PSC) line and after its differentiation to the neural progenitor cell (NPC) stage. We find that nearly 3% of nucleosomes are highly positioned in NPC, but significantly, there are eightfold fewer positioned nucleosomes in pluripotent cells, indicating increased positioning during cell differentiation. Positioned nucleosomes do not strongly correlate with active chromatin marks or gene transcription. Unexpectedly, we find a small population of nucleosomes that occupy similar positions in pluripotent and neural progenitor cells and are found at binding sites of the key gene regulators NRSF/REST and CTCF. Remarkably, the presence of these nucleosomes appears to be independent of the associated regulatory complexes. Together, these results present a scenario in human cells, where positioned nucleosomes are sparse and dynamic, but may act to alter gene expression at a distance via the structural conformation at sites of chromatin regulation.Nucleosome positioning is important for neurodevelopment, and genes mediating chromatin remodelling are strongly associated with human neurodevelopmental disorders. To investigate changes in nucleosome positioning during neural differentiation, we generate genome‐wide nucleosome maps from an undifferentiated human‐induced pluripotent stem cell (hi Saccharomyces cerevisiaePlacement of nucleosomes has been implicated in gene regulation from position, the sequence coordinates where nucleosomes occur across the cell population; occupancy, the frequency that a nucleosome is present at an individual site; and accessibility, the degree to which the presence of nucleosomes restricts access to the DNA. In organisms with small genomes, such as in the yeasts and Dictyostelium, nearly 80% of nucleosomes are positioned in the same place in the genome across the cell population, forming arrays that span gene bodies Dictyostelium mutant lacking the CHD8 homologue, ChdC, alter gene expression. Nonetheless, even in these organisms the actual correlation between positioning and gene expression can be low; for example, only 15% of genes with altered nucleosome spacing in a chdC mutant show corresponding changes in gene expression Nucleosome interactions within chromatin are likely to be complex but can be described by the following quantitative parameters: In mammalian cells, including human cells, with large and complex genomes, non‐coding and intragenic DNA sequences can make up approximately 98% of the genome. In these larger and more complex genomes, the pattern of positioned nucleosomes appears to be radically different. Studies in human cells have shown that only a very small proportion of the total nucleosome number are strongly positioned Here, we focus on the relationship between gene expression and nucleosome positioning, rather than accessibility, in the context of human neural differentiation. Unlike the relationship of MACC to open chromatin and gene expression, the relationship of these positioned nucleosomes to gene expression is unclear. By comparing maps of well‐positioned nucleosomes with low MNase sensitivity for the same human iPSC line in the pluripotent state and following differentiation to neural progenitor cells (NPCs), we have directly examined the developmental dynamics of nucleosome positioning during early neural differentiation and its relationship to gene expression.in situ in permeabilised cells without cross‐linking 9 paired‐end reads per digest, and the positions of the fragment mid‐points were mapped to the genome. To monitor the initial digestions, the abundance of fragment sizes was plotted for both cell types  in the pluripotent cell state, indicating that a substantial increase in positioned nucleosomes occurs during differentiation from pluripotent cells to NPC. We recognise that it may be difficult to detect positioned nucleosomes that have high MNase sensitivity using our methodology. To investigate the impact of this possibility on the detected nucleosome number, we mapped the mid‐points of DNA fragments in the 112–137 bp sub‐nucleosome size range Fig B.de novo formation of positioned nucleosomes. Importantly, there is a small population of nucleosomes that retain their positions in both cell states, albeit corresponding to only approximately 0.1% of the total nucleosome population.Comparison of both pluripotent iPSC and NPC maps indicated that only 32% of the positioned nucleosomes present in the pluripotent state retain their position during differentiation to NPC Fig C. This iTo determine how human nucleosomes are distributed throughout the genome, the organisation of positioned nucleosomes was analysed in pluripotent iPSC and NPC states, and for the K562 cell line. A frequency distribution was plotted for all nucleosome positions and their surrounding window (± 300 bp) centred on the nucleosome peak Fig D. This sTo probe the relationship between nucleosome positions and gene activity further, we examined the distribution of positioned nucleosomes across different chromatin states. Using the 15‐state model of Ernst and Kellis Finally, we examined the relationship between nucleosome positioning and open and closed chromatin. Using the map coordinates for open chromatin regions (based on high ATAC‐seq accessibility) for pluripotent human embryonic stem cells (H9), The poor correlation between the presence of positioned nucleosomes and transcriptionally active chromatin states was unexpected given the known association of nucleosome positioning within active gene loci of non‐mammalian cells and the association of gene expression with SNF‐2 family chromatin remodelers We conducted a global analysis of chromatin patterns at the TSS of protein‐coding genes, using a non‐redundant list of 66,047 mapped human TSS. The frequency distribution of MNase‐protected fragments at and surrounding protein‐coding TSS showed a distinct MNase‐hypersensitive region at the TSS Fig C, a NFR,n = 83,179), we created datasets containing the locations of TSS of human genes that are transcribed only in pluripotent or NPCs. These datasets were then filtered for the presence or absence of a positioned nucleosome within ± 300 bp of the TSS. The results of this analysis show that for genes expressed only in pluripotent cells there were in fact more nucleosomes positioned at the TSS of genes inactive in the NPC state than for the same genes when they are actively expressed in pluripotent state  binding sites involved in neural differentiation, namely YY1, ATF2 and PAX6 RE1 sites were selected by mapping the consensus sequence of RE1 sites to NRSF/REST ChIP‐seq data To ensure that genome averaging did not mask any differences at these sites, we carried out cluster analysis Fig D to estaOur analysis of chromatin states indicated a strong enrichment of nucleosomes at CTCF sites (chromatin state 8). To probe this interaction further, we derived 9,516 CTCF sites based on the presence of the CTCF‐binding motif To investigate this further, we examined the pattern of nucleosomes at CTCF sites occupied only in NPCs and not iPSC. By cross‐comparison between our 122‐ to 137‐bp small fragment data and CTCF ChIP‐seq data from NPC (derived from H9 ESC), we identified 2,522 unique sites with CTCF bound only in the NPC state  and altered nucleosome spacing following retinoic acid‐induced differentiation In conclusion, we have used genome‐wide mapping of human iPSC to follow the dynamics of nucleosome positioning from the pluripotent state to an early stage of neuronal development. This provides the opportunity to follow changes across two developmental states and is particularly valuable to assess changes in gene activity. We observed a substantial increase in the number of positioned nucleosomes and re‐positioning of nucleosomes during differentiation to NPC. Although the existence of small subgroups of genes where positioning is important cannot be excluded, there was no strong correlation between nucleosome positioning and gene activity at the genome‐wide level. In general, there are very few organised arrays of nucleosomes within the genomes of these human cell types, but remarkably, where nucleosome arrays do occur, they mark chromatin structures that are retained during cell differentiation. These may represent defined regulatory sites that control long‐range chromatin changes and higher order 3D organisation 6 cells/10‐cm plate in complete mTeSR1TM medium containing 10 μM Y27632 (Tocris) and incubated at 37°C in a standard 5% CO2, humidified incubator (Binder). To passage iPSC, cells were first treated with 10 μM Y27632 for 2 h, then washed with Ca2+/ Mg2+‐free PBS and cell colonies lifted from the plate by incubation with Dispase (Stem Cell Technologies) containing 10 μM Y27632 (Tocris). Colonies were fragmented by gentle trituration, collected by centrifugation (180 g) and re‐suspended in medium for re‐plating.The 34D6, male, human iPSC line  l‐glutamine , 1× lipid concentrate (Invitrogen), 7.5 μg/ml holo‐transferrin (Sigma), 14 μg/ml insulin (Merck), and 10 μM β‐mercaptoethanol (Sigma). Medium was supplemented with 10 μM Y27632 (Tocris) for the first 2 days, with 10 μM SB‐431542 (Tocris) until day 4 of differentiation and 0.5 μM LDN193189 (Miltenyi) until day 8 of differentiation. Medium was changed every 2 days. At day 8, neuralised embryoid bodies were washed with Ca2+/Mg2+‐free PBS and then dissociated by incubation at 37°C with Accutase (PAA laboratories). A single‐cell suspension was obtained by gentle trituration and cells washed with ADF medium and harvested by centrifugation at 1,000 rpm. Neural progenitors were then plated onto tissue culture plates coated with 0.1 μg/ml poly‐L‐lysine (Sigma) and 10 μg/ml laminin (Sigma) in ADF medium + 5 ng/ml FGF2. 34D6‐derived neural progenitors were grown to sub‐confluency and passaged once by dissociation with Accutase and re‐plating. The 34D6 iPSC‐derived neural progenitors were harvested for nucleosome preparation on day 16 of differentiation. The NPC population was validated using immunocytochemistry by checking for the presence of the NPC‐specific markers, such as nestin and the loss of pluripotency markers, for example Oct‐4. Greater than 90% of the differentiated population contained neural progenitors.For neural differentiation, a dual SMAD inhibition protocol was used S. cerevisiae genome in vivo digestion with 300 U/ml MNase at room temperature for 4 min. DNA fragments were purified from each MNase treated sample, and then, the samples for each cell type were pooled in equimolar amounts. DNA extracted from chromatin samples was size‐fractionated on agarose gels. 25–35 μg of DNA less than 300 bp was size‐selected for each cell type.Chromatin was prepared from three bioreplicates of human iPSC and the same cells differentiated to NPCs as described previously for the http://www.sourcebioscience.com/) on an Illumina HiSeq 2000 platform (HiSeq) using a read‐length of 50 bp. Eight flow cells were used for each cell type to obtain a sufficient depth of coverage of the human genome. A standard Illumina paired‐end mode sequencing protocol was used, apart from the omission of the nebulisation step and the addition of a further gel purification step to eliminate any excess concatenated linkers after the ligation of linker DNA to the sample. Base calling and quality control of the sequencing data were performed using Real Time Analysis (RTA) 1.09, CASAVA 1.8 software.All of the DNA fragments less than 300 bp in size were utilised for paired‐end mode sequencing by Source BioScience , 161–188 bp. The frequency distribution for the mid‐point position of the sequencing reads was derived at 10‐bp resolution, and the data were smoothed using a 3‐bin moving average. Frequency distributions were output as chromosome‐specific files in .sgr format: chromosome identification: chromosomal location of the start of each 10‐bp bin: frequency of the paired‐read mid‐point values that fall within that 10‐bp bin.Published human nucleosome maps In order to locate and quantify the number of highly positioned nucleosomes, a heuristic peak‐finding algorithm was developed. Peaks were defined as three consecutive 10‐bp bins where the value of the paired‐read mid‐point frequency in the central 10‐bp bin was between 30 and < 1,000. The lower threshold for the paired‐read mid‐point frequency values for the bins either side of the central bin was set at two (the “noise” threshold). The upper threshold for each of the paired‐read mid‐point frequency values for the bins either side of the central bin was less than the paired‐read mid‐point frequency in the central bin. The upper threshold was chosen to exclude regions of the genome with high frequencies of paired‐read mid‐point values found at the ends of chromosomes and at runs of repeats and at centromeres. Peaks in the genomic distribution of sequence read mid‐points were given explicit genome positions using PeakFinder for all of the nucleosome maps: iPSC, NPC and K562.An in‐house python script was used to calculate the distance between the genomic locations of all highly positioned nucleosomes across the genome for each cell type, iPSC, NPC and K562. Positioned nucleosomes 150–200 bp apart were located, and those existing as singletons or in arrays of 2, 3 or more nucleosomes were counted. In‐house Perl scripts were used to compare the genome‐wide overlap in the locations of positioned nucleosomes within ± 10 bp in iPSC and NPC .Published open chromatin data We aligned the genomic positions of the peaks in the nucleosome map determined using the heuristic PeakFinder with the autosomal ATAC‐seq regions from each of two replicate cell lines C15_0_1_ATAC‐seq GSM2264802) and C15_0_2_ATAC‐seq (GSM2264803) using in‐house python scripts. The results of these analyses from the two replicates were similar. Figure 264802 ann = 83,179) and a list of non‐redundant, strand‐specific autosomal TSS from protein‐coding genes  using in‐house scripts was derived. Expression data from ESCs and ESCs differentiated to the N2 stage of development n = 3,833) and b) N2 cells . The minimum expression threshold was 0.1 , and the difference in expression was at least twofold difference between ESC and NPC in each case. TSS of genes expressed specifically in (i) ESC and (ii) N2 cells were tested for the presence of positioned nucleosomes within ± 300 bp of the TSS by mapping the genomic locations of highly positioned nucleosomes generated by the PeakFinder tool to a window ± 300 bp of the TSS in each case.The positions of transcriptional start sites for all of the full‐length transcripts for human genome assembly GRCH37/hg19 were derived as follows. Track = Gencode Genes v17, table = basic, was downloaded from the UCSC genome browser . From this, a list of non‐redundant, strand‐specific autosomal TSS was derived (http://hgdownload.cse.ucsc.edu/goldenPath/hg19/chromosomes/.The genomic positions of the consensus binding sequence for each transcription factor were extracted from FASTA files from human genome assembly GRCH37/hg19 using in‐house Perl scripts. FASTA files were downloaded from: http://www.factorbook.org) et alet alhttps://www.encodeproject.org/files/ENCFF796YPF), from data with conservative idr thresholded peaks using in‐house python scripts. RE1 sites were derived by mapping the consensus binding motif derived by Bruce et alThe consensus binding motif used in this study for each transcription factor is shown in The in‐house Perl script SiteWriter Cluster analysis was undertaken in R, using the Canberra method to generate a distance matrix from the C3.txt file from the output of the SiteWriter script. Dendrograms generated by hierarchical agglomerative clustering were used to determine the number of groups to use in k‐means clustering. Cluster data for genomic features were used to construct average frequency distributions of the read mid‐point values at and in the bins surrounding genomic feature loci within a user‐defined window for selected clusters.JCH, NDA and AJH designed the experiments; JCH and NAK generated the data; JCH and AJH performed the analysis and wrote the manuscript.The authors declare that they have no conflict of interest.Expanded View Figures PDFClick here for additional data file.Table EV1Click here for additional data file.Table EV2Click here for additional data file.Table EV3Click here for additional data file.Table EV4Click here for additional data file.Table EV5Click here for additional data file.Review Process FileClick here for additional data file.


Interferon regulatory factor 6 (IRF6) acts as a tumor suppressor and controls cell differentiation in ectodermal and craniofacial tissues by regulating expression of target genes. However, its function in gastric cancer (GC) remains unknown to date. In this study, we found that the IRF6 expression was significantly downregulated in GC. And the decreased expression of IRF6 was clinically correlated with poor prognosis of GC. Moreover, loss-of-function and gain-of-function studies showed that IRF6 was negatively regulated by ZEB1 but positively regulated by ELF3. Additionally, transcription factor ZEB1 and ELF3 could directly bind on IRF6 promoter, which suggested that transcription factor IRF6 is transcriptionally regulated by ZEB1 and ELF3. Nevertheless, we found that IRF6 expression was negatively related to its promoter methylation in TCGA stomach cancer cohorts. The downregulation of IRF6 in GC might be due to the overexpression of ZEB1 and the DNA methylation of IRF6 promoter. Gastric cancer (GC) is the third leading cause of cancer-related death worldwide, especially in East Asia . DespiteInterferon regulatory factor 6 (IRF6) belongs to a family of nine transcription factors that share a highly conserved helix–turn–helix DNA-binding domain and a less conserved protein-binding domain . Unlike Previous studies have reported that IRF6 was downregulated during EMT process of breast cancer and prostate cancer –13. ZEB1In this study, we identified that the expression level of transcription factor IRF6 protein and mRNA was significantly downregulated in GC. Besides, the lower expression of IRF6 predicts poorer prognosis of GC. In addition, our data highlights that ZEB1 and ELF3 are two transcriptional regulators of IRF6 in GC; IRF6 is negatively regulated by ZEB1 but positively regulated by ELF3 in GC.http://gepia.cancer-pku.cn/index.html) and UCSC (http://genome.ucsc.edu/). The chip-seq data of ELF3 and ZEB1 download from NCBI was analyzed by Cistrome (http://cistrome.org/db/#/). The chip-seq data of Dnase I, H3K27Ac, EP300, SRF, POLR2A, MED1, CREB1 and BRD4 were obtained from http://cistrome.org/browser/?genome=hg38wugb&datahub=http://dc2.cistrome.org/data5/browser/1535255763.json&gftk=refGene,full&coordinate = chr7:27066839-27266927. The possible binding sites of ELF3 and ZEB1 in the 2000-length IRF6 promoter was predicted by JASPAR (http://jaspar.genereg.net/). The correlation of IRF6 promoter methylation and IRF6 expression was analyzed by MEXPRESS (https://mexpress.be/) and LinkedOmics (http://www.linkedomics.org/login.php).Six public gastric cancer microarray gene profiling datasets  were downloaded from the Gene Expression Omnibus (GEO) in the NCBI web server. The clinical information of GSE62254 gastric cancer cohort was download from Cristescu et al. . The exp2.The human gastric cancer cell line  and a normal gastric epithelium cell line (GES-1) were purchased from the Shanghai Cell Bank of Chinese Academy of Sciences . All the GC cell lines and the GES-1 Cell line were cultured in DMEM medium containing 10% fetal bovine serum (FBS), 100 U/mL penicillin,100 U/mL streptomycin and 0.03% glutamine at 37°C in 5% COThe siRNAs  used to knock down ELF3 and ZEB1 expression in GC cell lines were designed and synthesized by Genepharma . The ORF region of ZEB1 cDNA was cloned into pcDNA3.1 (+). Gastric cancer cells were grown in 6-well plates and transfected by Lipofectamine 2000 (Invitrogen) according to the manufacturer's instructions. At 48 h post-transfection, cells were harvested for qPCR analysis. For ELF3 overexpression experiment, ELF3 and controlled scrambled plasmids were purchased from GeneChem . Transfection was performed with Lipofectamine 2000 (Invitrogen) according to the manufacturer's instructions.−ΔΔCt Method.For RNA extraction, gastric cancer cells were grown in 6-well plates and transfected with siRNAs. After 48 h, remove the medium and directly add 800 μL Trizol into the 6-well plate to harvest samples. Total RNA was extracted using Trizol reagent  according to the manufacturer's instructions. The isolated RNA was treated with RNase-free DNase I (Roche) for 15–30 min as we described before . PCR wasFor IRF6 promoter cloning, total genomic DNAs were extracted from AGS cell lines using TIANamp Genomic DNA Kit . The 1,000 bp-length of IRF6 promoters were amplified by PCR  and then clone into pMD18-T vectors (Takara) which were next used as templates for wildtype and mutant IRF6 promoters cloning. For reporter vectors construction (WT), the wildtype promoters of IRF6 (NM_006147) were amplified by PCR . After digesting the pEZX-FR01 vector  into a linear fragment by SwaI, the IRF6 promoters and the linear vector fragments are recombined by seamless cloning  according to the manufacturer's instructions. For reporter vectors construction (Mut), two DNA fragments (mutant IRF6 promoter) was amplified by using the templates that mentioned above. The primers are as follows: F1, actagtacgcgtatttTTGAACTGGGTGCCA; R1, GATCGATCTTCTTTTTTGTTGTTG; F2, AAAAGAAGATCGATCTTATTATTCTCATTG, R2, agagtttaaacgtcgacatttTCTCCCCGTCCCGCAC. After digesting the pEZX-FR01 vector into a linear fragment by SwaI, the linear vector fragments and the mutant IRF6 promoters are recombined by seamless cloning according to the manufacturer's instructions. AGS and SGC7901 cells were seeded into 12-well-tissue plates 24 h before transfection, and then co-transfected with 5 ng siRNA and 1 mg plasmid using the Lipofectamine 2000 Reagent (Invitrogen), according to the manufacturer's instructions. After another 48 h, cells were assayed using the Dual-Luciferase reporter assay system kit . All experiments were performed in triplicate and data were pooled from three independent experiments.Chromatin immunoprecipitation (CHIP) assays were performed using CHIP Assay Kit  according to the manufacturer's protocol. ELF3 antibody were purchase from Santa Cruz Biotechnology ; ZEB1 antibody were purchase from Santa Cruz Biotechnology . Briefly, SGC7901 cells were collected and fixed for 10 min at 37°C with 1% formaldehyde, followed in sequence with SDS lysis and DNA shearing, protein and DNA immunoprecipitation, cross-linked DNA reversal and DNA purification, and finally the immunoprecipitated DNA fragments were detected by PCR assays. The normal rabbit IgG was used as the negative control. The sequence of primers for CHIP (anti-ELF3) were used as follows ; the sequence of primers for CHIP (anti-ZEB1) were used as follows .t-test. Differences among multiple groups were determined by one-way ANOVA. Comparisons were performed using the Spearman's correlation test; p < 0.05 was considered statistically significant.Data from at least three independent experiments performed in triplicate were presented as the mean ± S.D. The differences between two groups were determined by student's http://www.proteinatlas.org/), which contains a large number of immunohistochemistry (IHC) images of sections from 46 different normal human tissue types and 20 different cancer types (The Human Protein Atlas (HPA) is an effort to map the subcellular location of all human proteins (er types . Furtherer types .n = 300). The results showed that diffuse GC tissues possessed lower IRF6 expression than intestinal GC tissues  family, consisting of nine members in mammals, commonly possessed a novel helix-turn-helix DNA-binding domain and was proved to be involved in regulation of immunity and oncogenesis . TranscrIn this study, we determined to investigate the function of transcription factor IRF6 in gastric cancer. Firstly, we identified that the expression levels of IRF6 protein and transcript are both significantly reduced in GC compared with normal stomach tissues . BesidesPrevious studies have reported that IRF6 was downregulated during EMT process of breast cancer and prostate cancer –13. Our In addition, previous studies showed that IRF6 is a downstream target gene of the NOTCH signaling pathway and induced by the NOTCH signaling pathway in breast cancer and keratinocytes , 31, 32.On the other hand, we tried to identify possible transcriptional regulators that positively regulate IRF6 expression. Due to IRF6 was known to be a target gene of TP63 in skin development and squamous cell carcinomas, we firstly attempted to analyze the co-expression of IRF6 and TP63 in human gastrointestinal tissues. However, we found that a certain degree of IRF6 expression can still be detected in the human gastrointestinal tissues that hardly express TP63, such as stomach, colon and small intestine . TherefoInspired of this, we considered to analyze all the transcription factors that highly co-expressed with IRF6 and finally identified ELF3 as a possible positive transcriptional regulator of IRF6 in GC due to ELF3 was highly co-expressed with IRF6 in normal stomach tissues, GC tissues and GC cell lines . In addiNevertheless, previous studies has reported that promoter DNA methylation at CpG islands is a common mechanism used by cancer cells to repress expression of tumor suppressor genes . BesidesIn conclusion, transcription factor IRF6 was downregulated in GC. The reduced expression of IRF6 predicted poor prognosis of GC. In addition, ZEB1 is identified to be a negative transcriptional factor of IRF6 gene, while ELF3 is identified to be a positive transcriptional factor of IRF6 gene in GC. The downregulation of IRF6 in GC might be owing to overexpression of ZEB1 and the DNA methylation of IRF6 promoter.The research was designed by YL and SQ. The experiments were performed by SQ, DL, PC, JW, XQ, XZ, and LX, and the data were analyzed by SQ. The manuscript was written by SQ.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Cerebrovascular and neurodegenerative disorders affect one billion people around the world and result from a combination of genomic, epigenomic, metabolic, and environmental factors. Diagnosis at late stages of disease progression, limited knowledge of gene biomarkers and molecular mechanisms of the pathology, and conventional compounds based on symptomatic rather than mechanistic features, determine the lack of success of current treatments, including current FDA-approved conventional drugs. The epigenetic approach opens new avenues for the detection of early presymptomatic pathological events that would allow the implementation of novel strategies in order to stop or delay the pathological process. The reversibility and potential restoring of epigenetic aberrations along with their potential use as targets for pharmacological and dietary interventions sited the use of epidrugs as potential novel candidates for successful treatments of multifactorial disorders involving neurodegeneration. This manuscript includes a description of the most relevant epigenetic mechanisms involved in the most prevalent neurodegenerative disorders worldwide, as well as the main potential epigenetic-based compounds under investigation for treatment of those disorders and their limitations. Brain disorders with a vascular and/or neurodegenerative component affect one billion people worldwide, according to the World Health Organization. Most of these pathologies share an onset of dementia. Disability caused by dementia increases dramatically with aging, by affecting 9 per 1000 of the population aged 65 to 74 years to 83 per 1000 in the population over 85 years old ,3. AlzheNeurodegeneration process begins with a series of earlier events, affecting cell development, metabolism, and axonal transport, which progressively lead to a massive cell death rate. Brain often compensates those premature features that remain rather asymptomatic. The lack of success of the current treatment strategies relies on our still limited knowledge of the pathogenic genomic variants. Importantly, currently detected polymorphic variants in pathogenic genes associate directly with a very low rate of Alzheimer’s or Parkinson’s disease patients. Personalization of treatments according to individual pharmacogenomic profiles would also increase the rate of success and reduce unnecessary costs. In addition, detection of the first symptomatic features normally occurs after a high rate of cell death and damaged tissue, which significantly affect brain function and hinders potential treatments. In this regard, novel epigenetically-based treatments are gaining a great interest as a potential novel treatments for complex multigenic neurodegenerative diseases ,15,16,1750 ranges and efficient drug delivery strategies; (ii) more specific targets; and (iii) personalized treatments according to the individual pharmacogenomic and pharmacoepigenomic profiles.Complex diseases often result from the interplay of genetic variants (genomics) and the environmental influence on gene function (epigenomics). The epigenetic machinery controls metabolic pathways by regulating gene expression through chemical and structural modifications on the genome, such as DNA/RNA methylation, chromatin structure, and non-coding RNA binding. The study of the epigenetic gene regulation might allow the identification of early biomarkers corresponding to previously undetectable features in the progression of neurodegeneration. In addition, these epigenetic aberrations may be restored with the use of appropriate epigenetic-based therapies. In this regard, during the last decade, scientists have been highly motivated in the search of epigenetic aberrations that occur during presymptomatic disease stages in order to establish novel treatment approaches using compounds (epidrugs) which target the epigenetic aberrations occurring during the progression of neurodegenerative processes ,19,20,21PSEN1 and PSEN2), Aβ-precursor protein (APP), apolipoprotein E (APOE), and the alpha-2-macroglobulin (A2M).The complexity of AD pathogenesis relies on the combination of genetic, epigenetic, and environmental factors. Current research accumulates data from over 600 single-nucleotide polymorphisms (SNPs), as well as Mendelian and mitochondrial mutations, in genes potentially associated with AD progression ,22,23,24PSEN1 and PSEN2 genes, detected in some AD patients, correlate with an impaired APP cleavage and Aβ aggregation into senile plates. Polymorphisms in the gene encoding the microtubule-associated protein tau (MAPT) promote tau protein hyperphosphorylation which results in microtubule destabilization leading to neurofibrillary degeneration [APOE), which associate with hypercholesterolemia and vascular disorders, constitute one of the most relevant genetic hallmark s of AD. Presence of the APOE-ε4/ε4 haplotype represents a 60 to 80% probability of an early AD onset [APOE-ε4 with an impaired APP metabolism leading to Aβ aggregation promoting tau hyperphosphorylation resulting in the formation of fibrillary tangles, as well as lipid metabolism and transport impairment and oxidative and neuroinflammatory processes leading to a massive cell death rate [APOE-ε2, tightly linked to pathologies with a vascular component, is nevertheless protective against dementia [A2M gene, encoding for the alpha-2-macroglobulin (a protease inhibitor), is also localized in amyloid plaques and interacts with Aβ and APOE. The polymorphism 2998 G > A (rs669) in homozygosis increases the risk for the onset of AD by 4-fold compared with the general population [APP cleavage, Aβ clearance, and microtubule stability regulated by phosphorylation of microtubule-associated tau protein, are key targets of AD progression. Presenilins are important determinants for the β-secretase-mediated APP cleavage. Polymorphic variants on neration ,23,25. PAD onset ,27. Althath rate ,28,29,30dementia . The A2Mpulation .N-methyl-d-aspartate (NMDA) receptors, memantine, is a current alternative strategy for patients with moderate or severe stages of the disease. Memantine reduces neuronal excitotoxicity by inhibiting the prolonged influx of Ca2+ ions from extrasynaptic receptors. Nevertheless, efficacy of this drug is under debate [Most current pharmacological approaches for AD treatment rely on promoting cholinergic synapses, reducing neuronal cytotoxicity, or preventing the formation of senile plates ,33,34,35r debate ,34,35. Lr debate .Recent studies provide explanations about the implications of α-synuclein in PD at the molecular level. It has been recently established the interaction of α-synuclein with mitochondrial membranes ,38,39,40SCNA gene, which encodes α-synuclein, over 100 other pathogeneic genes may be involved in PD, from which 15 PD loci (PARK1-15) as well as other loci might be a direct cause of the disease [SNCA), parkin 2 (PARK2), PTEN-induced putative kinase 1 (PINK1), parkin 7 , and leucine-rich repeat kinase 2 (LRRK2) genes are associated with the genetic etiology of PD, whereas other loci, such as, microtubule-associated protein tau (MAPT), spatacsin, polymerase (DNA) gamma, catalytic subunit (POLG1), glucosylceramidase beta (GBA), and ataxin , might be susceptibility genes associated with sporadic PD, normally associated with toxic or environmental exposure [Besides the  disease . Mutatioexposure ,46.O-methylatransferase (COMPT) inhibitors, such as entacapone and tolcapone. Unfortunately, all these pharmacological treatments only provide a symptomatic relief rather than stopping or delaying the progression of the disease. Furthermore, the chronic administration of antiparkinsonian drugs currently induces the “wearing-off phenomenon”, with additional psychomotor and autonomic complications [The loss of dopaminergic neurons during development of PD results in concomitant loss of dopamine in the affected areas  which is manifested with classic motor symptoms , and other non-motor symptoms . Current pharmacological treatments for PD are based on restoring the dopamine levels using different strategies: (i) increase dopamine availability by treatments with dopamine precursors, such as L-DOPA (levodopa), or dopaminergic agonists  and (ii) inhibition of dopamine catabolism or degradation, by using monoamine-oxidase B (MOB) inhibitors, such as rasagiline and selegiline, or catechol-ications ,17.Combination of current drugs with novel compounds, especially bioproducts seem to reduce these clinical complications and provide dopaminergic neuroprotection in order to enhance dopaminergic neurotransmission and reduce premature neurodegeneration .The analysis of the whole genome sequencing unveils a wide range of gene variants which facilitate the diagnosis of a number of complex, multigenic disorders. These polymorphic variants and gene mutations also serve as targets for developing more accurate and less expensive treatments. Nevertheless, genetic factors define only partially the onset of neurodegenerative diseases, which normally arouse due a complex interplay of genetic and epigenetic mechanisms. The strict epigenetic regulatory processes result in the control of gene expression in response to the metabolic demands of the organism. Epigenetic mechanisms regulate gene expression at both, transcriptionally and post-transcriptionally levels. While DNA methylation status and modulation of chromatin structure, mediated by ATP-dependent chromatin regulator complexes (ATP-CRCs) and post-translational histone modifications, exert a transcriptional control, non-coding RNAs suppress gene expression post-transcriptionally .Neurophysiologic mechanisms integrated in upper level complex processes, such as memory acquisition, learning, or motor coordination are, to a large extent, epigenetically regulated ,49,50. TDNA methylation consists in the incorporation of methyl groups into cytosine molecule, normally located at CpG islands where CG content is greater than 60%. The level and location of DNA methylation affect gene function in different manners. Levels of methylation at the promoter regions affect gene expression. Generally, the higher is the level of methylation at the promoter region, the lower is the expression of this gene, and vice versa. Promoter hypermethylation promotes the binding of transcription repressors or inhibits transcription factors leading to a reduced gene expression ,51,52. TS-adenosyl-l-methionine-dependent methyltransferase (SAMe) [BACE1) and presenilin 1 (PSEN1) genes in cell cultures, transgenic AD animal models, and post-mortem brains of AD patients [SCNA), which would promote the expression and aggregation of α-Syn.The two most prevalent neurodegenerative disorders worldwide, Alzheimer’s (AD) and Parkinson’s diseases (PD), share a reduced DNA methylation in brains and blood from animal models and human subjects ,62,63,64e (SAMe) ,65. Indee (SAMe) ,67,68,69patients ,72,73,74patients ,76. AccoContrary to AD and PD, the epigenetic pattern of the Amyotrophic Lateral Sclerosis (ALS) involves a general DNA hypermethylation  enforcedMost aberrant DNA methylation patterns leading to neurodegeneration target pathogenic genes directly involved in the disease, genes involved in neuroinflammatory pathways, and genes related to neurodevelopment and synaptic processes.APP methylation and AD progression [GSK3β) at the promoter region, which promotes the expression of this protein kinase that induces tau phosphorylation, NFT aggregation, loss of cytoskeleton integrity, and cell death [BIN1), complement receptor 1 (CR1), the CD33 molecule (CD33), and the tumor necrosis factor (TNF-α) [SORL1) and neprylisin (NEP) genes involved in the Aβ degradation and clearance. Sanchez-Mut et al. [TBXA2R), sorbin and SH3 domain containing 3 (SORBS3), and spectrin beta 4 (SPTBN4) genes in AD animal models and human subjects. Authors suggest that the activation of the cyclic AMP response element-binding protein (CREB) pathway and the axon initial segment might contribute to the pathogenesis of AD [Despite of the importance of β-secretase activity and APP cleavage in the progression of AD ,3,23,25,gression ,58,59,86ll death . Promote (TNF-α) ,56,88. Ht et al.  found this of AD . APOE gene haplotypes are among the most reliable biomarkers for AD diagnosis, information available about the epigenetic modulation of this gene is scarce. Some studies suggest that the C > T transition in the 3’-CpG island, which is specific of APOE-ε4, might prevent methylation of this site and promote APOE-ε4 expression in AD patients [Although patients ,71,90.SCNA gene, was significantly hypomethylated in blood and brain samples from PD patients as compared to controls [Genome wide association studies found a direct implication of methylation status of α-synuclein and development of PD. The putative gene promoter, located in the intron 1 of controls . This hycontrols . This hycontrols ,92.TNF-α levels are associated with neuroinflammation and dopaminergic cell death in PD. Therefore, the higher vulnerability to TNF-α regulation found in dopaminergic neurons suggests the gene promoter is hypomethylated [TNF-α overexpression is usually detected in the cerebrospinal fluid of PD patients, as TNF-α induces apoptosis in neuronal cells [Other genes were also found epigenetically regulated in PD. Increased thylated . Importaal cells . It was al cells ,95. Methal cells . In addial cells .Other studies revealed that methylation aberrations may associate with imprinting mechanisms, such as those responsible for huntingtin overexpression in Huntington’s disease patients , or the Chromatin stability and conformation regulates gene expression and silencing of transposable elements, as well as maintains genome integrity. ATP-dependent chromatin regulator complexes (ATP-CRCs) and post-translational histone modifications control chromatin structure.N-acetyltransferases (GNATs), which include GCN5, p300/cAmp-response element binding protein (CBP)-associated factor (PCAF), KAT6-8, CREB-binding protein/CBP (CREBBP/CBP), and EP300 promote histone acetylation [+-dependent HDACs, sirtuins (SIRT), promote lifespan and healthy aging by delaying the onset of neurodegenerative processes [Histone post-translational modifications alter the chromatin package into a tight (hetrochromatin) or loose (euchromatin) conformation, which affects gene accessibility to the transcription machinery. Histone acetylation, mediated by histone lysine-acetyltransferases (HATs or KATs) reduces the electrostatic interaction between DNA and histones which results in a looser chromatin conformation that allows gene accessibility and thus activates transcription ,102. Gcntylation ,105,106.tylation ,105,107.tylation ,109 and tylation ,110. Ovetylation ,112. HDAtylation ,113. Somtylation ,115. Indtylation ,115,116.rocesses ,117,118.rocesses ,120,121 rocesses ,123.Histone methylation and demethylation, mediated by histone methylases (HMTs) and demethylases (HDMTs), respectively, also contribute to neurodegenerative progression. Those enzymes have a high specificity as they usually modify one single lysine per histone which may be translated into activation or repression of transcription ,124,125.Histone methylation levels  increased significantly in young preplaque AD transgenic mice as compared with wild-type mice ,127,128.Differential expression of non-coding RNAs (ncRNAs) modulates gene expression post-transcriptionally. Aberrant expression of a number of ncRNAs alters expression of genes involved in metabolic pathways leading to neurodegeneration.These regulatory RNAs include long ncRNAs (lncRNAs), which target pathogenic genes directly involved in the disease or epigenetically regulated genes, small interference RNAs (siRNAs), piwi RNAs (piRNAs), and microRNAs (miRNAs). These last ones induce mRNA degradation by binding to the 3′ untranslated region and are the most popular biomarkers for disease diagnosis and progression. Altered expression of miRNAs affects modulation of direct pathogenic genes or those involved in other neurophysiological roles indirectly associated with the disease. A number of cell free blood and cerebrospinal fluid-circulating miRNAs are informative biomarkers of the stage and progression of the disease in vivo, with a rapid and noninvasive liquid biopsy. Circulating miRNAs are thus good candidates as presymptomatic biomarkers and for early diagnosis of the disease.Telomeres are protective structures located at the end of the chromosomes, which contain a number of TTAGGG repeats. Shortening of telomere length increases with aging and age-related and neurodegenerative disorders enhance this process. Several mechanisms mediate the protection of these telomeric regions in order to delay their degradation. The efficiency of these protective mechanisms depends on the length of telomeres, i.e., the number of TTAGGG repeats. Shelterin is a nucleoprotein complex that binds to those repeats and protects DNA from activation of DNA damage pathways. Ability of sheltering binding increases with telomeric length, which is modulated by telomerase activity. Telomerase replaces the missed repeats after each cell division, using an associated RNA molecule, TERC, as a template. However, aging-related telomerase activity decay leads to telomere shortening, resulting in a loss of shelterin’s ability to bind these shorter telomeres and activation of the DNA damage cascade and cell death ,132.The epigenetic machinery modulates DNA protection and chromatin structure and stability, which affects telomerase activity and the rate of telomere degradation. Histone hypoacetylation at telomeric regions induces a heterochromatin state which protects DNA at telomeric and subtelomeric regions from activation of DNA damaging pathways . On the Epigenetic mechanisms involving ncRNA also regulate telomere length. A number of subtelomeric loci express lnRNAs named telomeric repeat-containing RNAs (TERRAs) which control both chromatin remodeling at those regions and telomerase-mediated telomere elongation ,138,139.Available treatments for complex disorders are mostly symptomatic and provide limited beneficial effects on the progression of the disease, and often with a payback of unacceptable side effects. Epigenetic mechanisms unveil many hidden pathological alterations of memory and learning impairment, synaptic loss, and cell death, involved in neurodegenerative processes. Many epigenetic alterations appear in early asymptomatic stages of the disease and are reversible. Thus, the new age attempts of treating these disorders involve the use of epigenetic-based drugs (epidrugs) targeting DNA methylation, chromatin remodeling, and non-coding RNAs as potential candidates for the treatment of these complex polygenic disorders. These drugs include activators and inhibitors of DNA methyltransferases, histone deacetylase inhibitors, sirtuin activators, modulators of histone acetylation and histone methylation, as well as RNA interference analogs.6-dependent serine-hydroxymethyltransferase catalyzes the conversion of tetrahydrofolate (THF) into 5,10-methylenetetrahydrofolate (MTHF), followed by the synthesis of 5-MTHF catalyzed by vitamin B2-dependent MTHF reductase (MTHFR). 5-MTHF provides the methyl groups for Hcy methylation by cobalamin-dependent methionine synthase, yielding methionine, which is converted to SAM by methionine adenosyltransferase. SAM is responsible for methylation of main macromolecules, including DNA, proteins, phospholipids neurotransmitters, and hormones. Donation of methyl group promotes the synthesis of SAH, which hydrolyzes to Hcy and adenosine by SAH hydrolase. According to the consensus statement, based on the Bradford Hill criteria, elevated levels of total Hcy is a recognizable risk factor for development of dementia and AD in older individuals [Strategies attempting to restore DNA methylation may re-establish the proper metabolic pathways disrupted by the global DNA hypomethylation associated with the progression of most prevalent neurodegenerative disorders, including AD and PD. In most cases, detrimental Vitamin B- and SAMe-mediated global hypomethylation associates with high levels of homocysteine (Hcy) and S-adenosylhomocysteine (SAH) ,75,140, ividuals . Therefoividuals ,143,144 ividuals ,147,148 ividuals ,150,151.Hypermethylation of pathogenic genes also promotes neurodegeneration. Therefore, approaches using DNA methylation inhibitors may also be appropriate ,154,155.Camilla sinensis). EGCG prevents misfolded proteins from fibrillization [Bcl2 expression, preventing cell death in Aβ-treated neurons [®), which is an approved drug for the treatment of several forms of arthritis when administered by injection. Some studies suggest that perispinally injected Etanercept may modulate certain aspects of the immune system and provide some beneficial effect for people with Alzheimer’s disease. Studies suggest that supplementation with specific nutrients may also have a positive effect in support of cognitive function [The epigallocatechin-3-gallate (EGCG) is the main polyphenol of the green tea , catechfunction ,160. Etafunction   and 5-azacytidine (Azacitidine) and the small molecules hydralazine and procainamide are also potential treatments for neurodegeneration, although they are not yet submitted to clinical trials. However, these epidrugs are currently FDA approved for other prevalent disorders including diverse types of cancer, myelodisplastic syndrome, thalasemia, hypertension, and cardiac arrhythmia .HDAC inhibitors (HDACi) potentially restore global histone deacetylation, which is a common feature of most neurodegenerative processes. Most of HDACi under development provide beneficial effects at cognitive and memory levels in animal models of AD ,156,161 N-hydorxyacrylamide (4b), and N-hydroxy-3--acrylamide (3f)); and (v) the class III HDACi or SIRT inhibitor nicotinamide/niacinamide and SIRT activators as resveratrol and derivatives. Other benzamides, cyclic peptides, and ketones showed powerful HDAC inhibition properties and some of them are currently FDA approved for cancer treatment.The most effective HDACi tested in those models are (i) the short-chain fatty acids, class I HDACi ) and class I and II HDACis (sodium butyrate (NaB) and sodium phenylbutyrate ); (ii) the hydroxamic acids, class I and II HDACis  and trichostatin (TSA)); (iii) some benzamides, class I and II HDACi (entinostat (MS-275), W2); (iv) miscellaneous compounds, class I and II HDACi (FRM-0334) and HDAC6 specific inhibitors -3--Low toxicity of NaB makes this drug tolerable for treatment in animals and humans ,170,171.4-PBA constitutes one of the most promising HDACi-based therapeutic agents due to the successful results obtained in animal models. Histone acetylation mediated by 4-PBA, promotes transcription of genes associated with synaptic plasticity and promotes the active form of GSK-3β, preventing tau phosphorylation and restoring memory and learning activities in AD transgenic mice . Among tBDNF) and glial-derived neurotrophic factor (GDNF), which play critical roles in the growth, survival, and synaptic plasticity of neurons. In addition, VPA induces the expression of the heat-shock protein Hsp70, accompanied by increased levels of H3 lysine di- and trimethylation (H3K4Me2 and H3K4Me3), which promote the recruitment of HAT p300 [APP [The anticonvulsant VPA is a fatty acid originally used as treatment for epilepsy and as a mood stabilizing agent. This is one of the most studied compounds for as a potential treatment for neurodegeneration. VPA treatment promotes the expression of brain-derived neurotrophic factor  and the HDAC6-specific inhibitor Vorinostat (SAHA) are the most widely explored compounds for the treatment of neurodegenerative diseases ,185,186.GDNF upregulation in astrocytes [Trichostatin (TSA) is class I HDAC inhibitor that enhances the expression of genes involved in memory consolidation, possibly by promoting the acetylation of the histone H4 ,109,110.trocytes ,185,186.The HDAC6-selective inhibitor Vorinostat (SAHA) is one of the most developed HDAC inhibitors and was approved by FDA in 2006 for the treatment of advanced cutaneous T-cell lymphoma. SAHA treatment enhances basal postsynaptic excitatory, but not inhibitory, synaptic function and restores memory function in animal models of impaired learning tasks  and in tSome benzamides, such as entinostat and W2, provided promising results as HDACi in animal models of AD. The selective HDAC1 inhibitor entinostat (MS-275) improved behavioral activities in the AD-APPPS1-21 mouse model by reducing amyloid plaque deposition and neuroinflammatory processes , while tSeveral miscellaneous HDAC inhibitors are under testing for neurodegenerative diseases, especially for those involving dementia. Among this group, one of the most promising epidrugs is the Forum Pharmaceutical compound (FRM-0334), specifically tested for dementia, which inhibits a subset of class I and II human HDACs with a high efficiency  and addresses the issue of crossing the blood–brain barrier . FRM-033N-hydroxy-3--acrylamide (3f) is the synthetic compound with the highest affinity and efficiency to inhibit HDAC6 in vitro . This compound promoted the expression of the growth-associated protein 43 which favored neurite outgrowth and enhanced the synaptic activities of PC12 and SH-SY5Y neuronal cells without toxic or mitogenic effects, and decreased zinc-mediated β-amyloid aggregation without affecting membrane channel (IC50 >10 μM) or cytochrome P450 activity (IC50 > 6.5 μM) in vitro. In addition this quinazolin-4-one derivative enhanced memory performances in AD animal models with β-amyloid-induced hippocampal lesions. [HDACs, and specially HDAC6, correlate with neuronal impairment and cell death, normally via microtubule destabilization. These high levels of HDAC6 frequently lead to neurodegeneration in hippocampi of AD patients. Along with SAHA, other compounds including Tubacin, Tubastatin A, and quinazolin-4-one derivatives are HDAC6-selective inhibitors with valuable potential benefits on enhancing neurite extension and reducing cell death. Tubacin (EC50 = 2.5 μM in A549 cells) exhibits 70-fold higher selectivity for HDAC6 as compared to other HDAC inhibitors in alveolar basal epithelial A549 adenocarcinoma cells. Tubacin inhibits HDAC6-targeted α-tubulin deacetylation and migration in cancer cells expressing HDAC6. Furthermore, this compound attenuates tau phosphorylation in vitro ,190,191.lesions. .A number of studies demonstrate the beneficial effect of class III HDAC (SIRT) modulators for the treatment of several types of cancer; some of them are promising treatments for neurodegenerative disorders. Although SIRT inhibition often associates with activation of cell death pathways in multiple models of cancer, we will focus on those several SIRT inhibitors (SIRTi) that provide physiologically relevant benefits for neurodegenerative processes. Indeed, sirtuins, particularly SIRT2, favor the pathological progression of PD by promoting α-synuclein expression and aggregation. In this regard, SIRT2 inhibition rescued α-synuclein-mediated toxicity in several animal models of PD . Some of+-dependent HDACs (SIRT inhibitor) used in gene regulation experiments [Among the pan inhibitors, Nicotinamide is the most widely tested for treatment of neurodegenerative diseases, especially Alzheimer’s and Huntington diseases . Nicotineriments . This coeriments . Nicotineriments ,195,196.SIRT2 inhibitors are also widely tested in animal models of neurodegeneration ,198,199.50 of 3.5 μM), although SirReal2 is considered as the highest specific SIRT2 inhibitor, with an IC50 within the nM range [The vinyl nitrile compound AGK2 significantly reduces tubulin deacetylation and formation of large α-synuclein inclusions, resulting in the rescue of dopaminergic neurons in vitro and in animal PD models . AGK2 tanM range . SubstraOther relevant SIRT inhibitors are sirtinol and selisistat ,203,204.Stress signaling pathways resulting in DNA damage and impaired DNA repair mechanisms are common hallmarks of neurodegeneration. The brain protective roles of sirtuins (SIRT), which include response to stress and activation of DNA repair pathways, site SIRT activating compounds as good potential candidates for treatment of neurodegeneration ,208,209.2+ homeostasis, reduction of Aβ25–35 neurotoxicity, and Rho-associated kinase 1 downregulation [Resveratrol is a neuroprotective compound extracted from red grapes, with important antioxidant and anti-inflammatory roles which result in the inhibition of Aβ aggregation and Aβ-induced apoptosis ,211. Thigulation . Resveragulation ,214. Curgulation ,214 -2-ethoxy-6-pentadecyl benzamide (CTPB), which is considered as one of the unique p300-specific activator with the capability of crossing the blood brain barrier after intraperitoneal injection [Importantly, a variety of chemical modifications of different nonspecific HAT inhibitors in attempts to identify enzyme-specific inhibitors, came up with the synthesis of the njection ,54.Alternative strategies also consider natural products as HAT inhibitors . The mosCurcuma longa, L., used for dyspepsia, stress, and mood disorders [Curcumin is a phytochemical compound extracted from the rhizome of isorders . Curcumiisorders . This coisorders . Some stisorders . The comisorders , enhanceisorders ,223. Thrisorders ,226,227 isorders   as an additive for a nutraceutical compound versus placebo for treatment of mild to moderate AD [PSEN1 promoter methylation resulting in gene downregulation, which meliorate AD symptoms [This subgroup of epidrugs includes histone methyltransferase and histone demethylase inhibitors. The first ones modulate gene expression and promote DNA repair by inducing histone acetylation. Despite of their potential activity, these compounds are not often good candidates for preclinical studies due to their high toxicity and low specificity in different cell lines. SAMe, one of the most important methyl donors in the body, along with erate AD ,147,148 erate AD   that irreversibly blocks MAO A and MAO B with IC50 values of 2.3 and 0.95 μM and Ki values of 101.9 and 16 μM, respectively [The most analyzed histone demethylase family is the Lysine-specific demethylase 1 (LSD1), which is a flavin-dependent monoamine oxidase (MAO) that can demethylate mono- and dimethylated lysines, specifically histone 3 and lysines 4 and 9 (H3K4 and H3K9) and shares catalytic sites with MAO-A and MAO-B . Inhibitectively .Non-coding RNAs (ncRNAs) modulate the expression of genes involved in brain development and function. A number of diseases link with aberrant expression of those ncRNAs, which requires the implementation of new strategies that regulate ncRNA expression and function. Indeed several approaches include RNA interference as a novel and promising therapeutic strategy for the treatment of neurodegenerative diseases. These ncRNA-based treatment strategies include the use or modulation of miRNA analogs, miRNA precursors, and anti-miRNAs.BACE1 [One of the most popular strategies to reduce the detrimental effects involves downregulation of pathogenic genes. This may be achieved posttranscriptional levels by RNA interference mediated by small interference RNAs (siRNAs), short-hairpin RNAs (shRNAs), and micro-RNAs (miRNAs). Altering the expression of ncRNAs targeting pathogenic genes associated with the disease may be an acceptable strategy. However, the extremely high number of gene targets and associated ncRNAs would make the approach rather difficult. In this regard, different studies suggest more specific targets that may be suitable as potential treatments. In this regard, overexpression of miR-124 and miR-195 reduce Aβ levels by targeting BACE1 ,235, or BACE1 . Other nBACE1 ,240,241,BACE1 ,242, areBACE1 , while dBACE1 ,240. In BACE1 ,242. A rBACE1 .Other strategies deal with the regulation of other ncRNAs involved in cell growth, development, and homeostasis, such as miR-485 and miR-26a ,245. TheOther miRNA-based approaches target the components of the epigenetic machinery and exert direct control in DNA methylation and chromatin remodeling processes . These mOther promising epigenetic-based therapeutic approaches, currently submitted to preclinical studies ,247,248,ADHs), monoamine oxidases (MAOs), cytochrome p450 family genes (CYPs), and Phase II enzymes, which include UDP glucuronosyltransferases (UGTs), gluthatione S-transferase family genes (GSTs), N-acetyltransferase (NATs), and sulfonotransferases (SULTs); (iv) genes encoding drug transporters (Phase III), such as ATP-binding cassette family members (ABCs), solute carrier superfamily (SLCs), and the solute carrier organic transporter family (SLCOs); and (v) pleiotropic genes involved in multiple pathways and metabolic reactions [Drug pharmacodynamics and pharmacokinetics influence drug response in terms of efficiency, required dosage, and toxicity. The variability of genetic and epigenetic profiles, as well as disease determinants, explain the individual differences in drug response. Pharmacogenomics accounts for 30 to 90% of the variability in pharmacokinetics and pharmacodynamics. This variability depends on polymorphic variants of five different categories of genes: (i) pathogenic genes associated with disease development or potential risk. Not all individuals carrying the same disease present the same affected pathogenic genes; (ii) genes associated with the mechanism of action of drugs ; (iii) genes associated with drug metabolism. This category includes genes associated with Phase I enzymes, such as, alcohol dehydrogenases  in PD pathophysiology is fairly well-demonstrated , althougtibility  , are opening a novel, promising approach for the treatment of such complex diseases ,18,19,20Vicia faba L., for the prevention and treatment of PD [Alternative strategies in order to minimize clinical complications include the development of novel natural bioproducts with neuroprotective properties and additional benefits including antioxidant, anti-inflammatory, and neurotrophic effects. E-PodoFavalin-15999 (Atremorine) is an example of a novel bioproduct obtained by means of nondenaturing biotechnological procedures from structural components of nt of PD ,286,287.nt of PD ,286,287,nt of PD ,283. TheSince therapeutic outcomes are highly dependent upon the individual genomic and epigenomic profiles, personalized treatments should rely on pharmacogenetic and pharmacoepigenetic procedures to optimize therapeutics. Versatility of the epigenetic machinery allows the manipulation of epigenetic aberrations leading to drug resistance. Thus, routine procedures should incorporate pharmacoepigenetic studies for the proper evaluation of efficacy and safety issues in drug development and clinical trials. However, there is not information about long-term effects of epigenetic-based using targets without any particular cell specificity. Thus, despite substantial progress, the field of pharmacoepigenetics and the role of epigenetic modifications in human health and the treatment of disease require further investigation.


Deregulated transcription is a major driver of diseases such as cancer. Bromodomain and extra-terminal (BET) proteins  are chromatin readers essential for maintaining proper gene transcription by specifically binding acetylated lysine residues. Targeted displacement of BET proteins from chromatin, using BET inhibitors (I-BETs), is a promising therapy, especially for acute myeloid leukemia (AML), and evaluation of resistance mechanisms is necessary to optimize the clinical efficacy of these drugs.To uncover mechanisms of intrinsic I-BET resistance, we quantified chromatin binding and displacement for BRD2, BRD3 and BRD4 after dose response treatment with I-BET151, in sensitive and resistant in vitro models of leukemia, and mapped BET proteins/I-BET interactions genome wide using antibody- and compound-affinity capture methods followed by deep sequencing. The genome-wide map of BET proteins sensitivity to I-BET revealed a bimodal pattern of binding flanking transcription start sites (TSSs), in which drug-mediated displacement from chromatin primarily affects BRD4 downstream of the TSS and prolongs the pausing of RNA Pol II. Correlation of BRD4 binding and drug-mediated displacement at RNA Pol II pause sites with gene expression revealed a differential behavior of sensitive and resistant tumor cells to I-BET and identified a BRD4 signature at promoters of sensitive coding and non-coding genes.We provide evidence that I-BET-induced shift of Pol II pausing at promoters via displacement of BRD4 is a determinant of intrinsic I-BET sensitivity. This finding may guide pharmacological treatment to enhance the clinical utility of such targeted therapies in AML and potentially other BET proteins-driven diseases.The online version of this article (10.1186/s13072-019-0286-5) contains supplementary material, which is available to authorized users. Since the identification of the first epigenetic mechanism of oncogene regulation in 1983 –4. In adbromodomain and extra-terminal repeat (BET) proteins composed of the four paralogs BRD2, BRD3, BRD4 and BRDT [cis-regulation of genes by binding at enhancers and facilitating eRNA transcription [Bromodomain (BD)-containing proteins, 61 in humans, are readers of acetyl-lysine residues present on histones and other proteins . Membersand BRDT  with theand BRDT . The occand BRDT , 12. BRDand BRDT , 14, theand BRDT –18. Besicription , 20.Nut midline carcinoma), prostate cancer and ovarian cancer [The discovery of BRD3- and BRD4-NUT fusion genes in midline carcinoma  providedn cancer , 25–29. n cancer –32. Thron cancer , 33 causn cancer , 23, 25.n cancer , 34.I-BET-dependent displacement of BRD4 was observed at promoter as well as on enhancers and super-enhancers of target genes –37 such To understand the mechanism of intrinsic sensitivity and resistance to I-BET, we have undertaken an integrative epigenomic, chemo-genomic and transcriptomic approach by assessing the effects of increasing concentrations of I-BET151 on chromatin-bound BRD2, BRD3 and BRD4 and gene expression in one resistant (K562) and one sensitive  leukemia cell lines. Analysis of the spatial patterns of BRD2, BRD3 and BRD4 occupancy at promoters revealed a bimodal signature around the TSS and indicates that I-BET-mediated BRD4 displacement 150–180 bp downstream of the TSS is linked to strong and selective downregulation of gene expression in the I-BET-sensitive cell line. Finally, a handful of gene loci including four non-coding RNAs was identified for which BET protein binding is selectively affected upon I-BET treatment in MV4;11 compared to K562 cells as well as a transcriptional enrichment signature which hints at the molecular mechanism of intrinsic sensitivity to I-BET drugs.To evaluate I-BET resistance in leukemia, we used the pan-BET inhibitor GSK1210151A (I-BET151) [Quantitative PCR on both cell lines showed general and gradual decrease in BET proteins binding upon treatment with increasing inhibitor concentration Fig. c.Peak calling based on a MACS2-derived pipeline  followedInterestingly, more BRD4 binding was observed in the I-BET-sensitive MV4;11 cells compared to the I-BET-resistant K562 cells  analysis using DESeq2  “Materi” sectionThe number of affected TSSs increased with I-BET151 concentration in both cell lines: In total, 11% TSSs 3531) in the I-BET-sensitive MV4;11 and 1.6% TSSs (519) in the I-BET-resistant K562 showed significant displacement of BRD4 upon treatment with I-BET151 . Since most long non-coding RNAs including LINC-ROR are known to have very low expression levels at steady state [To check whether differential BRD4 displacement is reflected on transcription, we quantified the expression of the five genes which showed BRD4 displacement exclusively in the I-BET-sensitive cells after 50 nM I-BET treatment. All five genes were downregulated in MV4;11 cells and either not detected or less affected in K562 Fig. e. In MV4dy state –48, the The finding that four long non-coding RNAs with BRD4 binding at their promoters are among the most sensitive transcripts to I-BET in MV4;11 but not in K562 suggests a previously uncharacterized role for non-coding RNAs in conferring sensitivity to I-BET treatment.In order to map genome-wide BRD4/I-BET151 interactions, we used a chemical affinity capture-based method, Chem-seq , 24 Fig” sectionConversely, TSSs belonging to the highly sensitive core promoter cluster (cluster 4) showed a typical bimodal distribution with no notable enrichment downstream or upstream of the TSS after Chem-seq. Chemical affinity capture of BET proteins bound to chromatin occurs mainly via the BD2 domain and thus is a measure of BD2 occupancy . This obNext, we were interested to know whether I-BET treatment also affected global gene expression differentially in resistant and sensitive cell lines and if so, whether the differentially affected genes are connected to specific cellular pathways.RNA-seq was performed in MV4;11 and K562 cells treated with 50, 500 or 5000 nM I-BET151 “” sectionTo correlate BRD4 displacement from promoter regions with corresponding gene expression at a global level, we compared the number of genes showing differential BRD4 binding at TSS to those exhibiting differential expression. Although both MV4;11 and K562 exhibited a similar number of downregulated genes  and conversely downregulated in the I-BET-resistant K562-treated cells . Although K562 cells do not express a functional form of TP53, the P53 pathway is known to be functional in this cell line [We then identified enriched pathways using gene set enrichment analysis (GSEA)  in pre-rell line . SimilarBRD4 displacement at promoters has been linked to downregulation of its target genes. Since BRD4 is essential for transcription elongation which starts downstream of the TSS, we postulated that BRD4 displacement at 1 Kb downstream of the TSS, spanning the Pol II pause site, is mostly responsible for affecting gene expression. To test for this hypothesis, we compared gene expression of the different DB clusters identified above Fig. c betweenp = 3.5e−13 and p < 2.2 e−16, respectively). The expression of genes belonging to clusters 1 and 2 defined in K562 is similarly affected by I-BET treatment in both cell lines . Most interestingly, genes belonging to the highly sensitive pause site cluster in MV4;11 showed a very significant reduction in expression in this cell line compared to the corresponding category of genes in K562 . Moreover, this is in strong contrast to the genes in the highly sensitive core promoter cluster that show no reduction in expression in the sensitive cell line MV4;11 (p = 0.96).Genes with sensitive and highly sensitive core promoter and pause site to I-BET in MV4;11 cells  are highly downregulated by I-BET in this cell line but not in the I-BET-resistant K562 cells . For the sensitive and highly sensitive core promoter and pause site clusters, 5.4% (68/1265) and 6.3% (28/444) genes displayed an increase in their TR, respectively, when compared to the core promoter sensitive cluster  , also known as travelling ratio (TR). To test this hypothesis, we compared the TR for all four MV4;11 clusters before and after treatment with 500 nM I-BET  “Materi” sectionrs, 5.4% 8/1265 anTo summarize, sensitivity of MV4;11 cells to I-BET is characterized by a strong displacement of BRD4 downstream of the TSS which coincides with a longer pausing of RNA Pol II and a subsequent decrease in gene expression.Quantitative analysis of drug response enables the evaluation of compound-effect relationship and allows us to distinguish specific and direct outcomes of compound treatment from random and downstream consequences. Epigenetic drugs function by engaging their target(s) on chromatin, which usually induces or modifies a transcriptional response. Albeit the consequences of I-BET binding to their targets have been extensively studied , a genomGene set enrichment analysis revealed that the expression of genes belonging to proliferation/apoptosis-associated pathways is differentially regulated between the two cell lines upon I-BET treatment. Upregulated genes of the P53 pathway were mostly enriched in the I-BET-sensitive MV4;11 cells and downregulated in K562 cells . Cells were seeded at 5000 cells/well in 96-well plates, 1 µl of I-BET151 was added per well from 100 × DMSO stocks , and cells were incubated for 72 h. Cell viability was measured using CellTiter Glo assay kit (Promega) following the manufacturer’s instructions. The response area in Fig. ® Enzymatic Chromatin IP Kit (CST #9004), and DNA was digested to mostly mononucleosomes as recommended by the manufacturer.ChIP-seq and Chem-seq assays were performed as described previously . Briefly® Chromatin IP Buffer (#14231), once with SimpleChIP® Chromatin IP Buffer containing 350 mM NaCl, once with SimpleChIP® Chromatin IP Buffer containing 125 mM LiCl and once with Tris–EDTA buffer. Beads were eluted with SimpleChIP® elution buffer by incubation at 65 °C for 30 min. After addition of 200 mM final NaCl, samples were placed at 65 °C overnight for reverse cross-linking. ChIP conditions were optimized for each protein by ChIP-qPCR using the recovery of positive and negative regions. For this, the positive primer set used to target the ZC3H4 locus was AATGCACGAAAAAGGACTGC as forward and TATACCCCATTCCCATCAGG as reverse. The negative primers were ordered form Active Motif ® .For ChIP-seq, anti-BRD4 (Bethyl labs #A301-985A), anti-BRD3 (Bethyl Labs #A302-368A) and anti-BRD2 (Bethyl Labs #A302-583A) antibodies were added to the lysate and incubated for 3 h at 4 °C. Protein G magnetic beads (Thermo Scientific #10004D) were then added and incubated for 1 h at 4 °C. The lysate was then aspirated, and the beads were washed twice with 200 µl SimpleChIPFor Chem-seq, lysates from untreated cells were incubated either with DMSO or with 10μM I-BET121 for 2.5 h at 4 °C. Dynabeads MyOne Streptavidin T1 (Thermo Scientific #65602) coupled to biotinylated I-BET121, were added to the lysate and incubated for 1 h at 4 °C. After washing, beads were eluted by incubation in elution buffer at 65 °C for 30 min. After addition of 200 mM final NaCl, samples were placed at 65 °C overnight for reverse X-linking.® ChIP-Seq Library Prep Master Mix Set for Illumina® (NEB), and samples were sequenced in a 50 bp single end run on the Illumina HiSeq-2000.Library preparation of immunoprecipitated DNA was done using the NEBNextBarcoded stranded mRNA-seq libraries were prepared from high-quality total RNA samples (~ 200 ng/sample) using the Illumina TruSeq RNA Sample Preparation Kit  implemented on the liquid handling robot Beckman FXP2. Obtained libraries that passed the QC step were pooled in equimolar amounts; 10 pM solution of this pool was loaded on the Illumina sequencer HiSeq 2000 and sequenced unidirectionally, generating ~ 180 million reads (30 million reads per each library), each 50 bases long.MV4;11 and K562 cells were cultured as described above, plated in 6-well plates and treated for 6 h with either DMSO or I-BET151 . Four replicates were cultured per condition. Cells were lysed immediately after collection, and lysates were stored at − 80 °C. RNA was extracted using the Rneasy mini kit . cDNA was synthesized using the Protoscript 2 kit  according to manufacturer’s specifications. qPCR was performed in duplicate using 0.9 µl cDNA per reaction, default SYBR green cycling settings (StepOne software), StepOnePlus thermocyclers  and SYBR Green PCR master mix .Reference transcripts were chosen based on RNA-seq data with the following criteria: (1) unaffected by the experimental treatment (nonsignificant expression changes up to 500 nM I-BET 151 treatment) and (2) expression higher than 0.8 quantile in both K562 and MV4;11.otud5, nap1l1 and tm9sf4), otud5 was chosen as reference since it exhibited the smallest change in expression between DMSO and I-BET151-treated samples in both cell lines.Out of three reference genes having the requirements listed above , LOC101930452 , LINC01585 , LINC-ROR , NRON , OTUD5 .The primers used are: A list of MV4;11 enhancers and super-enhancers were obtained from the Dawson lab . They co−3 –broad –broad-cutoff 1e−3). We then obtained the pre-final set of peaks by considering common peaks to the tree runs performed above. Peaks were then filtered for ENCODE blacklisted regions corresponding to regions with anomalous and high signal/read counts using bedtools [To overcome limitations in peak calling algorithms for factors with broad signal, including chromatin readers, we derived a macs2 -based pibedtools  leading Quality check for raw sequencing reads was performed using FastQC  mainly tPol II Traveling ratio was calculated by dividing read density on promoter, defined as − 100 bp to + 300 bp from TSS, by read density on gene body defined as 301 bp from TSS until end of gene.MV4;11 raw data and peaks (fastq files) for H3K27ac, H4K5ac and Pol II were downloaded from NCBI GEO (GSE71780) . AnalysiRefSeq TSSs were downloaded from UCSC genome browser (hg19), and duplicate records were removed. Two categories were created using bedtools slop  in orderReads were aligned to the human genome (G1k V37) with Tophat2  and BowtAdditional file 1: Table S1. Counts of raw and processed reads for each assay (ChIP-seq or Chem-Seq), protein (BRD2/3/4), condition  and cell line  used. Percentage of uniquely mapped reads is also shown.Additional file 2: Figure S1. Diagram depicting the strategy used to call peaks described in Materials and Methods.Additional file 3: Figure S2. Barplot with the number of peaks called for each condition and for both cell lines (a) for all peaks and (b) for peaks overlapping a TSS − 1 Kb or a TSS + 1 Kb. (c) Stacked barplot showing the percentage of peaks falling in TSS −/+ 1 Kb (blue), H3K27ac marked regions excluding TSS −/+ 1 Kb (orange) and other intergenic or genic regions excluding TSS −/+ 1 Kb and H3K27ac marked sites (gray) after treating cells in DMSO, 50 nM, 500 nM or 5000 nM I-BET151.Additional file 4: Table S2. Number of peaks called for each condition and cell line, peaks falling on the TSS −/+ 1 Kb, those present in H3K27ac marked regions excluding TSS −/+ 1 Kb and remaining peaks.Additional file 5: Figure S3. Genome-wide ChIP-seq profiles on intergenic typical enhancers and super-enhancers for BRD2, BRD3 and BRD4 after treating cells in DMSO and with different concentrations of I-BET151. Upper panel shows the profiles for K562 and lower panel for MV4;11. All ChIP-seq profiles are RPGC (Reads Per Genomic Content) normalized with input subtraction. Plots are generated with the same y-scale for comparison purposes. “Start” and “End” for typical and super-enhancers were based on the median size of the corresponding enhancer category.Additional file 6: Table S3. Number of events with differential binding at TSS − 1 Kb and + 1 Kb. In addition to information in Fig. Additional file 7: Table S4. Table of DESeq2 differential binding (DB) results for all TSSs in MV4;11. TSSs are represented by their gene name followed by the Refseq ID in the form name_REFSEQ_ID. This nomenclature allows us to differentiate between TSSs belonging to different transcripts of the same gene. Column names contain the information on the protein (BRD4) and the inhibitor concentration, i.e., mb4_50_1 Kb_Up.log2FoldChange corresponds to the log2 fold change of the DB analysis on MV4;11 (m), for the protein BRD4 (b4) at 50 nM of inhibitor (50) for TSS − 1 Kb (1 Kb_UP).Additional file 8: Table S5. Same as supplementary Table 4 but for K562.Additional file 9: Table S6. List of all clusters and TSSs belonging to each of them (represented by their gene and transcript name) in MV4;11 and K562 as defined in Fig. Additional file 10: Figure S4. Genome browser visualization of a locus from each of the 4 clusters defined in MV4;11 in Fig. Additional file 11: Table S7. Table of DESeq2 differential expression (DE) in MV4;11 representing for each gene (ensID and symbol) the log fold change and adjusted p value for all inhibitor concentrations using DMSO as a reference.Additional file 12: Table S8. Same as supplementary Table 7 but for K562.Additional file 13: Figure S5. Gene set enrichment analysis for all I-BET treatment conditions in both cell lines. Normalized enrichment scores (NES) of GSEA for hallmark gene sets v6.1. Listed are all hallmark that shows significant NES (− 1 < NES or NES > 1). Log2 fold changes of gene expression in MV4;11 or K562 treated with I-BET 50 nM, 500 nM or 5000 nM compared to DMSO were used to identify enriched sets. Red bars correspond to enriched gene sets for upregulated genes and blue for downregulated genes.