DNA Methylation Studies Research Articles

Malignancies in Patients with Celiac Disease: Diagnostic Challenges and Molecular Advances.

Celiac disease (CD) is a multiorgan autoimmune disorder of the chronic intestinal disease group characterized by duodenal inflammation in genetically predisposed individuals, precipitated by gluten ingestion. The pathogenesis of celiac disease is now widely studied, overcoming the limits of the purely autoimmune concept and explaining its hereditability. The genomic profiling of this condition has led to the discovery of numerous genes involved in interleukin signaling and immune-related pathways. The spectrum of disease manifestations is not limited to the gastrointestinal tract, and a significant number of studies have considered the possible association between CD and neoplasms. Patients with CD are found to be at increased risk of developing malignancies, with a particular predisposition of certain types of intestinal cancer, lymphomas, and oropharyngeal cancers. This can be partially explained by common cancer hallmarks present in these patients. The study of gut microbiota, microRNAs, and DNA methylation is evolving to find the any possible missing links between CD and cancer incidence in these patients. However, the literature is extremely mixed and, therefore, our understanding of the biological interplay between CD and cancer remains limited, with significant implications in terms of clinical management and screening protocols. In this review article, we seek to provide a comprehensive overview of the genomics, epigenomics, and transcriptomics data on CD and its relation to the most frequent types of neoplasms that may occur in these patients.

Differential CpG DNA methylation of peripheral B cells, CD4+ T cells, and salivary gland tissues in IgG4-related disease

ObjectivesImmunoglobulin-G4-related disease (IgG4-RD) is a distinct systemic autoimmune-mediated disease manifesting as chronic inflammation and tissue fibrosis. Since the role of DNA methylation in the pathogenesis of IgG4-RD is still unclear, we conduct this study to investigate epigenetic modifications in IgG4-RD.MethodsA genome-wide DNA methylation study was conducted with B cells, CD4+ T cells, and salivary gland tissues from IgG4-RD patients and matched controls by using the Illumina HumanMethylation 850K BeadChip. We further performed pyrosequencing and immunohistochemistry assays to validate the methylation status of some targets of interest.ResultsWe identified differentially methylated CpG sites including 44 hypomethylated and 166 hypermethylated differentially methylated probes (DMPs) in B cells and 260 hypomethylated and 112 hypermethylated DMPs in CD4+ T cells from 10 IgG4-RD patients compared with 10 healthy controls. We also identified 36945 hypomethylated and 78380 hypermethylated DMPs in salivary gland tissues of 4 IgG4-RD patients compared with 4 controls. DPM2 (cg21181453), IQCK (cg10266221), and ABCC13 (cg05699681, cg04985582) were hypermethylated and MBP (cg18455083) was hypomethylated in B cells, CD4+ T cells, and salivary gland tissues of IgG4-RD patients. We also observed the hypomethylated HLA-DQB2 in CD4+ T cells from IgG4-RD patients. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis of DMPs in salivary gland tissues of IgG4-RD patients revealed enrichment of pathways involved in the regulation of immune cell responses and fibrosis.ConclusionThis is the first DNA methylation study in peripheral B cells, CD4+ T cells, and salivary gland tissues from IgG4-RD patients. Our findings highlighted the role of epigenetic modification of DNA methylation and identified several genes and pathways possibly involved in IgG4-RD pathogenesis.

Integrated DNA Methylation/RNA Profiling in Middle Temporal Gyrus of Alzheimer’s Disease

Alzheimer’s disease is a neurodegenerative disorder clinically defined by gradual cognitive impairment and alteration in executive function. We conducted an epigenome-wide association study (EWAS) of a clinically and neuropathologically characterized cohort of 296 brains, including Alzheimer’s disease (AD) and non-demented controls (ND), exploring the relationship with the RNA expression from matched donors. We detected 5246 CpGs and 832 regions differentially methylated, finding overlap with previous EWAS but also new associations. CpGs previously identified in ANK1, MYOC, and RHBDF2 were differentially methylated, and one of our top hits (GPR56) was not previously detected. ANK1 was differentially methylated at the region level, along with APOE and RHBDF2. Only a small number of genes showed a correlation between DNA methylation and RNA expression statistically significant. Multiblock partial least-squares discriminant analysis showed several CpG sites and RNAs discriminating AD and ND (AUC = 0.908) and strongly correlated with each other. Furthermore, the CpG site cg25038311 was negatively correlated with the expression of 22 genes. Finally, with the functional epigenetic module analysis, we identified a protein–protein network characterized by inverse RNA/DNA methylation correlation and enriched for “Regulation of insulin-like growth factor transport”, with IGF1 as the hub gene. Our results confirm and extend the previous EWAS, providing new information about a brain region not previously explored in AD DNA methylation studies. The relationship between DNA methylation and gene expression is not significant for most of the genes in our sample, consistently with the complexities in the gene expression regulation.Graphical

DNA Methylation Analysis in Monozygotic Twins Discordant for ALS in Blood Cells.

ALS is a fatal motor neuron disease that displays a broad variety of phenotypes ranging from early fatal courses to slowly progressing and rather benign courses. Such divergence can also be seen in genetic ALS cases with varying phenotypes bearing specific mutations, suggesting epigenetic mechanisms like DNA methylation act as disease modifiers. However, the epigenotype dictated by, in addition to other mechanisms, DNA methylation is also strongly influenced by the individual's genotype. Hence, we performed a DNA methylation study using EPIC arrays on 7 monozygotic (MZ) twin pairs discordant for ALS in whole blood, which serves as an ideal model for eliminating the effects of the genetic-epigenetic interplay to a large extent. We found one CpG site showing intra-pair hypermethylation in the affected co-twins, which maps to the Glutamate Ionotropic Receptor Kainate Type Subunit 1 gene (GRIK1). Additionally, we found 4 DMPs which were subsequently confirmed using 2 different statistical approaches. Differentially methylated regions or blocks could not be detected within the scope of this work. In conclusion, we revealed that despite a low sample size, monozygotic twin studies discordant for the disease can bring new insights into epigenetic processes in ALS, pointing to new target loci for further investigations.

A Metaheuristic Technique for Cluster-Based Feature Selection of DNA Methylation Data for Cancer

Epigenetics is the study of phenotypic variations that do not alter DNA sequences. Cancer epigenetics has grown rapidly over the past few years as epigenetic alterations exist in all human cancers. One of these alterations is DNA methylation; an epigenetic process that regulates gene expression and often occurs at tumor suppressor gene loci in cancer. Therefore, studying this methylation process may shed light on different gene functions that cannot otherwise be interpreted using the changes that occur in DNA sequences. Currently, microarray technologies; such as Illumina Infinium BeadChip assays; are used to study DNA methylation at an extremely large number of varying loci. At each DNA methylation site, a beta value (β) is used to reflect the methylation intensity. Therefore, clustering this data from various types of cancers may lead to the discovery of large partitions that can help objectively classify different types of cancers as well as identify the relevant loci without user bias. This study proposed a Nested Big Data Clustering Genetic Algorithm (NBDC-GA); a novel evolutionary metaheuristic technique that can perform cluster-based feature selection based on the DNA methylation sites. The efficacy of the NBDC-GA was tested using real-world data sets retrieved from The Cancer Genome Atlas (TCGA); a cancer genomics program created by the National Cancer Institute (NCI) and the National Human Genome Research Institute. The performance of the NBDC-GA was then compared with that of a recently developed metaheuristic Immuno-Genetic Algorithm (IGA) that was tested using the same data sets. The NBDC-GA outperformed the IGA in terms of convergence performance. Furthermore, the NBDC-GA produced a more robust clustering configuration while simultaneously decreasing the dimensionality of features to a maximum of 67% and of 94.5% for individual cancer type and collective cancer, respectively. The proposed NBDC-GA was also able to identify two chromosomes with highly contrasting DNA methylations activities that were previously linked to cancer.

A Cautionary Tale of Sexing by Methylation: Hybrid Bisulfite-Conversion Sequencing of Immunoprecipitated Methylated DNA in Chrysemys picta Turtles with Temperature-Dependent Sex Determination Reveals Contrasting Patterns of Somatic and Gonadal Methylation, but No Unobtrusive Sex Diagnostic.

Background: The gonads of Chrysemys picta, a turtle with temperature-dependent sex determination (TSD), exhibit differential DNA methylation between males and females, but whether the same is true in somatic tissues remains unknown. Such differential DNA methylation in the soma would provide a non-lethal sex diagnostic for TSD turtle hatchings who lack visually detectable sexual dimorphism when young. Methods: Here, we tested multiple approaches to study DNA methylation in tail clips of Chrysemys picta hatchlings, to identify differentially methylated candidate regions/sites that could serve as molecular sex markers To detect global differential methylation in the tails we used methylation-sensitive ELISA, and to test for differential local methylation we developed a novel hybrid method by sequencing immunoprecipitated and bisulfite converted DNA (MeDIP-BS-seq) followed by PCR validation of candidate regions/sites after digestion with a methylation-sensitive restriction enzyme. Results: We detected no global differences in methylation between males and females via ELISA. While we detected inter-individual variation in DNA methylation in the tails, this variation was not sexually dimorphic, in contrast with hatchling gonads. Conclusions: Results highlight that differential DNA methylation is tissue-specific and plays a key role in gonadal formation (primary sexual development) and maintenance post-hatching, but not in the somatic tail tissue.

Inferring regulatory element landscapes and gene regulatory networks from integrated analysis in eight hulless barley varieties under abiotic stress

BackgroundThe cis-regulatory element became increasingly important for resistance breeding. There were many DNA variations identified by resequencing. To investigate the links between the DNA variations and cis-regulatory element was the fundamental work. DNA variations in cis-regulatory elements caused phenotype variations in general.ResultsWe used WGBS, ChIP-seq and RNA-seq technology to decipher the regulatory element landscape from eight hulless barley varieties under four kinds of abiotic stresses. We discovered 231,440 lowly methylated regions (LMRs) from the methylome data of eight varieties. The LMRs mainly distributed in the intergenic regions. A total of 97,909 enhancer-gene pairs were identified from the correlation analysis between methylation degree and expression level. A lot of enriched motifs were recognized from the tolerant-specific LMRs. The key transcription factors were screened out and the transcription factor regulatory network was inferred from the enhancer-gene pairs data for drought stress. The NAC transcription factor was predicted to target to TCP, bHLH, bZIP transcription factor genes. We concluded that the H3K27me3 modification regions overlapped with the LMRs more than the H3K4me3. The variation of single nucleotide polymorphism was more abundant in LMRs than the remain regions of the genome.ConclusionsEpigenetic regulation is an important mechanism for organisms to adapt to complex environments. Through the study of DNA methylation and histone modification, we found that many changes had taken place in enhancers and transcription factors in the abiotic stress of hulless barley. For example, transcription factors including NAC may play an important role. This enriched the molecular basis of highland barley stress response.

DNA methylation QTL mapping across diverse human tissues provides molecular links between genetic variation and complex traits.

Studies of DNA methylation (DNAm) in solid human tissues are relatively scarce; tissue-specific characterization of DNAm is needed to understand its role in gene regulation and its relevance to complex traits. We generated array-based DNAm profiles for 987 human samples from the Genotype-Tissue Expression (GTEx) project, representing 9 tissue types and 424 subjects. We characterized methylome and transcriptome correlations (eQTMs), genetic regulation in cis (mQTLs and eQTLs) across tissues and e/mQTLs links to complex traits. We identified mQTLs for 286,152 CpG sites, many of which (>5%) show tissue specificity, and mQTL colocalizations with 2,254 distinct GWAS hits across 83 traits. For 91% of these loci, a candidate gene link was identified by integration of functional maps, including eQTMs, and/or eQTL colocalization, but only 33% of loci involved an eQTL and mQTL present in the same tissue type. With this DNAm-focused integrative analysis, we contribute to the understanding of molecular regulatory mechanisms in human tissues and their impact on complex traits.

Evaluation of cytosine conversion methods for whole-genome DNA methylation profiling

Background: DNA methylation, the most common epigenetic modification, is defined as the removal or addition of methyl groups to cytosine bases. Studying DNA methylation provides insight into the regulation of gene expression, transposon mobility, genomic stability, and genomic imprinting. Whole-genome DNA methylation profiling (WGDM) is a powerful tool to find DNA methylation. This technique combines standard whole-genome sequencing methodology (e.g., Illumina high-throughput sequencing) with additional steps where unmethylated cytosine is converted to uracil. However, factors such as low cytosine conversion efficiency and inadequate DNA recovery during sample preparation oftentimes render poor-quality data. It is therefore imperative to benchmark sample preparation protocols to increase sequencing data quality and reduce false positives in methylation detection. Methods: A survey analysis was performed to investigate the efficiency of the following commercially available cytosine conversion kits when coupled with the NEBNext® Ultra™ DNA Library Prep Kit for Illumina (NEB): Zymo Research EZ DNA Methylation™ kit (hereafter known as Zymo Conversion kit), QIAGEN EpiTect Bisulfite kit (hereafter known as QIAGEN Conversion kit), and NEBNext® Enzymatic Methyl-seq Conversion Module (hereafter known as NEB EM-seq kit). Input DNA was derived from soybean (Glycine max [L.] Merrill) leaf tissue. Results: Of those tested, the QIAGEN Conversion kit provided the best sample recovery and the highest number of sequencing reads, whereas the Zymo Conversion kit had the best cytosine conversion efficiency and the least duplication. The sequence library obtained with the NEB EM-seq kit had the highest mapping efficiency (percentage of reads mapped to the genome). The data quality (defined by Phred score) and methylated cytosine call were similar between kits. Conclusions: This study offers the groundwork for selecting an effective DNA methylation detection kit for crop genome research.

Genome-wide DNA methylation profiling in tongue squamous cell carcinoma.

To provide a comprehensive characterization of DNA methylome of oral tongue squamous cell carcinoma (OTSCC) and identify novel tumor-specific DNA methylation markers for early detection using saliva. Genome-wide DNA methylation analysis including six OTSCC matched adjacent non-tumoral tissue and saliva was performed using Infinium MethylationEPIC array. Differentially methylated levels of selected genes in our OTSCC cohort were further validated using OTSCC methylation data from The Cancer Genome Atlas database (TCGA). The methylation levels of a set of tumor-specific hypermethylated genes associated with a downregulated expression were evaluated in saliva. Receiver operating characteristic (ROC) curves were performed to assess the diagnostic value of DNA methylation markers. A total of 25,890 CpGs (20,505 hypomethylated and 5385 hypermethylated) were differentially methylated (DMCpGs) between OTSCC and adjacent non-tumoral tissue. Hypermethylation of 11 tumor-specific genes was validated in OTSCC TCGA cohort. Of these 11 genes, A2BP1, ANK1, ALDH1A2, GFRA1, TTYH1, and PDE4B were also hypermethylated in saliva. These six salivary methylated genes showed high diagnostic accuracy (≥0.800) for discriminating patients from controls. This is the first largest genome-wide DNA methylation study on OTSCC that identifies a group of novel tumor-specific DNA methylation markers with diagnostic potential in saliva.

Transcriptome and DNA Methylation Responses in the Liver of Yellowfin Seabream Under Starvation Stress.

Fish suffer from starvation due to environmental risks such as extreme weather in the wild and due to insufficient feedings in farms. Nutrient problems from short-term or long-term starvation conditions can result in stress-related health problems for fish. Yellowfin seabream (Acanthopagrus latus) is an important marine economic fish in China. Understanding the molecular responses to starvation stress is vital for propagation and culturing yellowfin seabream. In this study, the transcriptome and genome-wide DNA methylation levels in the livers of yellowfin seabream under 14-days starvation stress were analyzed. One hundred sixty differentially expressed genes (DEGs) by RNA-Seq analysis and 737 differentially methylated-related genes by whole genome bisulfite sequencing analysis were identified. GO and KEGG pathway enrichment analysis found that energy metabolism-related pathways such as glucose metabolism and lipid metabolism were in response to starvation. Using bisulfite sequencing PCR, we confirmed the presence of CpG methylation differences within the regulatory region of a DEG ppargc1a in response to 14-days starvation stress. This study revealed the molecular responses of livers in response to starvation stress at the transcriptomic and whole genome DNA methylation levels in yellowfin seabream.

Genome-wide DNA methylation study identifies significant epigenomic changes associated with internalized stigma in adults with non-specific chronic low back pain.

Non-specific chronic low back pain (cLBP) represents a common musculoskeletal condition with no identifiable cause. It cannot be diagnosed with conventional neuroimaging techniques such as computerized tomography (CT). The diagnostic uncertainty that characterizes non-specific cLBP can lead to stigmatizing responses from others that can become internalized Among individuals with non-specific cLBP, internalized stigma is associated with greater pain intensity and disability. Yet, no study has examined the biological mechanism linking high internalized stigma to worse outcomes in individuals with non-specific cLBP. We aimed to identify differentially methylated loci (DML), enrichment pathways, and associated network interactions among individuals with non-specific cLBP experiencing low vs. high internalized stigma. We examined DNA methylation in whole blood samples from 48 adults, ages 19-85, using reduced representation bisulfite sequencing (RRBS). After controlling for age, sex, race, and multiple testing, differentially methylated loci (DML) differed in adults with low vs. high internalized stigma by at least 10% and q < 0.01 in 3,665 CpG sites: 2,280 hypomethylated and 1,385 hypermethylated. Gene ontology (GO) analyses of the annotated genes from these sites revealed significant enrichment of 274 biological processes, 29 cellular components, and 24 molecular functions (adjusted p < 0.05). The top enriched molecular functions regulate protein binding and DNA binding of transcription factor activity. Pathway analyses indicated that many functional genomic pathways, including Hippo Signaling, Melanogenesis, and Pathways in Cancer, were enriched with differentially methylated genes. Also, there was a significant interaction between relevance pathways such as P53, mTOR, PI3K-Akt, and Wnt signaling pathways. These pathways have previously been associated with neuroinflammation, neurodegeneration, and stress-related conditions. Thus, findings point to possible stress-induced DNAm changes as the link between high levels of internalized stigma and worse outcomes in adults with non-specific cLBP.

EPCO-13. IDENTIFYING REGULATORS OF GLIOMA CELL STATE DIVERSITY AND EVOLUTION VIA JOINT SINGLE NUCLEUS RNA AND CHROMATIN ACCESSIBILITY

Abstract Glioma cellular heterogeneity and plasticity represent fundamental obstacles to effective therapies. Understanding the determinants that govern glioma cell diversity and adaptability is critical to overcoming treatment resistance. Recent single cell DNA methylation studies have demonstrated that dynamic epigenetic alterations facilitate glioma cell state shifts and stress response. However, information regarding other modes of epigenetic gene regulation, such as chromatin accessibility, and how therapy shapes cellular heterogeneity remains limited. To determine the critical regulators of glioma cell state plasticity under treatment, we profiled 36 tumors (n = 23 adult patients) with joint single nucleus RNA and ATACseq including 13 longitudinal initial – recurrent pairs that yielded a total of 79,945 cells (37,883 malignant cells). We identified chromatin peaks that were uniquely open in glioma cells (n = 14,462 peaks, FDR &amp;lt; 0.05) compared with tumor microenvironmental cells including neuronal, perivascular, glial, and immune populations. Among malignant cells, differentiated-like cells exhibited more recurrent regions of accessibility than stem-like cells. These populations could be further delineated by differential peak enrichment of transcription factor binding sites in the stem-like (TCF12, ASCL1), differentiated-like (SMARCC1, JUN), and proliferating stem-like (E2F4) malignant cells nominating these transcription factors as master regulators. We confirmed that these cell state-specific open chromatin peaks overlapped enhancer regions via single nucleus multiomics and bulk H3K27ac profiling in 3 patient-derived cell lines. We further demonstrated that there are cell state-specific chromatin changes at recurrence with a trend toward a more open chromatin state that was associated with coordinated transcriptional changes. Finally, we incorporated matched longitudinal whole genome sequencing data to evaluate mutational profiles and differentiate between predominantly epigenetically driven changes and epigenomic co-evolution with the genome. Together, these findings define the key epigenetic switches that shape glioma cell states and facilitate plasticity during tumor progression.

Comparison of global DNA methylation analysis by whole genome bisulfite sequencing and the Infinium Mouse Methylation BeadChip using fresh and fresh-frozen mouse epidermis

ABSTRACT Until recently, studying the murine methylome was restricted to sequencing-based methods. In this study we compared the global DNA methylation levels of hairless mouse epidermis using the recently released Infinium Mouse Methylation BeadChip from Illumina and whole genome bisulphite sequencing (WGBS). We also studied the effect of sample storage conditions by using fresh and fresh-frozen epidermis. The DNA methylation levels of 123,851 CpG sites covered by both the BeadChip and WGBS were compared. DNA methylation levels obtained with WGBS and the BeadChip were strongly correlated (Pearson correlation r = 0.984). We applied a threshold of 15 reads for the WGBS methylation analysis. Even at a threshold of 10 reads, we observed no substantial difference in DNA methylation levels compared with that obtained with the BeadChip. The DNA methylation levels from the fresh and the fresh-frozen samples were strongly correlated when analysed with both the BeadChip (r = 0.999) and WGBS (r = 0.994). We conclude that the two methods of analysis generally work equally well for studies of DNA methylation of mouse epidermis and find that fresh and fresh-frozen epidermis can generally be used equally well. The choice of method will depend on the specific study’s aims and the available resources in the laboratory.

A single-nucleus transcriptomics study of alcohol use disorder in the nucleus accumbens.

Gene expression studies offer promising opportunities to better understand the processes underlying alcohol use disorder (AUD). As cell types differ in their function, gene expression profiles will typically vary across cell types. When studying bulk tissue, failure to account for this cellular diversity has a detrimental impact on the ability to detect disease associations. We therefore assayed the transcriptomes of 32,531 individual nuclei extracted from the nucleus accumbens (NAc) of nine donors with AUD and nine controls (72% male). Our study identified 17 clearly delineated cell types. We detected 26 transcriptome-wide significant differentially expressed genes (DEGs) that mainly involved medium spiny neurons with both D1-type and D2-type dopamine receptors, microglia (MGL) and oligodendrocytes. A higher than expected number of DEGs replicated in an existing single nucleus gene expression study of alcohol dependence in the prefrontal cortex (enrichment ratio 1.91, p value 0.019) with two genes remaining significant after a Bonferroni correction. Our most compelling result involved CD53 in MGL that replicated in the same cell type in the prefrontal cortex and was previously implicated in studies of DNA methylation, bulk gene expression and genetic variants. Several DEGs were previously reported to be associated with AUD (e.g., PER1 and MGAT5). The DEGs for MSN.3 seemed involved in neurodegeneration, disruption of circadian rhythms, alterations in glucose metabolism and changes in synaptic plasticity. For MGL, the DEGs implicated neuroinflammation and immune-related processes and for OLI, disruptions in myelination. This identification of the specific cell-types from which the association signals originate will be key for designing proper follow-up experiments and, eventually, novel clinical interventions.

Epigenome-wide DNA methylation analysis of whole blood cells derived from patients with GAD and OCD in the Chinese Han population

Generalized anxiety disorder (GAD) and obsessive-compulsive disorder (OCD) had high comorbidity and affected more than 44 million people around the world leading to a huge burden on health and economy. Here, we conducted an epigenome-wide DNA methylation study employing 93 patients with GAD, 65 patients with OCD, and 302 health controls, to explore epigenetic alterations associated with the onset and differences of GAD and OCD. We identified multiple differentially methylated positions (DMPs) and regions (DMRs): three DMP genes included RIOK3 (cg21515243, p = 8.00 × 10−10), DNASE2 (cg09379601, p = 1.10 × 10−9), and PSMB4 (cg01334186, p = 3.70 × 10−7) and two DMR genes USP6NL (p = 4.50 × 10−4) and CPLX1 (p = 6.95 × 10−4) were associated with the onset of GAD and OCD; three DMPs genes included LDLRAP1 (cg21400344, p = 4.40 × 10−12), ACIN1 (cg23712970, p = 2.98×10−11), and SCRT1 (cg25472897, p = 5.60 × 10−11) and three DMR genes WDR19 (p = 3.39 × 10−3), SYCP1 (p = 6.41 × 10−3), and FAM172A (p = 5.74 × 10−3) were associated with the differences between GAD and OCD. Investigation of epigenetic age and chronological age revealed a different epigenetic development trajectory of GAD and OCD. Conclusively, our findings which yielded robust models may aid in distinguishing patients from healthy controls (AUC = 0.90–0.99) or classifying patients with GAD and OCD (AUC = 0.89–0.99), and may power the precision medicine for them.

Uncertainty quantification of reference-based cellular deconvolution algorithms

ABSTRACT The majority of epigenetic epidemiology studies to date have generated genome-wide profiles from bulk tissues (e.g., whole blood) however these are vulnerable to confounding from variation in cellular composition. Proxies for cellular composition can be mathematically derived from the bulk tissue profiles using a deconvolution algorithm; however, there is no method to assess the validity of these estimates for a dataset where the true cellular proportions are unknown. In this study, we describe, validate and characterize a sample level accuracy metric for derived cellular heterogeneity variables. The CETYGO score captures the deviation between a sample’s DNA methylation profile and its expected profile given the estimated cellular proportions and cell type reference profiles. We demonstrate that the CETYGO score consistently distinguishes inaccurate and incomplete deconvolutions when applied to reconstructed whole blood profiles. By applying our novel metric to >6,300 empirical whole blood profiles, we find that estimating accurate cellular composition is influenced by both technical and biological variation. In particular, we show that when using a common reference panel for whole blood, less accurate estimates are generated for females, neonates, older individuals and smokers. Our results highlight the utility of a metric to assess the accuracy of cellular deconvolution, and describe how it can enhance studies of DNA methylation that are reliant on statistical proxies for cellular heterogeneity. To facilitate incorporating our methodology into existing pipelines, we have made it freely available as an R package (https://github.com/ds420/CETYGO).

Overview of methodology for studying DNA methylation: A review

DNA methylation is the addition of a methyl group to the 5th carbon atom of cytosine in a CpG dinucleotide. It is a mechanism that causes a change in expression without altering the base sequence. It is associated with a wide range of biological processes, including deactivation of chromosome X, genomic imprinting, stem cell differentiation, gene expression control, and chromosomal stability. There are several methods available to determine the methylation status of DNA samples in the field of epigenetics. However, selecting the method that is best suited to answering a particular biological question still proves to be a difficult task. This review aims to provide biologists, with an outline of methods available, for the determination of DNA Methylation, principally those new to the field of epigenetics, with a modest procedure to help guide them in the selection of the most suitable assay to meet their research requirements, but with a particular focus on commercially available tools or other simple and straightforward explanations that have proven to be effective.

Childhood Trauma and Epigenetics: State of the Science and Future.

There is a great deal of interest regarding the biological embedding of childhood trauma and social exposures through epigenetic mechanisms, including DNA methylation (DNAm), but a comprehensive understanding has been hindered by issues of limited reproducibility between studies. This review presents a summary of the literature on childhood trauma and DNAm, highlights issues in the field, and proposes some potential solutions. Investigations of the associations between DNAm and childhood trauma are commonly performed using candidate gene approaches, specifically involving genes related to neurological and stress pathways. Childhood trauma is defined in a wide range of ways in several societal contexts. However, although variations in DNAm are frequently found in stress-related genes, unsupervised epigenome-wide association studies (EWAS) have shown limited reproducibility both between studies and in relating these changes to exposures. The reproducibility of childhood trauma DNAm studies, and the field of social epigenetics in general, may be improved by increasing sample sizes, standardizing variables, making use of effect size thresholds, collecting longitudinal and intervention samples, appropriately accounting for known confounding factors, and applying causal analysis wherever possible, such as "two-step epigenetic Mendelian randomization."

DNA Methylation Research in Autologous Hematopoietic Stem Cell Transplant Population.

Despite increased sophistication in DNA methylation (DNAm) measurement and methods, conducting studies in specific populations such as the hematopoietic stem cell transplant (HCT) population, presents unique challenges and study design considerations. In this article, we explain the motivation for investigating DNAm in the HCT population, highlighting important study design features and key findings in a longitudinal prospective pilot study of DNAm in 32 patients undergoing autologous HCT in Central Virginia, USA. We also discuss limitations and challenges to generating robust results. We observed that HCT does not prevent high-quality DNA from being extracted from whole blood for DNAm research and that longitudinal prospective studies that span pre- and 2-months post-HCT are feasible. Critically, we did not observe significant impacts of cancer diagnosis, time since transplant, age, or chromosomal sex on overall DNAm data dimensionality. These observations demonstrate that while extreme care is required to ensure generalizable, accurate, and interpretable results, researchers should not avoid HCT-DNAm research simply for fear that the transplant procedure or presence of a cancer diagnosis will prevent meaningful conclusions from being drawn. DNAm is an attractive biomarker that is understudied in patients undergoing HCT and needs to expand to improve precise prediction of HCT outcomes.