A novel workflow for the qualitative analysis of DNA methylation data.

DNA methylation is an epigenetic modification that plays a pivotal role in major biological mechanisms, such as gene regulation, genomic imprinting, and genome stability. Different combinations of methylated cytosines for a given DNA locus generate different epialleles and alterations of these latter have been associated with several pathological conditions. Existing computational methods and statistical tests relevant to DNA methylation analysis are mostly based on the comparison of average CpG sites methylation levels and they often neglect non-CG methylation. Here, we present EpiStatProfiler, an R package that allows the analysis of CpG and non-CpG based epialleles starting from bisulfite sequencing data through a collection of dedicated extraction functions and statistical tests. EpiStatProfiler is provided with a set of useful auxiliary features, such as customizable genomic ranges, strand-specific epialleles analysis, locus annotation and gene set enrichment analysis. We showcase the package functionalities on two public datasets by identifying putative relevant loci in mice harboring the Huntington's disease-causing Htt gene mutation and in Ctcf +/- mice compared to their wild-type counterparts. To our knowledge, EpiStatProfiler is the first package providing functionalities dedicated to the analysis of epialleles composition derived from any kind of bisulfite sequencing experiment.

Relationship between COVID-19 Mortality, Hospital Beds, and Primary Care by Italian Regions: A Lesson for the Future.

One of the characteristics of the SARS-CoV-2 infection in Italy is the significant regional difference in terms of lethality and mortality. These geographical variances were clear in the first wave and confirmed in the second one as well. The study aimed to analyze the correlation between regional differences in COVID-19 mortality and different regional care models, by retrospectively analyzing the association between the Italian COVID-19 deaths and the number of hospital beds, long-term care facilities, general practitioners (GPs), and the health expenditure per capita. The period considered was from 1 March 2020 to 1 March 2021. The number of hospital beds (p < 0.0001) and the number of GPs (p = 0.0094) significantly predicted the COVID-19 death rate. The Italian regions with a higher number of hospital beds and a lower number of GPs showed a higher number of deaths. Multivariate analyses confirmed the results. The Italian regions with a higher amount of centralized healthcare, as represented by the number of hospital beds, experienced a higher number of deaths, while the regions with greater community support, as exemplified by the number of the GPs, faced higher survival. These results suggest the need for a change in the current healthcare system organization.

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.

MC profiling: a novel approach to analyze DNA methylation heterogeneity in genome-wide bisulfite sequencing data.

DNA methylation is an epigenetic mark implicated in crucial biological processes. Most of the knowledge about DNA methylation is based on bulk experiments, in which DNA methylation of genomic regions is reported as average methylation. However, average methylation does not inform on how methylated cytosines are distributed in each single DNA molecule. Here, we propose Methylation Class (MC) profiling as a genome-wide approach to the study of DNA methylation heterogeneity from bulk bisulfite sequencing experiments. The proposed approach is built on the concept of MCs, groups of DNA molecules sharing the same number of methylated cytosines. The relative abundances of MCs from sequencing reads incorporates the information on the average methylation, and directly informs on the methylation level of each molecule. By applying our approach to publicly available bisulfite-sequencing datasets, we individuated cell-to-cell differences as the prevalent contributor to methylation heterogeneity. Moreover, we individuated signatures of loci undergoing imprinting and X-inactivation, and highlighted differences between the two processes. When applying MC profiling to compare different conditions, we identified methylation changes occurring in regions with almost constant average methylation. Altogether, our results indicate that MC profiling can provide useful insights on the epigenetic status and its evolution at multiple genomic regions.

DNA Methylation Profiles of Tph1A and BDNF in Gut and Brain of L. Rhamnosus-Treated Zebrafish.

The bidirectional microbiota-gut-brain axis has raised increasing interest over the past years in the context of health and disease, but there is a lack of information on molecular mechanisms underlying this connection. We hypothesized that change in microbiota composition may affect brain epigenetics leading to long-lasting effects on specific brain gene regulation. To test this hypothesis, we used Zebrafish (Danio Rerio) as a model system. As previously shown, treatment with high doses of probiotics can modulate behavior in Zebrafish, causing significant changes in the expression of some brain-relevant genes, such as BDNF and Tph1A. Using an ultra-deep targeted analysis, we investigated the methylation state of the BDNF and Tph1A promoter region in the brain and gut of probiotic-treated and untreated Zebrafishes. Thanks to the high resolution power of our analysis, we evaluated cell-to-cell methylation differences. At this resolution level, we found slight DNA methylation changes in probiotic-treated samples, likely related to a subgroup of brain and gut cells, and that specific DNA methylation signatures significantly correlated with specific behavioral scores.

Artificial Intelligence for Epigenetics: Towards Personalized Medicine.

Epigenetics is a field of biological sciences focused on the study of reversible, heritable changes in gene function, not due to modifications of the genomic sequence. These changes are the result of a complex cross-talk between several molecular mechanisms that is in turn orchestrated by genetic and environmental factors. The epigenetic profile captures the unique regulatory landscape and the exposure to environmental stimuli of an individual. It thus constitutes a valuable reservoir of information for personalized medicine, which is aimed at customizing health-care interventions based on the unique characteristics of each individual. Nowadays, the complex milieu of epigenomic marks can be studied at the genome-wide level thanks to massive, high-throughput technologies. This new experimental approach is opening up new and interesting knowledge perspectives. However, the analysis of these complex omic data requires to face important analytic issues. Artificial Intelligence, and in particular Machine Learning, are emerging as powerful resources to decipher epigenomic data. In this review, we will first describe the most used ML approaches in epigenomics. We then will recapitulate some of the recent applications of ML to epigenomic analysis. Finally, we will provide some examples of how the ML approach to epigenetic data can be useful for personalized medicine.

Modeling DNA Methylation Profiles through a Dynamic Equilibrium between Methylation and Demethylation.

DNA methylation is a heritable epigenetic mark that plays a key role in regulating gene expression. Mathematical modeling has been extensively applied to unravel the regulatory mechanisms of this process. In this study, we aimed to investigate DNA methylation by performing a high-depth analysis of particular loci, and by subsequent modeling of the experimental results. In particular, we performed an in-deep DNA methylation profiling of two genomic loci surrounding the transcription start site of the D-Aspartate Oxidase and the D-Serine Oxidase genes in different samples (n = 51). We found evidence of cell-to-cell differences in DNA methylation status. However, these cell differences were maintained between different individuals, which indeed showed very similar DNA methylation profiles. Therefore, we hypothesized that the observed pattern of DNA methylation was the result of a dynamic balance between DNA methylation and demethylation, and that this balance was identical between individuals. We hence developed a simple mathematical model to test this hypothesis. Our model reliably captured the characteristics of the experimental data, suggesting that DNA methylation and demethylation work together in determining the methylation state of a locus. Furthermore, our model suggested that the methylation status of neighboring cytosines plays an important role in this balance.

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.

Prevalence of GLA gene mutations and polymorphisms in patients with multiple sclerosis: A cross-sectional study.

PURPOSE: Fabry Disease (FD) has been frequently proposed as possible underestimated differential diagnosis of Multiple Sclerosis (MS), but no study has been performed to test prevalence of GLA gene mutations in a population fulfilling diagnostic criteria of MS. Aim of this study is to determine the prevalence of GLA gene mutations in a large and representative population diagnosed with MS, simultaneously providing a critical revision of current literature reports of coexistence or misdiagnosis between these two conditions. METHODS: In this mono-centric cross-sectional study, 927 patients fulfilling McDonald diagnostic criteria and encompassing all MS phenotypes were enrolled. Patients underwent evaluation of α-GalA activity and genotyping. Both genetic variants annotated as pathogenic and GVUS were considered. Estimated alleles frequencies were then compared to the ones reported in the gnomAD database. RESULTS: GLA gene variants were found in seven individuals. Five patients carried variants previously described having controversial impact on FD phenotype, and the analysis of exome database revealed that they are not rare among healthy individuals. One patient showed a new variant never described before, and another one carried a late-onset FD cardiac variant. CONCLUSIONS: The overall prevalence of GLA gene variants in MS patients is comparable to the one estimated in healthy population. This result is further supported by critical revision of current literature evidences of misdiagnosis between MS and FD, arguing in favour of independence between these disorders.

Participation to Leisure Activities and Well-Being in a Group of Residents of Naples-Italy: The Role of Resilience.

We explored the relationship between cultural and social participation, physical activity, and well-being in a group of residents of the metropolitan area of Naples, Italy and the role that resilience plays in this relationship. Naples offers a remarkable urban environment with the potentially beneficial psychological effects of outstanding natural beauty, and one of the world's most impressive repositories of tangible and intangible cultural heritage. However, Naples was also, and still is, heavily affected by the 2008 economic crisis, in addition to preexisting social and economic issues. The major finding of this study is that, despite this highly contrasting urban environment, the combination of physical activity and engagement in social and cultural activities has a positive effect on subjective (self-reported) psychological well-being (SPWB) in a group of residents, and that resilience mediates this relationship.

The genomic landscape of 8-oxodG reveals enrichment at specific inherently fragile promoters.

8-Oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) is the most common marker of oxidative stress and its accumulation within the genome has been associated with major human health issues such as cancer, aging, cardiovascular and neurodegenerative diseases. The characterization of the different genomic sites where 8-oxodG accumulates and the mechanisms underlying its formation are still poorly understood. Using OxiDIP-seq, we recently derived the genome-wide distribution of 8-oxodG in human non-tumorigenic epithelial breast cells (MCF10A). Here, we identify a subset of human promoters that accumulate 8-oxodG under steady-state condition. 8-oxodG nucleotides co-localize with double strand breaks (DSBs) at bidirectional and CG skewed promoters and their density correlate with RNA Polymerase II co-occupancy and transcription. Furthermore, by performing OxiDIP-seq in quiescent (G0) cells, we found a strong reduction of oxidatively-generated damage in the majority of 8-oxodG-positive promoters in the absence of DNA replication. Overall, our results suggest that the accumulation of 8-oxodG at gene promoters occurs through DNA replication-dependent or -independent mechanisms, with a possible contribution to the formation of cancer-associated translocation events.

DNA sequence context as a marker of CpG methylation instability in normal and cancer tissues.

DNA methylation alterations are related to multiple molecular mechanisms. The DNA context of CpG sites plays a crucial role in the maintenance and stability of methylation patterns. The quantitative relationship between DNA composition and DNA methylation has been studied in normal as well as pathological conditions, showing that DNA methylation status is highly dependent on the local sequence context. In this work, we describe this relationship by analyzing the DNA sequence context associated to methylation profiles in both physiological and pathological conditions. In particular, we used DNA motifs to describe methylation stability patterns in normal tissues and aberrant methylation events in cancer lesions. In this manuscript, we show how different groups of DNA sequences can be related to specific epigenetic events, across normal and cancer tissues, and provide a thorough structural and functional characterization of these sequences.

Nucleotide distance influences co-methylation between nearby CpG sites.

The tendency of individual CpG sites to be methylated is distinctive, non-random and well-regulated throughout the genome. We investigated the structural and spatial factors influencing CpGs methylation by performing an ultra-deep targeted methylation analysis on human, mouse and zebrafish genes. We found that methylation is not a random process and that closer neighboring CpG sites are more likely to share the same methylation status. Moreover, if the distance between CpGs increases, the degree of co-methylation decreases. We set up a simulation model to analyze the contribution of both the intrinsic susceptibility and the distance effect on the probability of a CpG to be methylated. Our finding suggests that the establishment of a specific methylation pattern follows a universal rule that must take into account of the synergistic and dynamic interplay of these two main factors: the intrinsic methylation susceptibility of specific CpG and the nucleotide distance between two CpG sites.

Selective demethylation of two CpG sites causes postnatal activation of the Dao gene and consequent removal of D-serine within the mouse cerebellum.

BACKGROUND: Programmed epigenetic modifications occurring at early postnatal brain developmental stages may have a long-lasting impact on brain function and complex behavior throughout life. Notably, it is now emerging that several genes that undergo perinatal changes in DNA methylation are associated with neuropsychiatric disorders. In this context, we envisaged that epigenetic modifications during the perinatal period may potentially drive essential changes in the genes regulating brain levels of critical neuromodulators such as D-serine and D-aspartate. Dysfunction of this fine regulation may contribute to the genesis of schizophrenia or other mental disorders, in which altered levels of D-amino acids are found. We recently demonstrated that Ddo, the D-aspartate degradation gene, is actively demethylated to ultimately reduce D-aspartate levels. However, the role of epigenetics as a mechanism driving the regulation of appropriate D-ser levels during brain development has been poorly investigated to date. METHODS: We performed comprehensive ultradeep DNA methylation and hydroxymethylation profiling along with mRNA expression and HPLC-based D-amino acids level analyses of genes controlling the mammalian brain levels of D-serine and D-aspartate. DNA methylation changes occurring in specific cerebellar cell types were also investigated. We conducted high coverage targeted bisulfite sequencing by next-generation sequencing and single-molecule bioinformatic analysis. RESULTS: We report consistent spatiotemporal modifications occurring at the Dao gene during neonatal development in a specific brain region (the cerebellum) and within specific cell types (astrocytes) for the first time. Dynamic demethylation at two specific CpG sites located just downstream of the transcription start site was sufficient to strongly activate the Dao gene, ultimately promoting the complete physiological degradation of cerebellar D-serine a few days after mouse birth. High amount of 5'-hydroxymethylcytosine, exclusively detected at relevant CpG sites, strongly evoked the occurrence of an active demethylation process. CONCLUSION: The present investigation demonstrates that robust and selective demethylation of two CpG sites is associated with postnatal activation of the Dao gene and consequent removal of D-serine within the mouse cerebellum. A single-molecule methylation approach applied at the Dao locus promises to identify different cell-type compositions and functions in different brain areas and developmental stages.

Whole transcriptome targeted gene quantification provides new insights on pulmonary sarcomatoid carcinomas.

Pulmonary sarcomatoid carcinomas (PSC) are a rare group of lung cancer with a median overall survival of 9-12 months. PSC are divided into five histotypes, challenging to diagnose and treat. The identification of PSC biomarkers is warranted, but PSC molecular profile remains to be defined. Herein, a targeted whole transcriptome analysis was performed on 14 PSC samples, evaluated also for the presence of the main oncogene mutations and rearrangements. PSC expression data were compared with transcriptome data of lung adenocarcinomas (LUAD) and squamous cell carcinomas (LUSC) from The Cancer Genome Atlas. Deregulated genes were used for pathway enrichment analysis; the most representative genes were tested by immunohistochemistry (IHC) in an independent cohort (30 PSC, 31 LUAD, 31 LUSC). All PSC cases were investigated for PD-L1 expression. Thirty-eight genes deregulated in PSC were identified, among these IGJ and SLMAP were confirmed by IHC. Moreover, Forkhead box signaling and Fanconi anemia pathways were specifically enriched in PSC. Finally, some PSC harboured alterations in genes targetable by tyrosine kinase inhibitors, as EGFR and MET. We provide a deep molecular characterization of PSC; the identification of specific molecular profiles, besides increasing our knowledge on PSC biology, might suggest new strategies to improve patients management.

Association between DNA methylation profile and malignancy in follicular-patterned thyroid neoplasms.

Molecular differentiation between benign (follicular thyroid adenoma, FTA) and malignant (follicular thyroid carcinoma, FTC) thyroid neoplasms is challenging. Here, we explored the genome-wide DNA methylation profile of FTA (n.10) and FTC (n.11) compared to normal thyroid (NT) (n.7) tissues. FTC featured 3,564 differentially-methylated CpGs (DMCpG), most (84%) of them hypermethylated, with respect to normal controls. At the principal component analysis (PCA), the methylation profile of FTA occupied an intermediate position between FTC and normal tissue. A large fraction (n. 2,385) of FTC-associated DMCpG were related (intragenic or within 1500 bp from the transcription start site) to annotated genes (n. 1,786). FTC-hypermethylated genes were enriched for targets of the Polycomb transcriptional repressor complex and the specific histone H3 marks (H3K4me2/me3-H3K27me3) found in chromatin domains known as "bivalent". Transcriptome profiling by RNAseq showed that 7.9% of the DMCpGs-associated genes were differentially expressed in FTC compared to NT, suggesting that altered DNA methylation may contribute to their altered expression. Overall, this study suggests that perturbed DNA methylation, in particular hypermethylation, is a component of the molecular mechanisms leading to the formation of FTC and that DNA methylation profiling may help differentiating FTCs from their benign counterpart.

Genome-wide mapping of 8-oxo-7,8-dihydro-2'-deoxyguanosine reveals accumulation of oxidatively-generated damage at DNA replication origins within transcribed long genes of mammalian cells.

8-Oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG) is one of the major DNA modifications and a potent pre-mutagenic lesion prone to mispair with 2'-deoxyadenosine (dA). Several thousand residues of 8-oxodG are constitutively generated in the genome of mammalian cells, but their genomic distribution has not yet been fully characterized. Here, by using OxiDIP-Seq, a highly sensitive methodology that uses immuno-precipitation with efficient anti-8-oxodG antibodies combined with high-throughput sequencing, we report the genome-wide distribution of 8-oxodG in human non-tumorigenic epithelial breast cells (MCF10A), and mouse embryonic fibroblasts (MEFs). OxiDIP-Seq revealed sites of 8-oxodG accumulation overlapping with γH2AX ChIP-Seq signals within the gene body of transcribed long genes, particularly at the DNA replication origins contained therein. We propose that the presence of persistent single-stranded DNA, as a consequence of transcription-replication clashes at these sites, determines local vulnerability to DNA oxidation and/or its slow repair. This oxidatively-generated damage, likely in combination with other kinds of lesion, might contribute to the formation of DNA double strand breaks and activation of DNA damage response.

DNA methylation landscape of the genes regulating D-serine and D-aspartate metabolism in post-mortem brain from controls and subjects with schizophrenia.

The spatio-temporal regulation of genes involved in the synthesis and degradation of D-serine and D-aspartate such as serine racemase (SR), D-amino acid oxidase (DAO), G72 and D-aspartate oxidase (DDO), play pivotal roles in determining the correct levels of these D-amino acids in the human brain. Here we provide a comprehensive analysis of mRNA expression and DNA methylation status of these genes in post-mortem samples from hippocampus, dorsolateral prefrontal cortex, and cerebellum from patients with schizophrenia and non-psychiatric controls. DNA methylation analysis was performed at an ultradeep level, measuring individual epialleles frequency by single molecule approach. Differential CpG methylation and expression was detected across different brain regions, although no significant correlations were found with diagnosis. G72 showed the highest CpG and non-CpG methylation degree, which may explain the repression of G72 transcription in the brain regions considered here. Conversely, in line with the sustained SR mRNA expression in the analyzed areas, very low methylation levels were detected at this gene's regulatory regions. Furthermore, for DAO and DDO, our single-molecule methylation approach demonstrated that analysis of epiallele distribution was able to detect differences in DNA methylation representing area-specific methylation signatures, which are likely not detectable with targeted or genome-wide classic methylation analyses.

DNA Methylation variability among individuals is related to CpGs cluster density and evolutionary signatures.

BACKGROUND: In recent years, epigenetics has gained a central role in the understanding of the process of natural selection. It is now clear how environmental impacts on the methylome could promote methylation variability with direct effects on disease etiology as well as phenotypic and genotypic variations in evolutionary processes. To identify possible factors influencing inter-individual methylation variability, we studied methylation values standard deviation of 166 healthy individuals searching for possible associations with genomic features and evolutionary signatures. RESULTS: We analyzed methylation variability values in relation to CpG cluster density and we found a strong association between them (p-value < 2.2 × 10- 16). Furthermore, we found that genes related to CpGs with high methylation variability values were enriched for immunological pathways; instead, those associated with low ones were enriched for pathways related to basic cellular functions. Finally, we found an association between methylation variability values and signals of both ancient (p-value < 2.2 × 10- 16) and recent selective pressure (p-value < 1 × 10- 4). CONCLUSION: Our results indicate the presence of an intricate interplay between genetics, epigenetic code and evolutionary constraints in humans.

Sex-related alterations of gut microbiota composition in the BTBR mouse model of autism spectrum disorder.

Alterations of microbiota-gut-brain axis have been invoked in the pathogenesis of autism spectrum disorders (ASD). Mouse models could represent an excellent tool to understand how gut dysbiosis and related alterations may contribute to autistic phenotype. In this study we paralleled gut microbiota (GM) profiles, behavioral characteristics, intestinal integrity and immunological features of colon tissues in BTBR T + tf/J (BTBR) inbred mice, a well established animal model of ASD. Sex differences, up to date poorly investigated in animal models, were specifically addressed. Results showed that BTBR mice of both sexes presented a marked intestinal dysbiosis, alterations of behavior, gut permeability and immunological state with respect to prosocial C57BL/6j (C57) strain. Noticeably, sex-related differences were clearly detected. We identified Bacteroides, Parabacteroides, Sutterella, Dehalobacterium and Oscillospira genera as key drivers of sex-specific gut microbiota profiles associated with selected pathological traits. Taken together, our findings indicate that alteration of GM in BTBR mice shows relevant sex-associated differences and supports the use of BTBR mouse model to dissect autism associated microbiota-gut-brain axis alteration.