SWAN: Subset-quantile within array normalization for illumina infinium HumanMethylation450 BeadChips

Methods in DNA methylation array dataset analysis: A review

Understanding the intricate relationships between gene expression levels and epigenetic modifications in a genome is crucial to comprehending the pathogenic mechanisms of many diseases. With the advancement of DNA Methylome Profiling techniques, the emphasis on identifying Differentially Methylated Regions (DMRs/DMGs) has become crucial for biomarker discovery, offering new insights into the etiology of illnesses. This review surveys the current state of computational tools/algorithms for the analysis of microarray-based DNA methylation profiling datasets, focusing on key concepts underlying the diagnostic/prognostic CpG site extraction. It addresses methodological frameworks, algorithms, and pipelines employed by various authors, serving as a roadmap to address challenges and understand changing trends in the methodologies for analyzing array-based DNA methylation profiling datasets derived from diseased genomes. Additionally, it highlights the importance of integrating gene expression and methylation datasets for accurate biomarker identification, explores prognostic prediction models, and discusses molecular subtyping for disease classification. The review also emphasizes the contributions of machine learning, neural networks, and data mining to enhance diagnostic workflow development, thereby improving accuracy, precision, and robustness.

Direction-aware functional class scoring enrichment analysis of infinium DNA methylation data

Infinium Methylation BeadChip arrays remain one of the most popular platforms for epigenome-wide association studies, but tools for downstream pathway analysis have their limitations. Functional class scoring (FCS) is a group of pathway enrichment techniques that involve the ranking of genes and evaluation of their collective regulation in biological systems, but the implementations described for Infinium methylation array data do not retain direction information, which is important for mechanistic understanding of genomic regulation. Here, we evaluate several candidate FCS methods that retain directional information. According to simulation results, the best-performing method involves the mean aggregation of probe limma t-statistics by gene followed by a rank-ANOVA enrichment test using the mitch package. This method, which we call 'LAM,' outperformed an existing over-representation analysis method in simulations, and showed higher sensitivity and robustness in an analysis of real lung tumour-normal paired datasets. Using matched RNA-seq data, we examine the relationship of methylation differences at promoters and gene bodies with RNA expression at the level of pathways in lung cancer. To demonstrate the utility of our approach, we apply it to three other contexts where public data were available. First, we examine the differential pathway methylation associated with chronological age. Second, we investigate pathway methylation differences in infants conceived with in vitro fertilization. Lastly, we analyse differential pathway methylation in 19 disease states, identifying hundreds of novel associations. These results show LAM is a powerful method for the detection of differential pathway methylation complementing existing methods. A reproducible vignette is provided to illustrate how to implement this method.

Widespread genomic de novo DNA methylation occurs following CD8+ T cell activation and proliferation

This research investigates the intricate dynamics of DNA methylation in the hours following CD8+ T cell activation, during a critical yet understudied temporal window. DNA methylation is an epigenetic modification central to regulation of gene expression and directing immune responses. Our investigation spanned 96-h post-activation and unveils a nuanced tapestry of global and site-specific methylation changes. We identified 15,626 significant differentially methylated CpGs spread across the genome, with the most significant changes occurring within the genes ADAM10, ICA1, and LAPTM5. While many changes had modest effect sizes, approximately 120 CpGs exhibited a log2FC above 1.5, with cell activation and proliferation pathways the most affected. Relatively few of the differentially methylated CpGs occurred along adjacent gene regions. The exceptions were seven differentially methylated gene regions, with the Human T cell Receptor Alpha Joining Genes demonstrating consistent methylation change over a 3kb window. We also investigated whether an inflammatory environment could alter DNA methylation during activation, with proliferating cells exposed to the oxidant glycine chloramine. No substantial differential methylation was observed in this context. The temporal perspective of early activation adds depth to the evolving field of epigenetic immunology, offering insights with implications for therapeutic innovation and expanding our understanding of epigenetic modulation in immune function.

Immune cell distribution and DNA methylation signatures differ between tumor and stroma enriched compartment in pancreatic ductal adenocarcinoma

The presence of abundant tumor stroma is a prominent characteristic of pancreatic ductal adenocarcinomas (PDAC) that potentially influences disease progression and therapy response. This study aims to investigate immune cell infiltration and epigenetic profiles in tumor cell enriched ("Tumor") and stroma cell enriched ("Stroma") regions within human PDAC tissue samples. By comparing those regions, we identified 25,410 differentially methylated positions (DMPs) distributed across 6,963 unique genes. Pathway enrichment analysis using the top 2,000 DMPs that were either hyper- or hypomethylated indicated that immune response pathways and the estrogen receptor pathway are epigenetically dysregulated in Tumor and Stroma regions, respectively. In terms of immune cell infiltration, we observed overall low levels of T cells in both regions. In Tumor regions however, occurrence of tumor-associated macrophages (TAMs) was higher than in Stroma regions (p = 0.02) concomitant with a dualistic distribution that stratifies PDAC patients into those with high and low TAM infiltration. By categorizing TAM levels into quartiles, our analysis revealed that PDAC patients with more than 1,515 TAMs per mm² exhibited significantly shorter overall survival (p = 0.036). Our data suggest that variations in inflammatory characteristics between the Tumor and Stroma defined compartments of PDAC may primarily stem from the presence of macrophages rather than lymphocytes. The abundance of TAMs within regions enriched with tumor cells correlates with patient survival, underscoring the potential significance of exploring therapeutic interventions targeting TAMs. Furthermore, directing attention towards the estrogen receptor pathway may represent a promising strategy to address the stroma cell component within the PDAC tumor microenvironment.

Differential methylation region detection via an array-adaptive normalized kernel-weighted model

A differentially methylated region (DMR) is a genomic region that has significantly different methylation patterns between biological conditions. Identifying DMRs between different biological conditions is critical for developing disease biomarkers. Although methods for detecting DMRs in microarray data have been introduced, developing methods with high precision, recall, and accuracy in determining the true length of DMRs remains a challenge. In this study, we propose a normalized kernel-weighted model to account for similar methylation profiles using the relative probe distance from "nearby" CpG sites. We also extend this model by proposing an array-adaptive version in attempt to account for the differences in probe spacing between Illumina's Infinium 450K and EPIC bead array respectively. We also study the asymptotic results of our proposed statistic. We compare our approach with a popular DMR detection method via simulation studies under large and small treatment effect settings. We also discuss the susceptibility of our method in detecting the true length of the DMRs under these two settings. Lastly, we demonstrate the biological usefulness of our method when combined with pathway analysis methods on oral cancer data. We have created an R package called idDMR, downloadable from GitHub repository with link: https://github.com/DanielAlhassan/idDMR, that allows for the convenient implementation of our array-adaptive DMR method.

Sex-related DNA methylation is associated with inflammation and gene expression in the lungs of healthy individuals

Lung cancer exhibits sex-biased molecular characteristics and epidemiological trends, suggesting a need for sex-specific approaches to understanding its etiology and treatment. DNA methylation alterations play critical roles in lung carcinogenesis and may serve as valuable biomarkers for precision medicine strategies. We employed the Infinium MethylationEPIC array to identify autosomal sex-related differentially methylated CpG sites (DM-CpGs) in lung epithelium of healthy individuals (32 females and 37 males) while controlling for age, BMI, and tobacco use. We correlated DM-CpGs with gene expression in lung epithelium and immune responses in bronchoalveolar lavage. We validated these DM-CpGs in lung tumors and adjacent normal tissue from The Cancer Genome Atlas (TCGA). Among 522 identified DM-CpGs, 61% were hypermethylated in females, predominantly located in promoter regions. These DM genes were implicated in cell-to-cell signaling, cellular function, transport, and lipid metabolism. Correlation analysis revealed sex-specific patterns between DM-CpGs and gene expression. Additionally, several DM-CpGs were correlated significantly with cytokines (IL-1β, IL-4, IL-12p70, and IFN-γ), macrophage, and lymphocyte counts. Also, some DM-CpGs were observed in TCGA lung adenocarcinoma, squamous cell carcinoma, and adjacent normal tissues. Our findings highlight sex-specific DNA methylation patterns in healthy lung epithelium and their associations with lung gene expression and lung immune biomarkers. These findings underscore the potential role of lung sex-related CpGs as epigenetic predispositions influencing sex disparities in lung cancer risk and outcomes, warranting further investigation for personalized lung cancer management strategies.

Job-related exhaustion risk variant in UST is associated with dementia and DNA methylation

Previous genome-wide association and replication study for job-related exhaustion indicated a risk variant, rs13219957 in the UST gene. Epidemiological studies suggest connection of stress-related conditions and dementia risk. Therefore, we first studied association of rs13219957 and register-based incident dementia using survival models in the Finnish National FINRISK study surveys (N = 26,693). The AA genotype of rs13219957 was significantly associated with 40% increased risk of all-cause dementia. Then we analysed the UST locus association with brain pathology in the Vantaa 85+ cohort and found association with tau pathology (Braak stage) but not with amyloid pathology. Finally, in the functional analyses, rs13219957 showed a highly significant association with two DNA methylation sites of UST, and UST expression. Thus, the results suggest a common risk variant for a stress-related condition and dementia. Mechanisms to mediate the connection may include differential DNA methylation and transcriptional regulation of UST.

Assessing the association of epigenetic age acceleration with osteoarthritis in the Multicenter Osteoarthritis Study (MOST)

PURPOSE

Advancing age is one of the strongest risk factors for osteoarthritis (OA). DNA methylation-based measures of epigenetic age acceleration may provide insights into mechanisms underlying OA.

METHODS

We analyzed data from the Multicenter Osteoarthritis Study in a subset of 671 participants ages 45-69 years with no or mild radiographic knee OA. DNA methylation was assessed with the Illumina Infinium MethylationEPIC 850K array. We calculated predicted epigenetic age according to Hannum, Horvath, PhenoAge, and GrimAge epigenetic clocks, then regressed epigenetic age on chronological age to obtain the residuals. Associations between the residuals and knee, hand, and multi-joint OA were assessed using logistic regression, adjusted for chronological age, sex, clinical site, smoking status, and race.

RESULTS

Twenty-three percent met criteria for radiographic hand OA, 25% met criteria for radiographic knee OA, and 8% met criteria for multi-joint OA. Mean chronological age (SD) was 58.4 (6.7) years. Mean predicted epigenetic age (SD) according to Horvath, Hannum, PhenoAge, and GrimAge epigenetic clocks was 64.9 (6.4), 68.6 (5.9), 50.5 (7.7), and 67.0 (6.2), respectively. Horvath epigenetic age acceleration was not associated with an increased odds of hand OA, odds ratio (95% confidence intervals) = 1.03 (0.99-1.08), with similar findings for knee and multi-joint OA. We found similar magnitudes of associations for Hannum epigenetic age, PhenoAge, and GrimAge acceleration compared to Horvath epigenetic age acceleration.

CONCLUSIONS

Epigenetic age acceleration as measured by various well-validated epigenetic clocks based on DNA methylation was not associated with increased risk of knee, hand, or multi-joint OA independent of chronological age.

Analytical challenges in omics research on asthma and allergy: A National Institute of Allergy and Infectious Diseases workshop

Studies of asthma and allergy are generating increasing volumes of omics data for analysis and interpretation. The National Institute of Allergy and Infectious Diseases (NIAID) assembled a workshop comprising investigators studying asthma and allergic diseases using omics approaches, omics investigators from outside the field, and NIAID medical and scientific officers to discuss the following areas in asthma and allergy research: genomics, epigenomics, transcriptomics, microbiomics, metabolomics, proteomics, lipidomics, integrative omics, systems biology, and causal inference. Current states of the art, present challenges, novel and emerging strategies, and priorities for progress were presented and discussed for each area. This workshop report summarizes the major points and conclusions from this NIAID workshop. As a group, the investigators underscored the imperatives for rigorous analytic frameworks, integration of different omics data types, cross-disciplinary interaction, strategies for overcoming current limitations, and the overarching goal to improve scientific understanding and care of asthma and allergic diseases.

The Pace of Biological Aging Predicts Nonspecific Chronic Low Back Pain Severity

This study aimed to determine if and how the pace of biological aging was associated with nonspecific chronic low back pain (cLBP) and compare what measure of epigenetic age acceleration most strongly predicts cLBP outcomes. We used the Dunedin Pace of Aging from the Epigenome (DunedinPACE), Horvath's, Hannum's, and PhenoAge clocks to determine the pace of biological aging in 69 cLBP, and 49 pain-free controls (PFCs) adults, ages 18 to 85 years. On average, participants with cLBP had higher DunedinPACE (P < .001) but lower Horvath (P = .04) and Hannum (P = .02) accelerated epigenetic age than PFCs. There was no significant difference in PhenoAge acceleration between the cLBP and PFC groups (P = .97). DunedinPACE had the largest effect size (Cohen's d = .78) on group differences. In univariate regressions, a unit increase in DunedinPACE score was associated with 265.98 times higher odds of cLBP than the PFC group (P < .001). After controlling for sex, race, and body mass index (BMI), the odds ratio of cLBP to PFC group was 149.62 (P < .001). Furthermore, among participants with cLBP, DunedinPACE scores positively correlated with pain severity (rs = .385, P = .001) and interference (rs = .338, P = .005). Epigenetic age acceleration from Horvath, Hannum, and PhenoAge clocks were not significant predictors of cLBP. The odds of a faster pace of biological aging are higher among adults with cLBP, and this was associated with greater pain severity and disability. Future interventions to slow the pace of biological aging may improve cLBP outcomes. PERSPECTIVE: Accelerated epigenetic aging is common among adults with nonspecific cLBP. Higher DunedinPACE scores positively correlate with pain severity and interference, and better predict cLBP than other DNA methylation clocks. Interventions to slow the pace of biological aging may be viable targets for improving pain outcomes.

Tunable DNMT1 degradation reveals DNMT1/DNMT3B synergy in DNA methylation and genome organization

DNA methylation (DNAme) is a key epigenetic mark that regulates critical biological processes maintaining overall genome stability. Given its pleiotropic function, studies of DNAme dynamics are crucial, but currently available tools to interfere with DNAme have limitations and major cytotoxic side effects. Here, we present cell models that allow inducible and reversible DNAme modulation through DNMT1 depletion. By dynamically assessing whole genome and locus-specific effects of induced passive demethylation through cell divisions, we reveal a cooperative activity between DNMT1 and DNMT3B, but not of DNMT3A, to maintain and control DNAme. We show that gradual loss of DNAme is accompanied by progressive and reversible changes in heterochromatin, compartmentalization, and peripheral localization. DNA methylation loss coincides with a gradual reduction of cell fitness due to G1 arrest, with minor levels of mitotic failure. Altogether, this system allows DNMTs and DNA methylation studies with fine temporal resolution, which may help to reveal the etiologic link between DNAme dysfunction and human disease.

Methylome-wide and meQTL analysis helps to distinguish treatment response from non-response and pathogenesis markers in schizophrenia

Schizophrenia is a complex condition with entwined genetic and epigenetic risk factors, posing a challenge to disentangle the intermixed pathological and therapeutic epigenetic signatures. To resolve this, we performed 850K methylome-wide and 700K genome-wide studies on the same set of schizophrenia patients by stratifying them into responders, non-responders, and drug-naïve patients. The key genes that signified the response were followed up using real-time gene expression studies to understand the effect of antipsychotics at the gene transcription level. The study primarily implicates hypermethylation in therapeutic response and hypomethylation in the drug-non-responsive state. Several differentially methylated sites and regions colocalized with the schizophrenia genome-wide association study (GWAS) risk genes and variants, supporting the convoluted gene-environment association. Gene ontology and protein-protein interaction (PPI) network analyses revealed distinct patterns that differentiated the treatment response from drug resistance. The study highlights the strong involvement of several processes related to nervous system development, cell adhesion, and signaling in the antipsychotic response. The ability of antipsychotic medications to alter the pathology by modulating gene expression or methylation patterns is evident from the general increase in the gene expression of response markers and histone modifiers and the decrease in class II human leukocyte antigen (HLA) genes following treatment with varying concentrations of medications like clozapine, olanzapine, risperidone, and haloperidol. The study indicates a directional overlap of methylation markers between pathogenesis and therapeutic response, thereby suggesting a careful distinction of methylation markers of pathogenesis from treatment response. In addition, there is a need to understand the trade-off between genetic and epigenetic observations. It is suggested that methylomic changes brought about by drugs need careful evaluation for their positive effects on pathogenesis, course of disease progression, symptom severity, side effects, and refractoriness.

Characterisation and reproducibility of the HumanMethylationEPIC v2.0 BeadChip for DNA methylation profiling

BACKGROUND

The Illumina family of Infinium Methylation BeadChip microarrays has been widely used over the last 15 years for genome-wide DNA methylation profiling, including large-scale and population-based studies, due to their ease of use and cost effectiveness. Succeeding the popular HumanMethylationEPIC BeadChip (EPICv1), the recently released Infinium MethylationEPIC v2.0 BeadChip (EPICv2) claims to extend genomic coverage to more than 935,000 CpG sites. Here, we comprehensively characterise the reproducibility, reliability and annotation of the EPICv2 array, based on bioinformatic analysis of both manifest data and new EPICv2 data from diverse biological samples.

RESULTS

We find a high degree of reproducibility with EPICv1, evidenced by comparable sensitivity and precision from empirical cross-platform comparison incorporating whole genome bisulphite sequencing (WGBS), and high correlation between technical sample replicates, including between samples with DNA input levels below the manufacturer's recommendation. We provide a full assessment of probe content, evaluating genomic distribution and changes from previous array versions. We characterise EPICv2's new feature of replicated probes and provide recommendations as to the superior probes. In silico analysis of probe sequences demonstrates that probe cross-hybridisation remains a significant problem in EPICv2. By mapping the off-target sites at single nucleotide resolution and comparing with WGBS we show empirical evidence for preferential off-target binding.

CONCLUSIONS

Overall, we find EPICv2 a worthy successor to the previous Infinium methylation microarrays, however some technical issues remain. To support optimal EPICv2 data analysis we provide an expanded version of the EPICv2 manifest to aid researchers in understanding probe design, data processing, choosing appropriate probes for analysis and for integration with methylation datasets from previous versions of the Infinium Methylation BeadChip.

Advances in cancer DNA methylation analysis with methPLIER: use of non-negative matrix factorization and knowledge-based constraints to enhance biological interpretability

DNA methylation is an epigenetic modification that results in dynamic changes during ontogenesis and cell differentiation. DNA methylation patterns regulate gene expression and have been widely researched. While tools for DNA methylation analysis have been developed, most of them have focused on intergroup comparative analysis within a dataset; therefore, it is difficult to conduct cross-dataset studies, such as rare disease studies or cross-institutional studies. This study describes a novel method for DNA methylation analysis, namely, methPLIER, which enables interdataset comparative analyses. methPLIER combines Pathway Level Information Extractor (PLIER), which is a non-negative matrix factorization (NMF) method, with regularization by a knowledge matrix and transfer learning. methPLIER can be used to perform intersample and interdataset comparative analysis based on latent feature matrices, which are obtained via matrix factorization of large-scale data, and factor-loading matrices, which are obtained through matrix factorization of the data to be analyzed. We used methPLIER to analyze a lung cancer dataset and confirmed that the data decomposition reflected sample characteristics for recurrence-free survival. Moreover, methPLIER can analyze data obtained via different preprocessing methods, thereby reducing distributional bias among datasets due to preprocessing. Furthermore, methPLIER can be employed for comparative analyses of methylation data obtained from different platforms, thereby reducing bias in data distribution due to platform differences. methPLIER is expected to facilitate cross-sectional DNA methylation data analysis and enhance DNA methylation data resources.

DNA Methylation Signatures Correlate with Response to Immune Checkpoint Inhibitors in Metastatic Melanoma

BACKGROUND

DNA methylation profiles have emerged as potential predictors of therapeutic response in various solid tumors.

OBJECTIVE

This study aimed to analyze the DNA methylation profiles of patients with stage IV metastatic melanoma undergoing first-line immune checkpoint inhibitor treatment and evaluate their correlation with a radiological response according to immune-related Response Evaluation Criteria in Solid Tumors (iRECIST).

METHODS

A total of 81 tissue samples from 71 patients with metastatic melanoma (27 female, 44 male) were included in this study. We utilized Illumina Methylation EPIC Beadchips to retrieve their genome-wide methylation profile by interrogating >850,000 CpG sites. Clustering based on the 500 most differentially methylated genes was conducted to identify distinct methylation patterns associated with immune checkpoint inhibitor response. Results were further aligned with an independent, previously published data set.

RESULTS

The median progression-free survival was 8.5 months (range: 0-104.1 months), and the median overall survival was 30.6 months (range: 0-104.1 months). Objective responses were observed in 29 patients (40.8%). DNA methylation profiling revealed specific signatures that correlated with radiological response to immune checkpoint inhibitors. Three distinct clusters were identified based on the methylation patterns of the 500 most differentially methylated genes. Cluster 1 (12/12) and cluster 2 (12/24) exhibited a higher proportion of responders, while cluster 3 (39/45) predominantly consisted of non-responders. In the validation data set, responders also showed more frequent hypomethylation although differences in the data sets limit the interpretation.

CONCLUSIONS

These findings suggest that DNA methylation profiling of tumor tissues might serve as a predictive biomarker for immune checkpoint inhibitor response in patients with metastatic melanoma. Further validation studies are warranted to confirm the efficiency of DNA methylation profiling as a predictive tool in the context of immunotherapy for metastatic melanoma.

Cancer predisposition signaling in Beckwith-Wiedemann Syndrome drives Wilms tumor development

BACKGROUND

Wilms tumor (WT) exhibits structural and epigenetic changes at chromosome 11p15, which also cause Beckwith-Wiedemann Syndrome (BWS). Children diagnosed with BWS have increased risk for WT. The aim of this study is to identify the molecular signaling signatures in BWS driving these tumors.

METHODS

We performed whole exome sequencing, methylation array analysis, and gene expression analysis on BWS-WT samples. Our data were compared to publicly available nonBWS data. We categorized WT from BWS and nonBWS patients by assessment of 11p15 methylation status and defined 5 groups- control kidney, BWS-nontumor kidney, BWS-WT, normal-11p15 nonBWS-WT, altered-11p15 nonBWS-WT.

RESULTS

BWS-WT samples showed single nucleotide variants in BCORL1, ASXL1, ATM and AXL but absence of recurrent gene mutations associated with sporadic WT. We defined a narrow methylation range stratifying nonBWS-WT samples. BWS-WT and altered-11p15 nonBWS-WT showed enrichment of common and unique molecular signatures based on global differential methylation and gene expression analysis. CTNNB1 overexpression and broad range of interactions were seen in the BWS-WT interactome study.

CONCLUSION

While WT predisposition in BWS is well-established, as are 11p15 alterations in nonBWS-WT, this study focused on stratifying tumor genomics by 11p15 status. Further investigation of our findings may identify novel therapeutic targets in WT oncogenesis.

Comprehensive profiling of DNA methylation in Korean patients with colorectal cancer

Alterations in DNA methylation play an important pathophysiological role in the development and progression of colorectal cancer. We comprehensively profiled DNA methylation alterations in 165 Korean patients with colorectal cancer (CRC), and conducted an in-depth investigation of cancer-specific methylation patterns. Our analysis of the tumor samples revealed a significant presence of hypomethylated probes, primarily within the gene body regions; few hypermethylated sites were observed, which were mostly enriched in promoter-like and CpG island regions. The CpG Island Methylator PhenotypeHigh (CIMP-H) exhibited notable enrichment of microsatellite instability-high (MSI-H). Additionally, our findings indicated a significant correlation between methylation of the MLH1 gene and MSI-H status. Furthermore, we found that the CIMP-H had a higher tendency to affect the right-side of the colon tissues and was slightly more prevalent among older patients. Through our methylome profile analysis, we successfully verified the thylation patterns and clinical characteristics of Korean patients with CRC. This valuable dataset lays a strong foundation for exploring novel molecular insights and potential therapeutic targets for the treatment of CRC. [BMB Reports 2024; 57(2): 110-115].

An assessment of alterations to human sperm methylation patterns in coronavirus disease 2019 infected and healthy control males

OBJECTIVE

To determine whether severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection affects male reproductive health, considering the many potential factors that contribute to declines in male fertility on a semiglobal scale.

DESIGN

In total, 64 human semen samples-32 treatment and 32 control-were laboratory processed and bioinformatically analyzed to assess differences in DNA methylation patterns. Implementing multiple bioinformatic tools, the analyses conducted will elicit between-group differences with respect to epigenetic age, epigenetic instability, semiglobal, and regional methylation, in addition to methylation patterns as a function of time since infection.

SETTING

University hospital.

PATIENTS

The study cohort of 64 individuals was drawn from a larger population of 94 volunteer participants recruited at the Human Reproduction Center at the Clinical Hospital of the Ribeirao Preto Medical School-University of São Paulo between June 2021 and January 2022 as well as in accordance with the ethical guidelines established by the Declaration of Helsinki.

INTERVENTION

Exposure to SARS-CoV-2.

MAIN OUTCOME MEASURE(S)

Effects on male reproductive health were reported as differences in DNA methylation measured using an array. Mean β values at key regulatory loci for human spermatocytes were analyzed and compared between groups. Further analysis of β values using epigenetic age, instability, semiglobal, and regional methylation tools provided an analysis with substantial breadth and depth.

RESULTS

In all analyses, there were no differences between groups. Considering these results, it can be inferred that infection with SARS-CoV-2 does not alter the epigenome of human spermatocytes in significant and/or persistent ways. Tangentially, these data also suggest that human male reproductive health is minimally altered by the virus, or that it is altered in a way that is independent of epigenetic programming.

CONCLUSION

Infection with SARS-CoV-2 has been reportedly associated with alterations in male fertility. This study asserts that such alterations do not have an epigenetic basis but are likely a result of concomitant symptomatology, i.e., fever and inflammation. Across the multiple bioinformatic analyses conducted, the results of this test did not detect any differences in DNA methylation patterns between coronavirus disease 2019 and noncoronavirus disease semen donor groups.

Differential methylation of linoleic acid pathway genes is associated with PTSD symptoms - a longitudinal study with Burundian soldiers returning from a war zone

Soldiers may be exposed to traumatic stress during combat deployment and thus are at risk for developing posttraumatic stress disorder (PTSD). Genetic and epigenetic evidence suggests that PTSD is linked to forming stress-related memories. In the current study, we investigated post-deployment associations of PTSD symptoms with differential DNA methylation in a sample of Burundian soldiers returning from the African Union Mission in Somalia's war zone. We used a matched longitudinal study design to explore epigenetic changes associated with PTSD symptoms in N = 191 participants. PTSD symptoms and saliva samples were collected at 1-3 (t1) and 9-14 months (t2) after the return of the soldiers to their home base. Individuals with either worsening or improving PTSD symptoms were matched for age, stressful, traumatic and self-perpetrated events prior to the post-assessment, traumatic and violent experiences between the post- and the follow-up assessment, and violence experienced during childhood. A mixed model analysis was conducted to identify top nominally significantly differentially methylated genes, which were then used to perform a gene enrichment analysis. The linoleic acid metabolism pathway was significantly associated with post-deployment PTSD symptoms, after accounting for multiple comparisons. Linoleic acid has been linked to memory and immune related processes in previous research. Our findings suggest that differential methylation of linoleic acid pathway genes is associated with PTSD and thus may merit closer inspection as a possible mediator of resilience.

Characterization of HOXB13 expression patterns in localized and metastatic castration-resistant prostate cancer

HOXB13 is a key lineage homeobox transcription factor that plays a critical role in the differentiation of the prostate gland. Several studies have suggested that HOXB13 alterations may be involved in prostate cancer development and progression. Despite its potential biological relevance, little is known about the expression of HOXB13 across the disease spectrum of prostate cancer. To this end, we validated a HOXB13 antibody using genetic controls and investigated HOXB13 protein expression in murine and human developing prostates, localized prostate cancers, and metastatic castration-resistant prostate cancers. We observed that HOXB13 expression increases during later stages of murine prostate development. All localized prostate cancers showed HOXB13 protein expression. Interestingly, lower HOXB13 expression levels were observed in higher-grade tumors, although no significant association between HOXB13 expression and recurrence or disease-specific survival was found. In advanced metastatic prostate cancers, HOXB13 expression was retained in the majority of tumors. While we observed lower levels of HOXB13 protein and mRNA levels in tumors with evidence of lineage plasticity, 84% of androgen receptor-negative castration-resistant prostate cancers and neuroendocrine prostate cancers (NEPCs) retained detectable levels of HOXB13. Notably, the reduced expression observed in NEPCs was associated with a gain of HOXB13 gene body CpG methylation. In comparison to the commonly used prostate lineage marker NKX3.1, HOXB13 showed greater sensitivity in detecting advanced metastatic prostate cancers. Additionally, in a cohort of 837 patients, 383 with prostatic and 454 with non-prostatic tumors, we found that HOXB13 immunohistochemistry had a 97% sensitivity and 99% specificity for prostatic origin. Taken together, our studies provide valuable insight into the expression pattern of HOXB13 during prostate development and cancer progression. Furthermore, our findings support the utility of HOXB13 as a diagnostic biomarker for prostate cancer, particularly to confirm the prostatic origin of advanced metastatic castration-resistant tumors. © 2023 The Pathological Society of Great Britain and Ireland.

Genetic and epigenetic features of bilateral Wilms tumor predisposition in patients from the Children's Oncology Group AREN18B5-Q

Developing synchronous bilateral Wilms tumor suggests an underlying (epi)genetic predisposition. Here, we evaluate this predisposition in 68 patients using whole exome or genome sequencing (n = 85 tumors from 61 patients with matched germline blood DNA), RNA-seq (n = 99 tumors), and DNA methylation analysis (n = 61 peripheral blood, n = 29 non-diseased kidney, n = 99 tumors). We determine the predominant events for bilateral Wilms tumor predisposition: 1)pre-zygotic germline genetic variants readily detectable in blood DNA [WT1 (14.8%), NYNRIN (6.6%), TRIM28 (5%), and BRCA-related genes (5%)] or 2)post-zygotic epigenetic hypermethylation at 11p15.5 H19/ICR1 that may require analysis of multiple tissue types for diagnosis. Of 99 total tumor specimens, 16 (16.1%) have 11p15.5 normal retention of imprinting, 25 (25.2%) have 11p15.5 copy neutral loss of heterozygosity, and 58 (58.6%) have 11p15.5 H19/ICR1 epigenetic hypermethylation (loss of imprinting). Here, we ascertain the epigenetic and genetic modes of bilateral Wilms tumor predisposition.

Alterations in DNA methylation associate with reduced migraine and headache days after medication withdrawal treatment in chronic migraine patients: a longitudinal study

BACKGROUND

Chronic migraine, a highly disabling migraine subtype, affects nearly 2% of the general population. Understanding migraine chronification is vital for developing better treatment and prevention strategies. An important factor in the chronification of migraine is the overuse of acute headache medication. However, the mechanisms behind the transformation of episodic migraine to chronic migraine and vice versa have not yet been elucidated. We performed a longitudinal epigenome-wide association study to identify DNA methylation (DNAm) changes associated with treatment response in patients with chronic migraine and medication overuse as part of the Chronification and Reversibility of Migraine clinical trial. Blood was taken from patients with chronic migraine (n = 98) at baseline and after a 12-week medication withdrawal period. Treatment responders, patients with ≥ 50% reduction in monthly headache days (MHD), were compared with non-responders to identify DNAm changes associated with treatment response. Similarly, patients with ≥ 50% versus < 50% reduction in monthly migraine days (MMD) were compared.

RESULTS

At the epigenome-wide significant level (p < 9.42 × 10-8), a longitudinal reduction in DNAm at an intronic CpG site (cg14377273) within the HDAC4 gene was associated with MHD response following the withdrawal of acute medication. HDAC4 is highly expressed in the brain, plays a major role in synaptic plasticity, and modulates the expression and release of several neuroinflammation markers which have been implicated in migraine pathophysiology. Investigating whether baseline DNAm associated with treatment response, we identified lower baseline DNAm at a CpG site (cg15205829) within MARK3 that was significantly associated with MMD response at 12 weeks.

CONCLUSIONS

Our findings of a longitudinal reduction in HDAC4 DNAm status associated with treatment response and baseline MARK3 DNAm status as an early biomarker for treatment response, provide support for a role of pathways related to chromatin structure and synaptic plasticity in headache chronification and introduce HDAC4 and MARK3 as novel therapeutic targets.

Integration of datasets for individual prediction of DNA methylation-based biomarkers

BACKGROUND

Epigenetic scores (EpiScores) can provide biomarkers of lifestyle and disease risk. Projecting new datasets onto a reference panel is challenging due to separation of technical and biological variation with array data. Normalisation can standardise data distributions but may also remove population-level biological variation.

RESULTS

We compare two birth cohorts (Lothian Birth Cohorts of 1921 and 1936 - nLBC1921 = 387 and nLBC1936 = 498) with blood-based DNA methylation assessed at the same chronological age (79 years) and processed in the same lab but in different years and experimental batches. We examine the effect of 16 normalisation methods on a novel BMI EpiScore (trained in an external cohort, n = 18,413), and Horvath's pan-tissue DNA methylation age, when the cohorts are normalised separately and together. The BMI EpiScore explains a maximum variance of R2=24.5% in BMI in LBC1936 (SWAN normalisation). Although there are cross-cohort R2 differences, the normalisation method makes a minimal difference to within-cohort estimates. Conversely, a range of absolute differences are seen for individual-level EpiScore estimates for BMI and age when cohorts are normalised separately versus together. While within-array methods result in identical EpiScores whether a cohort is normalised on its own or together with the second dataset, a range of differences is observed for between-array methods.

CONCLUSIONS

Normalisation methods returning similar EpiScores, whether cohorts are analysed separately or together, will minimise technical variation when projecting new data onto a reference panel. These methods are important for cases where raw data is unavailable and joint normalisation of cohorts is computationally expensive.

Comprehensive evaluation of the implementation of episignatures for diagnosis of neurodevelopmental disorders (NDDs)

Episignatures are popular tools for the diagnosis of rare neurodevelopmental disorders. They are commonly based on a set of differentially methylated CpGs used in combination with a support vector machine model. DNA methylation (DNAm) data often include missing values due to changes in data generation technology and batch effects. While many normalization methods exist for DNAm data, their impact on episignature performance have never been assessed. In addition, technologies to quantify DNAm evolve quickly and this may lead to poor transposition of existing episignatures generated on deprecated array versions to new ones. Indeed, probe removal between array versions, technologies or during preprocessing leads to missing values. Thus, the effect of missing data on episignature performance must also be carefully evaluated and addressed through imputation or an innovative approach to episignatures design. In this paper, we used data from patients suffering from Kabuki and Sotos syndrome to evaluate the influence of normalization methods, classification models and missing data on the prediction performances of two existing episignatures. We compare how six popular normalization methods for methylarray data affect episignature classification performances in Kabuki and Sotos syndromes and provide best practice suggestions when building new episignatures. In this setting, we show that Illumina, Noob or Funnorm normalization methods achieved higher classification performances on the testing sets compared to Quantile, Raw and Swan normalization methods. We further show that penalized logistic regression and support vector machines perform best in the classification of Kabuki and Sotos syndrome patients. Then, we describe a new paradigm to build episignatures based on the detection of differentially methylated regions (DMRs) and evaluate their performance compared to classical differentially methylated cytosines (DMCs)-based episignatures in the presence of missing data. We show that the performance of classical DMC-based episignatures suffers from the presence of missing data more than the DMR-based approach. We present a comprehensive evaluation of how the normalization of DNA methylation data affects episignature performance, using three popular classification models. We further evaluate how missing data affect those models' predictions. Finally, we propose a novel methodology to develop episignatures based on differentially methylated regions identification and show how this method slightly outperforms classical episignatures in the presence of missing data.

Multiomics analysis of adaptation to repeated DNA damage in prostate cancer cells

DNA damage is frequently utilized as the basis for cancer therapies; however, resistance to DNA damage remains one of the biggest challenges for successful treatment outcomes. Critically, the molecular drivers behind resistance are poorly understood. To address this question, we created an isogenic model of prostate cancer exhibiting more aggressive characteristics to better understand the molecular signatures associated with resistance and metastasis. 22Rv1 cells were repeatedly exposed to DNA damage daily for 6 weeks, similar to patient treatment regimes. Using Illumina Methylation EPIC arrays and RNA-seq, we compared DNA methylation and transcriptional profiles between the parental 22Rv1 cell line and the lineage exposed to prolonged DNA damage. Here we show that repeated DNA damage drives the molecular evolution of cancer cells to a more aggressive phenotype and identify molecular candidates behind this process. Total DNA methylation was increased while RNA-seq demonstrated these cells had dysregulated expression of genes involved in metabolism and the unfolded protein response (UPR) with Asparagine synthetase (ASNS) identified as central to this process. Despite the limited overlap between RNA-seq and DNA methylation, oxoglutarate dehydrogenase-like (OGDHL) was identified as altered in both data sets. Utilising a second approach we profiled the proteome in 22Rv1 cells following a single dose of radiotherapy. This analysis also highlighted the UPR in response to DNA damage. Together, these analyses identified dysregulation of metabolism and the UPR and identified ASNS and OGDHL as candidates for resistance to DNA damage. This work provides critical insight into molecular changes which underpin treatment resistance and metastasis.

Prevalence of chromosomal alterations in first-trimester spontaneous pregnancy loss

Pregnancy loss is often caused by chromosomal abnormalities of the conceptus. The prevalence of these abnormalities and the allocation of (ab)normal cells in embryonic and placental lineages during intrauterine development remain elusive. In this study, we analyzed 1,745 spontaneous pregnancy losses and found that roughly half (50.4%) of the products of conception (POCs) were karyotypically abnormal, with maternal and paternal age independently contributing to the increased genomic aberration rate. We applied genome haplarithmisis to a subset of 94 pregnancy losses with normal parental and POC karyotypes. Genotyping of parental DNA as well as POC extra-embryonic mesoderm and chorionic villi DNA, representing embryonic and trophoblastic tissues, enabled characterization of the genomic landscape of both lineages. Of these pregnancy losses, 35.1% had chromosomal aberrations not previously detected by karyotyping, increasing the rate of aberrations of pregnancy losses to 67.8% by extrapolation. In contrast to viable pregnancies where mosaic chromosomal abnormalities are often restricted to chorionic villi, such as confined placental mosaicism, we found a higher degree of mosaic chromosomal imbalances in extra-embryonic mesoderm rather than chorionic villi. Our results stress the importance of scrutinizing the full allelic architecture of genomic abnormalities in pregnancy loss to improve clinical management and basic research of this devastating condition.

Genome-wide DNA methylation pattern in whole blood of patients with Hashimoto thyroiditis

Background

Hashimoto thyroiditis (HT), a prevalent autoimmune disorder, is not yet thoroughly understood, especially when it comes to the influence of epigenetics in its pathogenesis. The primary goal of this research was to probe the DNAm profile across the genome in the whole blood derived from patients suffering from HT.

Method

Using the Illumina 850K BeadChip, we conducted a genome-wide DNAm assessment on 10 matched pairs of HT sufferers and healthy individuals. Genes with differential methylation (DMGs) were identified and underwent functional annotation via the databases of Gene Ontology and Kyoto Encyclopedia of Genes and Genomes. The transcriptional significance of potential epigenetic biomarker genes was corroborated through qRT-PCR.

Results

The DNAm profiling across the genome indicated an overall reduction in methylation in HT subjects in comparison with their healthy counterparts. We detected 283 DMPs (adjusted P < 0.05 and |Δβ| > 0.1), among which 152 exhibited hypomethylation and 131 demonstrated hypermethylation. Further analysis exposed a noteworthy concentration of hypermethylated DMPs in the 3´UTR, North Shore, and CpG islands, while there was a significant decrease in the Open Sea (all P < 0.001). The 283 DMPs were broadly distributed from chromosome 1 to 22, with chromosome 6 harboring the most DMPs (n = 51) and chromosome 12 carrying the most DMGs (n = 15). The SLFN12 gene, which presented with extreme hypomethylation in its promoter DMPs among HT patients, was identified as the epigenetic marker gene. Consequently, the SLFN12 mRNA expression was markedly upregulated in HT, displaying a negative relationship with its methylation levels. The area under curve (AUC) value for the SLFN12 gene among HT patients was 0.85 (sensitivity: 0.7, specificity: 0.7), a significant difference compared with healthy controls. The methylation levels of all DMPs in SLFN12 gene were negatively correlated with TSH and one CpG site (cg24470734) was positively assocciated with FT4.

Conclusion

This investigation presents an initial comprehensive DNAm blueprint for individuals with HT, which permits clear differentiation between HT subjects and normal controls through an epigenetic lens. The SLFN12 gene plays a pivotal role in the onset of HT, suggesting that the methylation status of this gene could serve as a potential epigenetic indicator for HT.

DNA-methylation signature accurately differentiates pancreatic cancer from chronic pancreatitis in tissue and plasma

OBJECTIVE

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy. Differentiation from chronic pancreatitis (CP) is currently inaccurate in about one-third of cases. Misdiagnoses in both directions, however, have severe consequences for patients. We set out to identify molecular markers for a clear distinction between PDAC and CP.

DESIGN

Genome-wide variations of DNA-methylation, messenger RNA and microRNA level as well as combinations thereof were analysed in 345 tissue samples for marker identification. To improve diagnostic performance, we established a random-forest machine-learning approach. Results were validated on another 48 samples and further corroborated in 16 liquid biopsy samples.

RESULTS

Machine-learning succeeded in defining markers to differentiate between patients with PDAC and CP, while low-dimensional embedding and cluster analysis failed to do so. DNA-methylation yielded the best diagnostic accuracy by far, dwarfing the importance of transcript levels. Identified changes were confirmed with data taken from public repositories and validated in independent sample sets. A signature of six DNA-methylation sites in a CpG-island of the protein kinase C beta type gene achieved a validated diagnostic accuracy of 100% in tissue and in circulating free DNA isolated from patient plasma.

CONCLUSION

The success of machine-learning to identify an effective marker signature documents the power of this approach. The high diagnostic accuracy of discriminating PDAC from CP could have tremendous consequences for treatment success, once the result from still a limited number of liquid biopsy samples would be confirmed in a larger cohort of patients with suspected pancreatic cancer.

The long non-coding RNA OTX2-AS1 promotes tumor growth and predicts response to BCL-2 inhibition in medulloblastoma

PURPOSE

Primary brain tumors are a leading cause of cancer-related death in children, and medulloblastoma is the most common malignant pediatric brain tumor. The current molecular characterization of medulloblastoma is mainly based on protein-coding genes, while little is known about the involvement of long non-coding RNAs (lncRNAs). This study aimed to elucidate the role of the lncRNA OTX2-AS1 in medulloblastoma.

METHODS

Analyses of DNA copy number alterations, methylation profiles, and gene expression data were used to characterize molecular alterations of OTX2-AS1 in medulloblastoma tissue samples. In vitro analyses of medulloblastoma cell models and orthotopic in vivo experiments were carried out for functional characterization of OTX2-AS1. High-throughput drug screening was employed to identify pharmacological inhibitors, while proteomics and metabolomics analyses were performed to address potential mechanisms of drug action.

RESULTS

We detected amplification and consecutive overexpression of OTX2 and OTX2-AS1 in a subset of medulloblastomas. In addition, OTX2-AS1 promoter methylation was linked to OTX2-AS1 expression. OTX2-AS1 knockout reduced medulloblastoma cell viability and cell migration in vitro and prolonged survival in the D283 orthotopic medulloblastoma mouse xenograft model. Pharmacological inhibition of BCL-2 suppressed the growth of OTX2-AS1 overexpressing medulloblastoma cells in vitro.

CONCLUSIONS

Our study revealed a pro-tumorigenic role of OTX2-AS1 in medulloblastoma and identified BCL-2 inhibition as a potential therapeutic approach to target OTX2-AS1 overexpressing medulloblastoma cells.

Genome-wide neonatal epigenetic changes associated with maternal exposure to the COVID-19 pandemic

BACKGROUND

During gestation, stressors to the fetus, including viral exposure or maternal psychological distress, can fundamentally alter the neonatal epigenome, and may be associated with long-term impaired developmental outcomes. The impact of in utero exposure to the COVID-19 pandemic on the newborn epigenome has yet to be described.

METHODS

This study aimed to determine whether there are unique epigenetic signatures in newborns who experienced otherwise healthy pregnancies that occurred during the COVID-19 pandemic (Project RESCUE). The pre-pandemic control and pandemic cohorts (Project RESCUE) included in this study are part of a prospective observational and longitudinal cohort study that evaluates the impact of elevated prenatal maternal stress during the COVID-19 pandemic on early childhood neurodevelopment. Using buccal swabs collected at birth, differential DNA methylation analysis was performed using the Infinium MethylationEPIC arrays and linear regression analysis. Pathway analysis and gene ontology enrichment were performed on resultant gene lists.

RESULTS

Widespread differential methylation was found between neonates exposed in utero to the pandemic and pre-pandemic neonates. In contrast, there were no apparent epigenetic differences associated with maternal COVID-19 infection during pregnancy. Differential methylation was observed among genomic sites that underpin important neurological pathways that have been previously reported in the literature to be differentially methylated because of prenatal stress, such as NR3C1.

CONCLUSIONS

The present study reveals potential associations between exposure to the COVID-19 pandemic during pregnancy and subsequent changes in the newborn epigenome. While this finding warrants further investigation, it is a point that should be considered in any study assessing newborn DNA methylation studies obtained during this period, even in otherwise healthy pregnancies.

The application of epiphenotyping approaches to DNA methylation array studies of the human placenta

BACKGROUND

Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied.

RESULTS

Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry-informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, as well as over very long placental processing times. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component.

CONCLUSIONS

This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. We further demonstrate the specific utility of epiphenotyping tools developed for use with placental DNAme data, and show that these variables (i) provide an independent check of clinically obtained data and (ii) provide a robust approach to compare variables across different datasets. Finally, we present a general framework for the processing and analysis of placental DNAme data, integrating the epiphenotype variables discussed here.

Epigenetic insights into colorectal cancer: comprehensive genome-wide DNA methylation profiling of 294 patients in Korea

DNA methylation regulates gene expression and contributes to tumorigenesis in the early stages of cancer. In colorectal cancer (CRC), CpG island methylator phenotype (CIMP) is recognized as a distinct subset that is associated with specific molecular and clinical features. In this study, we investigated the genomewide DNA methylation patterns among patients with CRC. The methylation data of 1 unmatched normal, 142 adjacent normal, and 294 tumor samples were analyzed. We identified 40,003 differentially methylated positions with 6,933 (79.8%) hypermethylated and 16,145 (51.6%) hypomethylated probes in the genic region. Hypermethylated probes were predominantly found in promoter-like regions, CpG islands, and N shore sites; hypomethylated probes were enriched in open-sea regions. CRC tumors were categorized into three CIMP subgroups, with 90 (30.6%) in the CIMP-high (CIMP-H), 115 (39.1%) in the CIMP-low (CIMP-L), and 89 (30.3%) in the non-CIMP group. The CIMP-H group was associated with microsatellite instabilityhigh tumors, hypermethylation of MLH1, older age, and rightsided tumors. Our results showed that genome-wide methylation analyses classified patients with CRC into three subgroups according to CIMP levels, with clinical and molecular features consistent with previous data. [BMB Reports 2023; 56(10): 563-568].

DNA methylome profiling of blood to identify individuals in a pair of monozygotic twins

BACKGROUND

Short tandem repeat (STR) markers cannot be used to distinguish between genetically identical monozygotic (MZ) twins, causing problems in a case with an MZ twin as a suspect. Many studies have shown that in older MZ twins, there are significant differences in overall content and genomic distribution of methylation.

OBJECTIVE

In this study, we analyzed the DNA methylome profile of blood to identify recurrent differentially methylated CpG sites (DMCs) to discriminate between MZ twins.

METHODS

Blood samples were collected from 47 paired MZ twins. We performed the DNA methylation profiling using the HumanMethylation EPIC BeadChip platform and identified recurrent DMCs between MZ twins. Then, Kyoto Encyclopedia of Genes and Genomes (KEGG), Gene Ontology (GO), and motif enrichment analyses were performed to reveal the biological functions of recurrent DMCs. We collected DNA methylome data from the Gene Expression Omnibus (GEO) public database to verify the recurrent DMCs between MZ twins.

RESULTS

We identified recurrent DMCs between MZ twin samples and observed that they were enriched in immune-related genes. In addition, we verified our DMCs in a public dataset.

CONCLUSION

Our results suggest that the methylation level at recurrent DMCs between MZ twins may serve as a valuable biomarker for identification of individuals in a pair of MZ twins.

Epigenome-wide DNA methylation profiling in comparison between pathological and physiological hypertrophy of human cardiomyocytes

Background: Physiological and pathological stimuli result in distinct forms of cardiac hypertrophy, but the molecular regulation comparing the two, especially at the DNA methylation level, is not well understood. Methods: We conducted an in vitro study using human cardiomyocytes exposed to angiotensin II (AngII) and insulin-like growth factor 1 (IGF-1) to mimic pathologically and physiologically hypertrophic heart models, respectively. Whole genome DNA methylation patterns were profiled by the Infinium human MethylationEPIC platform with >850 K DNA methylation loci. Two external datasets were used for comparisons and qRT-PCR was performed for examining expression of associated genes of those identified DNA methylation loci. Results: We detected 194 loci that are significantly differentially methylated after AngII treatment, and 206 significant loci after IGF-1 treatment. Mapping the significant loci to genes, we identified 158 genes corresponding to AngII treatment and 175 genes to IGF-1 treatment. Using the gene-set enrichment analysis, the PI3K-Akt signaling pathway was identified to be significantly enriched for both AngII and IGF-1 treatment. The Hippo signaling pathway was enriched after IGF-1 treatment, but not for AngII treatment. CDK6 and RPTOR are components of the PI3K-Akt pathway but have different DNA methylation patterns in response to AngII and IGF-1. qRT-PCR confirmed the different gene expressions of CDK6 and PRTOR. Conclusion: Our study is pioneering in profiling epigenome DNA methylation changes in adult human cardiomyocytes under distinct stress conditions: pathological (AngII) and physiological (IGF-1). The identified DNA methylation loci, genes, and pathways might have the potential to distinguish between pathological and physiological cardiac hypertrophy.

eoPred: predicting the placental phenotype of early-onset preeclampsia using public DNA methylation data

Background: A growing body of literature has reported molecular and histological changes in the human placenta in association with preeclampsia (PE). Placental DNA methylation (DNAme) and transcriptomic patterns have revealed molecular subgroups of PE that are associated with placental histopathology and clinical phenotypes of the disease. However, the clinical and molecular heterogeneity of PE both across and within subtypes complicates the study of this disease. PE is most strongly associated with placental pathology and adverse fetal and maternal outcomes when it develops early in pregnancy. We focused on placentae from pregnancies affected by preeclampsia that were delivered before 34 weeks of gestation to develop eoPred, a predictor of the DNAme signature associated with the placental phenotype of early-onset preeclampsia (EOPE). Results: Public data from 83 placental samples (HM450K), consisting of 42 EOPE and 41 normotensive preterm birth (nPTB) cases, was used to develop eoPred-a supervised model that relies on a highly discriminative 45 CpG DNAme signature of EOPE in the placenta. The performance of eoPred was assessed using cross-validation (AUC = 0.95) and tested in an independent validation cohort (n = 49, AUC = 0.725). A subset of fetal growth restriction (FGR) and late-PE cases showed a similar DNAme profile at the 45 predictive CpGs, consistent with the overlap in placental pathology between these conditions. The relationship between the EOPE probability generated by eoPred and various phenotypic variables was also assessed, revealing that it is associated with gestational age, and it is not driven by cell composition differences. Conclusion: eoPred relies on a 45-CpG DNAme signature to predict a homogeneous placental phenotype of EOPE in a discrete or continuous manner. Using this classifier should 1) aid in the study of placental insufficiency and improve the consistency of future placental DNAme studies of PE, 2) facilitate identifying the placental phenotype of EOPE in public data sets and 3) importantly, standardize the placental diagnosis of EOPE to allow better cross-cohort comparisons. Lastly, classification of cases with eoPred will be useful for investigating the relationship between placental pathology and genetic or environmental variables.

Frequent Overexpression of HER3 in Brain Metastases from Breast and Lung Cancer

PURPOSE

HER3 belongs to a family of receptor tyrosine kinases with oncogenic properties and is targeted by a variety of novel anticancer agents. There is a huge unmet medical need for systemic treatment options in patients with brain metastases (BM). Therefore, we aimed to investigate HER3 expression in BM of breast (BCa) and non-small cell lung cancer (NSCLC) as the basis for future clinical trial design.

EXPERIMENTAL DESIGN

We analyzed 180 BM samples of breast cancer or NSCLC and 47 corresponding NSCLC extracranial tissue. IHC was performed to evaluate protein expression of HER3, and immune cells based on CD3, CD8, and CD68. To identify dysregulated pathways based on differential DNA methylation patterns, we used Infinium MethylationEPIC microarrays.

RESULTS

A total of 99/132 (75.0%) of BCa-BM and 35/48 (72.9%) of NSCLC-BM presented with HER3 expression. Among breast cancer, HER2-positive and HER2-low BM showed significantly higher rates of HER3 coexpression than HER2-negative BM (87.1%/85.7% vs. 61.0%, P = 0.004). Among NSCLC, HER3 was more abundantly expressed in BM than in matched extracranial samples (72.9% vs. 41.3%, P = 0.003). No correlation of HER3 expression and intratumoral immune cell density was observed. HER3 expression did not correlate with overall survival from BM diagnosis. Methylation signatures differed according to HER3 status in BCa-BM samples. Pathway analysis revealed subtype-specific differences, such as TrkB and Wnt signaling pathways dysregulated in HER2-positive and triple-negative breast cancer BM, respectively.

CONCLUSIONS

HER3 is highly abundant in BM of breast cancer and NSCLC. Given the promising results of antibody-drug conjugates in extracranial disease, BM-specific trials that target HER3 are warranted. See related commentary by Kabraji and Lin, p. 2961.

Prenatal exposures to per- and polyfluoroalkyl substances and epigenetic aging in umbilical cord blood: The Healthy Start study

BACKGROUND

Per- and polyfluoroalkyl substances (PFAS) are ubiquitous, environmentally persistent chemicals, and prenatal exposures have been associated with adverse child health outcomes. Prenatal PFAS exposure may lead to epigenetic age acceleration (EAA), defined as the discrepancy between an individual's chronologic and epigenetic or biological age.

OBJECTIVES

We estimated associations of maternal serum PFAS concentrations with EAA in umbilical cord blood DNA methylation using linear regression, and a multivariable exposure-response function of the PFAS mixture using Bayesian kernel machine regression.

METHODS

Five PFAS were quantified in maternal serum (median: 27 weeks of gestation) among 577 mother-infant dyads from a prospective cohort. Cord blood DNA methylation data were assessed with the Illumina HumanMethylation450 array. EAA was calculated as the residuals from regressing gestational age on epigenetic age, calculated using a cord-blood specific epigenetic clock. Linear regression tested for associations between each maternal PFAS concentration with EAA. Bayesian kernel machine regression with hierarchical selection estimated an exposure-response function for the PFAS mixture.

RESULTS

In single pollutant models we observed an inverse relationship between perfluorodecanoate (PFDA) and EAA (-0.148 weeks per log-unit increase, 95% CI: -0.283, -0.013). Mixture analysis with hierarchical selection between perfluoroalkyl carboxylates and sulfonates indicated the carboxylates had the highest group posterior inclusion probability (PIP), or relative importance. Within this group, PFDA had the highest conditional PIP. Univariate predictor-response functions indicated PFDA and perfluorononanoate were inversely associated with EAA, while perfluorohexane sulfonate had a positive association with EAA.

CONCLUSIONS

Maternal mid-pregnancy serum concentrations of PFDA were negatively associated with EAA in cord blood, suggesting a pathway by which prenatal PFAS exposures may affect infant development. No significant associations were observed with other PFAS. Mixture models suggested opposite directions of association between perfluoroalkyl sulfonates and carboxylates. Future studies are needed to determine the importance of neonatal EAA for later child health outcomes.

Epigenome-wide association study identifies Vogt-Koyanagi-Harada disease-associated DNA methylation loci in Chinese

DNA methylation is one of the important epigenetic mechanisms for modulating gene expression. By performing a genome-wide methylation association analysis of whole peripheral blood from 60 Vogt-Koyanagi-Harada disease (VKH) patients and 60 healthy controls, we depicted the global DNA methylation status of VKH disease. Further pyrosequencing validation in 160 patients and 159 controls identified 3 aberrant CpG sites in HLA gene regions including cg04026937 and cg18052547 (located in HLA-DRB1 region), and cg13778567 (HLA-DQA1). We also identified 9 aberrant CpG sites in non-HLA gene regions including cg13979407, cg21075643, cg24290586, cg10135747 and cg22707857 (BTNL2), cg22155039 (NOTCH4), cg02605387 (TNXB), cg06255004 (AGPAT2) and cg18855195 (RIBC2). Increased mRNA levels of BTNL2, NOTCH4 and TNXB were identified in VKH patients when compared with healthy controls, consistent with the hypomethylated CpG status in these gene regions. Moreover, seven aberrantly methylated CpG sites may serve as a diagnostic marker for VKH disease (AUC = 84.95%, 95%CI: 79.49%-90.41%).

The application of epiphenotyping approaches to DNA methylation array studies of the human placenta

Background : Genome-wide DNA methylation (DNAme) profiling of the placenta with Illumina Infinium Methylation bead arrays is often used to explore the connections between in utero exposures, placental pathology, and fetal development. However, many technical and biological factors can lead to signals of DNAme variation between samples and between cohorts, and understanding and accounting for these factors is essential to ensure meaningful and replicable data analysis. Recently, "epiphenotyping" approaches have been developed whereby DNAme data can be used to impute information about phenotypic variables such as gestational age, sex, cell composition, and ancestry. These epiphenotypes offer avenues to compare phenotypic data across cohorts, and to understand how phenotypic variables relate to DNAme variability. However, the relationships between placental epiphenotyping variables and other technical and biological variables, and their application to downstream epigenome analyses, have not been well studied. Results : Using DNAme data from 204 placentas across three cohorts, we applied the PlaNET R package to estimate epiphenotypes gestational age, ancestry, and cell composition in these samples. PlaNET ancestry estimates were highly correlated with independent polymorphic ancestry informative markers, and epigenetic gestational age, on average, was estimated within 4 days of reported gestational age, underscoring the accuracy of these tools. Cell composition estimates varied both within and between cohorts, but reassuringly were robust to placental processing time. Interestingly, the ratio of cytotrophoblast to syncytiotrophoblast proportion decreased with increasing gestational age, and differed slightly by both maternal ethnicity (lower in white vs. non-white) and genetic ancestry (lower in higher probability European ancestry). The cohort of origin and cytotrophoblast proportion were the largest drivers of DNAme variation in this dataset, based on their associations with the first principal component. Conclusions : This work confirms that cohort, array (technical) batch, cell type proportion, self-reported ethnicity, genetic ancestry, and biological sex are important variables to consider in any analyses of Illumina DNAme data. Further, we demonstrate that estimating epiphenotype variables from the DNAme data itself, when possible, provides both an independent check of clinically-obtained data and can provide a robust approach to compare variables across different datasets.

DNA methylation markers for kidney function and progression of diabetic kidney disease

Epigenetic markers are potential biomarkers for diabetes and related complications. Using a prospective cohort from the Hong Kong Diabetes Register, we perform two independent epigenome-wide association studies to identify methylation markers associated with baseline estimated glomerular filtration rate (eGFR) and subsequent decline in kidney function (eGFR slope), respectively, in 1,271 type 2 diabetes subjects. Here we show 40 (30 previously unidentified) and eight (all previously unidentified) CpG sites individually reach epigenome-wide significance for baseline eGFR and eGFR slope, respectively. We also develop a multisite analysis method, which selects 64 and 37 CpG sites for baseline eGFR and eGFR slope, respectively. These models are validated in an independent cohort of Native Americans with type 2 diabetes. Our identified CpG sites are near genes enriched for functional roles in kidney diseases, and some show association with renal damage. This study highlights the potential of methylation markers in risk stratification of kidney disease among type 2 diabetes individuals.

Epigenomic variability is associated with age-specific naïve CD4 T cell response to activation in infants and adolescents

Childhood is a critical period of immune development. During this time, naïve CD4 (nCD4) T cells undergo programmed cell differentiation, mediated by epigenetic changes, in response to external stimuli leading to a baseline homeostatic state that may determine lifelong disease risk. However, the ontogeny of epigenetic signatures associated with CD4 T cell activation during key developmental periods are yet to be described. We investigated genome-wide DNA methylation (DNAm) changes associated with nCD4 T activation following 72 h culture in media+anti-CD3/CD28 beads in healthy infants (aged 12 months, n = 18) and adolescents (aged 10-15 years, n = 15). We integrated these data with transcriptomic and cytokine profiling from the same samples. nCD4 T cells from both age groups show similar extensive epigenetic reprogramming following activation, with the majority of genes involved in the T cell receptor signaling pathway associated with differential methylation. Additionally, we identified differentially methylated probes showing age-specific responses, that is, responses in only infants or adolescents, including within a cluster of T cell receptor (TCR) genes. These encoded several TCR alpha joining (TRAJ), and TCR alpha variable (TRAV) genes. Cytokine data analysis following stimulation revealed enhanced release of IFN-γ, IL-2 and IL-10, in nCD4 T cells from adolescents compared with infants. Overlapping differential methylation and cytokine responses identified four probes potentially underpinning these age-specific responses. We show that DNAm in nCD4T cells in response to activation is dynamic in infancy and adolescence, with additional evidence for age-specific effects potentially driving variation in cytokine responses between these ages.

Epigenetic reactivation of tumor suppressor genes with CRISPRa technologies as precision therapy for hepatocellular carcinoma

BACKGROUND

Epigenetic silencing of tumor suppressor genes (TSGs) is a key feature of oncogenesis in hepatocellular carcinoma (HCC). Liver-targeted delivery of CRISPR-activation (CRISPRa) systems makes it possible to exploit chromatin plasticity, by reprogramming transcriptional dysregulation.

RESULTS

Using The Cancer Genome Atlas HCC data, we identify 12 putative TSGs with negative associations between promoter DNA methylation and transcript abundance, with limited genetic alterations. All HCC samples harbor at least one silenced TSG, suggesting that combining a specific panel of genomic targets could maximize efficacy, and potentially improve outcomes as a personalized treatment strategy for HCC patients. Unlike epigenetic modifying drugs lacking locus selectivity, CRISPRa systems enable potent and precise reactivation of at least 4 TSGs tailored to representative HCC lines. Concerted reactivation of HHIP, MT1M, PZP, and TTC36 in Hep3B cells inhibits multiple facets of HCC pathogenesis, such as cell viability, proliferation, and migration.

CONCLUSIONS

By combining multiple effector domains, we demonstrate the utility of a CRISPRa toolbox of epigenetic effectors and gRNAs for patient-specific treatment of aggressive HCC.

Examining the immunoepigenetic-gut microbiome axis in the context of self-esteem among Native Hawaiians and other Pacific Islanders

Introduction: Native Hawaiian and other Pacific Islander (NHPI) populations experience higher rates of immunometabolic diseases compared to other racial-ethnic groups in Hawaii. As annual NHPI mortality rates for suicide and type 2 diabetes mellitus (T2DM) exceed those of the state as a whole, understanding the social and biological mechanisms underlying these disparities are urgently needed to enable preventive strategies. Methods: A community-based approach was used to investigate the immunoepigenetic-gut microbiome axis in an NHPI-enriched cohort of Oahu residents (N = 68). Self-esteem (SE) data was collected using a modified Rosenberg self-esteem (SE) assessment as a proxy measure for mental wellbeing in consideration for cultural competency. T2DM status was evaluated using point-of-care A1c (%) tests. Stool samples were collected for 16s-based metagenomic sequencing analyses. Plasma from blood samples were isolated by density-gradient centrifugation. Peripheral blood mononuclear cells (PBMCs) were collected from the same samples and enriched for monocytes using negative selection techniques. Flow-cytometry was used for immunoprofiling assays. Monocyte DNA was extracted for Illumina EPIC array-based methylation analysis. Results: Compared to individuals with normal SE (NSE), those with low SE (LSE) exhibited significantly higher plasma concentrations (pg/ml) of proinflammatory cytokines IL-8 (p = 0.051) and TNF-α (p = 0.011). Metagenomic analysis revealed that the relative abundance (%) of specific gut bacteria significantly differed between SE groups - some of which directly correlated with SE scores. Gene ontology analysis revealed that 104 significantly differentially methylated loci (DML) between SE groups were preferentially located at genes involved in immunometabolic processes. Horvath clock analyses indicated epigenetic age (Epi-Age) deceleration in individuals with LSE and acceleration in individuals with NSE (p = 0.042), yet was not reproduced by other clocks. Discussion: These data reveal novel differences in the immunoepigenetic-gut microbiome axis with respect to SE, warranting further investigation into its relationship to brain activity and mental health in NHPI. Unexpected results from Epi-Age analyses warrant further investigation into the relationship between biological age and disparate health outcomes among the NHPI population. The modifiable component of epigenetic processes and the gut microbiome makes this axis an attractive target for potential therapeutics, biomarker discovery, and novel prevention strategies.

DNA methylation epi-signature and biological age in attention deficit hyperactivity disorder patients

OBJECTIVE

Attention Deficit/Hyperactivity Disorder (ADHD) is a common behavioral syndrome that begins in childhood and affects 3.4% of children worldwide. Due to its etiological complexity, there are no consistent biomarkers for ADHD, however the high heritability presented by the disorder indicates a genetic/epigenetic influence. The main epigenetic mechanism is DNA methylation, a process with an important role in gene expression and in many psychiatric disorders. Thus, our study sought to identify epi-signatures biomarkers in 29 children clinically diagnosed with ADHD.

METHODS

After DNA extraction and bisulfite conversion, we performed methylation array experiment for differential methylation, ontological and biological age analysis.

RESULTS

The biological response in ADHD patients was not sufficient to determine a conclusive epi-signature in our study. However, our results highlighted the interaction of energy metabolism and oxidative stress pathways in ADHD patients detected by differential methylation patterns. Furthermore, we were able to identify a marginal association between the DNAmAge and ADHD.

CONCLUSION

Our study present new methylation biomarkers findings associated with energy metabolism and oxidative stress pathways, in addition to DNAmAge in ADHD patients. However, we propose that further multiethnic studies, with larger cohorts and including maternal conditions, are necessary to demonstrate a definitive association between ADHD and these methylation biomarkers.

Crosstalk between Gut Microbiota and Epigenetic Markers in Obesity Development: Relationship between Ruminococcus, BMI, and MACROD2/SEL1L2 Methylation

Changes in gut microbiota composition and in epigenetic mechanisms have been proposed to play important roles in energy homeostasis, and the onset and development of obesity. However, the crosstalk between epigenetic markers and the gut microbiome in obesity remains unclear. The main objective of this study was to establish a link between the gut microbiota and DNA methylation patterns in subjects with obesity by identifying differentially methylated DNA regions (DMRs) that could be potentially regulated by the gut microbiota. DNA methylation and bacterial DNA sequencing analysis were performed on 342 subjects with a BMI between 18 and 40 kg/m². DNA methylation analyses identified a total of 2648 DMRs associated with BMI, while ten bacterial genera were associated with BMI. Interestingly, only the abundance of Ruminococcus was associated with one BMI-related DMR, which is located between the MACROD2/SEL1L2 genes. The Ruminococcus abundance negatively correlated with BMI, while the hypermethylated DMR was associated with reduced MACROD2 protein levels in serum. Additionally, the mediation test showed that 19% of the effect of Ruminococcus abundance on BMI is mediated by the methylation of the MACROD2/SEL1L2 DMR. These findings support the hypothesis that a crosstalk between gut microbiota and epigenetic markers may be contributing to obesity development.

Indirect epigenetic testing identifies a diagnostic signature of cardiomyocyte DNA methylation in heart failure

Precision-based molecular phenotyping of heart failure must overcome limited access to cardiac tissue. Although epigenetic alterations have been found to underlie pathological cardiac gene dysregulation, the clinical utility of myocardial epigenomics remains narrow owing to limited clinical access to tissue. Therefore, the current study determined whether patient plasma confers indirect phenotypic, transcriptional, and/or epigenetic alterations to ex vivo cardiomyocytes to mirror the failing human myocardium. Neonatal rat ventricular myocytes (NRVMs) and single-origin human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and were treated with blood plasma samples from patients with dilated cardiomyopathy (DCM) and donor subjects lacking history of cardiovascular disease. Following plasma treatments, NRVMs and hiPSC-CMs underwent significant hypertrophy relative to non-failing controls, as determined via automated high-content screening. Array-based DNA methylation analysis of plasma-treated hiPSC-CMs and cardiac biopsies uncovered robust, and conserved, alterations in cardiac DNA methylation, from which 100 sites were validated using an independent cohort. Among the CpG sites identified, hypo-methylation of the ATG promoter was identified as a diagnostic marker of HF, wherein cg03800765 methylation (AUC = 0.986, P < 0.0001) was found to out-perform circulating NT-proBNP levels in differentiating heart failure. Taken together, these findings support a novel approach of indirect epigenetic testing in human HF.

The Genetic and Epigenetic Features of Bilateral Wilms Tumor Predisposition: A Report from the Children's Oncology Group AREN18B5-Q Study

This study comprehensively evaluated the landscape of genetic and epigenetic events that predispose to synchronous bilateral Wilms tumor (BWT). We performed whole exome or whole genome sequencing, total-strand RNA-seq, and DNA methylation analysis using germline and/or tumor samples from 68 patients with BWT from St. Jude Children's Research Hospital and the Children's Oncology Group. We found that 25/61 (41%) of patients evaluated harbored pathogenic or likely pathogenic germline variants, with WT1 (14.8%), NYNRIN (6.6%), TRIM28 (5%) and the BRCA-related genes (5%) BRCA1, BRCA2, and PALB2 being most common. Germline WT1 variants were strongly associated with somatic paternal uniparental disomy encompassing the 11p15.5 and 11p13/WT1 loci and subsequent acquired pathogenic CTNNB1 variants. Somatic coding variants or genome-wide copy number alterations were almost never shared between paired synchronous BWT, suggesting that the acquisition of independent somatic variants leads to tumor formation in the context of germline or early embryonic, post-zygotic initiating events. In contrast, 11p15.5 status (loss of heterozygosity, loss or retention of imprinting) was shared among paired synchronous BWT in all but one case. The predominant molecular events for BWT predisposition include pathogenic germline variants or post-zygotic epigenetic hypermethylation at the 11p15.5 H19/ICR1 locus (loss of imprinting). This study demonstrates that post-zygotic somatic mosaicism for 11p15.5 hypermethylation/loss of imprinting is the single most common initiating molecular event predisposing to BWT. Evidence of somatic mosaicism for 11p15.5 loss of imprinting was detected in leukocytes of a cohort of BWT patients and long-term survivors, but not in unilateral Wilms tumor patients and long-term survivors or controls, further supporting the hypothesis that post-zygotic 11p15.5 alterations occurred in the mesoderm of patients who go on to develop BWT. Due to the preponderance of BWT patients with demonstrable germline or early embryonic tumor predisposition, BWT exhibits a unique biology when compared to unilateral Wilms tumor and therefore warrants continued refinement of its own treatment-relevant biomarkers which in turn may inform directed treatment strategies in the future.

A systematic evaluation of normalization methods and probe replicability using infinium EPIC methylation data

BACKGROUND

The Infinium EPIC array measures the methylation status of > 850,000 CpG sites. The EPIC BeadChip uses a two-array design: Infinium Type I and Type II probes. These probe types exhibit different technical characteristics which may confound analyses. Numerous normalization and pre-processing methods have been developed to reduce probe type bias as well as other issues such as background and dye bias.

METHODS

This study evaluates the performance of various normalization methods using 16 replicated samples and three metrics: absolute beta-value difference, overlap of non-replicated CpGs between replicate pairs, and effect on beta-value distributions. Additionally, we carried out Pearson's correlation and intraclass correlation coefficient (ICC) analyses using both raw and SeSAMe 2 normalized data.

RESULTS

The method we define as SeSAMe 2, which consists of the application of the regular SeSAMe pipeline with an additional round of QC, pOOBAH masking, was found to be the best performing normalization method, while quantile-based methods were found to be the worst performing methods. Whole-array Pearson's correlations were found to be high. However, in agreement with previous studies, a substantial proportion of the probes on the EPIC array showed poor reproducibility (ICC < 0.50). The majority of poor performing probes have beta values close to either 0 or 1, and relatively low standard deviations. These results suggest that probe reliability is largely the result of limited biological variation rather than technical measurement variation. Importantly, normalizing the data with SeSAMe 2 dramatically improved ICC estimates, with the proportion of probes with ICC values > 0.50 increasing from 45.18% (raw data) to 61.35% (SeSAMe 2).

Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders

Increasing evidence supports the role of placenta in neurodevelopment and potentially, in the later onset of neuropsychiatric disorders. Recently, methylation quantitative trait loci (mQTL) and interaction QTL (iQTL) maps have proven useful to understand SNP-genome wide association study (GWAS) relationships, otherwise missed by conventional expression QTLs. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation (DNAm). We constructed the first public placental cis-mQTL database including nearly eight million mQTLs calculated in 368 fetal placenta DNA samples from the INMA project, ran cell type- and gestational age-imQTL models and combined those data with the summary statistics of the largest GWAS on 10 neuropsychiatric disorders using Summary-based Mendelian Randomization (SMR) and colocalization. Finally, we evaluated the influence of the DNAm sites identified on placental gene expression in the RICHS cohort. We found that placental cis-mQTLs are highly enriched in placenta-specific active chromatin regions, and useful to map the etiology of neuropsychiatric disorders at prenatal stages. Specifically, part of the genetic burden for schizophrenia, bipolar disorder and major depressive disorder confers risk through placental DNAm. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, regional pleiotropic methylation signals associated to the same disorder, and cell type-imQTLs, additionally associated to the expression levels of relevant immune genes in placenta. In conclusion, the genetic risk of several neuropsychiatric disorders could operate, at least in part, through DNAm and associated gene expression in placenta.

CeDAR: incorporating cell type hierarchy improves cell type-specific differential analyses in bulk omics data

Bulk high-throughput omics data contain signals from a mixture of cell types. Recent developments of deconvolution methods facilitate cell type-specific inferences from bulk data. Our real data exploration suggests that differential expression or methylation status is often correlated among cell types. Based on this observation, we develop a novel statistical method named CeDAR to incorporate the cell type hierarchy in cell type-specific differential analyses of bulk data. Extensive simulation and real data analyses demonstrate that this approach significantly improves the accuracy and power in detecting cell type-specific differential signals compared with existing methods, especially in low-abundance cell types.