Gene-set analysis is severely biased when applied to genome-wide methylation data

High allelic diversity in Arabidopsis NLRs is associated with distinct genomic features

Plants rely on Nucleotide-binding, Leucine-rich repeat Receptors (NLRs) for pathogen recognition. Highly variable NLRs (hvNLRs) show remarkable intraspecies diversity, while their low-variability paralogs (non-hvNLRs) are conserved between ecotypes. At a population level, hvNLRs provide new pathogen-recognition specificities, but the association between allelic diversity and genomic and epigenomic features has not been established. Our investigation of NLRs in Arabidopsis Col-0 has revealed that hvNLRs show higher expression, less gene body cytosine methylation, and closer proximity to transposable elements than non-hvNLRs. hvNLRs show elevated synonymous and nonsynonymous nucleotide diversity and are in chromatin states associated with an increased probability of mutation. Diversifying selection maintains variability at a subset of codons of hvNLRs, while purifying selection maintains conservation at non-hvNLRs. How these features are established and maintained, and whether they contribute to the observed diversity of hvNLRs is key to understanding the evolution of plant innate immune receptors.

Genome-wide DNA methylation analysis in female veterans with military sexual trauma and comorbid PTSD/MDD

BACKGROUND

Military sexual trauma (MST) is a prevalent issue within the U.S. military. Victims are more likely to develop comorbid diseases such as posttraumatic stress disorder (PTSD) and major depressive disorder (MDD). Nonetheless, not everyone who suffers from MST develops PTSD and/or MDD. DNA methylation, which can regulate gene expression, might give us insight into the molecular mechanisms behind this discrepancy. Therefore, we sought to identify genomic loci and enriched biological pathways that differ between patients with and without MST, PTSD, and MDD.

METHODS

Saliva samples were collected from 113 female veterans. Following DNA extraction and processing, DNA methylation levels were measured through the Infinium HumanMethylationEPIC BeadChip array. We used limma and bump hunting methods to generate the differentially methylated positions and differentially methylated regions (DMRs), respectively. Concurrently, we used Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genome to find enriched pathways.

RESULTS

A DMR close to the transcription start site of ZFP57 was differentially methylated between subjects with and without PTSD, replicating previous findings and emphasizing the potential role of ZFP57 in PTSD susceptibility. In the pathway analyses, none survived multiple correction, although top GO terms included some potentially relevant to MST, PTSD, and MDD etiology.

CONCLUSION

We conducted one of the first DNA methylation analyses investigating MST along with PTSD and MDD. In addition, we found one DMR near ZFP57 to be associated with PTSD. The replication of this finding indicates further investigation of ZFP57 in PTSD may be warranted.

Cortico-striatal differences in the epigenome in attention-deficit/ hyperactivity disorder

While epigenetic modifications have been implicated in ADHD through studies of peripheral tissue, to date there has been no examination of the epigenome of the brain in the disorder. To address this gap, we mapped the methylome of the caudate nucleus and anterior cingulate cortex in post-mortem tissue from fifty-eight individuals with or without ADHD. While no single probe showed adjusted significance in differential methylation, several differentially methylated regions emerged. These regions implicated genes involved in developmental processes including neurogenesis and the differentiation of oligodendrocytes and glial cells. We demonstrate a significant association between differentially methylated genes in the caudate and genes implicated by GWAS not only in ADHD but also in autistic spectrum, obsessive compulsive and bipolar affective disorders through GWAS. Using transcriptomic data available on the same subjects, we found modest correlations between the methylation and expression of genes. In conclusion, this study of the cortico-striatal methylome points to gene and gene pathways involved in neurodevelopment, consistent with studies of common and rare genetic variation, as well as the post-mortem transcriptome in ADHD.

The association of cigarette smoking with DNA methylation and gene expression in human tissue samples

Cigarette smoking adversely affects many aspects of human health, and epigenetic responses to smoking may reflect mechanisms that mediate or defend against these effects. Prior studies of smoking and DNA methylation (DNAm), typically measured in leukocytes, have identified numerous smoking-associated regions (e.g., AHRR). To identify smoking-associated DNAm features in typically inaccessible tissues, we generated array-based DNAm data for 916 tissue samples from the GTEx (Genotype-Tissue Expression) project representing 9 tissue types (lung, colon, ovary, prostate, blood, breast, testis, kidney, and muscle). We identified 6,350 smoking-associated CpGs in lung tissue (n = 212) and 2,735 in colon tissue (n = 210), most not reported previously. For all 7 other tissue types (sample sizes 38-153), no clear associations were observed (false discovery rate 0.05), but some tissues showed enrichment for smoking-associated CpGs reported previously. For 1,646 loci (in lung) and 22 (in colon), smoking was associated with both DNAm and local gene expression. For loci detected in both lung and colon (e.g., AHRR, CYP1B1, CYP1A1), top CpGs often differed between tissues, but similar clusters of hyper- or hypomethylated CpGs were observed, with hypomethylation at regulatory elements corresponding to increased expression. For lung tissue, 17 hallmark gene sets were enriched for smoking-associated CpGs, including xenobiotic- and cancer-related gene sets. At least four smoking-associated regions in lung were impacted by lung methylation quantitative trait loci (QTLs) that co-localize with genome-wide association study (GWAS) signals for lung function (FEV1/FVC), suggesting epigenetic alterations can mediate the effects of smoking on lung health. Our multi-tissue approach has identified smoking-associated regions in disease-relevant tissues, including effects that are shared across tissue types.

Bayesian Multi-View Clustering given complex inter-view structure

Multi-view datasets are becoming increasingly prevalent. These datasets consist of different modalities that provide complementary characterizations of the same underlying system. They can include heterogeneous types of information with complex relationships, varying degrees of missingness, and assorted sample sizes, as is often the case in multi-omic biological studies. Clustering multi-view data allows us to leverage different modalities to infer underlying systematic structure, but most existing approaches are limited to contexts in which entities are the same across views or have clear one-to-one relationships across data types with a common sample size. Many methods also make strong assumptions about the similarities of clusterings across views. We propose a Bayesian multi-view clustering approach (BMVC) which can handle the realities of multi-view datasets that often have complex relationships and diverse structure. BMVC incorporates known and complex many-to-many relationships between entities via a probabilistic graphical model that enables the joint inference of clusterings specific to each view, but where each view informs the others. Additionally, BMVC estimates the strength of the relationships between each pair of views, thus moderating the degree to which it imposes dependence constraints. We benchmarked BMVC on simulated data to show that it accurately estimates varying degrees of inter-view dependence when inter-view relationships are not limited to one-to-one correspondence. Next, we demonstrated its ability to capture visually interpretable inter-view structure in a public health survey of individuals and households in Puerto Rico following Hurricane Maria. Finally, we showed that BMVC clusters integrate the complex relationships between multi-omic profiles of breast cancer patient data, improving the biological homogeneity of clusters and elucidating hypotheses for functional biological mechanisms. We found that BMVC leverages complex inter-view structure to produce higher quality clusters than those generated by standard approaches. We also showed that BMVC is a valuable tool for real-world discovery and hypothesis generation.

Maternal adverse childhood experiences (ACEs) and DNA methylation of newborns in cord blood

BACKGROUND

Adverse childhood experiences (ACEs) increase the risk of poor health outcomes later in life. Psychosocial stressors may also have intergenerational health effects by which parental ACEs are associated with mental and physical health of children. Epigenetic programming may be one mechanism linking parental ACEs to child health. This study aimed to investigate epigenome-wide associations of maternal preconception ACEs with DNA methylation patterns of children. In the Center for the Health Assessment of Mothers and Children of Salinas study, cord blood DNA methylation was measured using the Illumina HumanMethylation450 BeadChip. Preconception ACEs, which occurred during the mothers' childhoods, were collected using a standard ACE questionnaire including 10 ACE indicators. Maternal ACE exposures were defined in this study as (1) the total number of ACEs; (2) the total number of ACEs categorized as 0, 1-3, and > 4; and (3) individual ACEs. Associations of ACE exposures with differential methylated positions, regions, and CpG modules determined using weighted gene co-expression network analysis were evaluated adjusting for covariates.

RESULTS

Data on maternal ACEs and cord blood DNA methylation were available for 196 mother/newborn pairs. One differential methylated position was associated with maternal experience of emotional abuse (cg05486260/FAM135B gene; q value < 0.05). Five differential methylated regions were significantly associated with the total number of ACEs, and 36 unique differential methylated regions were associated with individual ACEs (Šidák p value < 0.05). Fifteen CpG modules were significantly correlated with the total number of ACEs or individual ACEs, of which 8 remained significant in fully adjusted models (p value < 0.05). Significant modules were enriched for pathways related to neurological and immune development and function.

CONCLUSIONS

Maternal ACEs prior to conception were associated with cord blood DNA methylation of offspring at birth. Although there was limited overlap between differential methylated regions and CpGs in modules associated with ACE exposures, statistically significant regions and networks were related to genes involved in neurological and immune function. Findings may provide insights to pathways linking psychosocial stressors to health. Further research is needed to understand the relationship between changes in DNA methylation and child health.

Diagnostic Utility of Genome-wide DNA Methylation Analysis in Genetically Unsolved Developmental and Epileptic Encephalopathies and Refinement of a CHD2 Episignature

Sequence-based genetic testing currently identifies causative genetic variants in ∼50% of individuals with developmental and epileptic encephalopathies (DEEs). Aberrant changes in DNA methylation are implicated in various neurodevelopmental disorders but remain unstudied in DEEs. Rare epigenetic variations ("epivariants") can drive disease by modulating gene expression at single loci, whereas genome-wide DNA methylation changes can result in distinct "episignature" biomarkers for monogenic disorders in a growing number of rare diseases. Here, we interrogate the diagnostic utility of genome-wide DNA methylation array analysis on peripheral blood samples from 516 individuals with genetically unsolved DEEs who had previously undergone extensive genetic testing. We identified rare differentially methylated regions (DMRs) and explanatory episignatures to discover causative and candidate genetic etiologies in 10 individuals. We then used long-read sequencing to identify DNA variants underlying rare DMRs, including one balanced translocation, three CG-rich repeat expansions, and two copy number variants. We also identify pathogenic sequence variants associated with episignatures; some had been missed by previous exome sequencing. Although most DEE genes lack known episignatures, the increase in diagnostic yield for DNA methylation analysis in DEEs is comparable to the added yield of genome sequencing. Finally, we refine an episignature for CHD2 using an 850K methylation array which was further refined at higher CpG resolution using bisulfite sequencing to investigate potential insights into CHD2 pathophysiology. Our study demonstrates the diagnostic yield of genome-wide DNA methylation analysis to identify causal and candidate genetic causes as ∼2% (10/516) for unsolved DEE cases.

High intraspecies allelic diversity in Arabidopsis NLR immune receptors is associated with distinct genomic and epigenomic features

Plants rely on Nucleotide-binding, Leucine-rich repeat Receptors (NLRs) for pathogen recognition. Highly variable NLRs (hvNLRs) show remarkable intraspecies diversity, while their low variability paralogs (non-hvNLRs) are conserved between ecotypes. At a population level, hvNLRs provide new pathogen recognition specificities, but the association between allelic diversity and genomic and epigenomic features has not been established. Our investigation of NLRs in Arabidopsis Col-0 has revealed that hvNLRs show higher expression, less gene body cytosine methylation, and closer proximity to transposable elements than non-hvNLRs. hvNLRs show elevated synonymous and nonsynonymous nucleotide diversity and are in chromatin states associated with an increased probability of mutation. Diversifying selection maintains variability at a subset of codons of hvNLRs, while purifying selection maintains conservation at non-hvNLRs. How these features are established and maintained, and whether they contribute to the observed diversity of hvNLRs is key to understanding the evolution of plant innate immune receptors.

Candidate biomarkers from the integration of methylation and gene expression in discordant autistic sibling pairs

While the genetics of autism spectrum disorders (ASD) has been intensively studied, resulting in the identification of over 100 putative risk genes, the epigenetics of ASD has received less attention, and results have been inconsistent across studies. We aimed to investigate the contribution of DNA methylation (DNAm) to the risk of ASD and identify candidate biomarkers arising from the interaction of epigenetic mechanisms with genotype, gene expression, and cellular proportions. We performed DNAm differential analysis using whole blood samples from 75 discordant sibling pairs of the Italian Autism Network collection and estimated their cellular composition. We studied the correlation between DNAm and gene expression accounting for the potential effects of different genotypes on DNAm. We showed that the proportion of NK cells was significantly reduced in ASD siblings suggesting an imbalance in their immune system. We identified differentially methylated regions (DMRs) involved in neurogenesis and synaptic organization. Among candidate loci for ASD, we detected a DMR mapping to CLEC11A (neighboring SHANK1) where DNAm and gene expression were significantly and negatively correlated, independently from genotype effects. As reported in previous studies, we confirmed the involvement of immune functions in the pathophysiology of ASD. Notwithstanding the complexity of the disorder, suitable biomarkers such as CLEC11A and its neighbor SHANK1 can be discovered using integrative analyses even with peripheral tissues.

Plasma PFOA and PFOS Levels, DNA Methylation, and Blood Lipid Levels: A Pilot Study

Exposure to perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) is associated with blood lipids in adults, but the underlying mechanisms remain unclear. This pilot study aimed to investigate the associations between PFOA or PFOS and epigenome-wide DNA methylation and assess the mediating effect of DNA methylation on the PFOA/PFOS-blood lipid association. We measured plasma PFOA/PFOS and leukocyte DNA methylation in 98 patients enrolled from the hospital between October 2018 and August 2019. The median plasma PFOA/PFOS levels were 0.85 and 2.29 ng/mL. Plasma PFOA and PFOS levels were significantly associated with elevated total cholesterol (TC) and low-density lipoprotein cholesterol (LDL) levels. There were 63/87 CpG positions and 8/11 differentially methylated regions (DMRs) associated with plasma PFOA/PFOS levels, respectively. In addition, 5 CpG positions (annotated to AFF3, CREB5, NRG2, USF2, and intergenic region) and one DMR annotated to IRF6 may mediate the association between plasma PFOA/PFOS and LDL levels (mediated proportion from 7.29 to 46.77%); two CpG positions may mediate the association between plasma PFOA/PFOS and TC levels (annotated to CREB5 and USF2, mediated proportion is around 30%). The data suggest that PFOA/PFOS exposure alters DNA methylation. More importantly, the association of PFOA/PFOS with lipid indicators was partly mediated by DNA methylation changes in lipid metabolism-related genes.

Epigenome-wide association studies of occupational exposure to benzene and formaldehyde

Sufficient evidence supports a relationship between certain myeloid neoplasms and exposure to benzene or formaldehyde. DNA methylation could underlie benzene- and formaldehyde-induced health outcomes, but data in exposed human populations are limited. We conducted two cross-sectional epigenome-wide association studies (EWAS), one in workers exposed to benzene and another in workers exposed to formaldehyde. Using HumanMethylation450 BeadChips, we investigated differences in blood cell DNA methylation among 50 benzene-exposed subjects and 48 controls, and among 31 formaldehyde-exposed subjects and 40 controls. We performed CpG-level and regional-level analyses. In the benzene EWAS, we found genome-wide significant alterations, i.e., FWER-controlled P-values <0.05, in the mean and variance of methylation at 22 and 318 CpG sites, respectively, and in mean methylation of a large genomic region. Pathway analysis of genes corresponding to benzene-associated differential methylation sites revealed an impact on the AMPK signalling pathway. In formaldehyde-exposed subjects compared to controls, 9 CpGs in the DUSP22 gene promoter had genome-wide significant decreased methylation variability and a large region of the HOXA5 promoter with 44 CpGs was hypomethylated. Our findings suggest that DNA methylation may contribute to the pathogenesis of diseases related to benzene and formaldehyde exposure. Aberrant expression and methylation of HOXA5 previously has been shown to be clinically significant in myeloid leukaemias. The tumour suppressor gene DUSP22 is a potential biomarker of exposure to formaldehyde, and irregularities have been associated with multiple exposures and diseases.

Whole blood methylome-derived features to discriminate endocrine hypertension

Background

Arterial hypertension represents a worldwide health burden and a major risk factor for cardiovascular morbidity and mortality. Hypertension can be primary (primary hypertension, PHT), or secondary to endocrine disorders (endocrine hypertension, EHT), such as Cushing's syndrome (CS), primary aldosteronism (PA), and pheochromocytoma/paraganglioma (PPGL). Diagnosis of EHT is currently based on hormone assays. Efficient detection remains challenging, but is crucial to properly orientate patients for diagnostic confirmation and specific treatment. More accurate biomarkers would help in the diagnostic pathway. We hypothesized that each type of endocrine hypertension could be associated with a specific blood DNA methylation signature, which could be used for disease discrimination. To identify such markers, we aimed at exploring the methylome profiles in a cohort of 255 patients with hypertension, either PHT (n = 42) or EHT (n = 213), and at identifying specific discriminating signatures using machine learning approaches.

Results

Unsupervised classification of samples showed discrimination of PHT from EHT. CS patients clustered separately from all other patients, whereas PA and PPGL showed an overall overlap. Global methylation was decreased in the CS group compared to PHT. Supervised comparison with PHT identified differentially methylated CpG sites for each type of endocrine hypertension, showing a diffuse genomic location. Among the most differentially methylated genes, FKBP5 was identified in the CS group. Using four different machine learning methods—Lasso (Least Absolute Shrinkage and Selection Operator), Logistic Regression, Random Forest, and Support Vector Machine—predictive models for each type of endocrine hypertension were built on training cohorts (80% of samples for each hypertension type) and estimated on validation cohorts (20% of samples for each hypertension type). Balanced accuracies ranged from 0.55 to 0.74 for predicting EHT, 0.85 to 0.95 for predicting CS, 0.66 to 0.88 for predicting PA, and 0.70 to 0.83 for predicting PPGL.

Conclusions

The blood DNA methylome can discriminate endocrine hypertension, with methylation signatures for each type of endocrine disorder.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01347-y.

Altered DNA methylation pattern characterizes the peripheral immune cells of patients with autoimmune hepatitis

BACKGROUND AND AIMS

Little is known about the impact of DNA methylation modifications on autoimmune hepatitis (AIH) pathogenesis and therapeutic response. We investigated the potential alterations of DNA methylation in AIH peripheral lymphocytes at diagnosis and remission.

METHODS

Ten AIH patients at diagnosis (time-point 1; AIH-tp1), 8/10 following biochemical response (time-point 2; AIH-tp2), 9 primary biliary cholangitis (PBC) and 10 healthy controls (HC) were investigated. Peripheral CD19(+) and CD4(+) cells were isolated. Global DNA methylation (5^m C)/hydroxymethylation (5^hm C) was studied by ELISAs. mRNA of DNA methylation (DNMT1/3A/3B) and their counteracting hydroxymethylation enzymes (TET1/2/3) was determined by quantitative RT-PCR. Epigenome wide association study (EWAS) was performed in CD4(+) cells (Illumina HumanMethylation 850 K array) in AIH and HC. Total 5^m C/5^hm C was also assessed by immunohistochemistry (IHC) on paraffin-embedded liver sections.

RESULTS

Reduced TET1 and increased DNMT3A mRNA levels characterized CD19(+) and CD4(+)-lymphocytes from AIH-tp1 compared to HC and PBC, respectively, without affecting global DNA 5^m C/5^hm C. In AIH-tp1, CD4(+) DNMT3A expression was negatively correlated with serum IgG (P = .03). In remission, DNMT3A decreased in both CD19(+) and CD4(+) cells compared to AIH-tp1 (P = .02, P = .03 respectively). EWAS in CD4(+) cells from AIH patients confirmed important modifications in genes implicated in immune responses (HLA-DP, TNF, lnRNAs and CD86). IHC showed increased 5^hm C staining of periportal infiltrating lymphocytes in AIH-tp1 compared to HC and PBC.

CONCLUSION

Altered TET1 and DNMT3A expressions, characterize peripheral lymphocytes in AIH. DNMT3A was associated with disease activity and decreased following remission. Gene DNA methylation modifications affect immunological pathways that may play an important role in AIH pathogenesis.

Epigenome-wide association analyses of active injection drug use

BACKGROUND

Injection drug use (IDU) is prevalent in the US and is associated with substantial risk of blood-borne infections, morbidity, and mortality. However, the spectrum of its biologic effects on DNA methylation in blood is not well characterized.

METHODS

401 participants (M_age = 47.9; 68% male; 90% African American) over several timepoints (1054 visits) were drawn from a longitudinal cohort of people who inject drugs. DNA methylation was measured among buffy coat samples from the 1054 visits. Compared to samples collected after ≥ 6 months of abstinence, separate EWAS were conducted for active injecting of any drug, quantitative injection frequency, injecting of heroin and injecting of cocaine. Linear mixed effect models were used and analyses were adjusted for repeated measurements and key technical, biological, and sociodemographic characteristics.

RESULTS

We found epigenome-wide significant CpG sites associated with active injection (cg10636246, AIM2, p = 2.33 × 10^-8) and injection intensity (cg13117953, p = 4.30 × 10^-8). We found converging evidence that cg10636246 (AIM2), cg23110600 (PRKCH), cg03546163 (FKBP5), cg04590956 (GMCL1), and cg16317961 (MAPRE2) were among the top 0.1% significantly differentially methylated CpG sites shared across the five EWAS. Top ranked CpGs among the five EWAS were enriched (p < 0.0001) in AIM2 inflammasome complex, T cell migration, insulin regulation and epinephrine synthesis pathways. During periods of active injection, samples had 0.46 years of epigenetic age acceleration relative to the abstinence period, within the same subject (p = 0.03).

CONCLUSIONS

Findings from this study demonstrate modest, common, and specific effects on DNA methylation during a relatively short time between periods of active drug injection and abstinence.

TGFβ2 is a Prognostic Biomarker for Gastric Cancer and is Associated With Methylation and Immunotherapy Responses

TGFβ signaling plays a key role in cancer progression and by shaping tumor architecture and inhibiting the anti-tumor activity of immune cells. It was reported that high expression of TGFβ can promote the invasion and metastasis of cancer cells in a variety of tumors. However, there are few studies on TGFβ2 and its methylation in gastric cancer. We analyzed the Harbin Medical University Cancer Hospital (HMUCH) sequencing data and used public data to explore the potential function and prognostic value of TGFβ2 and its methylation in gastric cancer. In this study, we used the ssGSEA algorithm to quantify 23 methylation sites related to TGFβ2. Survival analysis showed that high expression of TGFβ2 and hypomethylation levels of TGFβ2 were negative factors in the prognosis of gastric cancer. Functional enrichment analysis of methylation revealed that methylation of different TGFβ2 methylation scores was mainly involved in energy metabolism, extracellular matrix formation and cell cycle regulation. In the gastric cancer microenvironment TGFβ2 was associated with high levels of multiple immune cell infiltration and cytokine expression, and high TGFβ2 expression was significantly and positively correlated with stemness markers, stromalscore and EMT. Gene set enrichment analysis also revealed an important role of TGFβ2 in promoting EMT. In addition, we discussed the relationship between TGFβ2 and immunotherapy. The expression of PD-1, PD-L1 and CTLA-4 was elevated in the TGFβ2 high expression group. Also when TGFβ2 was highly expressed, the responsiveness of immune checkpoint blockade (ICB) was significantly enhanced. This indicates that TGFβ2 may become an indicator for predicting the efficacy of immunosuppressive agents and a potential target for immunotherapy.

Functional Enrichment Analysis of Regulatory Elements

Statistical methods for enrichment analysis are important tools to extract biological information from omics experiments. Although these methods have been widely used for the analysis of gene and protein lists, the development of high-throughput technologies for regulatory elements demands dedicated statistical and bioinformatics tools. Here, we present a set of enrichment analysis methods for regulatory elements, including CpG sites, miRNAs, and transcription factors. Statistical significance is determined via a power weighting function for target genes and tested by the Wallenius noncentral hypergeometric distribution model to avoid selection bias. These new methodologies have been applied to the analysis of a set of miRNAs associated with arrhythmia, showing the potential of this tool to extract biological information from a list of regulatory elements. These new methods are available in GeneCodis 4, a web tool able to perform singular and modular enrichment analysis that allows the integration of heterogeneous information.

Arsenic exposure and human blood DNA methylation and hydroxymethylation profiles in two diverse populations from Bangladesh and Spain

BACKGROUND

Associations of arsenic (As) with the sum of 5-mC and 5-hmC levels have been reported; however, As exposure-related differences of the separated 5-mC and 5-hmC markers have rarely been studied.

METHODS

In this study, we evaluated the association of arsenic exposure biomarkers and 5-mC and 5-hmC in 30 healthy men (43-55 years) from the Aragon Workers Health Study (AWHS) (Spain) and 31 healthy men (31-50 years) from the Folic Acid and Creatinine Trial (FACT) (Bangladesh). We conducted 5-mC and 5-hmC profiling using Infinium MethylationEPIC arrays, on paired standard and modified (ox-BS in AWHS and TAB in FACT) bisulfite converted blood DNA samples.

RESULTS

The median for the sum of urine inorganic and methylated As species (ΣAs) (μg/L) was 12.5 for AWHS and 89.6 for FACT. The median of blood As (μg/L) was 8.8 for AWHS and 10.2 for FACT. At a statistical significance p-value cut-off of 0.01, the differentially methylated (DMP) and hydroxymethylated (DHP) positions were mostly located in different genomic sites. Several DMPs and DHPs were consistently found in AWHS and FACT both for urine ΣAs and blood models, being of special interest those attributed to the DIP2C gene. Three DMPs (annotated to CLEC12A) for AWHS and one DHP (annotated to NPLOC4) for FACT remained statistically significant after false discovery rate (FDR) correction. Pathways related to chronic diseases including cardiovascular, cancer and neurological were enriched.

CONCLUSIONS

While we identified common 5-hmC and 5-mC signatures in two populations exposed to varying levels of inorganic As, differences in As-related epigenetic sites across the study populations may additionally reflect low and high As-specific associations. This work contributes a deeper understanding of potential epigenetic dysregulations of As. However, further research is needed to confirm biological consequences associated with DIP2C epigenetic regulation and to investigate the role of 5-hmC and 5-mC separately in As-induced health disorders at different exposure levels.

DNA Methylation and Asthma Acquisition during Adolescence and Post-Adolescence, an Epigenome-Wide Longitudinal Study

The role of epigenetics in the pathogenesis of asthma acquisition in adolescence and post-adolescence has been unknown. We carried out a longitudinal epigenome-wide association study, using data from the Isle of Wight Birth Cohort (IOWBC). To improve statistical power, we first screened CpGs based on associations of DNA methylation (DNAm) at an age of 10 years (pre-adolescence) with asthma acquisition at 10-18 years (during adolescence). A logistic regression with repeated measures was applied to CpGs that passed screening to examine the associations of pre-adolescence DNAm with asthma acquisition from 10-18 years and 18-26 years, with an interaction term to evaluate transition period specificity. Findings were further tested in an independent birth cohort, ALSPAC. In total, 205 CpGs (with 150 being females) showed associations with asthma acquisition (main or interaction effects) at FDR = 0.05 in IOWBC, of which 112 (90 being females) showed consistent associations in the ALSPAC. Genes that the identified CpGs were mapped to, e.g., AKAP1 and ENO1, have been shown to be associated with the risk of asthma. Our findings indicated that DNAm at specific CpGs was associated with asthma acquisition. CpGs showing such associations were likely to be different between males and females and, at certain CpGs, were unique to a specific transition period.

Buffy Coat DNA Methylation Profile Is Representative of Methylation Patterns in White Blood Cell Types in Normal Pregnancy

Background: We aimed to assess the extent to which the buffy coat DNA methylome is representative of methylation patterns in constitutive white blood cell (WBC) types in normal pregnancy. Methods: A comparison of differential methylation of buffy coat DNA vs DNA isolated from polymorphonuclear (PMN) and lymphocytic fractions was performed for each blood sample obtained within 24 h prior to delivery from 29 normotensive pregnant women. Methylation profiles were obtained using an Illumina Human Methylation 450 BeadChip and CHaMP bioinformatics pipeline. A subset of differentially methylated probes (DMPs) showing discordant methylation were further investigated using statistical modeling and enrichment analysis. Results: The smallest number of DMPs was found between the buffy coat and the PMN fraction (2.96%). Pathway enrichment analysis of the DMPs identified biological pathways involved in the particular leukocyte lineage, consistent with perturbations during isolation. The comparisons between the buffy coat and the isolated fractions as a group using linear modeling yielded a small number of probes (∼29,000) with discordant methylation. Demethylation of probes in the buffy coat compared to derived cell lines was more common and was prevalent in shelf and open sea regions. Conclusion: Buffy coat is representative of methylation patterns in WBC types in normal pregnancy. The differential methylations are consistent with perturbations during isolation of constituent cells and likely originate in vitro due to the physical stress during cell separation and are of no physiological relevance. These findings help the interpretation of DNA methylation profiling in pregnancy and numerous other conditions.

Identification of glucocorticoid-related molecular signature by whole blood methylome analysis

OBJECTIVE

Cushing's syndrome represents a state of excessive glucocorticoids related to glucocorticoid treatments or to endogenous hypercortisolism. Cushing's syndrome is associated with high morbidity, with significant inter-individual variability. Likewise, adrenal insufficiency is a life-threatening condition of cortisol deprivation. Currently, hormone assays contribute to identify Cushing's syndrome or adrenal insufficiency. However, no biomarker directly quantifies the biological glucocorticoid action. The aim of this study was to identify such markers.

DESIGN

We evaluated whole blood DNA methylome in 94 samples obtained from patients with different glucocorticoid states (Cushing's syndrome, eucortisolism, adrenal insufficiency). We used an independent cohort of 91 samples for validation.

METHODS

Leukocyte DNA was obtained from whole blood samples. Methylome was determined using the Illumina methylation chip array (~850 000 CpG sites). Both unsupervised (principal component analysis) and supervised (Limma) methods were used to explore methylome profiles. A Lasso-penalized regression was used to select optimal discriminating features.

RESULTS

Whole blood methylation profile was able to discriminate samples by their glucocorticoid status: glucocorticoid excess was associated with DNA hypomethylation, recovering within months after Cushing's syndrome correction. In Cushing's syndrome, an enrichment in hypomethylated CpG sites was observed in the region of FKBP5 gene locus. A methylation predictor of glucocorticoid excess was built on a training cohort and validated on two independent cohorts. Potential CpG sites associated with the risk for specific complications, such as glucocorticoid-related hypertension or osteoporosis, were identified, needing now to be confirmed on independent cohorts.

CONCLUSIONS

Whole blood DNA methylome is dynamically impacted by glucocorticoids. This biomarker could contribute to better assessment of glucocorticoid action beyond hormone assays.

Epigenetic Age Acceleration Is Not Associated with Age-Related Macular Degeneration

DNA methylation age (DNAm age) estimation is a powerful biomarker of human ageing. To date, epigenetic clocks have not been evaluated in age-related macular degeneration (AMD). Here, we perform genome-wide DNA methylation analyses in blood of AMD patients with a documented smoking history (14 AMD, 16 Normal), identifying loci of differential methylation (DML) with a relaxed p-value criterion (p ≤ 10⁻⁴). We conduct DNAm age analyses using the Horvath-multi tissue, Hannum and Skin & Blood epigenetic clocks in both blood and retinal pigment epithelium (RPE). We perform Ingenuity Pathway Analysis Causal Network Analysis (IPA CNA) on the topmost significantly differentially methylated CpG probes in blood and RPE. Results show poor performance of epigenetic clocks in RPE. Epigenetic age acceleration (EAA) was not observed in AMD. However, we observe positive EAA in blood of smokers, and in smokers with AMD. DML analysis revealed hypomethylation at cg04953735 within RPTOR (p = 6.51 × 10⁻⁵; Δβ = −11.95%). IPA CNA in the RPE also identified RPTOR as the putative master regulator, predicted to be inhibited in AMD. In conclusion, this is the first study evaluating an association of epigenetic ageing in AMD. We posit a role for RPTOR as a common master regulator of methylation changes in the RPE in AMD.

Prenatal metal exposure, cord blood DNA methylation and persistence in childhood: an epigenome-wide association study of 12 metals

Background

Prenatal exposure to essential and non-essential metals impacts birth and child health, including fetal growth and neurodevelopment. DNA methylation (DNAm) may be involved in pathways linking prenatal metal exposure and health. In the Project Viva cohort, we analyzed the extent to which metals (As, Ba, Cd, Cr, Cs, Cu, Hg, Mg, Mn, Pb, Se, and Zn) measured in maternal erythrocytes were associated with differentially methylated positions (DMPs) and regions (DMRs) in cord blood and tested if associations persisted in blood collected in mid-childhood. We measured metal concentrations in first-trimester maternal erythrocytes, and DNAm in cord blood (N = 361) and mid-childhood blood (N = 333, 6–10 years) with the Illumina HumanMethylation450 BeadChip. For each metal individually, we tested for DMPs using linear models (considered significant at FDR < 0.05), and for DMRs using comb-p (Sidak p < 0.05). Covariates included biologically relevant variables and estimated cell-type composition. We also performed sex-stratified analyses.

Results

Pb was associated with decreased methylation of cg20608990 (CASP8) (FDR = 0.04), and Mn was associated with increased methylation of cg02042823 (A2BP1) in cord blood (FDR = 9.73 × 10^–6). Both associations remained significant but attenuated in blood DNAm collected at mid-childhood (p < 0.01). Two and nine Mn-associated DMPs were identified in male and female infants, respectively (FDR < 0.05), with two and six persisting in mid-childhood (p < 0.05). All metals except Ba and Pb were associated with ≥ 1 DMR among all infants (Sidak p < 0.05). Overlapping DMRs annotated to genes in the human leukocyte antigen (HLA) region were identified for Cr, Cs, Cu, Hg, Mg, and Mn.

Conclusions

Prenatal metal exposure is associated with DNAm, including DMRs annotated to genes involved in neurodevelopment. Future research is needed to determine if DNAm partially explains the relationship between prenatal metal exposures and health outcomes.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01198-z.

Associations between infant sex and DNA methylation across umbilical cord blood, artery, and placenta samples

DNA methylation (DNAm) is vulnerable to dysregulation by environmental exposures during epigenetic reprogramming that occurs in embryogenesis. Sexual dimorphism in environmentally induced DNAm dysregulation has been identified and therefore it is important to understand sex-specific DNAm patterns. DNAm at several autosomal sites has been consistently associated with sex in cord blood and placental foetal tissues. However, there is limited research comparing sex-specific DNAm across tissues, particularly differentially methylated regions (DMRs). This study leverages DNAm data measured using the Illumina HumanMethylation450 BeadChip in cord blood (N = 179), placenta (N = 229), and umbilical artery samples (N = 229) in the PRogramming of Intergenerational Stress Mechanisms (PRISM) cohort to identify autosomal DMRs and differentially methylated positions (DMPs). A replication analyses was conducted in an independent cohort (GEO Accession GSE129841). We identified 183, 257, and 419 DMRs and 2119, 2281, and 3405 DMPs (p_Bonferroni < 0.05) in cord blood, placenta, and artery samples, respectively. Thirty-nine DMRs overlapped in all three tissues, overlapping with genes involved in spermatogenesis (NKAPL, PIWIL2 and AURKC) and X-inactivation (LRIF1). In replication analysis, 85% of DMRs overlapped with those identified in PRISM. Overall, DMRs and DMPs had higher methylation levels among females in cord blood and artery samples, but higher methylation levels among males in placenta samples. Further research is necessary to understand biological mechanisms that contribute to differences in sex-specific DNAm signatures across tissues, as well as to determine if sexual dimorphism in the epigenome impacts response to environmental stressors.

Integrated analysis of patients with KEAP1/NFE2L2/CUL3 mutations in lung adenocarcinomas

Objectives

To explore the clinical features, molecular characteristics, and immune landscape of lung adenocarcinoma patients with KEAP1/NFE2L2/CUL3 mutations.

Methods

The multi‐omics data from the GDC‐TCGA LUAD project of The Cancer Genome Atlas (TCGA) database were downloaded from the Xena browser. The estimate of the immune infiltration was implemented by using the GSVA analysis and CIBERSORT. The status of KEAP1/NFE2L2/CUL3 mutation in 50 LUAD samples of our department was detected by using Sanger sequencing, following the relative expression level of differentially expressed genes (DEGs), miRNAs (DEmiRNAs), and lncRNAs (DElncRNAs) was validated by IHC and real‐time quantitative polymerase chain reaction (RT‐qPCR).

Results

The Kaplan–Meier and multivariable Cox regression analyses demonstrated that KEAP1/NFE2L2/CUL3 mutations had independent prognostic value for OS and PFS in LUAD patients. The differential analysis detected 207 upregulated genes (like GSR/UGT1A6) and 447 downregulated genes (such as PIGR). GO, KEGG, and GSEA analyses demonstrated that DEGs were enriched in glutamate metabolism and the immune response. The constructed ceRNA network shows the linkage of differential lncRNAs and mRNAs. Three hundred and nine somatic mutations were detected, alterations in immune infiltration DNA methylations and stemness scores were also founded between the two groups. Eight mutated LUAD patients were detected by Sanger DNA sequencing in 50 surgical patients. GSR and UGT1A6 were validated to express higher in the Mut group, whereas the expression of PIGR was restrained. Furthermore, the IHC staining conducted on paraffin‐embedded tissue emphasizes the consistency of our result.

Conclusion

This research implemented the comprehensive analysis of KEAP1/NFE2L2/CUL3 somatic mutations in the LUAD patients. Compared with the wild type of LUAD patients, the Mut group shows a large difference in clinical features, RNA sequence, DNA methylation, and immune infiltrations, indicating complex mechanism oncogenesis and also reveals potential therapeutic targets.

Longitudinal analysis of individual cfDNA methylome patterns in metastatic prostate cancer

Background

Disease progression and therapeutic resistance are hallmarks of advanced stage prostate cancer (PCa), which remains a major cause of cancer-related mortality around the world. Longitudinal studies, coupled with the use of liquid biopsies, offer a potentially new and minimally invasive platform to study the dynamics of tumour progression. Our aim was to investigate the dynamics of personal DNA methylomic profiles of metastatic PCa (mPCa) patients, during disease progression and therapy administration.

Results

Forty-eight plasma samples from 9 mPCa patients were collected, longitudinally, over 13–21 months. After circulating cell-free DNA (cfDNA) isolation, DNA methylation was profiled using the Infinium MethylationEPIC BeadChip. The top 5% most variable probes across time, within each individual, were utilised to study dynamic methylation patterns during disease progression and therapeutic response. Statistical testing was carried out to identify differentially methylated genes (DMGs) in cfDNA, which were subsequently validated in two independent mPCa (cfDNA and FFPE tissue) cohorts. Individual cfDNA global methylation patterns were temporally stable throughout the disease course. However, a proportion of CpG sites presented a dynamic temporal pattern that was consistent with clinical events, including different therapies, and were prominently associated with genes linked to immune response pathways. Additionally, study of the tumour fraction of cfDNA identified > 2000 DMGs with dynamic methylation patterns.

Conclusions

Longitudinal assessment of cfDNA methylation in mPCa patients unveiled dynamic patterns associated with disease progression and therapy administration, thus highlighting the potential of using liquid biopsies to study PCa evolution at a methylomic level.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-021-01155-w.

Association of medically assisted reproduction with offspring cord blood DNA methylation across cohorts

STUDY QUESTION

Is cord blood DNA methylation associated with having been conceived by medically assisted reproduction?

SUMMARY ANSWER

This study does not provide strong evidence of an association of conception by medically assisted reproduction with variation in infant blood cell DNA methylation.

WHAT IS KNOWN ALREADY

Medically assisted reproduction consists of procedures used to help infertile/subfertile couples conceive, including ART. Due to its importance in gene regulation during early development programming, DNA methylation and its perturbations associated with medically assisted reproduction could reveal new insights into the biological effects of assisted reproductive technologies and potential adverse offspring outcomes.

STUDY DESIGN, SIZE, DURATION

We investigated the association of DNA methylation and medically assisted reproduction using a case–control study design (N = 205 medically assisted reproduction cases and N = 2439 naturally conceived controls in discovery cohorts; N = 149 ART cases and N = 58 non-ART controls in replication cohort).

PARTICIPANTS/MATERIALS, SETTINGS, METHODS

We assessed the association between medically assisted reproduction and DNA methylation at birth in cord blood (205 medically assisted conceptions and 2439 naturally conceived controls) at >450 000 CpG sites across the genome in two sub-samples of the UK Avon Longitudinal Study of Parents and Children (ALSPAC) and two sub-samples of the Norwegian Mother, Father and Child Cohort Study (MoBa) by meta-analysis. We explored replication of findings in the Australian Clinical review of the Health of adults conceived following Assisted Reproductive Technologies (CHART) study (N = 149 ART conceptions and N = 58 controls).

MAIN RESULTS AND THE ROLE OF CHANCE

The ALSPAC and MoBa meta-analysis revealed evidence of association between conception by medically assisted reproduction and DNA methylation (false-discovery-rate-corrected P-value < 0.05) at five CpG sites which are annotated to two genes (percentage difference in methylation per CpG, cg24051276: Beta = 0.23 (95% CI 0.15,0.31); cg00012522: Beta = 0.47 (95% CI 0.31, 0.63); cg17855264: Beta = 0.31 (95% CI 0.20, 0.43); cg17132421: Beta = 0.30 (95% CI 0.18, 0.42); cg18529845: Beta = 0.41 (95% CI 0.25, 0.57)). Methylation at three of these sites has been previously linked to cancer, aging, HIV infection and neurological diseases. None of these associations replicated in the CHART cohort. There was evidence of a functional role of medically assisted reproduction-induced hypermethylation at CpG sites located within regulatory regions as shown by putative transcription factor binding and chromatin remodelling.

LIMITATIONS, REASONS FOR CAUTIONS

While insufficient power is likely, heterogeneity in types of medically assisted reproduction procedures and between populations may also contribute. Larger studies might identify replicable variation in DNA methylation at birth due to medically assisted reproduction.

WIDER IMPLICATIONS OF THE FINDINGS

Newborns conceived with medically assisted procedures present with divergent DNA methylation in cord blood white cells. If these associations are true and causal, they might have long-term consequences for offspring health.

STUDY FUNDING/COMPETING INTERESTS(S)

This study has been supported by the US National Institute of Health (R01 DK10324), the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC Grant agreement no. 669545, European Union’s Horizon 2020 research and innovation programme under Grant agreement no. 733206 (LifeCycle) and the NIHR Biomedical Centre at the University Hospitals Bristol NHS Foundation Trust and the University of Bristol. The UK Medical Research Council and Wellcome (Grant ref: 102215/2/13/2) and the University of Bristol provide core support for ALSPAC. Methylation data in the ALSPAC cohort were generated as part of the UK BBSRC funded (BB/I025751/1 and BB/I025263/1) Accessible Resource for Integrated Epigenomic Studies (ARIES, http://www.ariesepigenomics.org.uk). D.C., J.J., C.L.R. D.A.L and H.R.E. work in a Unit that is supported by the University of Bristol and the UK Medical Research Council (Grant nos. MC_UU_00011/1, MC_UU_00011/5 and MC_UU_00011/6). B.N. is supported by an NHMRC (Australia) Investigator Grant (1173314). ALSPAC GWAS data were generated by Sample Logistics and Genotyping Facilities at Wellcome Sanger Institute and LabCorp (Laboratory Corporation of America) using support from 23andMe. The Norwegian Mother, Father and Child Cohort Study is supported by the Norwegian Ministry of Health and Care Services and the Ministry of Education and Research, NIH/NIEHS (Contract no. N01-ES-75558), NIH/NINDS (Grant nos. (i) UO1 NS 047537-01 and (ii) UO1 NS 047537-06A1). For this work, MoBa 1 and 2 were supported by the Intramural Research Program of the NIH, National Institute of Environmental Health Sciences (Z01-ES-49019) and the Norwegian Research Council/BIOBANK (Grant no. 221097). This work was partly supported by the Research Council of Norway through its Centres of Excellence funding scheme, Project no. 262700.

D.A.L. has received support from national and international government and charity funders, as well as from Roche Diagnostics and Medtronic for research unrelated to this study. The other authors declare no conflicts of interest.

TRIAL REGISTRATION NUMBER

N/A.

Exposure to arsenic at different life-stages and DNA methylation meta-analysis in buccal cells and leukocytes

BACKGROUND

Arsenic (As) exposure through drinking water is a global public health concern. Epigenetic dysregulation including changes in DNA methylation (DNAm), may be involved in arsenic toxicity. Epigenome-wide association studies (EWAS) of arsenic exposure have been restricted to single populations and comparison across EWAS has been limited by methodological differences. Leveraging data from epidemiological studies conducted in Chile and Bangladesh, we use a harmonized data processing and analysis pipeline and meta-analysis to combine results from four EWAS.

METHODS

DNAm was measured among adults in Chile with and without prenatal and early-life As exposure in PBMCs and buccal cells (N = 40, 850K array) and among men in Bangladesh with high and low As exposure in PBMCs (N = 32, 850K array; N = 48, 450K array). Linear models were used to identify differentially methylated positions (DMPs) and differentially variable positions (DVPs) adjusting for age, smoking, cell type, and sex in the Chile cohort. Probes common across EWAS were meta-analyzed using METAL, and differentially methylated and variable regions (DMRs and DVRs, respectively) were identified using comb-p. KEGG pathway analysis was used to understand biological functions of DMPs and DVPs.

RESULTS

In a meta-analysis restricted to PBMCs, we identified one DMP and 23 DVPs associated with arsenic exposure; including buccal cells, we identified 3 DMPs and 19 DVPs (FDR < 0.05). Using meta-analyzed results, we identified 11 DMRs and 11 DVRs in PBMC samples, and 16 DMRs and 19 DVRs in PBMC and buccal cell samples. One region annotated to LRRC27 was identified as a DMR and DVR. Arsenic-associated KEGG pathways included lysosome, autophagy, and mTOR signaling, AMPK signaling, and one carbon pool by folate.

CONCLUSIONS

Using a two-step process of (1) harmonized data processing and analysis and (2) meta-analysis, we leverage four DNAm datasets from two continents of individuals exposed to high levels of As prenatally and during adulthood to identify DMPs and DVPs associated with arsenic exposure. Our approach suggests that standardizing analytical pipelines can aid in identifying biological meaningful signals.

A method of sample-wise region-set enrichment analysis for DNA methylomics

Aim: Gene set analysis has commonly been used to interpret DNA methylome data. However, summarizing the DNA methylation level of a gene is challenging due to variability in the number, density and methylation levels of CpG sites, and the numerous intergenic CpGs. Instead, we propose to use region sets to annotate the DNA methylome. Methods: We developed single sample region-set enrichment analysis for DNA methylome (methyl-ssRSEA) to conduct sample-wise, region-set enrichment analysis. Results: Methyl-ssRSEA can handle both microarray- and sequencing-based platforms and reproducibly recover the known biology from the methylation profiles of peripheral blood cells and breast cancers. The performance was superior to existing tools for region-set analysis in discriminating blood cell types. Conclusion: Methyl-ssRSEA offers a novel way to functionally interpret the DNA methylome in the cell.

Sex-specific associations with DNA methylation in lung tissue demonstrate smoking interactions

Cigarette smoking impacts DNA methylation, but the investigation of sex-specific features of lung tissue DNA methylation in smokers has been limited. Women appear more susceptible to cigarette smoke, and often develop more severe lung disease at an earlier age with less smoke exposure. We aimed to analyse whether there are sex differences in DNA methylation in lung tissue and whether these DNA methylation marks interact with smoking. We collected lung tissue samples from former smokers who underwent lung tissue resection. One hundred thirty samples from white subjects were included for this analysis. Regression models for sex as a predictor of methylation were adjusted for age, presence of COPD, smoking variables and technical batch variables revealed 710 associated sites. 294 sites demonstrated robust sex-specific methylation associations in foetal lung tissue. Pathway analysis identified 6 nominally significant pathways including the mitophagy pathway. Three CpG sites demonstrated a suggested interaction between sex and pack-years of smoking: GPR132, ANKRD44 and C19orf60. All of them were nominally significant in both male- and female-specific models, and the effect estimates were in opposite directions for male and female; GPR132 demonstrated significant association between DNA methylation and gene expression in lung tissue (P < 0.05). Sex-specific associations with DNA methylation in lung tissue are wide-spread and may reveal genes and pathways relevant to sex differences for lung damaging effects of cigarette smoking.

Wavelet Screening identifies regions highly enriched for differentially methylated loci for orofacial clefts

DNA methylation is the most widely studied epigenetic mark in humans and plays an essential role in normal biological processes as well as in disease development. More focus has recently been placed on understanding functional aspects of methylation, prompting the development of methods to investigate the relationship between heterogeneity in methylation patterns and disease risk. However, most of these methods are limited in that they use simplified models that may rely on arbitrarily chosen parameters, they can only detect differentially methylated regions (DMRs) one at a time, or they are computationally intensive. To address these shortcomings, we present a wavelet-based method called 'Wavelet Screening' (WS) that can perform an epigenome-wide association study (EWAS) of thousands of individuals on a single CPU in only a matter of hours. By detecting multiple DMRs located near each other, WS identifies more complex patterns that can differentiate between different methylation profiles. We performed an extensive set of simulations to demonstrate the robustness and high power of WS, before applying it to a previously published EWAS dataset of orofacial clefts (OFCs). WS identified 82 associated regions containing several known genes and loci for OFCs, while other findings are novel and warrant replication in other OFCs cohorts.

Epigenome-scale comparison of DNA methylation between blood leukocytes and bronchial epithelial cells

Aim: Agreement in DNA methylation (DNAm) at the genome scale between blood leukocytes (BL) and bronchial epithelial cells (BEC) is unknown. We examine as to what extent DNAm in BL is comparable with that in BEC and serves as a surrogate for BEC. Materials & methods: Overall agreement (paired t-tests with false discovery rate adjusted p > 0.05) and consistency (Pearson's correlation coefficients >0.5) between two tissues, at each of the 767,412 CpGs, were evaluated. Results: We identified 247,721 CpGs showing overall agreement and 47,371 CpGs showing consistency in DNAm. Identified CpGs are involved in certain immune pathways, indicating the potential of using blood as a biomarker for BEC at those CpGs in lower airway-related diseases. Conclusion: CpGs showing overall agreement and those without overall agreement are distributed differently on the genome.

Cigarette smoke-induced alterations in blood: A review of research on DNA methylation and gene expression

Worldwide, smoking remains a threat to public health, causing preventable diseases and premature mortality. Cigarette smoke is a powerful inducer of DNA methylation and gene expression alterations, which have been associated with negative health consequences. Here, we review the current knowledge on smoking-related changes in DNA methylation and gene expression in human blood samples. We identified 30 studies focused on the association between active smoking, DNA methylation modifications, and gene expression alterations. Overall, we identified 1,758 genes with differentially methylated sites (DMS) and differentially expressed genes (DEG) between smokers and nonsmokers, of which 261 were detected in multiple studies (≥4). The most frequently (≥10 studies) reported genes were AHRR, GPR15, GFI1, and RARA. Functional enrichment analysis of the 261 genes identified the aryl hydrocarbon receptor repressor and T cell pathways (T helpers 1 and 2) as influenced by smoking status. These results highlight specific genes for future mechanistic and translational research that may be associated with cigarette smoke exposure and smoking-related diseases. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

DNA methylation signatures of adolescent victimization: analysis of a longitudinal monozygotic twin sample

Accumulating evidence suggests that individuals exposed to victimization at key developmental stages may have different epigenetic fingerprints compared to those exposed to no/minimal stressful events, however results are inconclusive. This study aimed to strengthen causal inference regarding the impact of adolescent victimization on the epigenome by controlling for genetic variation, age, gender, and shared environmental exposures. We conducted longitudinal epigenome-wide association analyses (EWAS) on DNA methylation (DNAm) profiles of 118 monozygotic (MZ) twin pairs from the Environmental Risk study with and without severe adolescent victimization generated using buccal DNA collected at ages 5, 10 and 18, and the Illumina EPIC array. Additionally, we performed cross-sectional EWAS on age-18 blood and buccal DNA from the same individuals to elucidate tissue-specific signatures of severe adolescent victimization. Our analyses identified 20 suggestive differentially methylated positions (DMPs) (P < 5e-05), with altered DNAm trajectories between ages 10–18 associated with severe adolescent victimization (∆Beta range = −5.5%−5.3%). Age-18 cross-sectional analyses revealed 72 blood (∆Beta range = −2.2%−3.4%) and 42 buccal (∆Beta range = −3.6%−4.6%) suggestive severe adolescent victimization-associated DMPs, with some evidence of convergent signals between these two tissue types. Downstream regional analysis identified significant differentially methylated regions (DMRs) in LGR6 and ANK3 (Šidák P = 5e-09 and 4.07e-06), and one upstream of CCL27 (Šidák P = 2.80e-06) in age-18 blood and buccal EWAS, respectively. Our study represents the first longitudinal MZ twin analysis of DNAm and severe adolescent victimization, providing initial evidence for altered DNA methylomic signatures in individuals exposed to adolescent victimization.

Maternal lipodome across pregnancy is associated with the neonatal DNA methylome

Aim: To classify the association between the maternal lipidome and DNA methylation in cord blood leukocytes. Materials & methods: Untargeted lipidomics was performed on first trimester maternal plasma (M1) and delivery maternal plasma (M3) in 100 mothers from the Michigan Mother-Infant Pairs cohort. Cord blood leukocyte DNA methylation was profiled using the Infinium EPIC bead array and empirical Bayes modeling identified differential DNA methylation related to maternal lipid groups. Results: M3-saturated lysophosphatidylcholine was associated with 45 differentially methylated loci and M3-saturated lysophosphatidylethanolamine was associated with 18 differentially methylated loci. Biological pathways enriched among differentially methylated loci by M3 saturated lysophosphatidylcholines were related to cell proliferation and growth. Conclusion: The maternal lipidome may be influential in establishing the infant epigenome.

Epigenome-wide association scan identifies methylation sites associated with HIV infection

Aim: To investigate the role of epigenetics in HIV pathophysiology. Materials & methods: We conducted an epigenome-wide association scan on HIV infection status among people who inject drugs in the AIDS Linked to the IntraVenous Experience study with primary (n = 397) and validation samples (n = 390). DNA methylation from blood was measured by the Illumina EPIC BeadChip. We controlled for cell type heterogeneity by HIV status. Results: HIV infection status was associated (p < 10^-8) with DNA methylation at 49 CpG sites. Sites were enriched in response to virus, interferon signaling pathway, etc. Among these sites, discovery and validation t-statistics were highly correlated (r = 0.96). Conclusion: In a cohort of people who inject drugs, HIV status was associated with differential DNA methylation at biologically meaningful sites.

Association between DNA methylation and ADHD symptoms from birth to school age: a prospective meta-analysis

Attention-deficit and hyperactivity disorder (ADHD) is a common childhood disorder with a substantial genetic component. However, the extent to which epigenetic mechanisms play a role in the etiology of the disorder is unknown. We performed epigenome-wide association studies (EWAS) within the Pregnancy And Childhood Epigenetics (PACE) Consortium to identify DNA methylation sites associated with ADHD symptoms at two methylation assessment periods: birth and school age. We examined associations of both DNA methylation in cord blood with repeatedly assessed ADHD symptoms (age 4-15 years) in 2477 children from 5 cohorts and of DNA methylation at school age with concurrent ADHD symptoms (age 7-11 years) in 2374 children from 9 cohorts, with 3 cohorts participating at both timepoints. CpGs identified with nominal significance (p < 0.05) in either of the EWAS were correlated between timepoints (ρ = 0.30), suggesting overlap in associations; however, top signals were very different. At birth, we identified nine CpGs that predicted later ADHD symptoms (p < 1 × 10^-7), including ERC2 and CREB5. Peripheral blood DNA methylation at one of these CpGs (cg01271805 in the promoter region of ERC2, which regulates neurotransmitter release) was previously associated with brain methylation. Another (cg25520701) lies within the gene body of CREB5, which previously was associated with neurite outgrowth and an ADHD diagnosis. In contrast, at school age, no CpGs were associated with ADHD with p < 1 × 10^-7. In conclusion, we found evidence in this study that DNA methylation at birth is associated with ADHD. Future studies are needed to confirm the utility of methylation variation as biomarker and its involvement in causal pathways.

Germline-driven replication repair-deficient high-grade gliomas exhibit unique hypomethylation patterns

Replication repair deficiency (RRD) leading to hypermutation is an important driving mechanism of high-grade glioma (HGG) occurring predominantly in the context of germline mutations in RRD-associated genes. Although HGG presents specific patterns of DNA methylation corresponding to oncogenic mutations, this has not been well studied in replication repair-deficient tumors. We analyzed 51 HGG arising in the background of gene mutations in RRD utilizing either 450 k or 850 k methylation arrays. These were compared with HGG not known to be from patients with RRD. RRD HGG harboring secondary mutations in glioma genes such as IDH1 and H3F3A displayed a methylation pattern corresponding to these methylation subgroups. Strikingly, RRD HGG lacking these known secondary mutations clustered together with an incompletely described group of HGG previously labeled "Wild type-C" or "Paediatric RTK 1". Independent analysis of two comparator HGG cohorts showed that other RRD/hypermutant tumors clustered within these subgroups, suggesting that undiagnosed RRD may be driving some HGG clustering in this location. RRD HGG displayed a unique CpG Island Demethylator Phenotype in contrast to the CpG Island Methylator Phenotype described in other cancers. Hypomethylation was enriched at gene promoters with prominent demethylation in genes and pathways critical to cellular survival including cell cycle, gene expression, cellular metabolism, and organization. These data suggest that methylation arrays may provide diagnostic information for the detection of RRD HGG. Furthermore, our findings highlight the unique natural selection pressures in these highly dysregulated, hypermutant cancers and provide the novel impact of hypermutation and RRD on the cancer epigenome.

Co-methylation analysis in lung tissue identifies pathways for fetal origins of COPD

COPD likely has developmental origins; however, the underlying molecular mechanisms are not fully identified. Investigation of lung tissue-specific epigenetic modifications such as DNA methylation using network approaches might facilitate insights linking in utero smoke (IUS) exposure and risk for COPD in adulthood.We performed genome-wide methylation profiling for adult lung DNA from 160 surgical samples and 78 fetal lung DNA samples isolated from discarded tissue at 8-18 weeks of gestation. Co-methylation networks were constructed to identify preserved modules that shared methylation patterns in fetal and adult lung tissues and associations with fetal IUS exposure, gestational age and COPD.Weighted correlation networks highlighted preserved and co-methylated modules for both fetal and adult lung data associated with fetal IUS exposure, COPD and lower adult lung function. These modules were significantly enriched for genes involved in embryonic organ development and specific inflammation-related pathways, including Hippo, phosphatidylinositol 3-kinase/protein kinase B (PI3K/AKT), Wnt, mitogen-activated protein kinase and transforming growth factor-β signalling. Gestational age-associated modules were remarkably preserved for COPD and lung function, and were also annotated to genes enriched for the Wnt and PI3K/AKT pathways.Epigenetic network perturbations in fetal lung tissue exposed to IUS and of early lung development recapitulated in adult lung tissue from ex-smokers with COPD. Overlapping fetal and adult lung tissue network modules highlighted putative disease pathways supportive of exposure-related and age-associated developmental origins of COPD.

DNA methylation biomarker selected by an ensemble machine learning approach predicts mortality risk in an HIV-positive veteran population

Background: With the improved life expectancy of people living with HIV (PLWH), identifying vulnerable subpopulations at high mortality risk is important. Evidences showed that DNA methylation (DNAm) is associated with mortality in non-HIV populations. Here, we established a panel of DNAm biomarkers that can predict mortality risk among PLWH.

Methods: 1,081 HIV-positive participants from the Veterans Ageing Cohort Study (VACS) were divided into training (N = 460), validation (N = 114), and testing (N = 507) sets. VACS index was used as a measure of mortality risk among PLWH. Model training and fine-tuning were conducted using the ensemble method in the training and validation sets and prediction performance was assessed in the testing set. The survival analysis comparing the predicted high and low mortality risk groups and the Gene Ontology enrichment analysis of the predictive CpG sites were performed.

Results: We selected a panel of 393 CpGs for the ensemble prediction model that showed excellent performance in predicting high mortality risk with an auROC of 0.809 (95%CI: 0.767,0.851) and a balanced accuracy of 0.653 (95%CI: 0.611, 0.693) in the testing set. The high mortality risk group was significantly associated with 10-year mortality (hazard ratio = 1.79, p = 4E-05) compared with low risk group. These 393 CpGs were located in 280 genes enriched in immune and inflammation response pathways.

Conclusions: We identified a panel of DNAm features associated with mortality risk in PLWH. These DNAm features may serve as predictive biomarkers for mortality risk among PLWH.

Abbreviations: AUC: Area Under Curve; CI: Confidence interval; DMR: differentially methylated region; DNA: Deoxyribonucleic acid; DNAm: DNA methylation; DAVID: Database for Annotation, Visualization, and Integrated Discovery; EWA: epigenome-wide association; FDR: False discovery rate; FWER: Family-wise error rate; GLMNET: elastic-net-regularized generalized linear models; GO: Gene ontology; HIV: Human immunodeficiency virus; HM450K: Human Methylation 450 K BeadChip; k-NN: k-nearest neighbours; NK: Natural killer; PC: Principal component; PLWH: people living with HIV; QC: Quality control; SVM: Support Vector Machines; VACS: Veterans Ageing Cohort Study; XGBoost: Extreme Gradient Boosting Tree

The role of the gut microbiome in cancer-related fatigue: pilot study on epigenetic mechanisms

PURPOSE

Recent evidence supports a key role of gut microbiome in brain health. We conducted a pilot study to assess associations of gut microbiome with cancer-related fatigue and explore the associations with DNA methylation changes.

METHODS

Self-reported Multidimensional Fatigue Inventory and stool samples were collected at pre-radiotherapy and one-month post-radiotherapy in patients with head and neck cancer. Gut microbiome data were obtained by sequencing the 16S ribosomal ribonucleic acid gene. DNA methylation changes in the blood were assessed using Illumina Methylation EPIC BeadChip.

RESULTS

We observed significantly different gut microbiota patterns among patients with high vs. low fatigue across time. This pattern was characterized by low relative abundance in short-chain fatty acid-producing taxa (family Ruminococcaceae, genera Subdoligranulum and Faecalibacterium; all p < 0.05), with high abundance in taxa associated with inflammation (genera Family XIII AD3011 and Erysipelatoclostridium; all p < 0.05) for high-fatigue group. We identified nine KEGG Orthology pathways significantly different between high- vs. low-fatigue groups over time (all p < 0.001), including pathways related to fatty acid synthesis and oxidation, inflammation, and brain function. Gene set enrichment analysis (GSEA) was performed on the top differentially methylated CpG sites that were associated with the taxa and fatigue. All biological processes from the GSEA were related to immune responses and inflammation (FDR < 0.05).

CONCLUSIONS

Our results suggest different patterns of the gut microbiota in cancer patients with high vs. low fatigue. Results from functional pathways and DNA methylation analyses indicate that inflammation is likely to be the major driver in the gut-brain axis for cancer-related fatigue.

Mitochondrial DNA copy number can influence mortality and cardiovascular disease via methylation of nuclear DNA CpGs

BACKGROUND

Mitochondrial DNA copy number (mtDNA-CN) has been associated with a variety of aging-related diseases, including all-cause mortality. However, the mechanism by which mtDNA-CN influences disease is not currently understood. One such mechanism may be through regulation of nuclear gene expression via the modification of nuclear DNA (nDNA) methylation.

METHODS

To investigate this hypothesis, we assessed the relationship between mtDNA-CN and nDNA methylation in 2507 African American (AA) and European American (EA) participants from the Atherosclerosis Risk in Communities (ARIC) study. To validate our findings, we assayed an additional 2528 participants from the Cardiovascular Health Study (CHS) (N = 533) and Framingham Heart Study (FHS) (N = 1995). We further assessed the effect of experimental modification of mtDNA-CN through knockout of TFAM, a regulator of mtDNA replication, via CRISPR-Cas9.

RESULTS

Thirty-four independent CpGs were associated with mtDNA-CN at genome-wide significance (P < 5 × 10- 8). Meta-analysis across all cohorts identified six mtDNA-CN-associated CpGs at genome-wide significance (P < 5 × 10- 8). Additionally, over half of these CpGs were associated with phenotypes known to be associated with mtDNA-CN, including coronary heart disease, cardiovascular disease, and mortality. Experimental modification of mtDNA-CN demonstrated that modulation of mtDNA-CN results in changes in nDNA methylation and gene expression of specific CpGs and nearby transcripts. Strikingly, the "neuroactive ligand receptor interaction" KEGG pathway was found to be highly overrepresented in the ARIC cohort (P = 5.24 × 10- 12), as well as the TFAM knockout methylation (P = 4.41 × 10- 4) and expression (P = 4.30 × 10- 4) studies.

CONCLUSIONS

These results demonstrate that changes in mtDNA-CN influence nDNA methylation at specific loci and result in differential expression of specific genes that may impact human health and disease via altered cell signaling.

BioMethyl: an R package for biological interpretation of DNA methylation data

Motivation

The accumulation of publicly available DNA methylation datasets has resulted in the need for tools to interpret the specific cellular phenotypes in bulk tissue data. Current approaches use either single differentially methylated CpG sites or differentially methylated regions that map to genes. However, these approaches may introduce biases in downstream analyses of biological interpretation, because of the variability in gene length. There is a lack of approaches to interpret DNA methylation effectively. Therefore, we have developed computational models to provide biological interpretation of relevant gene sets using DNA methylation data in the context of The Cancer Genome Atlas.

Results

We illustrate that Biological interpretation of DNA Methylation (BioMethyl) utilizes the complete DNA methylation data for a given cancer type to reflect corresponding gene expression profiles and performs pathway enrichment analyses, providing unique biological insight. Using breast cancer as an example, BioMethyl shows high consistency in the identification of enriched biological pathways from DNA methylation data compared to the results calculated from RNA sequencing data. We find that 12 out of 14 pathways identified by BioMethyl are shared with those by using RNA-seq data, with a Jaccard score 0.8 for estrogen receptor (ER) positive samples. For ER negative samples, three pathways are shared in the two enrichments with a slight lower similarity (Jaccard score = 0.6). Using BioMethyl, we can successfully identify those hidden biological pathways in DNA methylation data when gene expression profile is lacking.

Availability and implementation

BioMethyl R package is freely available in the GitHub repository (https://github.com/yuewangpanda/BioMethyl).

Supplementary information

Supplementary data are available at Bioinformatics online.

ebGSEA: an improved Gene Set Enrichment Analysis method for Epigenome-Wide-Association Studies

Motivation

The biological interpretation of differentially methylated sites derived from Epigenome-Wide-Association Studies (EWAS) remains a significant challenge. Gene Set Enrichment Analysis (GSEA) is a general tool to aid biological interpretation, yet its correct and unbiased implementation in the EWAS context is difficult due to the differential probe representation of Illumina Infinium DNA methylation beadchips.

Results

We present a novel GSEA method, called ebGSEA, which ranks genes, not CpGs, according to the overall level of differential methylation, as assessed using all the probes mapping to the given gene. Applied on simulated and real EWAS data, we show how ebGSEA may exhibit higher sensitivity and specificity than the current state-of-the-art, whilst also avoiding differential probe representation bias. Thus, ebGSEA will be a useful additional tool to aid the interpretation of EWAS data.

Availability and implementation

ebGSEA is available from https://github.com/aet21/ebGSEA, and has been incorporated into the ChAMP Bioconductor package (https://www.bioconductor.org).

Supplementary information

Supplementary data are available at Bioinformatics online.

methylGSA: a Bioconductor package and Shiny app for DNA methylation data length bias adjustment in gene set testing

MOTIVATION

An important downstream analysis following differential expression from RNA sequencing (RNA-Seq) or DNA methylation analysis is the gene set testing to relate significant genes or CpGs to known biological properties. However, the traditional gene set testing approaches result in biased P-values due to the difference in gene length. Existing methods accounting for length bias were primarily developed for RNA-Seq data. For DNA methylation data profiled using the Illumina arrays, separate methods adjusting for the number of CpGs instead of gene length are necessary.

RESULTS

We developed methylGSA, a Bioconductor package for gene set testing in DNA methylation data. Our accompanying Shiny app provides an interactive way of accessing functions and visualizing the results in methylGSA package.

AVAILABILITY AND IMPLEMENTATION

methylGSA is available at Bioconductor repository: https://bioconductor.org/packages/methylGSA and Shiny app is available at: http://www.ams.sunysb.edu/%7epfkuan/softwares.html#methylGSA.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Locus-Specific Differential DNA Methylation and Urinary Arsenic: An Epigenome-Wide Association Study in Blood among Adults with Low-to-Moderate Arsenic Exposure

BACKGROUND

Chronic exposure to arsenic (As), a human toxicant and carcinogen, remains a global public health problem. Health risks persist after As exposure has ended, suggesting epigenetic dysregulation as a mechanistic link between exposure and health outcomes.

OBJECTIVES

We investigated the association between total urinary As and locus-specific DNA methylation in the Strong Heart Study, a cohort of American Indian adults with low-to-moderate As exposure [total urinary As, mean  ( ± SD )  μ g / g creatinine: 11.7 (10.6)].

METHODS

DNA methylation was measured in 2,325 participants using the Illumina MethylationEPIC array. We implemented linear models to test differentially methylated positions (DMPs) and the DMRcate method to identify regions (DMRs) and conducted gene ontology enrichment analysis. Models were adjusted for estimated cell type proportions, age, sex, body mass index, smoking, education, estimated glomerular filtration rate, and study center. Arsenic was measured in urine as the sum of inorganic and methylated species.

RESULTS

In adjusted models, methylation at 20 CpGs was associated with urinary As after false discovery rate (FDR) correction (FDR <   0.05 ). After Bonferroni correction, 5 CpGs remained associated with total urinary As (p Bonferroni < 0.05 ), located in SLC7A11, ANKS3, LINGO3, CSNK1D, ADAMTSL4. We identified one DMR on chromosome 11 (chr11:2,322,050-2,323,247), annotated to C11orf2; TSPAN32 genes.

DISCUSSION

This is one of the first epigenome-wide association studies to investigate As exposure and locus-specific DNA methylation using the Illumina MethylationEPIC array and the largest epigenome-wide study of As exposure. The top DMP was located in SLC7A11A, a gene involved in cystine/glutamate transport and the biosynthesis of glutathione, an antioxidant that may protect against As-induced oxidative stress. Additional DMPs were located in genes associated with tumor development and glucose metabolism. Further research is needed, including research in more diverse populations, to investigate whether As-related DNA methylation signatures are associated with gene expression or may serve as biomarkers of disease development. https://doi.org/10.1289/EHP6263.

Genome-wide DNA methylation and gene expression patterns reflect genetic ancestry and environmental differences across the Indonesian archipelago

Indonesia is the world's fourth most populous country, host to striking levels of human diversity, regional patterns of admixture, and varying degrees of introgression from both Neanderthals and Denisovans. However, it has been largely excluded from the human genomics sequencing boom of the last decade. To serve as a benchmark dataset of molecular phenotypes across the region, we generated genome-wide CpG methylation and gene expression measurements in over 100 individuals from three locations that capture the major genomic and geographical axes of diversity across the Indonesian archipelago. Investigating between- and within-island differences, we find up to 10.55% of tested genes are differentially expressed between the islands of Sumba and New Guinea. Variation in gene expression is closely associated with DNA methylation, with expression levels of 9.80% of genes correlating with nearby promoter CpG methylation, and many of these genes being differentially expressed between islands. Genes identified in our differential expression and methylation analyses are enriched in pathways involved in immunity, highlighting Indonesia's tropical role as a source of infectious disease diversity and the strong selective pressures these diseases have exerted on humans. Finally, we identify robust within-island variation in DNA methylation and gene expression, likely driven by fine-scale environmental differences across sampling sites. Together, these results strongly suggest complex relationships between DNA methylation, transcription, archaic hominin introgression and immunity, all jointly shaped by the environment. This has implications for the application of genomic medicine, both in critically understudied Indonesia and globally, and will allow a better understanding of the interacting roles of genomic and environmental factors shaping molecular and complex phenotypes.

MethylNet: an automated and modular deep learning approach for DNA methylation analysis

BACKGROUND

DNA methylation (DNAm) is an epigenetic regulator of gene expression programs that can be altered by environmental exposures, aging, and in pathogenesis. Traditional analyses that associate DNAm alterations with phenotypes suffer from multiple hypothesis testing and multi-collinearity due to the high-dimensional, continuous, interacting and non-linear nature of the data. Deep learning analyses have shown much promise to study disease heterogeneity. DNAm deep learning approaches have not yet been formalized into user-friendly frameworks for execution, training, and interpreting models. Here, we describe MethylNet, a DNAm deep learning method that can construct embeddings, make predictions, generate new data, and uncover unknown heterogeneity with minimal user supervision.

RESULTS

The results of our experiments indicate that MethylNet can study cellular differences, grasp higher order information of cancer sub-types, estimate age and capture factors associated with smoking in concordance with known differences.

CONCLUSION

The ability of MethylNet to capture nonlinear interactions presents an opportunity for further study of unknown disease, cellular heterogeneity and aging processes.

Intraspecific and interspecific investigations of skeletal DNA methylation and femur morphology in primates

OBJECTIVES

Epigenetic mechanisms influence the development and maintenance of complex phenotypes and may also contribute to the evolution of species-specific phenotypes. With respect to skeletal traits, little is known about the gene regulation underlying these hard tissues or how tissue-specific patterns are associated with bone morphology or vary among species. To begin exploring these topics, this study evaluates one epigenetic mechanism, DNA methylation, in skeletal tissues from five nonhuman primate species which display anatomical and locomotor differences representative of their phylogenetic groups.

MATERIALS AND METHODS

First, we test whether intraspecific variation in skeletal DNA methylation is associated with intraspecific variation in femur morphology. Second, we identify interspecific differences in DNA methylation and assess whether these lineage-specific patterns may have contributed to species-specific morphologies. Specifically, we use the Illumina Infinium MethylationEPIC BeadChip to identify DNA methylation patterns in femur trabecular bone from baboons (n = 28), macaques (n = 10), vervets (n = 10), chimpanzees (n = 4), and marmosets (n = 6).

RESULTS

Significant differentially methylated positions (DMPs) were associated with a subset of morphological variants, but these likely have small biological effects and may be confounded by other variables associated with morphological variation. Conversely, several species-specific DMPs were identified, and these are found in genes enriched for functions associated with complex skeletal traits.

DISCUSSION

Overall, these findings reveal that while intraspecific epigenetic variation is not readily associated with skeletal morphology differences, some interspecific epigenetic differences in skeletal tissues exist and may contribute to evolutionarily distinct phenotypes. This work forms a foundation for future explorations of gene regulation and skeletal trait evolution in primates.

Epigenomic analysis of 5-hydroxymethylcytosine (5hmC) reveals novel DNA methylation markers for lung cancers

BACKGROUND

DNA methylation at the fifth position of cytosine (5mC) is a common epigenetic alteration affecting a range of cellular processes. In recent years, 5-hydroxymethylcytosine (5hmC), an oxidized form of 5mC, has risen broad interests as a potential biomarker for lung cancer diagnosis and survival.

METHODS

We analyzed the epigenome-wide 5hmC profiles of paired lung tumor and adjacent normal tissues, using the TET-Assisted Bisulfite (TAB) array - Infinium MethylationEPIC BeadChip (EPIC) approach. The differentially methylated CpG sites were identified, and the biological relevance of 5hmC was assessed by differential methylation regions (DMR) analysis and gene set analysis (GSA).

RESULTS

We observed global hypomethylation of 5hmC comparing tumor to normal tissues, and hypermethylated 5hmC were enriched in CpG islands and gene upstream. Comparison of 5hmC and 5modC (total methylation: 5mC + 5hmC) profiling showed low correlation, and only a small proportion of the significant 5hmC loci overlapped with the significant total methylation loci. GSA analysis suggested that 5hmC was mainly involved in biological processes such as cellular process, biological regulation, and metabolic process.

CONCLUSION

This is the first study to analyze the epigenome-wide 5hmC profiles among paired lung tumor and normal tissues. We observed global hypomethylation of 5hmC in lung cancers, and hypermethylated 5hmC enriched in CpG islands and gene upstream. We found that the genome-wide 5hmC levels do not correlate with the total methylation, and the GSA suggested different biological functions of 5hmC compared to 5modC. Overall, our results demonstrate the potential of 5hmC as a novel biomarker for lung cancer.