Differential Methylation Analysis Research Articles

Abstract 3632: Differential DNA methylation in the benign and cancerous prostate tissue of African American and European American men

Abstract In this study, we compare patterns of differential DNA methylation (DNAm) distinguishing tumor and benign prostate tissue in European American (EA) and African American (AA) men to improve our understanding of biological mechanisms that may underlie prostate cancer (PCa) disparities. In the United States, AA men are more likely to be diagnosed with and to die of PCa compared with EA men. Changes in DNAm accompany tumor development and progression, and differences in DNAm across ancestry groups may be an important lens through which to study PCa disparities. We collected paired tumor and histologically benign formalin-fixed paraffin-embedded tissue blocks from 151 (76 AA, 75 EA) PCa patients undergoing prostatectomy at the University of Chicago. DNA was extracted and genome-wide DNAm was measured at ~850,000 CpG sites using the Illumina MethylationEpic Array. After quality control, 682,694 CpGs remained for analysis. We conducted differential methylation analyses, adjusting for batch, age, and individual and identified 29,236 and 38,035 tumor-associated CpGs in AA and EA respectively (p<5x10-8 and Δβ>0.3) with 25,263 CpGs common to both sets. There was a depletion of differentially methylated CpGs in CpG islands and promoters in both groups, but depletion was stronger in AA. Tumor-associated CpGs within islands and in promoters were more likely to be hypermethylated for both groups, though this was stronger in EA. We identified 2,392 genes with differentially methylated promoters common to both ancestry groups; 223 and 1,045 were unique to AA and EA respectively. Shared gene regions included GSTP1, APC, RARB, and GRASP, which have been previously reported. We assigned CpG sites to genes and used Gene Set Enrichment Analysis to identify differentially methylated pathways. The identified pathways include several previously associated with cancer development including the epithelial mesenchymal transition. We also identified ancestry-specific pathways including the early and late estrogen response pathways in AA. Examining the predictive ability of our differentially methylated CpGs, we found that relatively few CpGs (~10) were sufficient to distinguish tumor and benign tissue in AA and EA men (AUC>0.9). Scores constructed from differentially methylated CpGs in EA were able to predict tumor vs benign in AA (and vice versa) with high accuracy. Finally, we examined the association between ancestry and DNAm in both tumor and benign tissue. Here, 89 and 423 ancestry-associated CpGs were identified in tumor and benign respectively. Overall, we find that differential methylation patterns distinguishing tumor and benign tissue are generally similar for EA and AA men. However, differenced in tumor-associated DNAm as well as the presence of ancestry-associated CpGs provide a rich area for future studies exploring the impact of these differences on cancer development in AA and EA men. Citation Format: Meytal B. Chernoff, Marc Gillard, Kathryn Demanelis, Dayana Delgado, Anthony Williams, Donald Vander Griend, Brandon L. Pierce. Differential DNA methylation in the benign and cancerous prostate tissue of African American and European American men [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 3632.

Abstract 6283: Reannotation and normalisation of Infinium 850k data for improved analysis of methylation at enhancers and non-coding RNAs

Abstract In this study, we evaluated the MethylationEPIC BeadChip (850k) technology for enhancer methylation analysis with respect to RRBS, both high-throughput technologies commonly used to screen large patient cohorts. We developed and applied a new approach to re-annotate the 850k data, which greatly improved the association of probes to enhancers and show that 850k targets more enhancers than RRBS. We further investigated the reproducibility of the two technologies and applied various existing normalization methods to 850k data that reduce variability between replicates and variability with other technologies. We thereby showed that normalization methods developed for 450k greatly reduced variability in 850k data to a level below that of highly variable RRBS data. We finally performed differential methylation analysis with 850k data from breast cancer samples applying our new re-annotation method and highlight that the majority of differentially methylated cytosines were detected with probes specific to the 850k mapping to enhancers, confirming the deregulation of enhancer methylation in breast cancer. In summary, our study provides a new annotation for the 850k array, which greatly increases the number of cytosines mapping to enhancers and therefore allows for the improved analysis of enhancer methylation. Overall, we conclude that the 850k array allows for detection of methylation changes in regions not covered by previous Infinium arrays and is the best choice, as compared to RRBS, for high-throughput analysis of enhancer methylation in large clinical cohorts. Citation Format: Martin Bizet, Matthieu Defrance, Emilie Calonne, Gianluca Bontempi, François Fuks, Jana Jeschke. Reannotation and normalisation of Infinium 850k data for improved analysis of methylation at enhancers and non-coding RNAs [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6283.

DNA methylation signatures in airway cells from adult children of asthmatic mothers reflect subtypes of severe asthma

Maternal asthma (MA) is among the most consistent risk factors for asthma in children. Possible mechanisms for this observation are epigenetic modifications in utero that have lasting effects on developmental programs in children of mothers with asthma. To test this hypothesis, we performed differential DNA methylation analyses of 398,186 individual CpG sites in primary bronchial epithelial cells (BECs) from 42 nonasthma controls and 88 asthma cases, including 56 without MA (NMA) and 32 with MA. We used weighted gene coexpression network analysis (WGCNA) of 69 and 554 differentially methylated CpGs (DMCs) that were specific to NMA and MA cases, respectively, compared with controls. WGCNA grouped 66 NMA-DMCs and 203 MA-DMCs into two and five comethylation modules, respectively. The eigenvector of one MA-associated module (turquoise) was uniquely correlated with 85 genes expressed in BECs and enriched for 36 pathways, 16 of which discriminated between NMA and MA using machine learning. Genes in all 16 pathways were decreased in MA compared with NMA cases (P = 7.1 × 10−3), a finding that replicated in nasal epithelial cells from an independent cohort (P = 0.02). Functional interpretation of these pathways suggested impaired T cell signaling and responses to viral and bacterial pathogens. The MA-associated turquoise module eigenvector was additionally correlated with clinical features of severe asthma and reflective of type 2 (T2)-low asthma (i.e., low total serum immunoglobulin E, fractional exhaled nitric oxide, and eosinophilia). Overall, these data suggest that MA alters diverse epigenetically mediated pathways that lead to distinct subtypes of severe asthma in adults, including hard-to-treat T2-low asthma.

RARE-08. Profiling of recurrent adamantinomatous cranionpharyngioma confirms the activation of the MAPK pathway and identifies copy number aberrations in relapsed tumours

Craniopharyngiomas are rare challenging tumours, with around 25% of cases recurring despite surgery and/or radiotherapy. Whilst transcriptomic and proteomic profiling of adamantinomatous craniopharyngioma (ACP) have revealed activation of the MAPK pathway and IL-6 mediated inflammation, relatively little is known about the biological processes involved in tumour recurrence. To address this, we have analysed a cohort of primary and relapsed ACP tumour accessed from tissue banks, local pathology departments and international collaborators. Serial samples of recurrent ACP (n=11), recurrent papillary craniopharyngioma (PCP) (n=4) and 3 non-recurrent ACP were analysed using β-catenin, pERK1/2 immunostaining, DNA methylation array and RNA sequencing. Differential expression and methylation analyses confirmed differences between ACP and PCP, with over representation of WNT pathway genes in ACP and the MAPK pathway genes in PCP. All of the primary and all except for one of the relapsed ACP tumours showed a pERK1/2 expression. Differences in the immune environment were also identified between ACP and PCP, with higher levels of some inflammatory mediators and CD14+ cell signatures in PCP compared with ACP. Whilst differential methylation and expression analysis revealed relatively stable methylomes and transcriptomes between serial samples of cases, segmental chromosomal alterations were identified in recurrence samples from five ACP cases (5/11,45%). One relapsed case showed histological and molecular signs of malignant transformation, including high ki67 and deletion of TP53. Surprisingly, this malignant tumour showed nuclear beta-catenin in all neoplastic epithelial cells and absence of pERK1/2 staining, despite the primary tumour showing the typical beta-catenin and pERK1/2 expression patterns. These results suggest that the molecular landscape of craniopharyngioma remains stable between recurrences in most cases, but, there is evidence of molecular evolution in a subset of cases. Activation of the MAPK pathway in the vast majority of ACP tumours supports the clinical evaluation of MAPK pathway inhibitors in ACP patients.

MEDB-43. Development of a bioinformatics pipeline for identification of differential DNA methylation events associated with medulloblastoma relapse

Relapsed medulloblastoma (rMB) is treatment-resistant and fatal in ~95% of cases. The epigenetic features of rMB, and any role as drivers of disease relapse/treatment-resistance have yet to be investigated. We therefore developed a pipeline to identify differentially methylated CpGs (DM-CpGs) and regions (DMRs) in a paired-rMB cohort. Our paired-rMB cohort (n=61, relapsed tumours matched with diagnosis counterparts) with available Illumina Methylation 450K/850K microarray data was processed in R-Studio. The packages Limma and DMRcate were used to perform a paired differential methylation analysis on a filtered selection of array probes (n=335,767), identifying DM-CpGs and DMRs with a 5% FDR. DMRs were further retained if they had a maximum-Δβ of >0.2 and correlated with locus-specific gene expression in a separate paired DNA-methylation array/RNA-seq cohort from medulloblastoma diagnosis samples (n=202). Finally, we created univariable Cox models to assess the prognostic potential of DM-CpGs/DMRs in an independent survival cohort of medulloblastoma diagnosis samples (n=498). Across the paired-rMB cohort, there were few significant differential methylation events initially identified at relapse (n=258 DM-CpGs, n=32 DMRs). Upon sub-analysis by molecular group, MBGroup4 (n=18 pairs) alone yielded significant findings (n=189 DM-CpGs, n=26 DMRs). Most changes involved hypermethylation events detected at relapse. Multiple DM-CpGs identified at relapse were prognostic for both overall and event-free survival when assessed in our independent cohort (n=22 whole cohort, n=13 Group 4, BH-adjusted p<0.05). When applying the DMR filters, only the MBGroup4 DMRs passed the Δβ filter (n=18/26), with few correlating with gene expression (n=2, p<0.001), and none demonstrating prognostic significance. This pipeline facilitates exploration of the clinical relevance of epigenome-wide changes in a paired-rMB cohort. We highlight the potential prognostic significance of DM-CpGs, and future work will explore the potential functional role of candidate-genes associated with our DMRs, as novel drivers of rMB.

Epigenomic Analysis Reveals the KCNK9 Potassium Channel as a Potential Therapeutic Target for Adenomyosis.

Adenomyosis is linked to dysmenorrhea and infertility. The pathogenesis of adenomyosis remains unclear, and little is known of the genetic and epigenetic changes in the eutopic endometrium in adenomyosis, which may predispose patients to the invasion and migration of endometrial tissues into the myometrium. Transcriptome studies have identified genes related to various cell behaviors but no targets for therapeutic intervention. The epigenetics of the eutopic endometrium in adenomyosis have rarely been investigated. Endometrial tissue was obtained from premenopausal women with (n = 32) or without adenomyosis (n = 17) who underwent hysterectomy aged 34–57 years at a tertiary hospital. The methylome and transcriptome were assessed by using a Methylation 450 K BeadChip array and Affymetrix expression microarray. Protein expression was examined by immunohistochemistry. Differential methylation analysis revealed 53 lowly methylated genes and 176 highly methylated genes with consistent gene expression in adenomyosis, including three genes encoding potassium ion channels. High expression of KCNK9 in the eutopic and ectopic endometria in patients with adenomyosis but not in normal controls was observed. Hormone-free, antibody-based KCNK9 targeting is a potential therapeutic strategy for adenomyosis-related dysmenorrhea, menorrhagia, and infertility.

Differential Methylation Analysis of Suicidal Ideation Severity in Schizophrenia with the Illumina MethylationEPIC Array.

There is a multitude of factors that makes difficult to identify those at risk for suicide, especially among schizophrenia patients. Suicide cannot be explained by genetics alone, therefore epigenetic mechanisms including DNA methylation are thought to play a role. DNA methylation could be a valuable tool in helping predict those at-risk individuals. This cross-sectional study comprised 112 subjects diagnosed with schizophrenia spectrum disorders, and were grouped according to the current suicidal ideation severity. DNA methylation across the genome was measured with the Infinium® MethylationEPIC BeadChip. We utilized the dmpFinder and bumphunter functions within the Bioconductor minfi package to identify differentially methylated positions (DMPs) and differentially methylated regions (DMRs), respectively. Following quality control, we removed one sample from the analysis and reported the most significant DMPs and DMRs associated with suicidal ideation severity. All positions and regions identified in this analysis were only found to have suggestive levels of significance at the genome-wide level. The present study was one of the first to investigate genome-wide methylation and suicidal ideation severity. While there were many strengths of our study, including investigating both differentially methylated positions and regions, further larger-scale studies are necessary to replicate, support, and validate our findings presented here.

The Polymorphism and Expression of EGFL7 and miR-126 Are Associated With NSCLC Susceptibility.

Previous investigations have reported that microRNA-126 (miR-126) and its host gene, epidermal growth factor-like domain-containing protein 7 (EGFL7) are involved in lung cancer progression, suggesting EGFL7 and miR-126 play a joint role in lung cancer development. In this study, we analyzed the methylation-associated regulation of EGFL7 and miR-126 in non-small cell lung cancer (NSCLC) and further investigated the association between EGFL7/miR-126 polymorphisms and NSCLC susceptibility in the Han Chinese population. Based on our data, relative to those in adjacent normal tissue, both EGFL7 expression and miR-126 expression were decreased significantly in lung cancer tissue (P = 3x10-4 and P < 1x10-4), and the expression of EGFL7 mRNA and miR-126 was significantly correlated in both NSCLC tissue n = 46, r = 0.43, P = 0.003 and adjacent normal tissue n = 46, r = 0.37, P = 0.011. Differential methylation analysis indicated that methylation levels of multiple CG loci in EGFL7 were significantly higher in the lung cancer samples than in the normal samples (P < 0.01). Moreover, EGFL7 mRNA and miR-126 were significantly upregulated after treatment with the DNA demethylating agent 5-aza-2′-deoxycytidine (5-Aza-CdR) in lung cancer cell lines. In addition, the A allele of rs2297538 was significantly associated with a decreased NSCLC risk (OR = 0.68, 95% CI: 0.52~0.88), and the expression of EGFL7 and miR-126 was significantly lower in rs2297538 homozygous G/G tumor tissue than in A/G+A/A tumor tissue (P = 0.01 and P = 0.002). Our findings suggest that the expression of EGFL7 and miR-126 in NSCLC can be concomitantly downregulated through methylation and the EGFL7/miR-126 polymorphism rs2297538 is correlated with NSCLC risk. Together, these results provide new insights into the pathogenesis of NSCLC.

Interplay Between Stress and Reproduction: Novel Epigenetic Markers in Response to Shearing Patterns in Australian Merino Sheep (Ovis aries).

In this study, we determined the effect(s) of early shearing on Australian Merino ewes (Ovis aries) and their lambs. To test this research question, we used a suite of field and laboratory methods including GPS collars, wool cortisol, and epigenetic change between ewes and lambs identified using Illumina NovaSeq RRBS. Once shorn ewes (n = 24) were kept on their full fleece throughout the entire gestation period, whereas twice (early) shorn ewes (n = 24) had their wool shorn pre-joining. Top-knot wool sample was taken from ewes during pre-joining, day 50 (mid-gestation), and day 90 (late gestation) for laboratory analysis. Ewes were pregnancy scanned at mid-gestation to determine whether they were early or late parturition (this confirmation is provided by the pregnancy scanner based on fetus size). Top-knot wool sample was also taken from the lambs at weaning for hormone and wool quality testing. Ear tissue was taken from ewes at day 50 (mid-gestation) and from lambs at lamb marking for DNA analysis. Results showed that twice or early shorn ewes grazed 10% higher and maintained stronger body condition than once shorn ewes. Wool cortisol levels were also significantly lower in the early shorn ewes between mid- and late gestation. Lambs bred from twice shorn ewes had on average better visual wool quality parameters in terms of micron, spin finesses, and curvature. For the DNA methylation results, when comparing a group of once sheared with twice sheared ewes, we have discovered one locus (Chr20:50404014) that was significantly differentially methylated [False Discovery Rate (FDR) = 0.005]. This locus is upstream of a protein-coding gene (ENSOARG00000002778.1), which shows similarities to the forkhead box C1 (FOXC1) mRNA using BLAST searches. To further our understanding of the potential interaction between pregnancy status and shearing frequency of the ewes, we performed further differential methylation analysis using a combination of shearing treatment and pregnancy scanning status. The comparisons (1) late pregnancy vs. early pregnancy for ewes with one shearing treatment and (2) late pregnancy vs. early pregnancy for sheep with two shearing treatments were carried out to identify associations between loci and pregnancy duration for sheep with either one or two shearing events. We discovered that 36 gene loci were significantly modulated either between different shearing treatments or late vs. early pregnancy status of ewes. This result suggests that maternal pregnancy and nutritional status during gestation influence DNA methylation. We further investigated DNA methylation in lambs and identified 16 annotated gene loci that showed epigenetic modulation as a result of being born from an early or late stage pregnancy. From the genomics data, we pointed out that ewes go through epigenetic modifications during gestation, and there is a degree of intra-individual variation in the reproductive performance of ewes, which could be due to combination of intrinsic (genetic and physiological) and extrinsic (management and climatic) factors. Collectively, this research provides novel dataset combining physiological, molecular epigenetics, and digital tracking indices that advances our understanding of how Merino ewes respond to shearing frequency, and this information could guide further research on Merino sheep breeding and welfare.

Cellular context determines DNA methylation profiles in SWI/SNF-deficient cancers of the gynecologic tract.

SWI/SNF (SWItch/Sucrose Non-Fermentable) complex deficiency has been reported in a wide variety of cancers and is often associated with an undifferentiated phenotype. In the gynecologic tract SWI/SNF-deficient cancers are diagnostically challenging and little is known about their cellular origins. Here we show that undifferentiated endometrial carcinoma (UDEC), SMARCA4-deficient uterine sarcoma (SDUS), and ovarian small cell carcinoma, hypercalcemic type (SCCOHT) harbor distinct DNA methylation signatures despite shared morphology and SWI/SNF inactivation. Our results indicate that the cellular context is an important determinant of the epigenetic landscape, even in the setting of core SWI/SNF deficiency, and therefore methylation profiling may represent a useful diagnostic tool in undifferentiated, SWI/SNF-deficient cancers. Furthermore, applying copy number analyses and group-wise differential methylation analyses including endometrioid endometrial carcinomas and extracranial malignant rhabdoid tumors, we uncover analogous molecular features in SDUS and SCCOHT in contrast to UDEC. These results suggest that SDUS and SCCOHT represent chromosomally stable SWI/SNF-deficient cancers of the gynecologic tract, which are within the broader spectrum of malignant rhabdoid tumors. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Tissue-Specific Methylation Biosignatures for Monitoring Diseases: An In Silico Approach.

Tissue-specific gene methylation events are key to the pathogenesis of several diseases and can be utilized for diagnosis and monitoring. Here, we established an in silico pipeline to analyze high-throughput methylome datasets to identify specific methylation fingerprints in three pathological entities of major burden, i.e., breast cancer (BrCa), osteoarthritis (OA) and diabetes mellitus (DM). Differential methylation analysis was conducted to compare tissues/cells related to the pathology and different types of healthy tissues, revealing Differentially Methylated Genes (DMGs). Highly performing and low feature number biosignatures were built with automated machine learning, including: (1) a five-gene biosignature discriminating BrCa tissue from healthy tissues (AUC 0.987 and precision 0.987), (2) three equivalent OA cartilage-specific biosignatures containing four genes each (AUC 0.978 and precision 0.986) and (3) a four-gene pancreatic β-cell-specific biosignature (AUC 0.984 and precision 0.995). Next, the BrCa biosignature was validated using an independent ccfDNA dataset showing an AUC and precision of 1.000, verifying the biosignature’s applicability in liquid biopsy. Functional and protein interaction prediction analysis revealed that most DMGs identified are involved in pathways known to be related to the studied diseases or pointed to new ones. Overall, our data-driven approach contributes to the maximum exploitation of high-throughput methylome readings, helping to establish specific disease profiles to be applied in clinical practice and to understand human pathology.

Differential DNA methylation analysis of SUMF2, ADAMTS5, and PXDN provides novel insights into colorectal cancer prognosis prediction in Taiwan.

BACKGROUNDPatients with colorectal cancer (CRC) undergo surgery, as well as perioperative chemoradiation or adjuvant chemotherapy primarily based on the tumor–node– metastasis (TNM) cancer staging system. However, treatment responses and prognostic outcomes of patients within the same stage vary markedly. The potential use of novel biomarkers can improve prognostication and shared decision making before implementation into certain therapies.AIMTo investigate whether SUMF2, ADAMTS5, and PXDN methylation status could be associated with CRC prognosis.METHODSWe conducted a Taiwanese cohort study involving 208 patients with CRC recruited from Tri-Service General Hospital and applied the candidate gene approach to identify three genes involved in oncogenesis pathways. A methylation-specific polymerase chain reaction (MS-PCR) and EpiTYPER DNA methylation analysis were employed to detect methylation status and to quantify the methylation level of candidate genes in tumor tissue and adjacent normal tissue from participants. We evaluated SUMF2, ADAMTS5, and PXDN methylation as predictors of prognosis, including recurrence-free survival (RFS), progression-free survival (PFS), and overall survival (OS), using a Cox regression model and Kaplan–Meier analysis.RESULTSWe revealed various outcomes related to methylation and prognosis. Significantly shorter PFS and OS were associated with the CpG_3+CpG_7 hypermethylation of SUMF2 from tumor tissue compared with CpG_3+CpG_7 hypomethylation [hazard ratio (HR) = 2.24, 95% confidence interval (CI) = 1.03-4.85 for PFS, HR = 2.56 and 95%CI = 1.08-6.04 for OS]. By contrast, a significantly longer RFS was associated with CpG_2 and CpG_13 hypermethylation of ADAMTS5 from normal tissue compared with CpG_2 and CpG_13 hypomethylation [HR (95%CI) = 0.15 (0.03-0.71) for CpG_2 and 0.20 (0.04-0.97) for CpG_13]. The relationship between the methylation status of PXDN and the prognosis of CRC did not reach statistical significance.CONCLUSIONOur study found that CpG_3+CpG_7 hypermethylation of SUMF2 from tumor tissue was associated with significantly shorter PFS and OS compared with CpG_3+CpG_7 hypomethylation. CpG_2 and CpG_13 hypermethylation of ADAMTS5 from normal tissue was associated with a significantly longer RFS compared with CpG_2 and CpG_13 hypomethylation. These methylation-related biomarkers which have implications for CRC prognosis prediction may aid physicians in clinical decision-making.

Genomic variations and epigenomic landscape of the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel

BackgroundThe teleost medaka (Oryzias latipes) is a well-established vertebrate model system, with a long history of genetic research, and multiple high-quality reference genomes available for several inbred strains. Medaka has a high tolerance to inbreeding from the wild, thus allowing one to establish inbred lines from wild founder individuals.ResultsWe exploit this feature to create an inbred panel resource: the Medaka Inbred Kiyosu-Karlsruhe (MIKK) panel. This panel of 80 near-isogenic inbred lines contains a large amount of genetic variation inherited from the original wild population. We use Oxford Nanopore Technologies (ONT) long read data to further investigate the genomic and epigenomic landscapes of a subset of the MIKK panel. Nanopore sequencing allows us to identify a large variety of high-quality structural variants, and we present results and methods using a pan-genome graph representation of 12 individual medaka lines. This graph-based reference MIKK panel genome reveals novel differences between the MIKK panel lines and standard linear reference genomes. We find additional MIKK panel-specific genomic content that would be missing from linear reference alignment approaches. We are also able to identify and quantify the presence of repeat elements in each of the lines. Finally, we investigate line-specific CpG methylation and performed differential DNA methylation analysis across these 12 lines.ConclusionsWe present a detailed analysis of the MIKK panel genomes using long and short read sequence technologies, creating a MIKK panel-specific pan genome reference dataset allowing for investigation of novel variation types that would be elusive using standard approaches.

A Sight of the Diagnostic Value of Aberrant Cell-Free DNA Methylation in Lung Cancer.

Background Lung cancer is one of the most commonly diagnosed cancer worldwide. As one of the liquid biopsy analytes, alternations in cell-free DNA (cfDNA) methylation could function as promising biomarkers for lung cancer detection. Methods In this study, differential methylation analysis was performed to identify candidate markers, and lasso regression with 10-fold cross-validation (CV) was used to establish the diagnostic marker panel. The performance of the binary classifier was evaluated using the receiver operating characteristic (ROC) curve and the precision-recall (PR) curve. Results We identified 4072 differentially methylated regions (DMRs) based on cfDNA methylation data, and then a 10-DMR marker panel was established. The panel achieved an area under the ROC curve (AUROC) of 0.922 and an area under the PR curve (AUPR) of 0.899 in a cfDNA cohort containing 29 lung cancer and 74 normal samples, showing outstanding performance. Besides, the cfDNA-derived markers also performed well in primary tissue datasets, which were more robust than the tissue-derived markers. Conclusion Our study suggested that the 10-DMR marker panel attained high accuracy and robustness and may function as a novel and promising target for lung cancer detection.

DNA methylation signatures in Blood DNA of Hutchinson-Gilford Progeria syndrome.

Hutchinson–Gilford Progeria Syndrome (HGPS) is an extremely rare genetic disorder caused by mutations in the LMNA gene and characterized by premature and accelerated aging beginning in childhood. In this study, we performed the first genome‐wide methylation analysis on blood DNA of 15 patients with progeroid laminopathies using Infinium Methylation EPIC arrays including 8 patients with classical HGPS. We could observe DNA methylation alterations at 61 CpG sites as well as 32 significant regions following a 5 Kb tiling analysis. Differentially methylated probes were enriched for phosphatidylinositol biosynthetic process, phospholipid biosynthetic process, sarcoplasm, sarcoplasmic reticulum, phosphatase regulator activity, glycerolipid biosynthetic process, glycerophospholipid biosynthetic process, and phosphatidylinositol metabolic process. Differential methylation analysis at the level of promoters and CpG islands revealed no significant methylation changes in blood DNA of progeroid laminopathy patients. Nevertheless, we could observe significant methylation differences in classic HGPS when specifically looking at probes overlapping solo‐WCGW partially methylated domains. Comparing aberrantly methylated sites in progeroid laminopathies, classic Werner syndrome, and Down syndrome revealed a common significantly hypermethylated region in close vicinity to the transcription start site of a long non‐coding RNA located anti‐sense to the Catenin Beta Interacting Protein 1 gene (CTNNBIP1). By characterizing epigenetically altered sites, we identify possible pathways/mechanisms that might have a role in the accelerated aging of progeroid laminopathies.

CDK13-related disorder: Report of a series of 18 previously unpublished individuals and description of an epigenetic signature

PurposeRare genetic variants in CDK13 are responsible for CDK13-related disorder (CDK13-RD), with main clinical features being developmental delay or intellectual disability, facial features, behavioral problems, congenital heart defect, and seizures. In this paper, we report 18 novel individuals with CDK13-RD and provide characterization of genome-wide DNA methylation. MethodsWe obtained clinical phenotype and neuropsychological data for 18 and 10 individuals, respectively, and compared this series with the literature. We also compared peripheral blood DNA methylation profiles in individuals with CDK13-RD, controls, and other neurodevelopmental disorders episignatures. Finally, we developed a support vector machine–based classifier distinguishing CDK13-RD and non–CDK13-RD samples. ResultsWe reported health and developmental parameters, clinical data, and neuropsychological profile of individuals with CDK13-RD. Genome-wide differential methylation analysis revealed a global hypomethylated profile in individuals with CDK13-RD in a highly sensitive and specific model that could aid in reclassifying variants of uncertain significance. ConclusionWe describe the novel features such as anxiety disorder, cryptorchidism, and disrupted sleep in CDK13-RD. We define a CDK13-RD DNA methylation episignature as a diagnostic tool and a defining functional feature of the evolving clinical presentation of this disorder. We also show overlap of the CDK13 DNA methylation profile in an individual with a functionally and clinically related CCNK-related disorder.

The Effect of Model Directionality on Cell-Type-Specific Differential DNA Methylation Analysis.

Calling differential methylation at a cell-type level from tissue-level bulk data is a fundamental challenge in genomics that has recently received more attention. These studies most often aim at identifying statistical associations rather than causal effects. However, existing methods typically make an implicit assumption about the direction of effects, and thus far, little to no attention has been given to the fact that this directionality assumption may not hold and can consequently affect statistical power and control for false positives. We demonstrate that misspecification of the model directionality can lead to a drastic decrease in performance and increase in risk of spurious findings in cell-type-specific differential methylation analysis, and we discuss the need to carefully consider model directionality before choosing a statistical method for analysis.

Differential Methylation Analysis for Bisulfite Sequencing (BS-Seq) Data.

Bisulfite sequencing (BS-seq) technology has enabled the detection and measurement of DNA methylation at the single-nucleotide level. A fundamental question in functional epigenomics research is whether DNA methylation varies under different biological contexts. Thus, identifying differentially methylated loci/regions (DML/DMRs) is a key task in BS-seq data analysis. Here we describe detailed procedures to perform differential methylation analyses for BS-seq using the Bioconductor package DSS. The analysis scheme in this chapter will guide researchers through differential methylation analyses by providing step-by-step instructions for analytical tools.

Differential Methylation Analysis in Neuropathologically Confirmed Dementia with Lewy Bodies

Differential Methylation Analysis in Neuropathologically Confirmed Dementia with Lewy Bodies

BCurve: Bayesian Curve Credible Bands Approach for the Detection of Differentially Methylated Regions.

High-throughput assays have been developed to measure DNA methylation, among which bisulfite-based sequencing (BS-seq) and microarray technologies are the most popular for genome-wide profiling. A major goal in DNA methylation analysis is the detection of differentially methylated genomic regions under two different conditions. To accomplish this, many state-of-the-art methods have been proposed in the past few years; only a handful of these methods are capable of analyzing both types of data (BS-seq and microarray), though. On the other hand, covariates, such as sex and age, are known to be potentially influential on DNA methylation; and thus, it would be important to adjust for their effects on differential methylation analysis. In this chapter, we describe a Bayesian curve credible bands approach and the accompanying software, BCurve, for detecting differentially methylated regions for data generated from either microarray or BS-Seq. The unified theme underlying the analysis of these two different types of data is the model that accounts for correlation between DNA methylation in nearby sites, covariates, and between-sample variability. The BCurve R software package also provides tools for simulating both microarray and BS-seq data, which can be useful for facilitating comparisons of methods given the known "gold standard" in the simulated data. We provide detailed description of the main functions in BCurve and demonstrate the utility of the package for analyzing data from both platforms using simulated data from the functions provided in the package. Analyses of two real datasets, one from BS-seq and one from microarray, are also furnished to further illustrate the capability of BCurve.