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2021 ◽  
Vol 15 ◽  
Ada Man-Choi Ho ◽  
Stacey J. Winham ◽  
Bryan M. McCauley ◽  
Marija Kundakovic ◽  
Keith D. Robertson ◽  

Rapid cycling (RC) burdens bipolar disorder (BD) patients further by causing more severe disability and increased suicidality. Because diagnosing RC can be challenging, RC patients are at risk of rapid decline due to delayed suitable treatment. Here, we aimed to identify the differences in the circulating cell-free DNA (cfDNA) methylome between BD patients with and without RC. The cfDNA methylome could potentially be developed as a diagnostic test for BD RC. We extracted cfDNA from plasma samples of BD1 patients (46 RC and 47 non-RC). cfDNA methylation levels were measured by 850K Infinium MethylationEPIC array. Principal component analysis (PCA) was conducted to assess global differences in methylome. cfDNA methylation levels were compared between RC groups using a linear model adjusted for age and sex. PCA suggested differences in methylation profiles between RC groups (p = 0.039) although no significant differentially methylated probes (DMPs; q > 0.15) were found. The top four CpG sites which differed between groups at p < 1E-05 were located in CGGPB1, PEX10, NR0B2, and TP53I11. Gene set enrichment analysis (GSEA) on top DMPs (p < 0.05) showed significant enrichment of gene sets related to nervous system tissues, such as neurons, synapse, and glutamate neurotransmission. Other top notable gene sets were related to parathyroid regulation and calcium signaling. To conclude, our study demonstrated the feasibility of utilizing a microarray method to identify circulating cfDNA methylation sites associated with BD RC and found the top differentially methylated CpG sites were mostly related to the nervous system and the parathyroid.

Chengcheng Shi ◽  
Liang Yan ◽  
Jie Gao ◽  
Shitong Chen ◽  
Li-Rong Zhang

Aims: To investigate the effects of ABCB1 DNA methylation in donors on individual differences in tacrolimus blood concentrations following liver transplantation. Methods: Twenty-three donor liver samples carrying the CYP3A5*3/*3 genotype were classified into two groups based on the initial tacrolimus concentration/dose (C0/D) ratio following liver transplantation. ABCB1 mRNA levels in liver tissues and HepG2 cells were determined by qRT-PCR. DNA methylation status in liver tissues and HepG2 cells was determined using Illumina 850 methylation chip sequencing technology and pyrosequencing. 5-Aza-2dC was used to reverse methylation in HepG2 cells. Intracellular tacrolimus concentrations were determined by liquid mass spectrometry. Results: Genome-wide methylation sequencing and pyrosequencing analyses showed that the methylation levels of three ABCB1 CpG sites (cg12501229, cg00634941, and cg05496710) were significantly different between groups with different tacrolimus C0/D ratios. ABCB1 mRNA expression in donor livers was found to be positively correlated with tacrolimus C0/D ratio (r = 0.458, P < 0.05). After treatment with 5-Aza-2-Dc, the methylation levels of the ABCB1 CpG sites in HepG2 cells significantly decreased, and this was confirmed by pyrosequencing; there was also a significant increase in ABCB1 transcription, and this most likely induced a decrease in intracellular tacrolimus concentrations. Conclusions: ABCB1 CpG site methylation affects tacrolimus metabolism in humans by regulating ABCB1 expression. Therefore, ABCB1 DNA methylation in donor livers might be an important epigenetic factor that affects tacrolimus blood concentrations following liver transplantation.

2021 ◽  
Vol 22 (1) ◽  
Tong Wang ◽  
Weijing Wang ◽  
Weilong Li ◽  
Haiping Duan ◽  
Chunsheng Xu ◽  

Abstract Background Previous studies have determined the epigenetic association between DNA methylation and pulmonary function among various ethnics, whereas this association is largely unknown in Chinese adults. Thus, we aimed to explore epigenetic relationships between genome-wide DNA methylation levels and pulmonary function among middle-aged Chinese monozygotic twins. Methods The monozygotic twin sample was drawn from the Qingdao Twin Registry. Pulmonary function was measured by three parameters including forced expiratory volume the first second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio. Linear mixed effect model was used to regress the methylation level of CpG sites on pulmonary function. After that, we applied Genomic Regions Enrichment of Annotations Tool (GREAT) to predict the genomic regions enrichment, and used comb-p python library to detect differentially methylated regions (DMRs). Gene expression analysis was conducted to validate the results of differentially methylated analyses. Results We identified 112 CpG sites with the level of P < 1 × 10–4 which were annotated to 40 genes. We identified 12 common enriched pathways of three pulmonary function parameters. We detected 39 DMRs located at 23 genes, of which PRDM1 was related to decreased pulmonary function, and MPL, LTB4R2, and EPHB3 were related to increased pulmonary function. The gene expression analyses validated DIP2C, ASB2, SLC6A5, and GAS6 related to decreased pulmonary function. Conclusion Our DNA methylation sequencing analysis on identical twins provides new references for the epigenetic regulation on pulmonary function. Several CpG sites, genes, biological pathways and DMRs are considered as possible crucial to pulmonary function.

eLife ◽  
2021 ◽  
Vol 10 ◽  
Ipsita Agarwal ◽  
Molly Przeworski

Whole exome sequences have now been collected for millions of humans, with the related goals of identifying pathogenic mutations in patients and establishing reference repositories of data from unaffected individuals. As a result, we are approaching an important limit, in which datasets are large enough that, in the absence of natural selection, every highly mutable site will have experienced at least one mutation in the genealogical history of the sample. Here, we focus on CpG sites that are methylated in the germline and experience mutations to T at an elevated rate of ~10-7 per site per generation; considering synonymous mutations in a sample of 390,000 individuals, ~99% of such CpG sites harbor a C/T polymorphism. Methylated CpG sites provide a natural mutation saturation experiment for fitness effects: as we show, at current sample sizes, not seeing a non-synonymous polymorphism is indicative of strong selection against that mutation. We rely on this idea in order to directly identify a subset of CpG transitions that are likely to be highly deleterious, including ~27% of possible loss-of-function mutations, and up to 20% of possible missense mutations, depending on the type of functional site in which they occur. Unlike methylated CpGs, most mutation types, with rates on the order of 10-8 or 10-9, remain very far from saturation. We discuss what these findings imply for interpreting the potential clinical relevance of mutations from their presence or absence in reference databases and for inferences about the fitness effects of new mutations.

2021 ◽  
Vol 22 (22) ◽  
pp. 12572
Humaira Noor ◽  
Ashraf Zaman ◽  
Charles Teo ◽  
Michael E. Sughrue

Lower-grade glioma (LGG) is a diffuse infiltrative tumor of the central nervous system, which lacks targeted therapy. We investigated the role of Podocan-like 1 (PODNL1) methylation in LGG clinical outcomes using the TCGA-LGG transcriptomics dataset. We identified four PODNL1 CpG sites, cg07425555, cg26969888, cg18547299, and cg24354933, which were associated with unfavorable overall survival (OS) and disease-free survival (DFS) in univariate and multivariate analysis after adjusting for age, gender, tumor-grade, and IDH1-mutation. In multivariate analysis, the OS and DFS hazard ratios ranged from 0.44 to 0.58 (p < 0.001) and 0.62 to 0.72 (p < 0.001), respectively, for the four PODNL1 CpGs. Enrichment analysis of differential gene and protein expression and analysis of 24 infiltrating immune cell types showed significantly increased infiltration in LGGs and its histological subtypes with low-methylation levels of the PODNL1 CpGs. High PODNL1 expression and low-methylation subgroups of the PODNL1 CpG sites were associated with significantly increased PD-L1, PD-1, and CTLA4 expressions. PODNL1 methylation may thus be a potential indicator of immune checkpoint blockade response, and serve as a biomarker for determining prognosis and immune subtypes in LGG.

2021 ◽  
Vol 12 ◽  
Kari Guderud ◽  
Line H. Sunde ◽  
Siri T. Flåm ◽  
Marthe T. Mæhlen ◽  
Maria D. Mjaavatten ◽  

BackgroundMethotrexate (MTX) is the first line treatment of rheumatoid arthritis (RA), and methylation changes in bulk T cells have been reported after treatment with MTX. We have investigated cell-type specific DNA methylation changes across the genome in naïve and memory CD4+ T cells before and after MTX treatment of RA patients. DNA methylation profiles of newly diagnosed RA patients (N=9) were assessed by reduced representation bisulfite sequencing.ResultsWe found that MTX treatment significantly influenced DNA methylation levels at multiple CpG sites in both cell populations. Interestingly, we identified differentially methylated sites annotated to two genes; TRIM15 and SORC2, previously reported to predict treatment outcome in RA patients when measured in bulk T cells. Furthermore, several of the genes, including STAT3, annotated to the significant CpG sites are relevant for RA susceptibility or the action of MTX.ConclusionWe detected CpG sites that were associated with MTX treatment in CD4+ naïve and memory T cells isolated from RA patients. Several of these sites overlap genetic regions previously associated with RA risk and MTX treatment outcome.

2021 ◽  
Christopher Adanty ◽  
Ahmad Shakeri ◽  
John Strauss ◽  
Ariel Graff ◽  
Vincenzo De Luca

Aim: To explore possible differences in genome-wide methylation between schizophrenia patients who consume various antipsychotics. Methods: We compared DNA methylation in leukocytes between the following cohorts: clozapine (n = 19) versus risperidone (n = 19), clozapine (n = 12) versus olanzapine (n = 12), clozapine (n = 9) versus quetiapine (n = 9) and clozapine (n = 33) versus healthy controls (n = 33). Subjects were matched for age, sex, ethnicity, smoking status and leukocyte proportions. Results: No single CpG site reached genome-wide significance for clozapine versus risperidone/olanzapine/quetiapine. For clozapine versus quetiapine, one significantly differentially methylated region was found – ch5: 176797920–176798049 (fwer = 0.075). Clozapine versus healthy controls yielded thousands of significantly differentially methylated CpG sites. Conclusions: Establishing antipsychotic induced genome-wide methylation patterns will further elucidate the biological and clinical effects of antipsychotic administration.

Lea Zillich ◽  
Josef Frank ◽  
Fabian Streit ◽  
Marion M. Friske ◽  
Jerome C. Foo ◽  

AbstractAlcohol use disorder (AUD) is closely linked to the brain regions forming the neurocircuitry of addiction. Postmortem human brain tissue enables the direct study of the molecular pathomechanisms of AUD. This study aims to identify these mechanisms by examining differential DNA-methylation between cases with severe AUD (n = 53) and controls (n = 58) using a brain-region-specific approach, in which sample sizes ranged between 46 and 94. Samples of the anterior cingulate cortex (ACC), Brodmann Area 9 (BA9), caudate nucleus (CN), ventral striatum (VS), and putamen (PUT) were investigated. DNA-methylation levels were determined using the Illumina HumanMethylationEPIC Beadchip. Epigenome-wide association analyses were carried out to identify differentially methylated CpG-sites and regions between cases and controls in each brain region. Weighted correlation network analysis (WGCNA), gene-set, and GWAS-enrichment analyses were performed. Two differentially methylated CpG-sites were associated with AUD in the CN, and 18 in VS (q < 0.05). No epigenome-wide significant CpG-sites were found in BA9, ACC, or PUT. Differentially methylated regions associated with AUD case-/control status (q < 0.05) were found in the CN (n = 6), VS (n = 18), and ACC (n = 1). In the VS, the WGCNA-module showing the strongest association with AUD was enriched for immune-related pathways. This study is the first to analyze methylation differences between AUD cases and controls in multiple brain regions and consists of the largest sample to date. Several novel CpG-sites and regions implicated in AUD were identified, providing a first basis to explore epigenetic correlates of AUD.

2021 ◽  
Vol 1 ◽  
Yuxing Chen ◽  
Yixin Yan ◽  
Moping Xu ◽  
Wen Chen ◽  
Jinyu Lin ◽  

Background: More than 150 types of brain tumors have been documented. Accurate diagnosis is important for making appropriate therapeutic decisions in treating the diseases. The goal of this study is to develop a DNA methylation profile-based classifier to accurately identify various kinds of brain tumors.Methods: Thirteen datasets of DNA methylation profiles were downloaded from the Gene Expression Omnibus (GEO) database, of which GSE90496 and GSE109379 were used as the training set and the validation set, respectively, and the remaining 11 sets were used as the independent test set. The random forest algorithm was used to select the CpG sites based on the importance of the features and a multilayer perceptron (MLP) model was trained to classify the samples. Deconvolution with the debCAM package was used to explore the cellular composition difference among tumors.Results: From training datasets with 2,801 samples, 396,568 CpG sites were retained after preprocessing, of which 767 were selected as the modeling features. A three-layer MLP model was developed, which consists of 1,320 nodes in the hidden layer, to predict the histological types of brain tumors. The prediction accuracy is 99.2, 87.0, and 96.58%, respectively, on the training, validation and test sets. The results of deconvolution analysis showed that the cell proportions of different tumor subtypes were different, and it is approximately enough to distinguish different tumor entities.Conclusion: We developed a classifier that is robust for the classification of central nervous system tumors, and tried to analyze the reasons for the classification performance.

Blood ◽  
2021 ◽  
Vol 138 (Supplement 1) ◽  
pp. 2376-2376
Anilkumar Gopalakrishnapillai ◽  
Erin Lynn Crowgey ◽  
Adam Marsh ◽  
E. Anders Kolb ◽  
Sonali P. Barwe

Abstract Pediatric acute myeloid leukemia (AML) patients possessing rearrangement of the KMT2A (previously known as MLL) gene on 11q23 constitute a subclass with a particularly poor prognosis. The five-year survival rate for these patients is only about 44% due to poor response to conventional chemotherapy and frequent early relapse. Aberrant epigenetic modifications play an important role in leukemogenesis in KMT2A-rearranged leukemia. Accordingly, several epigenome modifying drugs have been tested in preclinical studies of KMT2A-rearranged leukemia. Acknowledging the co-regulatory effects of DNA methylation and histone modifications in determining chromatin structure and governing gene expression, we combined DNA hypomethylating agent azacitidine with histone deacetylase inhibitor panobinostat in the hopes of achieving greater efficacy. We showed that this epigenetic drug combination was more efficacious than single agents using cell line derived xenograft models of pediatric AML (Gopalakrishnapillai et al., Leuk Res, 2017). We evaluated the efficacy of this epigenetic drug combination in patient-derived xenograft models of KMT2A rearranged pediatric AML and observed that similar to MV4;11 model, this combination induced complete remission in NTPL-146 model with KMT2A-MLLT1 fusion (Fig. 1A, P&lt;0.001). We analyzed the methylome of AML cells harvested from xenografted mice treated with control, azacitidine, panobinostat, or a combination of the two. Methylation sensitive restriction endonucleases were utilized to fragment genomic DNA prior to library construction for next generation sequencing. GenPro software platform designed for highly quantitative, sensitive, and low error-rate detection of methylation at individual CpG sites was used. Methylation patterns between treatment groups were discriminated using an ordinate analysis technique of non-metric multidimensional scaling (NMDS) (Fig. 1B). CpG methylation profiles were compared among the four groups analyzed to isolate patterns conserved within groups while also differing between groups. The first two component axes were plotted to locate the individual sample points in a 2D plane. Samples from distinct PDX models undergoing similar treatment clustered together. The panobinostat-treated samples showed minimal differences compared to the control, while the azacitidine-treated samples clustered away. Interestingly, the samples treated with the combination, did not overlap with either treatment, indicating that although panobinostat alone showed minimal impact on methylation patterns, panobinostat together with azacitidine produced a distinct methylation pattern. Venn intersection sets of statistically significant differentially methylated CpG sites in the 3-way analyses derived from the control group comparisons showed 2086 CpG sites exclusively altered in the combination treatment (Fig. 1C). In order to determine the effect of the combination treatment on global methylation, the differences in methylation load (dML) per each CpG site between control and the combination treatment were summed across 1MB genome intervals and the distribution of these dML was plotted (Fig. 1D). There was a strong shift in methylation signal, with the majority of the intervals being hypomethylated in the treatment group compared to the control. Although global hypomethylation was observed in combination treatment, the most statistically significant CpG sites were hypermethylated in the combination treatment compared to the control as seen in the volcano plot in which log fold-change was plotted against the p-value (Fig. 1E). Circular ideogram presented with a mean subtraction of CpG methylation scores to calculate a summation methylation load score across chromosomal domains (Fig. 1F). The correlative association between top CpG sites is shown as arcs tracking the highest correlation for each CpG site. Gene labels indicate the positions of the top 60 CpG sites, with green and red indicating higher methylation in control and in combination treatment respectively. In conclusion, we have identified differential methylation patterns following in vivo treatment of KMT2A rearranged pediatric AML xenograft models with azacitidine and panobinostat combination compared to azacitidine alone. These methylation changes are likely to influence the increased survival seen in mice receiving combination treatment. Figure 1 Figure 1. Disclosures Gopalakrishnapillai: Geron: Research Funding. Marsh: Genome Profiling LLC: Current Employment. Barwe: Prelude Therapeutics: Research Funding.

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