DNA methylation and stroke prognosis: an epigenome-wide association study.

BACKGROUND AND AIMS: Stroke is the leading cause of adult-onset disability. Although clinical factors influence stroke outcome, there is a significant variability among individuals that may be attributed to genetics and epigenetics, including DNA methylation (DNAm). We aimed to study the association between DNAm and stroke prognosis. METHODS AND RESULTS: To that aim, we conducted a two-phase study (discovery-replication and meta-analysis) in Caucasian patients with ischemic stroke from two independent centers (BasicMar [discovery, N = 316] and St. Pau [replication, N = 92]). Functional outcome was assessed using the modified Rankin Scale (mRS) at three months after stroke, being poor outcome defined as mRS > 2. DNAm was determined using the 450K and EPIC BeadChips in whole-blood samples collected within the first 24 h. We searched for differentially methylated positions (DMPs) in 370,344 CpGs, and candidates below p-value < 10-5 were subsequently tested in the replication cohort. We then meta-analyzed DMP results from both cohorts and used them to identify differentially methylated regions (DMRs). After doing the epigenome-wide association study, we found 29 DMPs at p-value < 10-5 and one of them was replicated: cg24391982, annotated to thrombospondin-2 (THBS2) gene (p-valuediscovery = 1.54·10-6; p-valuereplication = 9.17·10-4; p-valuemeta-analysis = 6.39·10-9). Besides, four DMRs were identified in patients with poor outcome annotated to zinc finger protein 57 homolog (ZFP57), Arachidonate 12-Lipoxygenase 12S Type (ALOX12), ABI Family Member 3 (ABI3) and Allantoicase (ALLC) genes (p-value < 1·10-9 in all cases). DISCUSSION: Patients with poor outcome showed a DMP at THBS2 and four DMRs annotated to ZFP57, ALOX12, ABI3 and ALLC genes. This suggests an association between stroke outcome and DNAm, which may help identify new stroke recovery mechanisms.

Kernel-based testing for single-cell differential analysis.

Single-cell technologies offer insights into molecular feature distributions, but comparing them poses challenges. We propose a kernel-testing framework for non-linear cell-wise distribution comparison, analyzing gene expression and epigenomic modifications. Our method allows feature-wise and global transcriptome/epigenome comparisons, revealing cell population heterogeneities. Using a classifier based on embedding variability, we identify transitions in cell states, overcoming limitations of traditional single-cell analysis. Applied to single-cell ChIP-Seq data, our approach identifies untreated breast cancer cells with an epigenomic profile resembling persister cells. This demonstrates the effectiveness of kernel testing in uncovering subtle population variations that might be missed by other methods.

DNA methylation signatures of youth-onset type 2 diabetes and exposure to maternal diabetes.

OBJECTIVE: Youth-onset type 2 diabetes (T2D) is physiologically distinct from adult-onset, but it is not clear how the two diseases differ at a molecular level. In utero exposure to maternal type 2 diabetes (T2D) is known to be a specific risk factor for youth-onset T2D. DNA methylation (DNAm) changes associated with T2D but which differ between youth- and adult-onset might delineate the impacts of T2D development at different ages and could also determine the contribution of exposure to in utero diabetes. METHODS: We performed an epigenome-wide analysis of DNAm on whole blood from 218 youth with T2D and 77 normoglycemic controls from the iCARE (improving renal Complications in Adolescents with type 2 diabetes through REsearch) cohort. Associations were tested using multiple linear regression models while adjusting for maternal diabetes, sex, age, BMI, smoking status, second-hand smoking exposure, cell-type proportions and genetic ancestry. RESULTS: We identified 3830 differentially methylated sites associated with youth T2D onset, of which 3794 were moderately (adjusted p-value < 0.05 and effect size estimate > 0.01) associated and 36 were strongly (adjusted p-value < 0.05 and effect size estimate > 0.05) associated. A total of 3725 of these sites were not previously reported in the EWAS Atlas as associated with T2D, adult obesity or youth obesity. Moreover, three CpGs associated with youth-onset T2D in the PFKFB3 gene were also associated with maternal T2D exposure (FDR < 0.05 and effect size > 0.01). This is the first study to link PFKFB3 and T2D in youth. CONCLUSION: Our findings support that T2D in youth has different impacts on DNAm than adult-onset, and suggests that changes in DNAm could provide an important link between in utero exposure to maternal diabetes and the onset of T2D.

Genome wide inherited modifications of the tomato epigenome by trans-activated bacterial CG methyltransferase.

BACKGROUND: Epigenetic variation is mediated by epigenetic marks such as DNA methylation occurring in all cytosine contexts in plants. CG methylation plays a critical role in silencing transposable elements and regulating gene expression. The establishment of CG methylation occurs via the RNA-directed DNA methylation pathway and CG methylation maintenance relies on METHYLTRANSFERASE1, the homologue of the mammalian DNMT1. PURPOSE: Here, we examined the capacity to stably alter the tomato genome methylome by a bacterial CG-specific M.SssI methyltransferase expressed through the LhG4/pOP transactivation system. RESULTS: Methylome analysis of M.SssI expressing plants revealed that their euchromatic genome regions are specifically hypermethylated in the CG context, and so are most of their genes. However, changes in gene expression were observed only with a set of genes exhibiting a greater susceptibility to CG hypermethylation near their transcription start site. Unlike gene rich genomic regions, our analysis revealed that heterochromatic regions are slightly hypomethylated at CGs only. Notably, some M.SssI-induced hypermethylation persisted even without the methylase or transgenes, indicating inheritable epigenetic modification. CONCLUSION: Collectively our findings suggest that heterologous expression of M.SssI can create new inherited epigenetic variations and changes in the methylation profiles on a genome wide scale. This open avenues for the conception of epigenetic recombinant inbred line populations with the potential to unveil agriculturally valuable tomato epialleles.

Integrated analysis of the DNA methylome and RNA transcriptome during the development of skeletal muscle in Duroc pigs.

BACKGROUND: Skeletal muscle development plays a crucial role in yield and quality of pork; however, this process is influenced by various factors. In this study, we employed whole-genome bisulfite sequencing (WGBS) and transcriptome sequencing to comprehensively investigate the longissimus dorsi muscle (LDM), aiming to identify key genes that impact the growth and development of Duroc pigs with different average daily gains (ADGs). RESULTS: Eight pigs were selected and divided into two groups based on ADGs: H (774.89 g) group and L (658.77 g) group. Each pair of the H and L groups were half-siblings. The results of methylation sequencing revealed 2631 differentially methylated genes (DMGs) involved in metabolic processes, signalling, insulin secretion, and other biological activities. Furthermore, a joint analysis was conducted on these DMGs and the differentially expressed genes (DEGs) obtained from transcriptome sequencing of the same individual. This analysis identified 316 differentially methylated and differentially expressed genes (DMEGs), including 18 DMEGs in promoter regions and 294 DMEGs in gene body regions. Finally, LPAR1 and MEF2C were selected as candidate genes associated with muscle development. Bisulfite sequencing PCR (BSP) and quantitative real-time PCR (qRT-PCR) revealed that the promoter region of LPAR1 exhibited significantly lower methylation levels (P < 0.05) and greater expression levels (P < 0.05) in the H group than in the L group. Additionally, hypermethylation was observed in the gene body region of MEF2C, as was a low expression level, in the H group (P < 0.05). CONCLUSIONS: These results suggest that the differences in the ADGs of Duroc pigs fed the same diet may be influenced by the methylation levels and expression levels of genes related to skeletal muscle development.

Investigating neonatal health risk variables through cell-type specific methylome-wide association studies.

Adverse neonatal outcomes are a prevailing risk factor for both short- and long-term mortality and morbidity in infants. Given the importance of these outcomes, refining their assessment is paramount for improving prevention and care. Here we aim to enhance the assessment of these often correlated and multifaceted neonatal outcomes. To achieve this, we employ factor analysis to identify common and unique effects and further confirm these effects using criterion-related validity testing. This validation leverages methylome-wide profiles from neonatal blood. Specifically, we investigate nine neonatal health risk variables, including gestational age, Apgar score, three indicators of body size, jaundice, birth diagnosis, maternal preeclampsia, and maternal age. The methylomic profiles used for this research capture data from nearly all 28 million methylation sites in human blood, derived from the blood spot collected from 333 neonates, within 72 h post-birth. Our factor analysis revealed two common factors, size factor, that captured the shared effects of weight, head size, height, and gestational age and disease factor capturing the orthogonal shared effects of gestational age, combined with jaundice and birth diagnosis. To minimize false positives in the validation studies, validation was limited to variables with significant cumulative association as estimated through an in-sample replication procedure. This screening resulted in that the two common factors and the unique effects for gestational age, jaundice and Apgar were further investigated with full-scale cell-type specific methylome-wide association analyses. Highly significant, cell-type specific, associations were detected for both common effect factors and for Apgar. Gene Ontology analyses revealed multiple significant biologically relevant terms for the five fully investigated neonatal health risk variables. Given the established links between adverse neonatal outcomes and both immediate and long-term health, the distinct factor effects (representing the common and unique effects of the risk variables) and their biological profiles confirmed in our work, suggest their potential role as clinical biomarkers for assessing health risks and enhancing personalized care.

Benchmarking of methods for DNA methylome deconvolution.

Defining the number and abundance of different cell types in tissues is important for understanding disease mechanisms as well as for diagnostic and prognostic purposes. Typically, this is achieved by immunohistological analyses, cell sorting, or single-cell RNA-sequencing. Alternatively, cell-specific DNA methylome information can be leveraged to deconvolve cell fractions from a bulk DNA mixture. However, comprehensive benchmarking of deconvolution methods and modalities was not yet performed. Here we evaluate 16 deconvolution algorithms, developed either specifically for DNA methylome data or more generically. We assess the performance of these algorithms, and the effect of normalization methods, while modeling variables that impact deconvolution performance, including cell abundance, cell type similarity, reference panel size, method for methylome profiling (array or sequencing), and technical variation. We observe differences in algorithm performance depending on each these variables, emphasizing the need for tailoring deconvolution analyses. The complexity of the reference, marker selection method, number of marker loci and, for sequencing-based assays, sequencing depth have a marked influence on performance. By developing handles to select the optimal analysis configuration, we provide a valuable source of information for studies aiming to deconvolve array- or sequencing-based methylation data.

Multimodal analysis of cfDNA methylomes for early detecting esophageal squamous cell carcinoma and precancerous lesions.

Detecting early-stage esophageal squamous cell carcinoma (ESCC) and precancerous lesions is critical for improving survival. Here, we conduct whole-genome bisulfite sequencing (WGBS) on 460 cfDNA samples from patients with non-metastatic ESCC or precancerous lesions and matched healthy controls. We develop an expanded multimodal analysis (EMMA) framework to simultaneously identify cfDNA methylation, copy number variants (CNVs), and fragmentation markers in cfDNA WGBS data. cfDNA methylation markers are the earliest and most sensitive, detectable in 70% of ESCCs and 50% of precancerous lesions, and associated with molecular subtypes and tumor microenvironments. CNVs and fragmentation features show high specificity but are linked to late-stage disease. EMMA significantly improves detection rates, increasing AUCs from 0.90 to 0.99, and detects 87% of ESCCs and 62% of precancerous lesions with >95% specificity in validation cohorts. Our findings demonstrate the potential of multimodal analysis of cfDNA methylome for early detection and monitoring of molecular characteristics in ESCC.

Temporal dynamics of the multi-omic response to endurance exercise training.

Regular exercise promotes whole-body health and prevents disease, but the underlying molecular mechanisms are incompletely understood1-3. Here, the Molecular Transducers of Physical Activity Consortium4 profiled the temporal transcriptome, proteome, metabolome, lipidome, phosphoproteome, acetylproteome, ubiquitylproteome, epigenome and immunome in whole blood, plasma and 18 solid tissues in male and female Rattus norvegicus over eight weeks of endurance exercise training. The resulting data compendium encompasses 9,466 assays across 19 tissues, 25 molecular platforms and 4 training time points. Thousands of shared and tissue-specific molecular alterations were identified, with sex differences found in multiple tissues. Temporal multi-omic and multi-tissue analyses revealed expansive biological insights into the adaptive responses to endurance training, including widespread regulation of immune, metabolic, stress response and mitochondrial pathways. Many changes were relevant to human health, including non-alcoholic fatty liver disease, inflammatory bowel disease, cardiovascular health and tissue injury and recovery. The data and analyses presented in this study will serve as valuable resources for understanding and exploring the multi-tissue molecular effects of endurance training and are provided in a public repository ( https://motrpac-data.org/ ).

Fusobacterium nucleatum infection modulates the transcriptome and epigenome of HCT116 colorectal cancer cells in an oxygen-dependent manner.

Fusobacterium nucleatum, a gram-negative oral bacterium, has been consistently validated as a strong contributor to the progression of several types of cancer, including colorectal (CRC) and pancreatic cancer. While previous in vitro studies have shown that intracellular F. nucleatum enhances malignant phenotypes such as cell migration, the dependence of this regulation on features of the tumor microenvironment (TME) such as oxygen levels are wholly uncharacterized. Here we examine the influence of hypoxia in facilitating F. nucleatum invasion and its effects on host responses focusing on changes in the global epigenome and transcriptome. Using a multiomic approach, we analyze epigenomic alterations of H3K27ac and global transcriptomic alterations sustained within a hypoxia and normoxia conditioned CRC cell line HCT116 at 24 h following initial infection with F. nucleatum. Our findings reveal that intracellular F. nucleatum activates signaling pathways and biological processes in host cells similar to those induced upon hypoxia conditioning in the absence of infection. Furthermore, we show that a hypoxic TME favors F. nucleatum invasion and persistence and therefore infection under hypoxia may amplify malignant transformation by exacerbating the effects induced by hypoxia alone. These results motivate future studies to investigate host-microbe interactions in tumor tissue relevant conditions that more accurately define parameters for targeted cancer therapies.

Mapping genotypes to chromatin accessibility profiles in single cells.

In somatic tissue differentiation, chromatin accessibility changes govern priming and precursor commitment towards cellular fates1-3. Therefore, somatic mutations are likely to alter chromatin accessibility patterns, as they disrupt differentiation topologies leading to abnormal clonal outgrowth. However, defining the impact of somatic mutations on the epigenome in human samples is challenging due to admixed mutated and wild-type cells. Here, to chart how somatic mutations disrupt epigenetic landscapes in human clonal outgrowths, we developed genotyping of targeted loci with single-cell chromatin accessibility (GoT-ChA). This high-throughput platform links genotypes to chromatin accessibility at single-cell resolution across thousands of cells within a single assay. We applied GoT-ChA to CD34+ cells from patients with myeloproliferative neoplasms with JAK2V617F-mutated haematopoiesis. Differential accessibility analysis between wild-type and JAK2V617F-mutant progenitors revealed both cell-intrinsic and cell-state-specific shifts within mutant haematopoietic precursors, including cell-intrinsic pro-inflammatory signatures in haematopoietic stem cells, and a distinct profibrotic inflammatory chromatin landscape in megakaryocytic progenitors. Integration of mitochondrial genome profiling and cell-surface protein expression measurement allowed expansion of genotyping onto DOGMA-seq through imputation, enabling single-cell capture of genotypes, chromatin accessibility, RNA expression and cell-surface protein expression. Collectively, we show that the JAK2V617F mutation leads to epigenetic rewiring in a cell-intrinsic and cell type-specific manner, influencing inflammation states and differentiation trajectories. We envision that GoT-ChA will empower broad future investigations of the critical link between somatic mutations and epigenetic alterations across clonal populations in malignant and non-malignant contexts.

An integrative epigenome-based strategy for unbiased functional profiling of clinical kinase inhibitors.

More than 500 kinases are implicated in the control of most cellular process in mammals, and deregulation of their activity is linked to cancer and inflammatory disorders. 80 clinical kinase inhibitors (CKIs) have been approved for clinical use and hundreds are in various stages of development. However, CKIs inhibit other kinases in addition to the intended target(s), causing both enhanced clinical effects and undesired side effects that are only partially predictable based on in vitro selectivity profiling. Here, we report an integrative approach grounded on the use of chromatin modifications as unbiased, information-rich readouts of the functional effects of CKIs on macrophage activation. This approach exceeded the performance of transcriptome-based approaches and allowed us to identify similarities and differences among CKIs with identical intended targets, to recognize novel CKI specificities and to pinpoint CKIs that may be repurposed to control inflammation, thus supporting the utility of this strategy to improve selection and use of CKIs in clinical settings.

The methylome of motile cilia.

Cilia are highly complex motile, sensory, and secretory organelles that contain perhaps 1000 or more distinct protein components, many of which are subject to various posttranslational modifications such as phosphorylation, N-terminal acetylation, and proteolytic processing. Another common modification is the addition of one or more methyl groups to the side chains of arginine and lysine residues. These tunable additions delocalize the side-chain charge, decrease hydrogen bond capacity, and increase both bulk and hydrophobicity. Methylation is usually mediated by S-adenosylmethionine (SAM)-dependent methyltransferases and reversed by demethylases. Previous studies have identified several ciliary proteins that are subject to methylation including axonemal dynein heavy chains that are modified by a cytosolic methyltransferase. Here, we have performed an extensive proteomic analysis of multiple independently derived cilia samples to assess the potential for SAM metabolism and the extent of methylation in these organelles. We find that cilia contain all the enzymes needed for generation of the SAM methyl donor and recycling of the S-adenosylhomocysteine and tetrahydrofolate byproducts. In addition, we find that at least 155 distinct ciliary proteins are methylated, in some cases at multiple sites. These data provide a comprehensive resource for studying the consequences of methyl marks on ciliary biology.

Blood-based epigenome-wide analyses of chronic low-grade inflammation across diverse population cohorts.

Chronic inflammation is a hallmark of age-related disease states. The effectiveness of inflammatory proteins including C-reactive protein (CRP) in assessing long-term inflammation is hindered by their phasic nature. DNA methylation (DNAm) signatures of CRP may act as more reliable markers of chronic inflammation. We show that inter-individual differences in DNAm capture 50% of the variance in circulating CRP (N = 17,936, Generation Scotland). We develop a series of DNAm predictors of CRP using state-of-the-art algorithms. An elastic-net-regression-based predictor outperformed competing methods and explained 18% of phenotypic variance in the Lothian Birth Cohort of 1936 (LBC1936) cohort, doubling that of existing DNAm predictors. DNAm predictors performed comparably in four additional test cohorts (Avon Longitudinal Study of Parents and Children, Health for Life in Singapore, Southall and Brent Revisited, and LBC1921), including for individuals of diverse genetic ancestry and different age groups. The best-performing predictor surpassed assay-measured CRP and a genetic score in its associations with 26 health outcomes. Our findings forge new avenues for assessing chronic low-grade inflammation in diverse populations.

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.

Genome-wide profiling of DNA methylome and transcriptome reveals epigenetic regulation of Urechis unicinctus response to sulfide stress.

Sulfide is a well-known environmental pollutant that can have detrimental effects on most organisms. However, few metazoans living in sulfide-rich environments have developed mechanisms to tolerate and adapt to sulfide stress. Epigenetic mechanisms, including DNA methylation, have been shown to play a vital role in environmental stress adaptation. Nevertheless, the precise function of DNA methylation in biological sulfide adaptation remains unclear. Urechis unicinctus, a benthic organism inhabiting sulfide-rich intertidal environments, is an ideal model organism for studying adaptation to sulfide environments. In this study, we conducted a comprehensive analysis of the DNA methylome and transcriptome of U. unicinctus after exposure to 50 µM sulfide. The results revealed dynamic changes in the DNA methylation (5-methylcytosine) landscape in response to sulfide stress, with U. unicinctus exhibiting elevated DNA methylation levels following stress exposure. Integrating differentially expressed genes (DEGs) and differentially methylated regions (DMRs), we identified a crucial role of gene body methylation in predicting gene expression. Furthermore, using a DNA methyltransferase inhibitor, we validated the involvement of DNA methylation in the sulfide stress response and the gene regulatory network influenced by DNA methylation. The results indicated that by modulating DNA methylation levels during sulfide stress, the expression of glutathione S-transferase, glutamyl aminopeptidase, and cytochrome c oxidase could be up-regulated, thereby facilitating the metabolism and detoxification of exogenous sulfides. Moreover, DNA methylation was found to regulate and enhance the oxidative phosphorylation pathway, including NADH dehydrogenase, isocitrate dehydrogenase, and ATP synthase. Additionally, DNA methylation influenced the regulation of Cytochrome P450 and macrophage migration inhibitory factor, both of which are closely associated with oxidative stress and stress resistance. Our findings not only emphasize the role of DNA methylation in sulfide adaptation but also provide novel insights into the potential mechanisms through which marine organisms adapt to environmental changes.

Measuring cancer driving force of chromosomal aberrations through multi-layer Boolean implication networks.

Multi-layer Complex networks are commonly used for modeling and analysing biological entities. This paper presents the advantage of using COMBO (Combining Multi Bio Omics) to suggest a new role of the chromosomal aberration as a cancer driver factor. Exploiting the heterogeneous multi-layer networks, COMBO integrates gene expression and DNA-methylation data in order to identify complex bilateral relationships between transcriptome and epigenome. We evaluated the multi-layer networks generated by COMBO on different TCGA cancer datasets (COAD, BLCA, BRCA, CESC, STAD) focusing on the effect of a specific chromosomal numerical aberration, broad gain in chromosome 20, on different cancer histotypes. In addition, the effect of chromosome 8q amplification was tested in the same TCGA cancer dataset. The results demonstrate the ability of COMBO to identify the chromosome 20 amplification cancer driver force in the different TCGA Pan Cancer project datasets.

[Postnatal epigenome-mediated aging control and global trends].

The epigenome can adequately regulate the on/off states of genes in response to external environmental factors and stress. In recent years, it has been observed that the epigenome, which is modulated through DNA methylation, histone modifications, and chromatin remodeling, changes with age. Alterations in the epigenome lead to the loss of cell-specific epigenome/identity, which in turn triggers a decline in tissue function. In mammals, postnatal epigenomic variations are not only caused by metabolic diseases, such as diabetes or DNA damage, but also by social stress and infectious diseases. Unlike Genome-Wide Association Studies (GWAS), dynamically changing epigenomes, along with their cellular roles, need to be established as objective biomarkers in conjunction with various biological signals, such as walking speed, brain waves, and clinical data. The biological age/aging clock, determined by methylated DNA, has attracted attention, and calorie restriction not only slows the progression of aging, but also seems to suppress it. However, as indicated by gene expression analysis in aging mice, aging is not a linear model, but is represented by nonlinear dynamic changes. Consequently, the development of experimental models and analytical methods that enhance temporal resolution through time-series analysis, tailored to spatial resolution, such as cell distribution and organ specificity, is progressing. Moreover, in recent years, in addition to anti-aging efforts targeting epigenomic variations, global attention has increasingly focused on research and development aimed at rejuvenating treatments, thus leading to the birth of many biotech companies. Aging Hallmarks such as inflammation, stem cells, metabolism, genomic instability, and autophagy, interact closely with the epigenome. Various postnatal and reversible epigenomic controls of aging, including Yamanaka factors (OKSM and OSK), are now entering a new phase. In the future, the development of aging control using diverse modalities, such as mRNA, artificial peptides, and genome editing, is expected, along with an improved molecular understanding of aging and identification of useful biomarkers.

The Interplay between Endocrine-Disrupting Chemicals and the Epigenome towards Metabolic Dysfunction-Associated Steatotic Liver Disease: A Comprehensive Review.

Metabolic dysfunction-associated steatotic liver disease (MASLD), described as the most prominent cause of chronic liver disease worldwide, has emerged as a significant public health issue, posing a considerable challenge for most countries. Endocrine-disrupting chemicals (EDCs), commonly found in daily use items and foods, are able to interfere with nuclear receptors (NRs) and disturb hormonal signaling and mitochondrial function, leading, among other metabolic disorders, to MASLD. EDCs have also been proposed to cause transgenerationally inherited alterations leading to increased disease susceptibility. In this review, we are focusing on the most prominent linking pathways between EDCs and MASLD, their role in the induction of epigenetic transgenerational inheritance of the disease as well as up-to-date practices aimed at reducing their impact.

From morphology to methylome: epigenetic studies of Müllerian mesonephric-like adenocarcinoma reveal similarities to cervical mesonephric adenocarcinoma†.

Mesonephric adenocarcinomas (MAs) and mesonephric-like adenocarcinomas (MLAs) are rare, aggressive neoplasms that arise in the gynecologic tract and show overlapping morphologic, immunohistochemical, and molecular features. While MAs occur in the cervix and are thought to arise from mesonephric remnants, MLAs occur in the endometrium and ovary and are believed to originate from transdifferentiation of Müllerian lesions. Both MAs and MLAs show a variety of architectural patterns, exhibit frequent expression of GATA3 by immunohistochemistry, and harbor KRAS mutations. In a recent article published in The Journal of Pathology, Kommoss and colleagues used DNA methylation profiling to extend these similarities and showed that MLAs and MAs cluster together based on their epigenetic signatures and are epigenetically distinct from other Müllerian adenocarcinomas. They also showed that MLAs and MAs harbor a high number of global copy number alterations. This study provides evidence that MLAs more closely resemble MAs than Müllerian carcinomas on an epigenetic level. As a result, the authors argue that MLA should be renamed 'mesonephric-type adenocarcinoma.' Further research is needed to establish the relationship between these two entities, their etiology, and pathogenesis. © 2024 The Pathological Society of Great Britain and Ireland.