Comprehensive DNA Methylation Analysis of Human Neuroblastoma Cells Treated With Haloperidol and Risperidone

Accumulating evidence suggests that the epigenetic alterations induced by antipsychotics contribute to the therapeutic efficacy. However, global and site-specific epigenetic changes by antipsychotics and those shared by different classes of antipsychotics remain poorly understood. We conducted a comprehensive DNA methylation analysis of human neuroblastoma cells cultured with antipsychotics. The cells were cultured with low and high concentrations of haloperidol or risperidone for 8 days. DNA methylation assay was performed with the Illumina HumanMethylation450 BeadChip. We found that both haloperidol and risperidone tended to cause hypermethylation changes and showed similar DNA methylation changes closely related to neuronal functions. A total of 294 differentially methylated probes (DMPs), including 197 hypermethylated and 97 hypomethylated DMPs, were identified with both haloperidol and risperidone treatment. Gene ontology analysis of the hypermethylated probe-associated genes showed enrichment of genes related to the regulation of neurotransmitter receptor activity and lipoprotein lipase activity. Pathway analysis identified that among the DMP-associated genes, SHANK1 and SHANK2 were the major genes in the neuropsychiatric disorder-related pathways. Our data would be valuable for understanding the mechanisms of action of antipsychotics from an epigenetic viewpoint.

Longitudinal DNA methylation dynamics as a practical indicator in clinical epigenetics

Background One of the fundamental assumptions of DNA methylation in clinical epigenetics is that DNA methylation status can change over time with or without interplay with environmental and clinical conditions. However, little is known about how DNA methylation status changes over time under ordinary environmental and clinical conditions. In this study, we revisited the high frequency longitudinal DNA methylation data of two Japanese males (24 time-points within three months) and characterized the longitudinal dynamics. Results The results showed that the majority of CpGs on Illumina HumanMethylation450 BeadChip probe set were longitudinally stable over the time period of three months. Focusing on dynamic and stable CpGs extracted from datasets, dynamic CpGs were more likely to be reported as epigenome-wide association study (EWAS) markers of various traits, especially those of immune- and inflammatory-related traits; meanwhile, the stable CpGs were enriched in metabolism-related genes and were less likely to be EWAS markers, indicating that the stable CpGs are stable both in the short-term within individuals and under various environmental and clinical conditions. Conclusions This study indicates that CpGs with different stabilities are involved in different functions and traits, and thus, they are potential indicators that can be applied for clinical epigenetic studies to outline underlying mechanisms.

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.

Novel HumanMethylatyion450 Analyses Reveal DNA Methylation Predictors of Future Diabetes Onset in Women With Polycystic Ovarian Syndrome

Aims. Polycystic ovarian syndrome (PCOS) is a common endocrine disorder characterised by ovarian morphological, systemic biochemical, and menstrual changes. Women with PCOS are at significantly increased risk of raised fasting glucose, impaired glucose tolerance, and diabetes. Recognition of these complications and early intervention are key to good health outcomes. We sought to identify DNA methylation patterns that may predict future diabetes onset in this high-risk PCOS population. Patients and Methods. Peripheral blood samples from women with PCOS and women with PCOS who later developed diabetes, were analysed by Illumina HumanMethylation450 BeadChip-arrays. Bisulphite-Pyrosequencing™ was used to validate and confirm array methylation data. Results. Array analyses identified 273 differentially methylated CpG loci (≥ 0.2 β-value change) at initial diagnosis of PCOS, between women who did or did not later develop diabetes. 19 of these sites demonstrated differential methylation in the same direction in ≥ five sample pairs. Methylation in three of the candidates (cg11897887, cg02819655, and cg25542007) showed the best concordance with corresponding array β-values, and, most clearly differentiated ‘cases’ from ‘controls’. Conclusions. We have identified novel methylation biomarkers that could predict future onset of diabetes in this high-risk population. Use of methylation analyses to identify women who are likely to develop diabetes at diagnosis of PCOS may facilitate timely lifestyle interventions to reduce future morbidity.

Epigenome-Wide Association Study of Thyroid Function Traits Identifies Novel Associations of fT3 With KLF9 and DOT1L

Context Circulating concentrations of free triiodothyronine (fT3), free thyroxine (fT4), and thyrotropin (TSH) are partly heritable traits. Recent studies have advanced knowledge of their genetic architecture. Epigenetic modifications, such as DNA methylation (DNAm), may be important in pituitary-thyroid axis regulation and action, but data are limited. Objective To identify novel associations between fT3, fT4, and TSH and differentially methylated positions (DMPs) in the genome in subjects from 2 Australian cohorts. Method We performed an epigenome-wide association study (EWAS) of thyroid function parameters and DNAm using participants from: Brisbane Systems Genetics Study (median age 14.2 years, n = 563) and the Raine Study (median age 17.0 years, n = 863). Plasma fT3, fT4, and TSH were measured by immunoassay. DNAm levels in blood were assessed using Illumina HumanMethylation450 BeadChip arrays. Analyses employed generalized linear mixed models to test association between DNAm and thyroid function parameters. Data from the 2 cohorts were meta-analyzed. Results We identified 2 DMPs with epigenome-wide significant (P &lt; 2.4E−7) associations with TSH and 6 with fT3, including cg00049440 in KLF9 (P = 2.88E−10) and cg04173586 in DOT1L (P = 2.09E−16), both genes known to be induced by fT3. All DMPs had a positive association between DNAm and TSH and a negative association between DNAm and fT3. There were no DMPs significantly associated with fT4. We identified 23 differentially methylated regions associated with fT3, fT4, or TSH. Conclusions This study has demonstrated associations between blood-based DNAm and both fT3 and TSH. This may provide insight into mechanisms underlying thyroid hormone action and/or pituitary-thyroid axis function.

Blood-based epigenetic estimators of chronological age in human adults using DNA methylation data from the Illumina MethylationEPIC array

Background Epigenetic clocks have been recognized for their precise prediction of chronological age, age-related diseases, and all-cause mortality. Existing epigenetic clocks are based on CpGs from the Illumina HumanMethylation450 BeadChip (450 K) which has now been replaced by the latest platform, Illumina MethylationEPIC BeadChip (EPIC). Thus, it remains unclear to what extent EPIC contributes to increased precision and accuracy in the prediction of chronological age. Results We developed three blood-based epigenetic clocks for human adults using EPIC-based DNA methylation (DNAm) data from the Norwegian Mother, Father and Child Cohort Study (MoBa) and the Gene Expression Omnibus (GEO) public repository: 1) an Adult Blood-based EPIC Clock (ABEC) trained on DNAm data from MoBa (n = 1592, age-span: 19 to 59 years), 2) an extended ABEC (eABEC) trained on DNAm data from MoBa and GEO (n = 2227, age-span: 18 to 88 years), and 3) a common ABEC (cABEC) trained on the same training set as eABEC but restricted to CpGs common to 450 K and EPIC. Our clocks showed high precision (Pearson correlation between chronological and epigenetic age (r) > 0.94) in independent cohorts, including GSE111165 (n = 15), GSE115278 (n = 108), GSE132203 (n = 795), and the Epigenetics in Pregnancy (EPIPREG) study of the STORK Groruddalen Cohort (n = 470). This high precision is unlikely due to the use of EPIC, but rather due to the large sample size of the training set. Conclusions Our ABECs predicted adults’ chronological age precisely in independent cohorts. As EPIC is now the dominant platform for measuring DNAm, these clocks will be useful in further predictions of chronological age, age-related diseases, and mortality.

Association between DNA Methylation Levels in Brain Tissue and Late-Life Depression in Community-Based Participants

ObjectiveMajor depressive disorder (MDD) arises from a combination of genetic and environmental risk factors and DNA methylation is one of the molecular mechanisms through which these factors can manifest. However, little is known about the epigenetic signature of MDD in brain tissue. This study aimed to investigate associations between brain tissue-based DNA methylation and late-life MDD.MethodsWe performed a brain epigenome-wide association study (EWAS) of late-life MDD in 608 participants from the Religious Order Study and the Rush Memory and Aging Project (ROS/MAP) using DNA methylation profiles of the dorsal lateral prefrontal cortex (dPFC) generated using the Illumina HumanMethylation450 Beadchip array. We also conducted an EWAS of MDD in each sex separately.ResultsWe found epigenome-wide significant associations between brain-tissue-based DNA methylation and late-life MDD. The most significant and robust association was found with altered methylation levels in the YOD1 locus (cg25594636, p-value=2.55 × 10−11; cg03899372, p-value=3.12 × 10−09; cg12796440, p-value=1.51 × 10−08, cg23982678, p-value=7.94 × 10−08). Analysis of differentially methylated regions (DMR, p-value=5.06 × 10−10) further confirmed this locus. Other significant loci include UGT8 (cg18921206, p-value=1.75 × 10−08), FNDC3B (cg20367479, p-value=4.97 × 10−08) and SLIT2 (cg10946669, p-value=8.01 × 10−08). Notably, brain-tissue based methylation levels were strongly associated with late-life MDD in men more than in women.ConclusionsWe identified altered methylation in the YOD1, UGT8, FNDC3B and SLIT2 loci as new epigenetic factors associated with late-life MDD. Furthermore, our study highlights the sex-specific molecular heterogeneity of MDD.

Jllumina - A comprehensive Java-based API for statistical Illumina Infinium HumanMethylation450 and Infinium MethylationEPIC BeadChip data processing

Summary Measuring differential methylation of the DNA is the nowadays most common approach to linking epigenetic modifications to diseases (called epigenome-wide association studies, EWAS). For its low cost, its efficiency and easy handling, the Illumina HumanMethylation450 BeadChip and its successor, the Infinium MethylationEPIC BeadChip, is the by far most popular techniques for conduction EWAS in large patient cohorts. Despite the popularity of this chip technology, raw data processing and statistical analysis of the array data remains far from trivial and still lacks dedicated software libraries enabling high quality and statistically sound downstream analyses. As of yet, only R-based solutions are freely available for low-level processing of the Illumina chip data. However, the lack of alternative libraries poses a hurdle for the development of new bioinformatic tools, in particular when it comes to web services or applications where run time and memory consumption matter, or EWAS data analysis is an integrative part of a bigger framework or data analysis pipeline. We have therefore developed and implemented Jllumina, an open-source Java library for raw data manipulation of Illumina Infinium HumanMethylation450 and Infinium MethylationEPIC BeadChip data, supporting the developer with Java functions covering reading and preprocessing the raw data, down to statistical assessment, permutation tests, and identification of differentially methylated loci. Jllumina is fully parallelizable and publicly available at http://dimmer.compbio.sdu.dk/download.html