Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling

Comparing feature selection and machine learning approaches for predicting CYP2D6 methylation from genetic variation

Introduction

Pharmacogenetics currently supports clinical decision-making on the basis of a limited number of variants in a few genes and may benefit paediatric prescribing where there is a need for more precise dosing. Integrating genomic information such as methylation into pharmacogenetic models holds the potential to improve their accuracy and consequently prescribing decisions. Cytochrome P450 2D6 (CYP2D6) is a highly polymorphic gene conventionally associated with the metabolism of commonly used drugs and endogenous substrates. We thus sought to predict epigenetic loci from single nucleotide polymorphisms (SNPs) related to CYP2D6 in children from the GUSTO cohort.

Methods

Buffy coat DNA methylation was quantified using the Illumina Infinium Methylation EPIC beadchip. CpG sites associated with CYP2D6 were used as outcome variables in Linear Regression, Elastic Net and XGBoost models. We compared feature selection of SNPs from GWAS mQTLs, GTEx eQTLs and SNPs within 2 MB of the CYP2D6 gene and the impact of adding demographic data. The samples were split into training (75%) sets and test (25%) sets for validation. In Elastic Net model and XGBoost models, optimal hyperparameter search was done using 10-fold cross validation. Root Mean Square Error and R-squared values were obtained to investigate each models' performance. When GWAS was performed to determine SNPs associated with CpG sites, a total of 15 SNPs were identified where several SNPs appeared to influence multiple CpG sites.

Results

Overall, Elastic Net models of genetic features appeared to perform marginally better than heritability estimates and substantially better than Linear Regression and XGBoost models. The addition of nongenetic features appeared to improve performance for some but not all feature sets and probes. The best feature set and Machine Learning (ML) approach differed substantially between CpG sites and a number of top variables were identified for each model.

Discussion

The development of SNP-based prediction models for CYP2D6 CpG methylation in Singaporean children of varying ethnicities in this study has clinical application. With further validation, they may add to the set of tools available to improve precision medicine and pharmacogenetics-based dosing.

UHRF1 ubiquitin ligase activity supports the maintenance of low-density CpG methylation

The RING E3 ubiquitin ligase UHRF1 is an established cofactor for DNA methylation inheritance. Nucleosomal engagement through histone and DNA interactions directs UHRF1 ubiquitin ligase activity toward lysines on histone H3 tails, creating binding sites for DNMT1 through ubiquitin interacting motifs (UIM1 and UIM2). Here, we profile contributions of UHRF1 and DNMT1 to genome-wide DNA methylation inheritance and dissect specific roles for ubiquitin signaling in this process. We reveal DNA methylation maintenance at low-density CpGs is vulnerable to disruption of UHRF1 ubiquitin ligase activity and DNMT1 ubiquitin reading activity through UIM1. Hypomethylation of low-density CpGs in this manner induces formation of partially methylated domains (PMD), a methylation signature observed across human cancers. Furthermore, disrupting DNMT1 UIM2 function abolishes DNA methylation maintenance. Collectively, we show DNMT1-dependent DNA methylation inheritance is a ubiquitin-regulated process and suggest a disrupted UHRF1-DNMT1 ubiquitin signaling axis contributes to the development of PMDs in human cancers.

DNA methylation changes in association with trauma-focused psychotherapy efficacy in treatment-resistant depression patients: a prospective longitudinal study

Background: Stressful events increase the risk for treatment-resistant depression (TRD), and trauma-focused psychotherapy can be useful for TRD patients exposed to early life stress (ELS). Epigenetic processes are known to be related to depression and ELS, but there is no evidence of the effects of trauma-focused psychotherapy on methylation alterations.Objective: We performed the first epigenome-wide association study to investigate methylation changes related to trauma-focused psychotherapies effects in TRD patients.Method: Thirty TRD patients assessed for ELS underwent trauma-focused psychotherapy, of those, 12 received trauma-focused cognitive behavioural therapy, and 18 Eye Movement Desensitization and Reprocessing (EMDR). DNA methylation was profiled with Illumina Infinium EPIC array at T0 (baseline), after 8 weeks (T8, end of psychotherapy) and after 12 weeks (T12 - follow-up). We examined differentially methylated CpG sites and regions, as well as pathways analysis in association with the treatment.Results: Main results obtained have shown 110 differentially methylated regions (DMRs) with a significant adjusted p-value area associated with the effects of trauma-focused psychotherapies in the entire cohort. Several annotated genes are related to inflammatory processes and psychiatric disorders, such as LTA, GFI1, ARID5B, TNFSF13, and LST1. Gene enrichment analyses revealed statistically significant processes related to tumour necrosis factor (TNF) receptor and TNF signalling pathway. Stratified analyses by type of trauma-focused psychotherapy showed statistically significant adjusted p-value area in 141 DMRs only for the group of patients receiving EMDR, with annotated genes related to inflammation and psychiatric disorders, including LTA, GFI1, and S100A8. Gene set enrichment analyses in the EMDR group indicated biological processes related to inflammatory response, particularly the TNF signalling pathway.Conclusion: We provide preliminary valuable insights into global DNA methylation changes associated with trauma-focused psychotherapies effects, in particular with EMDR treatment.

Epigenome-wide association study of dietary fatty acid intake

BACKGROUND

Dietary intake of n-3 polyunsaturated fatty acids (PUFA) may have a protective effect on the development of cardiovascular diseases, diabetes, depression and cancer, while a high intake of n-6 PUFA was often reported to be associated with inflammation-related traits. The effect of PUFAs on health outcomes might be mediated by DNA methylation (DNAm). The aim of our study is to identify the impact of PUFA intake on DNAm in the Cooperative Health Research in the Region of Augsburg (KORA) FF4 cohort and the Leiden Longevity Study (LLS).

RESULTS

DNA methylation levels were measured in whole blood from the population-based KORA FF4 study (N = 1354) and LLS (N = 448), using the Illumina MethylationEPIC BeadChip and Illumina HumanMethylation450 array, respectively. We assessed associations between DNAm and intake of eight and four PUFAs in KORA and LLS, respectively. Where possible, results were meta-analyzed. Below the Bonferroni correction threshold (p < 7.17 × 10-8), we identified two differentially methylated positions (DMPs) associated with PUFA intake in the KORA study. The DMP cg19937480, annotated to gene PRDX1, was positively associated with docosahexaenoic acid (DHA) in model 1 (beta: 2.00 × 10-5, 95%CI: 1.28 × 10-5-2.73 × 10-5, P value: 6.98 × 10-8), while cg05041783, annotated to gene MARK2, was positively associated with docosapentaenoic acid (DPA) in our fully adjusted model (beta: 9.80 × 10-5, 95%CI: 6.25 × 10-5-1.33 × 10-4, P value: 6.75 × 10-8). In the meta-analysis, we identified the CpG site (cg15951061), annotated to gene CDCA7L below Bonferroni correction (1.23 × 10-7) associated with eicosapentaenoic acid (EPA) intake in model 1 (beta: 2.00 × 10-5, 95% CI: 1.27 × 10-5-2.73 × 10-5, P value = 5.99 × 10-8) and we confirmed the association of cg19937480 with DHA in both models 1 and 2 (beta: 2.07 × 10-5, 95% CI: 1.31 × 10-5-2.83 × 10-5, P value = 1.00 × 10-7 and beta: 2.19 × 10-5, 95% CI: 1.41 × 10-5-2.97 × 10-5, P value = 5.91 × 10-8 respectively).

CONCLUSIONS

Our study identified three CpG sites associated with PUFA intake. The mechanisms of these sites remain largely unexplored, highlighting the novelty of our findings. Further research is essential to understand the links between CpG site methylation and PUFA outcomes.

GrimAge is elevated in older adults with mild COVID-19 an exploratory analysis

COVID-19 has been contained; however, the side effects associated with its infection continue to be a challenge for public health, particularly for older adults. On the other hand, epigenetic status contributes to the inter-individual health status and is associated with COVID-19 severity. Nevertheless, current studies focus only on severe COVID-19. Considering that most of the worldwide population developed mild COVID-19 infection. In the present exploratory study, we aim to analyze the association of mild COVID-19 with epigenetic ages (HorvathAge, HannumAge, GrimAge, PhenoAge, SkinAge, and DNAmTL) and clinical variables obtained from a Mexican cohort of older adults. We found that all epigenetic ages significantly differ from the chronological age, but only GrimAge is elevated. Additionally, both the intrinsic epigenetic age acceleration (IEAA) and the extrinsic epigenetic age acceleration (EEAA) are accelerated in all patients. Moreover, we found that immunological estimators and DNA damage were associated with PhenoAge, SkinBloodHorvathAge, and HorvathAge, suggesting that the effects of mild COVID-19 on the epigenetic clocks are mainly associated with inflammation and immunology changes. In conclusion, our results show that the effects of mild COVID-19 on the epigenetic clock are mainly associated with the immune system and an increase in GrimAge, IEAA, and EEAA.

Effect of parental adverse childhood experiences on intergenerational DNA methylation signatures from peripheral blood mononuclear cells and buccal mucosa

In this study, the effect of cumulative ACEs experienced on human maternal DNA methylation (DNAm) was estimated while accounting for interaction with domains of ACEs in prenatal peripheral blood mononuclear cell samples from the Maternal and Developmental Risks from Environmental Stressors (MADRES) pregnancy cohort. The intergenerational transmission of ACE-associated DNAm was also explored used paired maternal (N = 120) and neonatal cord blood (N = 69) samples. Replication in buccal samples was explored in the Children's Health Study (CHS) among adult parental (N = 31) and pediatric (N = 114) samples. We used a four-level categorical indicator variable for ACEs exposure: none (0 ACEs), low (1-3 ACEs), moderate (4-6 ACEs), and high (>6 ACEs). Effects of ACEs on maternal DNAm (N = 240) were estimated using linear models. To evaluate evidence for intergenerational transmission, mediation analysis (N = 60 mother-child pairs) was used. Analysis of maternal samples displayed some shared but mostly distinct effects of ACEs on DNAm across low, moderate, and high ACEs categories. CLCN7 and PTPRN2 was associated with maternal DNAm in the low ACE group and this association replicated in the CHS. CLCN7 was also nominally significant in the gene expression correlation analysis among maternal profiles (N = 35), along with 11 other genes. ACE-associated methylation was observed in maternal and neonatal profiles in the COMT promoter region, with some evidence of mediation by maternal COMT methylation. Specific genomic loci exhibited mutually exclusive maternal ACE effects on DNAm in either maternal or neonatal population. There is some evidence for an intergenerational effect of ACEs, supported by shared DNAm signatures in the COMT gene across maternal-neonatal paired samples.

A supervised learning method for classifying methylation disorders

BACKGROUND

DNA methylation is one of the most stable and well-characterized epigenetic alterations in humans. Accordingly, it has already found clinical utility as a molecular biomarker in a variety of disease contexts. Existing methods for clinical diagnosis of methylation-related disorders focus on outlier detection in a small number of CpG sites using standardized cutoffs which differentiate healthy from abnormal methylation levels. The standardized cutoff values used in these methods do not take into account methylation patterns which are known to differ between the sexes and with age.

RESULTS

Here we profile genome-wide DNA methylation from blood samples drawn from within a cohort composed of healthy controls of different age and sex alongside patients with Prader-Willi syndrome (PWS), Beckwith-Wiedemann syndrome, Fragile-X syndrome, Angelman syndrome, and Silver-Russell syndrome. We propose a Generalized Additive Model to perform age and sex adjusted outlier analysis of around 700,000 CpG sites throughout the human genome. Utilizing z-scores among the cohort for each site, we deployed an ensemble based machine learning pipeline and achieved a combined prediction accuracy of 0.96 (Binomial 95% Confidence Interval 0.868[Formula: see text]0.995).

CONCLUSION

We demonstrate a method for age and sex adjusted outlier detection of differentially methylated loci based on a large cohort of healthy individuals. We present a custom machine learning pipeline utilizing this outlier analysis to classify samples for potential methylation associated congenital disorders. These methods are able to achieve high accuracy when used with machine learning methods to classify abnormal methylation patterns.

Mitochondrial DNA copy number reduction via in vitro TFAM knockout remodels the nuclear epigenome and transcriptome

Mitochondrial DNA copy number (mtDNA-CN) is associated with several age-related chronic diseases and is a predictor of all-cause mortality. Here, we examine site-specific differential nuclear DNA (nDNA) methylation and differential gene expression resulting from in vitro reduction of mtDNA-CN to uncover shared genes and biological pathways mediating the effect of mtDNA-CN on disease. Epigenome and transcriptome profiles were generated for three independent human embryonic kidney (HEK293T) cell lines harbouring a mitochondrial transcription factor A (TFAM) heterozygous knockout generated via CRISPR-Cas9, and matched control lines. We identified 4,242 differentially methylated sites, 228 differentially methylated regions, and 179 differentially expressed genes associated with mtDNA-CN. Integrated analysis uncovered 381 Gene-CpG pairs. GABAA receptor genes and related pathways, the neuroactive ligand receptor interaction pathway, ABCD1/2 gene activity, and cell signalling processes were overrepresented, providing insight into the underlying biological mechanisms facilitating these associations. We also report evidence implicating chromatin state regulatory mechanisms as modulators of mtDNA-CN effect on gene expression. We demonstrate that mitochondrial DNA variation signals to the nuclear DNA epigenome and transcriptome and may lead to nuclear remodelling relevant to development, aging, and complex disease.

Self-control is associated with health-relevant disparities in buccal DNA-methylation measures of biological aging in older adults

Self-control is a personality dimension that is associated with better physical health and a longer lifespan. Here, we examined (1) whether self-control is associated with buccal and saliva DNA-methylation (DNAm) measures of biological aging quantified in children, adolescents, and adults, and (2) whether biological aging measured in buccal DNAm is associated with self-reported health. Following preregistered analyses, we computed two DNAm measures of advanced biological age (principal-component PhenoAge and GrimAge Acceleration) and a DNAm measure of pace of aging (DunedinPACE) in buccal samples from the German Socioeconomic Panel Study (SOEP-G[ene], n = 1058, age range 0-72, Mage = 42.65) and saliva samples from the Texas Twin Project (TTP, n = 1327, age range 8-20, Mage = 13.50). We found that lower self-control was associated with advanced biological age in older adults (PhenoAge Acceleration β = - .34, [- .51, - .17], p < .001; GrimAge Acceleration β = - .34, [- .49, - .19], p < .001), but not young adults, adolescents or children. These associations remained statistically robust even after correcting for possible confounders such as socioeconomic contexts, BMI, or genetic correlates of low self-control. Moreover, a faster pace of aging and advanced biological age measured in buccal DNAm were associated with self-reported disease (PhenoAge Acceleration: β = .13 [.06, .19], p < .001; GrimAge Acceleration: β = .19 [.12, .26], p < .001; DunedinPACE: β = .09 [.02, .17], p = .01). However, effect sizes were weaker than observations in blood, suggesting that customization of DNAm aging measures to buccal and saliva tissues may be necessary. Our findings are consistent with the hypothesis that self-control is associated with health via pathways that accelerate biological aging in older adults.

Perceived Experiences of racism in Relation to Genome-Wide DNA Methylation and Epigenetic Aging in the Black Women's Health Study

BACKGROUND

African American women have a disproportionate burden of disease compared to US non-Hispanic white women. Exposure to psychosocial stressors may contribute to these health disparities. Racial discrimination, a major stressor for African American women, could affect health through epigenetic mechanisms.

METHODS

We conducted an epigenome-wide association study (EWAS) to examine the association of interpersonal racism (in daily life and in institutional settings) with DNA methylation in blood in 384 participants of the Black Women's Health Study (BWHS). We also evaluated whether a greater number of perceived experiences of racism was associated with epigenetic aging as measured using different methylation clocks. Models were adjusted for chronological age, body mass index, years of education, neighborhood SES, geographic region of residence, alcohol drinking, smoking, and technical covariates.

RESULTS

Higher scores of racism in daily life were associated with higher methylation levels at the cg04494873 site in chromosome 5 (β = 0.64%; 95% CI = 0.41%, 0.87%; P = 6.35E-08). We also replicated one CpG site, cg03317714, which was inversely associated with racial discrimination in a previous EWAS among African American women. In the BWHS, higher scores of racism in daily life were associated with lower methylation levels at that CpG site (β = -0.94%; 95% CI = -1.37%, -0.51%; P = 2.2E-05). Higher racism scores were associated with accelerated epigenetic aging in more than one methylation clock.

CONCLUSIONS

Exposure to discriminatory events may affect the epigenome and accelerate biological aging, which may explain in part the earlier onset of disease in African American women.

Discovery of novel DNA methylation biomarker panels for the diagnosis and differentiation between common adenocarcinomas and their liver metastases

Differentiation between adenocarcinomas is sometimes challenging. The promising avenue for discovering new biomarkers lies in bioinformatics using DNA methylation analysis. Utilizing a 2853-sample identification dataset and a 782-sample independent verification dataset, we have identified diagnostic DNA methylation biomarkers that are hypermethylated in cancer and differentiate between breast invasive carcinoma, cholangiocarcinoma, colorectal cancer, hepatocellular carcinoma, lung adenocarcinoma, pancreatic adenocarcinoma and stomach adenocarcinoma. The best panels for cancer type exhibit sensitivity of 77.8-95.9%, a specificity of 92.7-97.5% for tumors, a specificity of 91.5-97.7% for tumors and normal tissues and a diagnostic accuracy of 85.3-96.4%. We have shown that the results can be extended from the primary cancers to their liver metastases, as the best panels diagnose and differentiate between pancreatic adenocarcinoma liver metastases and breast invasive carcinoma liver metastases with a sensitivity and specificity of 83.3-100% and a diagnostic accuracy of 86.8-91.9%. Moreover, the panels could detect hypermethylation of selected regions in the cell-free DNA of patients with liver metastases. At the same time, these were unmethylated in the cell-free DNA of healthy donors, confirming their applicability for liquid biopsies.

Decoding the DNA methylome of central nervous system tumors: An emerging modality for integrated diagnosis

The definitive diagnosis and classification of individual cancers are crucial for patient care and cancer research. To achieve a robust diagnosis of central nervous system (CNS) tumors, a genotype-phenotype integrated diagnostic approach was introduced in recent versions of the World Health Organization classification, followed by the incorporation of a genome-wide DNA methylome-based classification. Microarray-based platforms are widely used to obtain DNA methylome data, and the German Cancer Research Center (Deutsches Krebsforschungszentrum [DKFZ]) has a webtool for a DNA methylation-based classifier (DKFZ classifier). Integration of DNA methylome will further enhance the precision of CNS tumor classification, especially in diagnostically challenging cases. However, in the clinical application of DNA methylome-based classification, challenges related to data interpretation persist, in addition to technical caveats, regulations, and limited accessibility. Dimensionality reduction (DMR) can complement integrated diagnosis by visualizing a profile and comparing it with other known samples. Therefore, DNA methylome-based classification is a highly useful research tool for auxiliary analysis in challenging diagnostic and rare disease cases, and for establishing novel tumor concepts. Decoding the DNA methylome, especially by DMR in addition to DKFZ classifier, emphasizes the capability of grasping the fundamental biological principles that provide new perspectives on CNS tumors.

TIME-seq reduces time and cost of DNA methylation measurement for epigenetic clock construction

Epigenetic 'clocks' based on DNA methylation have emerged as the most robust and widely used aging biomarkers, but conventional methods for applying them are expensive and laborious. Here we develop tagmentation-based indexing for methylation sequencing (TIME-seq), a highly multiplexed and scalable method for low-cost epigenetic clocks. Using TIME-seq, we applied multi-tissue and tissue-specific epigenetic clocks in over 1,800 mouse DNA samples from eight tissue and cell types. We show that TIME-seq clocks are accurate and robust, enriched for polycomb repressive complex 2-regulated loci, and benchmark favorably against conventional methods despite being up to 100-fold less expensive. Using dietary treatments and gene therapy, we find that TIME-seq clocks reflect diverse interventions in multiple tissues. Finally, we develop an economical human blood clock (R > 0.96, median error = 3.39 years) in 1,056 demographically representative individuals. These methods will enable more efficient epigenetic clock measurement in larger-scale human and animal studies.

Low-dose radiation from CT examination induces DNA double-strand breaks and detectable changes of DNA methylation in peripheral blood cells

BACKGROUND

Radiation burden from CT examinations increases rapidly with the increased clinical use frequency. Previous studies have disclosed the association between radiation exposure and increased double-strand breaks (DSBs) and changes in DNA methylation. However, whether the induced DSBs by CT examination recover within 24h and whether a CT examination induces detectable gene-specific methylation changes are still unclear. The aim of the present study was to analyze γ-H2AX in the peripheral blood lymphocyte (PBL) of healthy adults before and after CT examination and to discover the differentially methylated positions (DMPs) along with an analysis of DNA methylation changes caused by CT examination.

MATERIALS AND METHODS

Peripheral blood samples of 4 ml were drawn from 20 healthy volunteers at three time points: before CT examination, after CT examination 1h, and after CT examination 24h. γ-H2AX immunofluorescence and Illumina Infinium Human Methylation EPIC BeadChip (850k BeadChip) were used respectively for the test of DSBs and the epigenome-wide DNA methylation analysis. Linear mixed-effect (LME) models were used to evaluate the impacts of doses represented by different parameters and foci on genome-wide DNA methylation.

RESULTS

The number of γ-H2AX foci per cell at 1h showed linear dose-responses for the radiation doses represented by CT index volume (CTDIvol), dose length product (DLP), and blood absorbed dose, respectively. Residual γ-H2AX foci was observed after CT examination at 24h (p < .001). DMPs and γ-H2AX foci changes could be found within 1h. One CpG site related to PAX5 was significantly changed by using most of the parameters in LME models and did not recover till 24h.

CONCLUSIONS

Residual γ-H2AX foci exist after CT examination at 24h. The DNA methylation changes induced by CT examination may not recover within 24h. The DNA methylation had been changed as early as at 1h. The PAX5-related CpG site may be a potential biomarker of low-dose radiation.

CLINICAL RELEVANCE

The biological effects and the cancer risks of CT examination are still unclear. The present study is an effort to document the CT scan-induced events in 24h in vivo. The CT scanning area should be strictly limited, and non-essential repeated operations shouldn't be performed within 24h.

Quantifying the proportion of different cell types in the human cortex using DNA methylation profiles

BACKGROUND

Due to interindividual variation in the cellular composition of the human cortex, it is essential that covariates that capture these differences are included in epigenome-wide association studies using bulk tissue. As experimentally derived cell counts are often unavailable, computational solutions have been adopted to estimate the proportion of different cell types using DNA methylation data. Here, we validate and profile the use of an expanded reference DNA methylation dataset incorporating two neuronal and three glial cell subtypes for quantifying the cellular composition of the human cortex.

RESULTS

We tested eight reference panels containing different combinations of neuronal- and glial cell types and characterised their performance in deconvoluting cell proportions from computationally reconstructed or empirically derived human cortex DNA methylation data. Our analyses demonstrate that while these novel brain deconvolution models produce accurate estimates of cellular proportions from profiles generated on postnatal human cortex samples, they are not appropriate for the use in prenatal cortex or cerebellum tissue samples. Applying our models to an extensive collection of empirical datasets, we show that glial cells are twice as abundant as neuronal cells in the human cortex and identify significant associations between increased Alzheimer's disease neuropathology and the proportion of specific cell types including a decrease in NeuNNeg/SOX10Neg nuclei and an increase of NeuNNeg/SOX10Pos nuclei.

CONCLUSIONS

Our novel deconvolution models produce accurate estimates for cell proportions in the human cortex. These models are available as a resource to the community enabling the control of cellular heterogeneity in epigenetic studies of brain disorders performed on bulk cortex tissue.

Toward Explainable Artificial Intelligence for Precision Pathology

The rapid development of precision medicine in recent years has started to challenge diagnostic pathology with respect to its ability to analyze histological images and increasingly large molecular profiling data in a quantitative, integrative, and standardized way. Artificial intelligence (AI) and, more precisely, deep learning technologies have recently demonstrated the potential to facilitate complex data analysis tasks, including clinical, histological, and molecular data for disease classification; tissue biomarker quantification; and clinical outcome prediction. This review provides a general introduction to AI and describes recent developments with a focus on applications in diagnostic pathology and beyond. We explain limitations including the black-box character of conventional AI and describe solutions to make machine learning decisions more transparent with so-called explainable AI. The purpose of the review is to foster a mutual understanding of both the biomedical and the AI side. To that end, in addition to providing an overview of the relevant foundations in pathology and machine learning, we present worked-through examples for a better practical understanding of what AI can achieve and how it should be done.

Alcohol Use Disorder-Associated DNA Methylation in the Nucleus Accumbens and Dorsolateral Prefrontal Cortex

Background

Alcohol use disorder (AUD) has a profound public health impact. However, understanding of the molecular mechanisms underlying the development and progression of AUD remain limited. Here, we interrogate AUD-associated DNA methylation (DNAm) changes within and across addiction-relevant brain regions: the nucleus accumbens (NAc) and dorsolateral prefrontal cortex (DLPFC).

Methods

Illumina HumanMethylation EPIC array data from 119 decedents of European ancestry (61 cases, 58 controls) were analyzed using robust linear regression, with adjustment for technical and biological variables. Associations were characterized using integrative analyses of public gene regulatory data and published genetic and epigenetic studies. We additionally tested for brain region-shared and -specific associations using mixed effects modeling and assessed implications of these results using public gene expression data.

Results

At a false discovery rate ≤ 0.05, we identified 53 CpGs significantly associated with AUD status for NAc and 31 CpGs for DLPFC. In a meta-analysis across the regions, we identified an additional 21 CpGs associated with AUD, for a total of 105 unique AUD-associated CpGs (120 genes). AUD-associated CpGs were enriched in histone marks that tag active promoters and our strongest signals were specific to a single brain region. Of the 120 genes, 23 overlapped with previous genetic associations for substance use behaviors; all others represent novel associations.

Conclusions

Our findings identify AUD-associated methylation signals, the majority of which are specific within NAc or DLPFC. Some signals may constitute predisposing genetic and epigenetic variation, though more work is needed to further disentangle the neurobiological gene regulatory differences associated with AUD.

Creation and Validation of the First Infinium DNA Methylation Array for the Human Imprintome

Background

Differentially methylated imprint control regions (ICRs) regulate the monoallelic expression of imprinted genes. Their epigenetic dysregulation by environmental exposures throughout life results in the formation of common chronic diseases. Unfortunately, existing Infinium methylation arrays lack the ability to profile these regions adequately. Whole genome bisulfite sequencing (WGBS) is the unique method able to profile these regions, but it is very expensive and it requires not only a high coverage but it is also computationally intensive to assess those regions.

Findings

To address this deficiency, we developed a custom methylation array containing 22,819 probes. Among them, 9,757 probes map to 1,088 out of the 1,488 candidate ICRs recently described. To assess the performance of the array, we created matched samples processed with the Human Imprintome array and WGBS, which is the current standard method for assessing the methylation of the Human Imprintome. We compared the methylation levels from the shared CpG sites and obtained a mean R 2 = 0.569. We also created matched samples processed with the Human Imprintome array and the Infinium Methylation EPIC v2 array and obtained a mean R 2 = 0.796. Furthermore, replication experiments demonstrated high reliability (ICC: 0.799-0.945).

Conclusions

Our custom array will be useful for replicable and accurate assessment, mechanistic insight, and targeted investigation of ICRs. This tool should accelerate the discovery of ICRs associated with a wide range of diseases and exposures, and advance our understanding of genomic imprinting and its relevance in development and disease formation throughout the life course.

Methylation profiles at birth linked to early childhood obesity

Childhood obesity represents a significant global health concern and identifying risk factors is crucial for developing intervention programs. Many 'omics' factors associated with the risk of developing obesity have been identified, including genomic, microbiomic, and epigenomic factors. Here, using a sample of 48 infants, we investigated how the methylation profiles in cord blood and placenta at birth were associated with weight outcomes (specifically, conditional weight gain, body mass index, and weight-for-length ratio) at age six months. We characterized genome-wide DNA methylation profiles using the Illumina Infinium MethylationEpic chip, and incorporated information on child and maternal health, and various environmental factors into the analysis. We used regression analysis to identify genes with methylation profiles most predictive of infant weight outcomes, finding a total of 23 relevant genes in cord blood and 10 in placenta. Notably, in cord blood, the methylation profiles of three genes (PLIN4, UBE2F, and PPP1R16B) were associated with all three weight outcomes, which are also associated with weight outcomes in an independent cohort suggesting a strong relationship with weight trajectories in the first six months after birth. Additionally, we developed a Methylation Risk Score (MRS) that could be used to identify children most at risk for developing childhood obesity. While many of the genes identified by our analysis have been associated with weight-related traits (e.g., glucose metabolism, BMI, or hip-to-waist ratio) in previous genome-wide association and variant studies, our analysis implicated several others, whose involvement in the obesity phenotype should be evaluated in future functional investigations.

Simultaneous assessment of mitochondrial DNA copy number and nuclear epigenetic age towards predictive models of development and aging

OBJECTIVE

Mitochondrial dysfunction and nuclear epigenetic alterations, two hallmarks of aging, are associated with aberrant development and complex disease risk. Here, we report a method for the simultaneous assessment of mitochondrial DNA copy number (mtDNA-CN) and DNA methylation age (DNAm age) from the same DNA extraction using quantitative polymerase chain reaction (qPCR) and array data, respectively.

RESULT

We present methods for the concurrent estimation of mtDNA-CN and DNAm age from the same DNA samples. This includes qPCR to estimate mtDNA-CN, representing the number of circular mitochondrial genomes in a cell, and DNA methylation microarray data to estimate the epigenetic age of an individual. Further, we provide a method for the combination of these metrics into a shared metric termed 'mtEpiAge'. This approach provides a valuable tool for exploring the interplay between mitochondrial dysfunction and nuclear epigenetic alterations, and their associations with disease and aging.

Characterizing epigenetic aging in an adult sickle cell disease cohort

ABSTRACT

Sickle cell disease (SCD) affects ∼100 000 predominantly African American individuals in the United States, causing significant cellular damage, increased disease complications, and premature death. However, the contribution of epigenetic factors to SCD pathophysiology remains relatively unexplored. DNA methylation (DNAm), a primary epigenetic mechanism for regulating gene expression in response to the environment, is an important driver of normal cellular aging. Several DNAm epigenetic clocks have been developed to serve as a proxy for cellular aging. We calculated the epigenetic ages of 89 adults with SCD (mean age, 30.64 years; 60.64% female) using 5 published epigenetic clocks: Horvath, Hannum, PhenoAge, GrimAge, and DunedinPACE. We hypothesized that in chronic disease, such as SCD, individuals would demonstrate epigenetic age acceleration, but the results differed depending on the clock used. Recently developed clocks more consistently demonstrated acceleration (GrimAge, DunedinPACE). Additional demographic and clinical phenotypes were analyzed to explore their association with epigenetic age estimates. Chronological age was significantly correlated with epigenetic age in all clocks (Horvath, r = 0.88; Hannum, r = 0.89; PhenoAge, r = 0.85; GrimAge, r = 0.88; DunedinPACE, r = 0.34). The SCD genotype was associated with 2 clocks (PhenoAge, P = .02; DunedinPACE, P < .001). Genetic ancestry, biological sex, β-globin haplotypes, BCL11A rs11886868, and SCD severity were not associated. These findings, among the first to interrogate epigenetic aging in adults with SCD, demonstrate epigenetic age acceleration with recently developed epigenetic clocks but not older-generation clocks. Further development of epigenetic clocks may improve their predictive ability and utility for chronic diseases such as SCD.

Usual dietary intake and change in DNA methylation over years: EWAS in KORA FF4 and KORA fit

Introduction

Changes in DNA methylation can increase or suppress the expression of health-relevant genes. We investigated for the first time the relationship between habitual food consumption and changes in DNA methylation.

Methods

The German KORA FF4 and KORA Fit studies were used to study the change in methylation over a median follow-up of 4 years. Only subjects participating in both surveys and with available dietary and methylation data were included in the analysis (n = 465). DNA methylation was measured using the Infinium MethylationEPIC BeadChip (Illumina), resulting in 735,527 shared CpGs across both studies. Generalized estimating equation models with an interaction term of exposure and time point were used to analyze the association of 34 food groups, folic acid, and two dietary patterns with changes in DNA methylation over time.

Results

The results were corrected for genomic inflation. Significant interaction terms indicate different effects between both time points. We observed only a few significant associations between food intake and change in DNA methylation, except for cream and spirit consumption. The annotated genes include CLN3, PROM1, DLEU7, TLL2, and UGT1A10.

Discussion

We identified weak associations between food consumption and DNA methylation change. The differential results for cream and spirits, both consumed in low quantities, require replication in independent studies.

Alterations in leukocyte DNA methylome are associated to immunosuppression in severe clinical phenotypes of septic patients

Introduction

Sepsis patients experience a complex interplay of host pro- and anti-inflammatory processes which compromise the clinical outcome. Despite considering the latest clinical and scientific research, our comprehension of the immunosuppressive events in septic episodes remains incomplete. Additionally, a lack of data exists regarding the role of epigenetics in modulating immunosuppression, subsequently impacting patient survival.

Methods

To advance the current understanding of the mechanisms underlying immunosuppression, in this study we explored the dynamics of DNA methylation using the Infinium Methylation EPIC v1.0 BeadChip Kit in leukocytes from patients suffering from sepsis, septic shock, and critically ill patients as controls, within the first 24 h after admission in the Intensive Care Unit of a tertiary hospital.

Results and discussion

Employing two distinct analysis approaches (DMRcate and mCSEA) in comparing septic shock and critically ill patients, we identified 1,256 differentially methylated regions (DMRs) intricately linked to critical immune system pathways. The examination of the top 100 differentially methylated positions (DMPs) between septic shock and critically ill patients facilitated a clear demarcation among the three patient groups. Notably, the top 6,657 DMPs exhibited associations with organ dysfunction and lactate levels. Among the individual genes displaying significant differential methylation, IL10, TREM1, IL1B, and TNFAIP8 emerged with the most pronounced methylation alterations across the diverse patient groups when subjected to DNA bisulfite pyrosequencing analysis. These findings underscore the dynamic nature of DNA methylation profiles, highlighting the most pronounced alterations in patients with septic shock, and revealing their close association with the disease.

Identifying epigenetic aging moderators using the epigenetic pacemaker

Epigenetic clocks are DNA methylation-based chronological age prediction models that are commonly employed to study age-related biology. The difference between the predicted and observed age is often interpreted as a form of biological age acceleration, and many studies have measured the impact of environmental and disease-associated factors on epigenetic age. Most epigenetic clocks are fit using approaches that minimize the error between the predicted and observed chronological age, and as a result, they may not accurately model the impact of factors that moderate the relationship between the actual and epigenetic age. Here, we compare epigenetic clocks that are constructed using penalized regression methods to an evolutionary framework of epigenetic aging with the epigenetic pacemaker (EPM), which directly models DNA methylation as a function of a time-dependent epigenetic state. In simulations, we show that the value of the epigenetic state is impacted by factors such as age, sex, and cell-type composition. Next, in a dataset aggregated from previous studies, we show that the epigenetic state is also moderated by sex and the cell type. Finally, we demonstrate that the epigenetic state is also moderated by toxins in a study on polybrominated biphenyl exposure. Thus, we find that the pacemaker provides a robust framework for the study of factors that impact epigenetic age acceleration and that the effect of these factors may be obscured in traditional clocks based on linear regression models.

Multi-omic and functional analysis for classification and treatment of sarcomas with FUS-TFCP2 or EWSR1-TFCP2 fusions

Linking clinical multi-omics with mechanistic studies may improve the understanding of rare cancers. We leverage two precision oncology programs to investigate rhabdomyosarcoma with FUS/EWSR1-TFCP2 fusions, an orphan malignancy without effective therapies. All tumors exhibit outlier ALK expression, partly accompanied by intragenic deletions and aberrant splicing resulting in ALK variants that are oncogenic and sensitive to ALK inhibitors. Additionally, recurrent CKDN2A/MTAP co-deletions provide a rationale for PRMT5-targeted therapies. Functional studies show that FUS-TFCP2 blocks myogenic differentiation, induces transcription of ALK and truncated TERT, and inhibits DNA repair. Unlike other fusion-driven sarcomas, TFCP2-rearranged tumors exhibit genomic instability and signs of defective homologous recombination. DNA methylation profiling demonstrates a close relationship with undifferentiated sarcomas. In two patients, sarcoma was preceded by benign lesions carrying FUS-TFCP2, indicating stepwise sarcomagenesis. This study illustrates the potential of linking precision oncology with preclinical research to gain insight into the classification, pathogenesis, and therapeutic vulnerabilities of rare cancers.

Using saliva epigenetic data to develop and validate a multivariable predictor of esophageal cancer status

Background: Salivary epigenetic biomarkers may detect esophageal cancer. Methods: A total of 256 saliva samples from esophageal adenocarcinoma patients and matched volunteers were analyzed with Illumina EPIC methylation arrays. Three datasets were created, using 64% for discovery, 16% for testing and 20% for validation. Modules of gene-based methylation probes were created using weighted gene coexpression network analysis. Module significance to disease and gene importance to module were determined and a random forest classifier generated using best-scoring gene-related epigenetic probes. A cost-sensitive wrapper algorithm maximized cancer diagnosis. Results: Using age, sex and seven probes, esophageal adenocarcinoma was detected with area under the curve of 0.72 in discovery, 0.73 in testing and 0.75 in validation datasets. Cancer sensitivity was 88% with specificity of 31%. Conclusion: We have demonstrated a potentially clinically viable classifier of esophageal cancer based on saliva methylation.

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.

Association of psychological distress and DNA methylation: A 5-year longitudinal population-based twin study

AIM

To identify the psychological distress (PD)-associated 5'-cytosine-phosphate-guanine-3' sites (CpGs), and investigate the temporal relationship between dynamic changes in DNA methylation (DNAm) and PD.

METHODS

This study included 1084 twins from the Chinese National Twin Register (CNTR). The CNTR conducted epidemiological investigations and blood withdrawal twice in 2013 and 2018. These included twins were used to perform epigenome-wide association studies (EWASs) and to validate the previously reported PD-associated CpGs selected from previous EWASs in PubMed, Embase, and the EWAS catalog. Next, a cross-lagged study was performed to examine the temporality between changes in DNAm and PD in 308 twins who completed both 2013 and 2018 surveys.

RESULTS

The EWAS analysis of our study identified 25 CpGs. In the validation analysis, 741 CpGs from 29 previous EWASs on PD were selected for validation, and 101 CpGs were validated to be significant at a false discovery rate <0.05. The cross-lagged analysis found a unidirectional path from PD to DNAm at 14 CpGs, while no sites showed significance from DNAm to PD.

CONCLUSIONS

This study identified and validated PD-related CpGs in a Chinese twin population, and suggested that PD may be the cause of changes in DNAm over time. The findings provide new insights into the molecular mechanisms underlying PD pathophysiology.

Serum DNA methylome of the colorectal cancer serrated pathway enables non-invasive detection

The clinical relevance of the colorectal cancer serrated pathway is evident, but the screening of serrated lesions remains challenging. We aimed to characterize the serum methylome of the serrated pathway and to evaluate circulating cell-free DNA (cfDNA) methylomes as a potential source of biomarkers for the non-invasive detection of serrated lesions. We collected serum samples from individuals with serrated adenocarcinoma (SAC), traditional serrated adenomas, sessile serrated lesions, hyperplastic polyps and individuals with no colorectal findings. First, we quantified cfDNA methylation with the MethylationEPIC array. Then, we compared the methylation profiles with tissue and serum datasets. Finally, we evaluated the utility of serum cfDNA methylation biomarkers. We identified a differential methylation profile able to distinguish high-risk serrated lesions from no serrated neoplasia, showing concordance with tissue methylation from SAC and sessile serrated lesions. Serum methylation profiles are pathway-specific, clearly separating serrated lesions from conventional adenomas. The combination of ninjurin 2 (NINJ2) and glutamate-rich 1 (ERICH1) methylation discriminated high-risk serrated lesions and SAC with 91.4% sensitivity (64.4% specificity), while zinc finger protein 718 (ZNF718) methylation reported 100% sensitivity for the detection of SAC (96% specificity). This is the first study exploring the serum methylome of serrated lesions. Differential methylation of cfDNA can be used for the non-invasive detection of colorectal serrated lesions.

Blood-based DNA methylation in advanced Nasopharyngeal Carcinoma exhibited distinct CpG methylation signature

The TNM staging system is currently used to detect cancer stages. Regardless, a small proportion of cancer patients recur even after therapy, suggesting more specific molecular tools are required to justify the stage-specific detection and prompt cancer diagnosis. Thus, we aimed to explore the blood-based DNA methylation signature of metastatic nasopharyngeal carcinoma (NPC) to establish a holistic methylation biomarker panel. For the identification of methylation signature, the EPIC BeadChip-based array was performed. Comparative analysis for identifying unique probes, validation, and functional studies was investigated by analyzing GEO and TCGA datasets. We observed 4093 differentially methylated probes (DMPs), 1232 hydroxymethylated probes, and 25 CpG islands. Gene expression study revealed both upregulated and downregulated genes. Correlation analysis suggested a positive (with a positive r, p ≤ 0.05) and negative (with a negative r, p ≤ 0.05) association with different cancers. TFBS analysis exhibited the binding site for many TFs. Furthermore, gene enrichment analysis indicated the involvement of those identified genes in biological pathways. However, blood-based DNA methylation data uncovered a distinct DNA methylation pattern, which might have an additive role in NPC progression by altering the TFs binding. Moreover, based on tissue-specificity, a variation of correlation between methylation and gene expression was noted in different cancers.

Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis

A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.

World Trade Center Exposure, DNA Methylation Changes, and Cancer: A Review of Current Evidence

Introduction: Known carcinogens in the dust and fumes from the destruction of the World Trade Center (WTC) towers on 9 November 2001 included metals, asbestos, and organic pollutants, which have been shown to modify epigenetic status. Epigenome-wide association analyses (EWAS) using uniform (Illumina) methodology have identified novel epigenetic profiles of WTC exposure. Methods: We reviewed all published data, comparing differentially methylated gene profiles identified in the prior EWAS studies of WTC exposure. This included DNA methylation changes in blood-derived DNA from cases of cancer-free "Survivors" and those with breast cancer, as well as tissue-derived DNA from "Responders" with prostate cancer. Emerging molecular pathways related to the observed DNA methylation changes in WTC-exposed groups were explored and summarized. Results: WTC dust exposure appears to be associated with DNA methylation changes across the genome. Notably, WTC dust exposure appears to be associated with increased global DNA methylation; direct dysregulation of cancer genes and pathways, including inflammation and immune system dysregulation; and endocrine system disruption, as well as disruption of cholesterol homeostasis and lipid metabolism. Conclusion: WTC dust exposure appears to be associated with biologically meaningful DNA methylation changes, with implications for carcinogenesis and development of other chronic diseases.

Retroelement-Age Clocks: Epigenetic Age Captured by Human Endogenous Retrovirus and LINE-1 DNA methylation states

Human endogenous retroviruses (HERVs), the remnants of ancient viral infections embedded within the human genome, and long interspersed nuclear elements 1 (LINE-1), a class of autonomous retrotransposons, are silenced by host epigenetic mechanisms including DNA methylation. The resurrection of particular retroelements has been linked to biological aging. Whether the DNA methylation states of locus specific HERVs and LINEs can be used as a biomarker of chronological age in humans remains unclear. We show that highly predictive epigenetic clocks of chronological age can be constructed from retroelement DNA methylation states in the immune system, across human tissues, and pan-mammalian species. We found retroelement epigenetic clocks were reversed during transient epigenetic reprogramming, accelerated in people living with HIV-1, responsive to antiretroviral therapy, and accurate in estimating long-term culture ages of human brain organoids. Our findings support the hypothesis of epigenetic dysregulation of retroelements as a potential contributor to the biological hallmarks of aging.

Epigenetics of the far northern Yakutian population

BACKGROUND

Yakuts are one of the indigenous populations of the subarctic and arctic territories of Siberia characterized by a continental subarctic climate with severe winters, with the regular January average temperature in the regional capital city of Yakutsk dipping below - 40 °C. The epigenetic mechanisms of adaptation to such ecologies and environments and, in particular, epigenetic age acceleration in the local population have not been studied before.

RESULTS

This work reports the first epigenetic study of the Yakutian population using whole-blood DNA methylation data, supplemented with the comparison to the residents of Central Russia. Gene set enrichment analysis revealed, among others, geographic region-specific differentially methylated regions associated with adaptation to climatic conditions (water consumption, digestive system regulation), aging processes (actin filament activity, cell fate), and both of them (channel activity, regulation of steroid and corticosteroid hormone secretion). Further, it is demonstrated that the epigenetic age acceleration of the Yakutian representatives is significantly higher than that of Central Russia counterparts. For both geographic regions, we showed that epigenetically males age faster than females, whereas no significant sex differences were found between the regions.

CONCLUSIONS

We performed the first study of the epigenetic data of the Yakutia cohort, paying special attention to region-specific features, aging processes, age acceleration, and sex specificity.

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.

Waterpipe and cigarette epigenome analysis reveals markers implicated in addiction and smoking type inference

Waterpipe smoking is frequent in the Middle East and Africa with emerging prevalence worldwide. The epigenome acts as a molecular sensor to exposures and a crucial driver in several diseases. With the widespread use of waterpipe smoking, it is timely to investigate its epigenomic markers and their role in addiction, as a central player in disease prevention and therapeutic strategies. DNA methylome-wide profiling was performed on an exposure-rich population from the Middle East, constituting of 216 blood samples split equally between never, cigarette-only and waterpipe-only smokers. Waterpipe smokers showed predominantly distinct epigenetic markers from cigarette smokers, even though both smoking forms are tobacco-based. Moreover, each smoking form could be accurately (∼90 %) inferred from the DNA methylome using machine learning. Top markers showed dose-response relationship with extent of smoking and were validated using independent technologies and additional samples (total N = 284). Smoking markers were enriched in regulatory regions and several biological pathways, primarily addiction. The epigenetically altered genes were not associated with genetic etiology of tobacco use, and the methylation levels of addiction genes, in particular, were more likely to reverse after smoking cessation. In contrast, other epigenetic markers continued to feature smoking exposure after cessation, which may explain long-term health effects observed in former smokers. This study reports, for the first time, blood epigenome-wide markers of waterpipe smokers and reveals new markers of cigarette smoking, with implications in mechanisms of addiction and the capacity to discriminate between different smoking types. These markers may offer actionable targets to reverse the epigenetic memory of addiction and can guide future prevention strategies for tobacco smoking as the most preventable cause of illnesses worldwide.

Linking Prenatal Environmental Exposures to Lifetime Health with Epigenome-Wide Association Studies: State-of-the-Science Review and Future Recommendations

BACKGROUND

The prenatal environment influences lifetime health; epigenetic mechanisms likely predominate. In 2016, the first international consortium paper on cigarette smoking during pregnancy and offspring DNA methylation identified extensive, reproducible exposure signals. This finding raised expectations for epigenome-wide association studies (EWAS) of other exposures.

OBJECTIVE

We review the current state-of-the-science for DNA methylation associations across prenatal exposures in humans and provide future recommendations.

METHODS

We reviewed 134 prenatal environmental EWAS of DNA methylation in newborns, focusing on 51 epidemiological studies with meta-analysis or replication testing. Exposures spanned cigarette smoking, alcohol consumption, air pollution, dietary factors, psychosocial stress, metals, other chemicals, and other exogenous factors. Of the reproducible DNA methylation signatures, we examined implementation as exposure biomarkers.

RESULTS

Only 19 (14%) of these prenatal EWAS were conducted in cohorts of 1,000 or more individuals, reflecting the still early stage of the field. To date, the largest perinatal EWAS sample size was 6,685 participants. For comparison, the most recent genome-wide association study for birth weight included more than 300,000 individuals. Replication, at some level, was successful with exposures to cigarette smoking, folate, dietary glycemic index, particulate matter with aerodynamic diameter < 10 μ m and < 2.5 μ m , nitrogen dioxide, mercury, cadmium, arsenic, electronic waste, PFAS, and DDT. Reproducible effects of a more limited set of prenatal exposures (smoking, folate) enabled robust methylation biomarker creation.

DISCUSSION

Current evidence demonstrates the scientific premise for reproducible DNA methylation exposure signatures. Better powered EWAS could identify signatures across many exposures and enable comprehensive biomarker development. Whether methylation biomarkers of exposures themselves cause health effects remains unclear. We expect that larger EWAS with enhanced coverage of epigenome and exposome, along with improved single-cell technologies and evolving methods for integrative multi-omics analyses and causal inference, will expand mechanistic understanding of causal links between environmental exposures, the epigenome, and health outcomes throughout the life course. https://doi.org/10.1289/EHP12956.

Biological stability of DNA methylation measurements over varying intervals of time and in the presence of acute stress

Identifying factors that influence the stability of DNA methylation measurements across biological replicates is of critical importance in basic and clinical research. Using a within-person between-group experimental design (n = 31, number of observations = 192), we report the stability of biological replicates over a variety of unique temporal scenarios, both in the absence and presence of acute psychosocial stress, and between individuals who have experienced early life adversity (ELA) and non-exposed individuals. We found that varying time intervals, acute stress, and ELA exposure influenced the stability of repeated DNA methylation measurements. In the absence of acute stress, probes were less stable as time passed; however, stress exerted a stabilizing influence on probes over longer time intervals. Compared to non-exposed individuals, ELA-exposed individuals had significantly lower probe stability immediately following acute stress. Additionally, we found that across all scenarios, probes used in most epigenetic-based algorithms for estimating epigenetic age or immune cell proportions had average or below-average stability, except for the Principal Component and DunedinPACE epigenetic ageing clocks, which were enriched for more stable probes. Finally, using highly stable probes in the absence of stress, we identified multiple probes that were hypomethylated in the presence of acute stress, regardless of ELA status. Two hypomethylated probes are located near the transcription start site of the glutathione-disulfide reductase gene (GSR), which has previously been shown to be an integral part of the stress response to environmental toxins. We discuss implications for future studies concerning the reliability and reproducibility of DNA methylation measurements.Abbreviations: DNAm - DNA methylation, CpG - 5'-cytosine-phosphate-guanine-3,' ICC - Interclass correlation coefficient, ELA - Early-life adversity, PBMCs - Peripheral blood mononuclear cells, mQTL - Methylation quantitative trait loci, TSS - Transcription start site, GSR - Glutathione-disulfide reductase gene, TSST - Trier social stress test, PC - Principal component.

A novel principal component based method for identifying differentially methylated regions in Illumina Infinium MethylationEPIC BeadChip data

Differentially methylated regions (DMRs) are genomic regions with methylation patterns across multiple CpG sites that are associated with a phenotype. In this study, we proposed a Principal Component (PC) based DMR analysis method for use with data generated using the Illumina Infinium MethylationEPIC BeadChip (EPIC) array. We obtained methylation residuals by regressing the M-values of CpGs within a region on covariates, extracted PCs of the residuals, and then combined association information across PCs to obtain regional significance. Simulation-based genome-wide false positive (GFP) rates and true positive rates were estimated under a variety of conditions before determining the final version of our method, which we have named DMRPC. Then, DMRPC and another DMR method, coMethDMR, were used to perform epigenome-wide analyses of several phenotypes known to have multiple associated methylation loci (age, sex, and smoking) in a discovery and a replication cohort. Among regions that were analysed by both methods, DMRPC identified 50% more genome-wide significant age-associated DMRs than coMethDMR. The replication rate for the loci that were identified by only DMRPC was higher than the rate for those that were identified by only coMethDMR (90% for DMRPC vs. 76% for coMethDMR). Furthermore, DMRPC identified replicable associations in regions of moderate between-CpG correlation which are typically not analysed by coMethDMR. For the analyses of sex and smoking, the advantage of DMRPC was less clear. In conclusion, DMRPC is a new powerful DMR discovery tool that retains power in genomic regions with moderate correlation across CpGs.

Validation of the new EPIC DNA methylation microarray (900K EPIC v2) for high-throughput profiling of the human DNA methylome

DNA methylation, one of the best characterized epigenetic marks in the human genome, plays a pivotal role in gene transcription regulation and other biological processes in humans. On top of that, the DNA methylome undergoes profound changes in cancer and other disorders. However, large-scale and population-based studies are limited by high costs and the need for considerable expertise in data analysis for whole-genome bisulphite-sequencing methodologies. Following the success of the EPIC DNA methylation microarray, the newly developed Infinium HumanMethylationEPIC version 2.0 (900K EPIC v2) is now available. This new array contains more than 900,000 CpG probes covering the human genome and excluding masked probes from the previous version. The 900K EPIC v2 microarray adds more than 200,000 probes covering extra DNA cis-regulatory regions such as enhancers, super-enhancers and CTCF binding regions. Herein, we have technically and biologically validated the new methylation array to show its high reproducibility and consistency among technical replicates and with DNA extracted from FFPE tissue. In addition, we have hybridized primary normal and tumoural tissues and cancer cell lines from different sources and tested the robustness of the 900K EPIC v2 microarray when analysing the different DNA methylation profiles. The validation highlights the improvements offered by the new array and demonstrates the versatility of this updated tool for characterizing the DNA methylome in human health and disease.

Gaps in current methods to detect polymorphic CpGs from Illumina Infinium human methylation microarrays and exploring their potential impact in multi-EWAS analyses

DNA methylation (DNAm) epigenome-wide association studies (EWAS) have been performed on diverse ethnicities to discover novel biomarkers associated with various diseases, such as cancers, autoimmune diseases, and neurological disorders. However, genetic polymorphisms can influence DNAm levels resulting in methylation quantitative trait loci (meQTL). These can be either direct effects, by altering the sequence of the methylation (CpG) site itself, or, in the case of array-based measures, indirectly altering the detection probe-binding site interaction. Given that genetic variant frequencies associated with meQTL can differ between population groups, these have the potential to confound EWAS observations, particularly in multi-ethnic populations. In this study, we analysed publicly available DNA methylation profiles (450K array), consisting of 1342 individuals from 6 distinct ancestral groups. We investigate two distinct tools (GapHunter and MethylToSNP) specifically designed to identify CpG sites that may be influenced by genetic variation. Results from this aggregated trans-ancestral epigenome-wide dataset suggest that both tools fail to consistently identify not only rarer (MAF < 0.05) genetic variant effects but also more than half of sites predicted to be associated with variants with much higher allele frequencies (MAF >0.2). In addition, there is a relatively low concordance in the detection of polymorphic CpGs between GapHunter and MethylToSNP. Screening of CpG site associations from EWAS using either of these tools is unlikely to be a robust or comprehensive means of identifying all genetic variant confounding effects.

Differential methylation pattern in pubertal girls associated with biochemical premature adrenarche

Biochemical premature adrenarche is defined by elevated serum DHEAS [≥40 μg/dL] before age 8 y in girls. This condition is receiving more attention due to its association with obesity, hyperinsulinemia, dyslipidemia, and polycystic ovary syndrome. Nevertheless, the link between early androgen excess and these risk factors remains unknown. Epigenetic modifications, and specifically DNA methylation, have been associated with the initiation and progression of numerous disorders, including obesity and insulin resistance. The aim of this study was to determine if prepubertal androgen exposure is associated with a different methylation profile in pubertal girls. Eighty-six healthy girls were studied. At age 7 y, anthropometric measurements were begun and DHEAS levels were determined. Girls were classified into Low DHEAS (LD) [<42 μg/dL] and High DHEAS (HD) [≥42 μg/dL] groups. At Tanner stages 2 and 4 a DNA methylation microarray was performed to identify differentially methylated CpG positions (DMPs) between HD and LD groups. We observed a differential methylation pattern between pubertal girls with and without biochemical PA. Moreover, a set of DNA methylation markers, selected by the LASSO method, successfully distinguished between HD and LD girls regardless of Tanner stage. Additionally, a subset of these markers were significantly associated with glucose-related measures such as insulin level, HOMA-IR, and glycaemia. This pilot study provides evidence consistent with the hypothesis that high DHEAS concentration, or its hormonally active metabolites, may induce a unique blood methylation signature in pubertal girls, and that this methylation pattern is associated with altered glucose metabolism.

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

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

An epigenome-wide analysis of sex hormone levels and DNA methylation in male blood samples

Endogenous sex hormones and DNA methylation both play important roles in various diseases. However, their interplay is largely unknown. A deeper understanding of their interrelationships could provide new insights into the pathology of disease development. We, therefore, investigated associations between circulating sex hormones, sex hormone binding globulin (SHBG), and DNA methylation in blood, using samples from 77 men (65 with repeated samples), from the population-based Northern Sweden Health and Disease Study (NSHDS). DNA methylation was measured in buffy coat using the Infinium Methylation EPIC BeadChip (Illumina). Sex hormone (oestradiol, oestrone, testosterone, androstenedione, dehydroepiandrosterone, and progesterone) and SHBG concentrations were measured in plasma using a high-performance liquid chromatography tandem mass spectrometry (LC/MS-MS) method and an enzyme-linked immunoassay, respectively. Associations between sex hormones, SHBG, and DNA methylation were estimated using both linear regression and mixed-effects models. Additionally, we used the comb-p method to identify differentially methylated regions based on nearby P values. We identified one novel CpG site (cg14319657), at which DNA methylation was associated with dehydroepiandrosterone, surpassing a genome-wide significance level. In addition, more than 40 differentially methylated regions were associated with levels of sex hormones and SHBG and several of these mapped to genes involved in hormone-related diseases. Our findings support a relationship between circulating sex hormones and DNA methylation and suggest that further investigation is warranted, both for validation, further exploration and to gain a deeper understanding of the mechanisms and potential consequences for health and disease.

Prenatal exposures to endocrine disrupting chemicals: The role of multi-omics in understanding toxicity

Endocrine disrupting chemicals (EDCs) are a diverse group of toxicants detected in populations globally. Prenatal EDC exposures impact birth and childhood outcomes. EDCs work through persistent changes at the molecular, cellular, and organ level. Molecular and biochemical signals or 'omics' can be measured at various functional levels - including the epigenome, transcriptome, proteome, metabolome, and the microbiome. In this narrative review, we introduce each omics and give examples of associations with prenatal EDC exposures. There is substantial research on epigenomic modifications in offspring exposed to EDCs during gestation, and a growing number of studies evaluating the transcriptome, proteome, metabolome, or microbiome in response to these exposures. Multi-omics, integrating data across omics layers, may improve understanding of disrupted function pathways related to early life exposures. We highlight several data integration methods to consider in multi-omics studies. Information from multi-omics can improve understanding of the biological processes and mechanisms underlying prenatal EDC toxicity.

Multifaceted immune dysregulation characterizes individuals at-risk for rheumatoid arthritis

Molecular markers of autoimmunity, such as antibodies to citrullinated protein antigens (ACPA), are detectable prior to inflammatory arthritis (IA) in rheumatoid arthritis (RA) and may define a state that is 'at-risk' for future RA. Here we present a cross-sectional comparative analysis among three groups that include ACPA positive individuals without IA (At-Risk), ACPA negative individuals and individuals with early, ACPA positive clinical RA (Early RA). Differential methylation analysis among the groups identifies non-specific dysregulation in peripheral B, memory and naïve T cells in At-Risk participants, with more specific immunological pathway abnormalities in Early RA. Tetramer studies show increased abundance of T cells recognizing citrullinated (cit) epitopes in At-Risk participants, including expansion of T cells reactive to citrullinated cartilage intermediate layer protein I (cit-CILP); these T cells have Th1, Th17, and T stem cell memory-like phenotypes. Antibody-antigen array analyses show that antibodies targeting cit-clusterin, cit-fibrinogen and cit-histone H4 are elevated in At-Risk and Early RA participants, with the highest levels of antibodies detected in those with Early RA. These findings indicate that an ACPA positive at-risk state is associated with multifaceted immune dysregulation that may represent a potential opportunity for targeted intervention.

Nepalese indoor cookstove smoke extracts alter human airway epithelial gene expression, DNA methylation and hydroxymethylation

Household air pollution caused by inefficient cooking practices causes 4 million deaths a year worldwide. In Nepal, 86% of the rural population use solid fuels for cooking. Over 25% of premature deaths associated with air pollution are respiratory in nature. Here we aimed to identify molecular signatures of different cookstove and fuel type exposures in human airway epithelial cells, to understand the mechanisms mediating cook stove smoke induced lung disease. Primary human airway epithelial cells in submerged culture were exposed to traditional cook stove (TCS), improved cook stove (ICS) and liquefied petroleum gas (LPG) stove smoke extracts. Changes to gene expression, DNA methylation and hydroxymethylation were measured by bulk RNA sequencing and HumanMethylationEPIC BeadChip following oxidative bisulphite conversion, respectively. TCS smoke extract alone reproducibly caused changes in the expression of 52 genes enriched for oxidative stress pathways. TCS, ICS and LPG smoke extract exposures were associated with distinct changes to DNA methylation and hydroxymethylation. A subset of TCS induced genes were associated with differentially methylated and/or hydroxymethylated CpGs sites, and enriched for the ferroptosis pathway and the upstream regulator NFE2L2. DNA methylation and hydroxymethylation changes not associated with a concurrent change in gene expression, were linked to biological processes and molecular pathways important to airway health, including neutrophil function, transforming growth factor beta signalling, GTPase activity, and cell junction organisation. Our data identified differential impacts of TCS, ICS and LPG cook stove smoke on the human airway epithelium transcriptome, DNA methylome and hydroxymethylome and provide further insight into the association between indoor air pollution exposure and chronic lung disease mechanisms.

Associations between the New DNA-Methylation-Based Telomere Length Estimator, the Mediterranean Diet and Genetics in a Spanish Population at High Cardiovascular Risk

Biological aging is a relevant risk factor for chronic diseases, and several indicators for measuring this factor have been proposed, with telomere length (TL) among the most studied. Oxidative stress may regulate telomere shortening, which is implicated in the increased risk. Using a novel estimator for TL, we examined whether adherence to the Mediterranean diet (MedDiet), a highly antioxidant-rich dietary pattern, is associated with longer TL. We determined TL using DNA methylation algorithms (DNAmTL) in 414 subjects at high cardiovascular risk from Spain. Adherence to the MedDiet was assessed by a validated score, and genetic variants in candidate genes and at the genome-wide level were analyzed. We observed several significant associations (p < 0.05) between DNAmTL and candidate genes (TERT, TERF2, RTEL1, and DCAF4), contributing to the validity of DNAmTL as a biomarker in this population. Higher adherence to the MedDiet was associated with lower odds of having a shorter TL in the whole sample (OR = 0.93; 95% CI: 0.85-0.99; p = 0.049 after fully multivariate adjustment). Nevertheless, this association was stronger in women than in men. Likewise, in women, we observed a direct association between adherence to the MedDiet score and DNAmTL as a continuous variable (beta = 0.015; SE: 0.005; p = 0.003), indicating that a one-point increase in adherence was related to an average increase of 0.015 ± 0.005 kb in TL. Upon examination of specific dietary items within the global score, we found that fruits, fish, "sofrito", and whole grains exhibited the strongest associations in women. The novel score combining these items was significantly associated in the whole population. In the genome-wide association study (GWAS), we identified ten polymorphisms at the suggestive level of significance (p < 1 × 10-5) for DNAmTL (intergenics, in the IQSEC1, NCAPG2, and ABI3BP genes) and detected some gene-MedDiet modulations on DNAmTL. As this is the first study analyzing the DNAmTL estimator, genetics, and modulation by the MedDiet, more studies are needed to confirm these findings.

Associations Between Epigenetic Age Acceleration and microRNA Expression Among U.S. Firefighters

Epigenetic changes may be biomarkers of health. Epigenetic age acceleration (EAA), the discrepancy between epigenetic age measured via epigenetic clocks and chronological age, is associated with morbidity and mortality. However, the intersection of epigenetic clocks with microRNAs (miRNAs) and corresponding miRNA-based health implications have not been evaluated. We analyzed DNA methylation and miRNA profiles from blood sampled among 332 individuals enrolled across 2 U.S.-based firefighter occupational studies (2015-2018 and 2018-2020). We considered 7 measures of EAA in leukocytes (PhenoAge, GrimAge, Horvath, skin-blood, and Hannum epigenetic clocks, and extrinsic and intrinsic epigenetic age acceleration). We identified miRNAs associated with EAA using individual linear regression models, adjusted for sex, race/ethnicity, chronological age, and cell type estimates, and investigated downstream effects of associated miRNAs with miRNA enrichment analyses and genomic annotations. On average, participants were 38 years old, 88% male, and 75% non-Hispanic white. We identified 183 of 798 miRNAs associated with EAA (FDR q < 0.05); 126 with PhenoAge, 59 with GrimAge, 1 with Horvath, and 1 with the skin-blood clock. Among miRNAs associated with Horvath and GrimAge, there were 61 significantly enriched disease annotations including age-related metabolic and cardiovascular conditions and several cancers. Enriched pathways included those related to proteins and protein modification. We identified miRNAs associated with EAA of multiple epigenetic clocks. PhenoAge had more associations with individual miRNAs, but GrimAge and Horvath had greater implications for miRNA-associated pathways. Understanding the relationship between these epigenetic markers could contribute to our understanding of the molecular underpinnings of aging and aging-related diseases.

Stability of DNA-Methylation Profiles of Biological Aging in Children and Adolescents

Background and Objectives

Methylation profile scores (MPSs) index biological aging and aging-related disease in adults and are cross-sectionally associated with social determinants of health in childhood. MPSs thus provide an opportunity to trace how aging-related biology responds to environmental changes in early life. Information regarding the stability of MPSs in early life is currently lacking.

Method

We use longitudinal data from children and adolescents ages 8-18 (N = 428, M age = 12.15 years) from the Texas Twin Project. Participants contributed two waves of salivary DNA-methylation data (mean lag = 3.94 years), which were used to construct four MPSs reflecting multi-system physiological decline and mortality risk (PhenoAgeAccel and GrimAgeAccel), pace of biological aging (DunedinPACE), and cognitive function (Epigenetic-g). Furthermore, we exploit variation among participants in whether they were exposed to the COVID-19 pandemic during the course of study participation, in order to test how a historical period characterized by environmental disruption might affect children's aging-related MPSs.

Results

All MPSs showed moderate longitudinal stability (test-retest rs = 0.42, 0.44, 0.46, 0.51 for PhenoAgeAccel, GrimAgeAccel, and Epigenetic-g, and DunedinPACE, respectively). No differences in the stability of MPSs were apparent between those whose second assessment took place after the onset of the COVID-19 pandemic vs. those for whom both assessments took place prior to the pandemic.

Conclusions

Aging-related DNA-methylation patterns are less stable in childhood than has been previously observed in adulthood. Further developmental research on the methylome is necessary to understand which environmental perturbations in childhood impact trajectories of biological aging and when children are most sensitive to those impacts.