Host fecal DNA specific methylation signatures mark gut dysbiosis and inflammation in children affected by autism spectrum disorder.

The gut-brain axis involves several bidirectional pathway communications including microbiome, bacterial metabolites, neurotransmitters as well as immune system and is perturbed both in brain and in gastrointestinal disorders. Consistently, microbiota-gut-brain axis has been found altered in autism spectrum disorder (ASD). We reasoned that such alterations occurring in ASD may impact both on methylation signatures of human host fecal DNA (HFD) and possibly on the types of human cells shed in the stools from intestinal tract giving origin to HFD. To test this hypothesis, we have performed whole genome methylation analysis of HFD from an age-restricted cohort of young children with ASD (N = 8) and healthy controls (N = 7). In the same cohort we have previously investigated the fecal microbiota composition and here we refined such analysis and searched for eventual associations with data derived from HFD methylome analysis. Our results showed that specific epigenetic signatures in human fecal DNA, especially at genes related to inflammation, associated with the disease. By applying methylation-based deconvolution algorithm, we found that the HFD derived mainly from immune cells and the relative abundance of those differed between patients and controls. Consistently, most of differentially methylated regions fitted with genes involved in inflammatory response. Interestingly, using Horvath epigenetic clock, we found that ASD affected children showed both epigenetic and microbiota age accelerated. We believe that the present unprecedented approach may be useful for the identification of the ASD associated HFD epigenetic signatures and may be potentially extended to other brain disorders and intestinal inflammatory diseases.

Targeted inhibition of the methyltransferase SETD8 synergizes with the Wee1 inhibitor adavosertib in restraining glioblastoma growth.

Despite intense research efforts, glioblastoma remains an incurable brain tumor with a dismal median survival time of 15 months. Thus, identifying new therapeutic targets is an urgent need. Here, we show that the lysine methyltransferase SETD8 is overexpressed in 50% of high-grade gliomas. The small molecule SETD8 inhibitor UNC0379, as well as siRNA-mediated inhibition of SETD8, blocked glioblastoma cell proliferation, by inducing DNA damage and activating cell cycle checkpoints. Specifically, in p53-proficient glioblastoma cells, SETD8 inhibition and DNA damage induced p21 accumulation and G1/S arrest whereas, in p53-deficient glioblastoma cells, DNA damage induced by SETD8 inhibition resulted in G2/M arrest mediated by Chk1 activation. Checkpoint abrogation, by the Wee1 kinase inhibitor adavosertib, induced glioblastoma cell lines and primary cells, DNA-damaged by UNC0379, to progress to mitosis where they died by mitotic catastrophe. Finally, UNC0379 and adavosertib synergized in restraining glioblastoma growth in a murine xenograft model, providing a strong rationale to further explore this novel pharmacological approach for adjuvant glioblastoma treatment.

A Rare Adult Primary Intracranial Sarcoma, DICER1-Mutant Identified by Epigenomic Profiling: A Case Report.

Diagnoses of primary malignant mesenchymal brain tumors are a challenge for pathologists. Here, we report the case of a 52-year-old man with a primary brain tumor, histologically diagnosed as a high-grade glioma, not otherwise specified (NOS). The patient underwent two neurosurgeries in several months, followed by radiotherapy and chemotherapy. We re-examined the tumor samples by methylome profiling. Methylome analysis revealed an epi-signature typical of a primary intracranial sarcoma, DICER1-mutant, an extremely rare tumor. The diagnosis was confirmed by DNA sequencing that revealed a mutation in DICER1 exon 25. DICER1 mutations were not found in the patient's blood cells, thus excluding an inherited DICER1 syndrome. The methylome profile of the DICER1 mutant sarcoma was then compared with that of a high-grade glioma, a morphologically similar tumor type. We found that several relevant regions were differentially methylated. Taken together, we report the morphological, epigenetic, and genetic characterization of the sixth described case of an adult primary intracranial sarcoma, DICER1-mutant to-date. Furthermore, this case report underscores the importance of methylome analysis to refine primary brain tumor diagnosis and to avoid misdiagnosis among morphologically similar subtypes.

Deep learning to detect significant coronary artery disease from plain chest radiographs AI4CAD.

BACKGROUND: The predictive role of chest radiographs in patients with suspected coronary artery disease (CAD) is underestimated and may benefit from artificial intelligence (AI) applications. OBJECTIVES: To train, test, and validate a deep learning (DL) solution for detecting significant CAD based on chest radiographs. METHODS: Data of patients referred for angina and undergoing chest radiography and coronary angiography were analysed retrospectively. A deep convolutional neural network (DCNN) was designed to detect significant CAD from posteroanterior/anteroposterior chest radiographs. The DCNN was trained for severe CAD binary classification (absence/presence). Coronary angiography reports were the ground truth. Stenosis severity of ≥70% for non-left main vessels and ≥ 50% for left main defined severe CAD. RESULTS: Information of 7728 patients was reviewed. Severe CAD was present in 4091 (53%). Patients were randomly divided for algorithm training (70%; n = 5454) and fine-tuning/model validation (10%; n = 773). Internal clinical validation (model testing) was performed with the remaining patients (20%; n = 1501). At binary logistic regression, DCNN prediction was the strongest severe CAD predictor (p < 0.0001; OR: 1.040; CI: 1.032-1.048). Using a high sensitivity operating cut-point, the DCNN had a sensitivity of 0.90 to detect significant CAD (specificity 0.31; AUC 0.73; 95% CI DeLong, 0.69-0.76). Adding to the AI chest radiograph interpretation angina status improved the prediction (AUC 0.77; 95% CI DeLong, 0.74-0.80). CONCLUSION: AI-read chest radiographs could be used to pre-test significant CAD probability in patients referred for suspected angina. Further studies are required to externally validate our algorithm, develop a clinically applicable tool, and support CAD screening in broader settings.

Epigenetic alterations in glioblastomas: Diagnostic, prognostic and therapeutic relevance.

Glioblastoma, the most common and heterogeneous tumor affecting brain parenchyma, is dismally characterized by a very poor prognosis. Thus, the search of new, more effective treatments is a vital need. Here, we will review the druggable epigenetic features of glioblastomas that are, indeed, currently explored in preclinical studies and in clinical trials for the development of more effective, personalized treatments. In detail, we will review the studies that have led to the identification of epigenetic signatures, IDH mutations, MGMT gene methylation, histone modification alterations, H3K27 mutations and epitranscriptome landscapes of glioblastomas, in each case discussing the corresponding targeted therapies and their potential efficacy. Finally, we will emphasize how recent technological improvements permit to routinely investigate many glioblastoma epigenetic biomarkers in clinical practice, further enforcing the hope that personalized drugs, targeting specific epigenetic features, could be in future a therapeutic option for selected patients.

Methylome Profiling in Fabry Disease in Clinical Practice: A Proof of Concept.

Anderson−Fabry disease (FD) is an X-linked disease caused by a functional deficit of the α-galactosidase A enzyme. FD diagnosis relies on the clinical manifestations and research of GLA gene mutations. However, because of the lack of a clear genotype/phenotype correlation, FD diagnosis can be challenging. Recently, several studies have highlighted the importance of investigating DNA methylation patterns for confirming the correct diagnosis of different rare Mendelian diseases, but to date, no such studies have been reported for FD. Thus, in the present investigation, we analyzed for the first time the genome-wide methylation profile of a well-characterized cohort of patients with Fabry disease. We profiled the methylation status of about 850,000 CpG sites in 5 FD patients, all carrying the same mutation in the GLA gene (exon 6 c.901C>G) and presenting comparable low levels of α-Gal A activity. We found that, although the whole methylome profile did not discriminate the FD group from the unaffected one, several genes were significantly differentially methylated in Fabry patients. Thus, we provide here a proof of concept, to be tested in patients with different mutations and in a larger cohort, that the methylation state of specific genes can potentially identify Fabry patients and possibly predict organ involvement and disease evolution.

MGMT and Whole-Genome DNA Methylation Impacts on Diagnosis, Prognosis and Therapy of Glioblastoma Multiforme.

Epigenetic changes in DNA methylation contribute to the development of many diseases, including cancer. In glioblastoma multiforme, the most prevalent primary brain cancer and an incurable tumor with a median survival time of 15 months, a single epigenetic modification, the methylation of the O6-Methylguanine-DNA Methyltransferase (MGMT) gene, is a valid biomarker for predicting response to therapy with alkylating agents and also, independently, prognosis. More recently, the progress from single gene to whole-genome analysis of DNA methylation has allowed a better subclassification of glioblastomas. Here, we review the clinically relevant information that can be obtained by studying MGMT gene and whole-genome DNA methylation changes in glioblastomas, also highlighting benefits, including those of liquid biopsy, and pitfalls of the different detection methods. Finally, we discuss how changes in DNA methylation, especially in glioblastomas bearing mutations in the Isocitrate Dehydrogenase (IDH) 1 and 2 genes, can be exploited as targets for tailoring therapy.

Looking Beyond the Glioblastoma Mask: Is Genomics the Right Path?

Glioblastomas are the most frequent and malignant brain tumor hallmarked by an invariably poor prognosis. They have been classically differentiated into primary isocitrate dehydrogenase 1 or 2 (IDH1 -2) wild-type (wt) glioblastoma (GBM) and secondary IDH mutant GBM, with IDH wt GBMs being commonly associated with older age and poor prognosis. Recently, genetic analyses have been integrated with epigenetic investigations, strongly implementing typing and subtyping of brain tumors, including GBMs, and leading to the new WHO 2021 classification. GBM genomic and epigenomic profile influences evolution, resistance, and therapeutic responses. However, differently from other tumors, there is a wide gap between the refined GBM profiling and the limited therapeutic opportunities. In addition, the different oncogenes and tumor suppressor genes involved in glial cell transformation, the heterogeneous nature of cancer, and the restricted access of drugs due to the blood-brain barrier have limited clinical advancements. This review will summarize the more relevant genetic alterations found in GBMs and highlight their potential role as potential therapeutic targets.

Epigenetic remodelling of Fxyd1 promoters in developing heart and brain tissues.

FXYD1 is a key protein controlling ion channel transport. FXYD1 exerts its function by regulating Na+/K+-ATPase activity, mainly in brain and cardiac tissues. Alterations of the expression level of the FXYD1 protein cause diastolic dysfunction and arrhythmias in heart and decreased neuronal dendritic tree and spine formation in brain. Moreover, FXYD1, a target of MeCP2, plays a crucial role in the pathogenesis of the Rett syndrome, a neurodevelopmental disorder. Thus, the amount of FXYD1 must be strictly controlled in a tissue specific manner and, likely, during development. Epigenetic modifications, particularly DNA methylation, represent the major candidate mechanism that may regulate Fxyd1 expression. In the present study, we performed a comprehensive DNA methylation analysis and mRNA expression level measurement of the two Fxyd1 transcripts, Fxyd1a and Fxyd1b, in brain and heart tissues during mouse development. We found that DNA methylation at Fxyd1a increased during brain development and decreased during heart development along with coherent changes in mRNA expression levels. We also applied ultra-deep methylation analysis to detect cell to cell methylation differences and to identify possible distinct methylation profile (epialleles) distribution between heart and brain and in different developmental stages. Our data indicate that the expression of Fxyd1 transcript isoforms inversely correlates with DNA methylation in developing brain and cardiac tissues suggesting the existence of a temporal-specific epigenetic program. Moreover, we identified a clear remodeling of epiallele profiles which were distinctive for single developmental stage both in brain and heart tissues.

Evaluation of MGMT Gene Methylation in Neuroendocrine Neoplasms.

Unresectable neuroendocrine neoplasms (NENs) often poorly respond to standard therapeutic approaches. Alkylating agents, in particular temozolomide, commonly used to treat high-grade brain tumors including glioblastomas, have recently been tested in advanced or metastatic NENs, where they showed promising response rates. In glioblastomas, prediction of response to temozolomide is based on the assessment of the methylation status of the MGMT gene, as its product, O 6-methylguanine-DNA methyltransferase, may counteract the damaging effects of the alkylating agent. However, in NENs, such a biomarker has not been validated yet. Thus, we have investigated MGMT methylation in 42 NENs of different grades and from various sites of origin by two different approaches: in contrast to methylation-specific PCR (MSP), which is commonly used in glioblastoma management, amplicon bisulfite sequencing (ABS) is based on high-resolution, next-generation sequencing and interrogates several additional CpG sites compared to those covered by MSP. Overall, we found MGMT methylation in 74% (31/42) of the NENs investigated. A higher methylation degree was observed in well-differentiated tumors and in tumors originating in the gastrointestinal tract. Comparing MSP and ABS results, we demonstrate that the region analyzed by the MSP test is sufficiently informative of the MGMT methylation status in NENs, suggesting that this predictive parameter could routinely be interrogated also in NENs.

Ultra-Deep DNA Methylation Analysis of X-Linked Genes: GLA and AR as Model Genes.

Recessive X-linked disorders may occasionally evolve in clinical manifestations of variable severity also in female carriers. For some of such diseases, the frequency of the symptoms' appearance during women's life may be particularly relevant. This phenomenon has been largely attributed to the potential skewness of the X-inactivation process leading to variable phenotypes. Nonetheless, in many cases, no correlation with X-inactivation unbalance was demonstrated. However, methods for analyzing skewness have been mainly limited to Human Androgen Receptor methylation analysis (HUMARA). Recently, the X-inactivation process has been largely revisited, highlighting the heterogeneity existing among loci in the epigenetic state within inactive and, possibly, active X-chromosomes. We reasoned that gene-specific and ultra-deep DNA methylation analyses could greatly help to unravel details of the X-inactivation process and the roles of specific X genes inactivation in disease manifestations. We recently provided evidence that studying DNA methylation at specific autosomic loci at a single-molecule resolution (epiallele distribution analysis) allows one to analyze cell-to-cell methylation differences in a given cell population. We here apply the epiallele analysis at two X-linked loci to investigate whether females show allele-specific epiallelic patterns. Due to the high potential of this approach, the method allows us to obtain clearly distinct allele-specific epiallele profiles.

Combined assessment of thrombotic and haemorrhagic risk in acute medical patients.

Acute medical patients have a high risk of venous thromboembolic events (VTE). Unfortunately, the fear of bleeding complications limits the use of antithrombotic prophylaxis in this setting. To stratify the VTE and haemorrhagic risk, two clinical scores (PADUA, IMPROVE) have recently been developed. However, it is not clear how many patients have a concomitant high VTE and haemorrhagic risk and what is the use of prophylaxis in this situation. To clarify these issues we performed a prospective cohort study enrolling consecutive patients admitted to internal medicine. Patients admitted to internal medicine (January to December 2013) were included. VTE and haemorrhagic risk were evaluated in all the included patients. Use and type of anti-thrombotic prophylaxis was recorded. A total of 1761 patients (mean age 77.6 years) were enrolled; 76.8% (95% CI 74.7-78.7) were at high VTE risk and 11.9% (95% CI 10.4-13.5) were at high haemorrhagic risk. Anti-thrombotic prophylaxis was used in 80.5% of patients at high VTE risk and in 6.5% at low VTE risk (p<0.001), and in 16.6% at high haemorrhagic risk and in 72.5% at low haemorrhagic risk (p<0.001). Prophylaxis was used in 20.4% at both high VTE and haemorrhagic risk and in 88.9% at high VTE risk but low haemorrhagic risk. At multivariate-analysis, use of prophylaxis appeared highly influenced by the VTE risk (OR 68.2, 95% CI 43.1 - 108.0). In conclusion, many patients admitted to internal medicine were at high risk of VTE. Since almost 90% of them were at low haemorrhagic risk, pharmacological prophylaxis may be safely prescribed in most of these patients.