradation, a new approach called post-bisulfite adapter tagging (PBAT) was developed to overcome this problem by adding adapters after bisulfite treatment. In mammals, the PBAT method is used for single-cell bisulfite sequencing (scBS-seq), which enables DNA methylation analysis using a very small amount of DNA from only a few cells, including single-cell input. This protocol involves bisulfite conversion, followed by preamplification and tagging with random hexamer primers prior to Illumina library preparation. Since many procedures are completed in one single test tube, the loss of DNA can be minimized, enabling highly sensitive experiments to study DNA methylation profiles from a very small amount of input material.

Sulfites↗
PubMed2026

Epigenetic Profiling for Early Detection and Treatment Response Monitoring in Non-Small Cell Lung Cancer: Protocol for a Prospective Translational Biomarker Study.

BACKGROUND: Non-small cell lung cancer (NSCLC) is the leading cause of cancer-related mortality worldwide and continues to have poor survival outcomes, with most patients diagnosed at advanced stages of disease. In New Zealand, NSCLC contributes substantially to cancer inequities, with Māori communities experiencing disproportionately high incidence and mortality rates. Although low-dose computed tomography screening can improve early detection, major limitations remain, including false-positive findings, overdiagnosis, high infrastructure costs, and limited accessibility for rural and underserved populations. Liquid biopsy approaches using circulating tumor DNA (ctDNA), particularly DNA methylation profiling, have emerged as promising, minimally invasive strategies for improving cancer detection, treatment monitoring, and precision oncology. OBJECTIVE: This study aims to establish integrated genomic and epigenomic predictive and prognostic biomarkers using ctDNA, tumor tissue, and transcriptomic profiling to improve early detection, risk stratification, treatment selection and response prediction, and longitudinal monitoring, with particular emphasis on identifying molecular mechanisms associated with treatment resistance and disease progression. METHODS: This prospective observational translational biomarker study is being conducted through the University of Otago and associated respiratory and oncology services in New Zealand. The study will recruit participants with NSCLC (including squamous and nonsquamous subtypes), individuals referred to fast-track lung nodule assessment clinics, and nonmalignant respiratory controls. Serial peripheral blood sampling will be performed in selected participants at predefined clinical follow-up time points to evaluate treatment response and disease progression. The availability of formalin-fixed paraffin-embedded archival tissues will be recorded, but will not be mandatory for enrollment. Genome-scale DNA methylation profiling will be performed using cell-free reduced representation bisulfite sequencing (cfRRBS), while targeted genomic profiling and transcriptomic analyses will be conducted using targeted sequencing panels and RNA sequencing. Integrative bioinformatic analyses will be used to identify molecular biomarkers associated with early-stage disease, advanced disease, treatment response, and therapeutic resistance. RESULTS: Ethics approval for the study has been obtained from the New Zealand Health and Disability Ethics Committee (2022 EXP 12566). This study commenced in 2022, and recruitment and biospecimen collection are ongoing. The study aims to recruit approximately 450 participants, including patients with NSCLC, individuals referred through respiratory diagnostic pathways, and nonmalignant controls. As of July 31, 2026, 205 participants have been recruited, with recruitment continuing until the target sample size is reached. Molecular and data analyses are ongoing, with additional publications expected as the cohort matures. CONCLUSIONS: This study will generate one of the first integrated genomic, epigenomic, and transcriptomic liquid biopsy datasets for NSCLC in New Zealand. The findings are expected to support the development of sensitive, accessible, and equitable blood-based biomarkers for NSCLC detection and treatment monitoring while also contributing to improved precision oncology approaches and reducing NSCLC inequities among Māori populations.

Humans↗
PubMed2026

Spinal low-grade ependymal tumors harboring telomerase reverse transcriptase promoter mutation and chromosome 7 gain with methylation profile of spinal subependymoma.

Spinal intramedullary tumors comprise a heterogeneous group of entities with diverse histopathological features, making their diagnosis particularly challenging. With the introduction of DNA methylation profiling, the underlying biological diversity of these tumors has been increasingly clarified and systematized; however, owing to the rarity of these tumors, case accumulation remains limited, and significant challenges persist. In this study, we identified two cases of spinal ependymal tumors exhibiting a methylation profile of spinal (SP-) subependymoma (SEPN). Both cases occurred in elderly patients and demonstrated circumscribed growth consistent with low-grade ependymal tumors; however, these tumors did not exhibit the typical histopathological features required for a diagnosis of SEPN in the 2021 WHO classification of central nervous system (CNS) tumors, showing indistinct cluster formation, an astrocytic immunohistochemical profile suggested by Olig2 expression, and relatively elevated Ki-67 labeling indices of 4.5% and 3.1%. At the molecular level, both cases harbored telomerase reverse transcriptase promoter mutations and whole chromosome 7 gain. On two-dimensional t-distributed stochastic neighbor embedding analysis, both clustered within the SP-SEPN methylation class at its periphery, with low classifier calibration scores (0.70 and 0.69). According to the current WHO classification, these cases are designated as low-grade ependymal tumors (CNS WHO grade 2) with methylation profile of SP-SEPN because they do not meet the essential WHO histopathological criteria. Ependymal tumors exhibiting a methylation profile consistent with SEPN, but discordant histopathological features have been increasingly recognized, and the appropriate classification of such tumors remains a subject of ongoing debate. These cases provide important insights into the histopathological diversity of ependymal tumors and contribute to establishing a more comprehensive and systematic classification of ependymal tumors.

Aged↗
PubMed2026

DNA Methylation and Proteomic Profiling of Postmortem Brain Tissue Reveals Epigenetic Dysregulation and Neuroinflammatory in Fragile X-associated Tremor/Ataxia Syndrome (FXTAS).

BACKGROUND: Fragile X-associated Tremor/Ataxia Syndrome (FXTAS) is a late-onset neurodegenerative disorder caused by FMR1 premutation CGG repeat expansions (55-200 repeats). The epigenetic landscape of the FXTAS brain remains uncharacterized. We performed genome-wide DNA methylation profiling of postmortem prefrontal cortex tissue to identify differentially methylated positions (DMPs) and candidate genes, and sought protein-level support for a neuroinflammatory signal. METHODS: DNA methylation was profiled in postmortem prefrontal cortex (Brodmann area 9) from 27 male FXTAS cases and 29 male controls using the Illumina MethylationEPIC array (EPICv1 and EPICv2 platforms), merging 721,802 common probes. Surrogate variable analysis (SVA) controlled for confounders. DMPs were defined by |&#x394;&#x3b2;| > 0.10 and FDR < 0.05; exploratory Reactome 2024 pathway analysis was performed on the DMP-associated gene list. Targeted proteomic profiling was performed in the same brain region using the Olink (proximity extension assay) Inflammation panel in 9 FXTAS cases and 12 controls, with SVA-adjusted differential abundance analysis, and concordance assessment against a prior mass spectrometry dataset. RESULTS: We identified 108 significant cg-type DMPs mapping to 80 genes (50 hypermethylated, 58 hypomethylated in FXTAS). The strongest signal was CYP2E1 (7 concordant hypomethylated DMPs, mean &#x394;&#x3b2; = -0.143), an oxidative stress gene also implicated in Parkinson's disease. FTCD, a one-carbon cycle enzyme, carried 5 hypermethylated DMPs (mean &#x394;&#x3b2; = +0.210). A cluster of DMP-associated genes with established roles in innate immune and NF-&#x3ba;B signaling, TRAF3 (the single most significant DMP among the inflammation genes, hypermethylated), BATF, RCOR1, and MSI2; they pointed toward neuroinflammatory dysregulation. Additional genes included LINGO1 (myelination inhibitor), SYT3 (synaptic vesicle), and SLC39A4 (zinc transporter). Exploratory Reactome enrichment using the DMP-associated gene set nominated themes including neuroinflammation resolution, axonal growth inhibition, zinc homeostasis, and CYP2E1 metabolism at nominal significance (p<0.05); however, the gene-to-pathway mapping rate was low and no pathway survived correction for multiple testing. Olink proteomic analysis independently identified 60 significantly altered inflammation proteins (59 downregulated), including CXCL8, CXCL10, IL6, IL15, IL18, TLR3, IRAK1/4, and complement C1QA, which were directionally concordant with prior mass spectrometry data. CONCLUSIONS: This integrated study reveals a genome-wide epigenetic signature in the FXTAS prefrontal cortex implicating oxidative stress, myelination failure, zinc dysregulation, one-carbon cycle disruption, and most notably a coordinated set of epigenetically altered genes governing innate immune and NF-&#x3ba;B signaling. Convergence of TRAF3 hypermethylation with independent downregulation of TLR3 and NF-&#x3ba;B-pathway proteins at the protein level supports a coherent, cross-platform model of dysregulated neuroinflammatory signaling in FXTAS, identified here through individual gene- and protein-level convergence rather than formal pathway enrichment. FTCD hypermethylation proposes a self-reinforcing epigenetic loop via SAM depletion. These multi-omic findings establish FXTAS as a disorder of pervasive epigenetic reprogramming and nominate candidate genes for future mechanistic and therapeutic investigation.

CYP2E1↗
PubMed2026

A stratified urine-based molecular diagnostic and prognostic model for non-muscle-invasive bladder cancer management.

BACKGROUND: Non-muscle-invasive bladder cancer (NMIBC) is characterized by a high recurrence rate requiring lifelong cystoscopic surveillance. Existing urine-based molecular assays mainly rely on mutations or methylation, which fail to capture large-scale genomic instability. Copy number variation (CNV) profiling offers complementary information on tumor evolution and aggressiveness, but its application in urinary diagnosis remains limited. We aimed to integrate CNV and DNA methylation signals from urinary DNA to establish a noninvasive and biologically informed stratified diagnostic model for NMIBC recurrence surveillance and risk stratification. METHODS: Urine samples were prospectively collected from 91 patients (75 evaluable) between June 2021 and August 2023. Shallow whole-genome sequencing (sWGS) was used to detect CNVs at chromosomal arm and focal gene levels, while ONECUT2 promoter methylation was quantified by qPCR. Diagnostic and prognostic performance was evaluated by ROC analysis, Kaplan-Meier survival, and stratified recurrence assessment. RESULTS: We evaluated a stratified diagnostic model combining CNV and ONECUT2 methylation testing in a cohort of 79 patients. CNV analysis alone showed high specificity (0.923) for NMIBC diagnosis. A combined model, using CNV as an initial screen followed by ONECUT2 methylation testing in CNV-positive cases, achieved a sensitivity of 0.783, specificity of 0.981, and a negative predictive value (NPV) of 0.911. This approach reduced the number of required ONECUT2 tests by 35% and identified a high proportion of true-negative patients (98.1%), which may help reduce unnecessary cystoscopy procedures. The model also demonstrated significant prognostic value, with the molecularly defined high-risk group showing significantly shorter recurrence-free survival (RFS) than the low-risk group (median RFS: 4.33 months vs. not reached; p&#x2009;<&#x2009;0.001). Additional, in patients with initially negative cystoscopy after urine sample collection, the model demonstrated a predictive accuracy of 0.922 for recurrence, with molecular positivity observed a median of 9.6 months prior to clinical diagnosis. CONCLUSIONS: Integrating CNV and DNA methylation profiling from urinary DNA provides a powerful and noninvasive molecular framework for NMIBC surveillance. By combining early epigenetic changes with genomic instability signals, this approach enhances recurrence risk assessment and enables earlier detection compared with conventional cystoscopy. It offers a practical route toward personalized and adaptive post-treatment monitoring of NMIBC. TRIAL REGISTRATION: NCT04994197.

Humans↗
PubMed2026

Methylation profiling in CNS tumor diagnostics: a single-centre real-world experience from Central Europe.

Genome-wide DNA methylation profiling has transformed neuro-oncology by providing an objective, machine learning-based taxonomy that mitigates interobserver variability and refines the histo-molecular criteria of the current WHO classification. We evaluate the real-world diagnostic performance and clinical utility of this modality in a prospective, consecutively accrued three-year cohort of 291 central nervous system (CNS) tumors across a mixed adult-pediatric population. Successful profiling was completed in 95.9% of cases. Using the Epignostix classifier, a high-confidence diagnostic match (calibrated score [CS]&#x2009;&#x2265;&#x2009;0.84) was achieved in 70.3% of analyzable samples, while 26.5% returned lower-confidence scores (&#x2265;&#x2009;0.3 to <&#x2009;0.84) and only 3.2% remained completely unclassifiable (CS&#x2009;<&#x2009;0.3). When integrated into a comprehensive diagnostic framework, methylation profiling provided clinically useful results in 81.1% of cases, establishing diagnoses in 70 cases submitted for molecular subclassification and resolving diagnostic uncertainty or prompting major revisions in 149 histologically challenging tumors. Within truly ambiguous lesions, integration of methylome data dictated tumor grade modifications in 38.8% of cases (upgrading in 29.4% and downgrading in 9.4%), shifting patient risk stratification. Crucially, over half (52.7%) of the lower-confidence cases yielded meaningful clinical integration when supported by histomorphology and ancillary genetic or immunohistochemical markers, demonstrating that rigid score cutoffs should not dictate assay failure. Discrepant or misleading classifications occurred in 1.9%. Updating bioinformatic pipelines from version 11b4 to 12.8 rescued multiple ambiguous entries, increasing overall clinical utility to 84.1%. These findings demonstrate that integrating computational epigenomics with classical neuropathology enhances diagnostic precision, while highlighting the ongoing need for careful clinical-pathological correlation.

Central nervous system tumors↗
PubMed2026

Epigenetic alterations of AKT1 orchestrate a metabolic reprogramming in advanced lipedema: translational insights from an integrated multi-omics study.

BACKGROUND: lipedema is a chronic, progressive adipose disorder predominantly affecting women, characterized by painful, symmetrical subcutaneous fat accumulation, and typically resistant to lifestyle interventions. The pathophysiology of advanced-stage lipedema remains poorly defined, and no validated biomarkers or targeted therapies are currently available. METHODS: in this observational study, we applied a comprehensive multi-omics approach to dissect the molecular and metabolic alterations underlying late-stage lipedema. RESULTS: Genome-wide DNA methylation profiling identified over 5,000 differentially methylated CpG sites affecting genes involved in receptor tyrosine kinase signaling, phospho-metabolism, and immune pathways. Transcriptomic analysis revealed profound downregulation of mitochondrial functions, including oxidative phosphorylation, the TCA cycle, and fatty acid &#x3b2;-oxidation, alongside disruption of the sirtuin pathway and extracellular matrix remodeling. Integrative analysis pinpointed AKT1 as a central regulatory node: its promoter region was hypomethylated, correlating with increased gene expression and protein phosphorylation. Metabolomic profiling confirmed AKT1-linked metabolic dysregulation, including altered levels of L-arginine, NADP+, ATP, guanosine, glycerol, and glutamate, indicating impaired redox balance and energy metabolism. Trans-omic network analysis positioned AKT1 at the intersection of multiple dysregulated pathways, suggesting its key role in advanced-stage lipedema. CONCLUSIONS: the consistent enhancing of AKT pathway signaling across omic layers highlights its potential not only as a biomarker for disease stratification but also as a putative druggable target for therapeutic intervention. These findings offer new mechanistic insights into lipedema pathophysiology and provide a rationale for future personalized treatment strategies guided by AKT1-centric molecular profiling.

Proto-Oncogene Proteins c-akt↗
PubMed2025

An Integrated Clinical Genomic and Transcriptomic Subgrouping of Central Chondrosarcoma.

Central conventional chondrosarcoma, a malignant cartilage-producing bone tumor, is the second most common bone sarcoma. Chondrosarcomas are histologically graded, which is so far the best predictor of survival. Early mutations in isocitrate dehydrogenase 1 (IDH1) and IDH2 genes are frequent, leading to the production of the oncometabolite D-2-hydroxyglutarate, which affects DNA methylation, resulting in a preferred chondrogenic differentiation over osteogenic differentiation of mesenchymal stem cells, which are currently considered the precursor cells of chondrosarcoma. DNA methylation profiling has previously revealed distinct profiles between IDH-mutant and IDH-wild-type chondrosarcomas, but the presence of further DNA methylation subgroups indicates that classification based solely on IDH status is too simplistic. In this study, we aim to identify biological subgroups in a total of 116 chondrosarcomas by integrating clinical data, IDH mutation status, gene expression, and genome-wide loss of heterozygosity (LOH). Clinical associations were observed between several factors, including sex and histological grade, as well as tumor site and IDH mutation status. RNA sequencing and genome-wide LOH confirmed the distinction between IDH-wild-type and IDH-mutant chondrosarcomas, where the number of chromosome arms affected by LOH was significantly higher in IDH-wild-type tumors than in IDH-mutant tumors. However, no clear subgroups emerged within each IDH group. Further clustering on RNA expression of differentiation markers identified subgroups characterized by chondrogenic, osteogenic, resting chondrocyte, or dedifferentiated profiles. These different subgroups showed a specific clinical presentation and suggest different precursor cells. Instead of a simple dichotomy between IDH-mutant and IDH-wild-type, our integrated approach highlights interconnected clinical, genomic, and transcriptomic patterns that offer a more nuanced view of chondrosarcoma biology and might potentially guide treatment stratification.

Humans↗
PubMed2025

Blood-based DNA methylation markers for autism spectrum disorder identification using machine learning.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder lacking objective biomarkers for early diagnosis. DNA methylation is a promising epigenetic marker, and machine learning offers a data-driven classification approach. However, few studies have examined whole-blood, genome-wide DNA methylation profiles for ASD diagnosis in school-aged children. METHODS: We analyzed genome-wide DNA methylation data from GEO dataset GSE113967, including 52 children with ASD and 48 typically developing (TD) controls. Differentially methylated positions (DMPs) were identified, and feature selection was performed using support vector machine-recursive feature elimination with cross-validation (SVM-RFECV). Classification models were developed using random forest (RF), extreme gradient boosting (XGBoost), and decision tree (DT) classifiers. A nomogram visualized feature contributions. RESULTS: A total of 138 DMPs differentiated ASD from TD children. Eleven CpG sites selected by SVM-RFECV formed the basis for model construction. RF and XGBoost achieved the highest accuracy (75%), with DT reaching 70%. Functional annotation indicated enrichment in cell adhesion and immune-related pathways. CONCLUSIONS: This exploratory study demonstrates the feasibility of integrating peripheral blood DNA methylation data with machine learning to distinguish children with ASD. While limited by sample size and moderate accuracy, this study provides methodological insights into the feasibility of integrating epigenetic and computational approaches for ASD-related biomarker exploration.

Humans↗