Positional effects revealed in Illumina methylation array and the impact on analysis

Parkinson's disease-associated shifts between DNA methylation and DNA hydroxymethylation in human brain in PD-related genes, including PARK19 (DNAJC6) and PTPRN2 (IA-2β)

Background

The majority of Parkinson's disease (PD) cases are due to a complex interaction between aging, genetics, and environmental factors; epigenetic mechanisms are thought to act as important mediators of these risk factors. While multiple studies to date have explored the role of DNA modifications in PD, few focus on 5-hydroxymethylcytosine (5hmC). Because 5hmC occurs at its highest levels in the brain and is thought to be particularly important in the central nervous system, particularly in the response to neurotoxicants, it is important to explore the potential role of 5hmC in PD. This study expands on our previously published epigenome-wide association study (EWAS) performed on DNA isolated from neuron-enriched nuclei from human postmortem parietal cortex from the Banner Sun Health Research Institute Brain Bank. The study aimed to identify paired changes in 5hmC and 5mC in PD in enriched neuronal nuclei isolated from PD post-mortem parietal cortex and age- and sex-matched controls. We performed oxidative bisulfite (oxBS) conversion and paired it with our previously published bisulfite (BS)-based EWAS on the same samples to identify cytosines with significant shifts between these two related epigenetic marks. Interaction differentially modified cytosines (iDMCs) were identified using our recently published mixed-effects model for co-analyzing βmC and βhmC data.

Results

We identified 1,030 iDMCs with paired changes in 5mC and 5hmC (FDR < 0.05) that map to 695 genes, including PARK19 (DNAJC6), a familial PD gene, and PTPRN2 (IA-2), which has been previously implicated in PD in both epigenetic and mechanistic studies. The majority of iDMC-containing genes have not previously been implicated in PD and were not identified in our previous BS-based EWAS.

Conclusions

These data potentially link epigenetic regulation of the PARK19 and PTPRN2 loci in the pathogenesis of idiopathic PD. In addition, iDMC-containing genes have known functions in synaptic formation and function, cell cycle and senescence, neuroinflammation, and epigenetic regulation. These data suggest that there are significant shifts between 5mC and 5hmC associated with PD in genes relevant to PD pathogenesis that are not captured by analyzing BS-based data alone or by analyzing each mark as a distinct dataset.

Differential Impact of Smoking on Methylome and Transcriptome in Crohn's Disease and Ulcerative Colitis

BACKGROUND

Smoking is an environmental factor that differentially impacts Crohn's disease (CD) and ulcerative colitis (UC). The mechanism of impact of smoking on disease risk and clinical outcomes remains to be established.

METHODS

This study used a prospective cohort of patients with CD or UC. Self-reported smoking status was validated using serum cotinine measurement. We profiled methylation changes in peripheral blood using the Illumina Methylation BeadChip. Transcriptomic profiling was performed on ileal and colonic tissue using an Illumina TruSeq platform. We compared the methylation and transcriptional changes in current, former, and never smokers stratified by disease type.

RESULTS

Our cohort included 200 patients with CD or UC with methylation profiles and 160 with transcriptomic data. The mean serum cotinine level was higher in current compared with former or never smokers. Epigenetic changes common to both CD and UC included hypomethylation at AHRR. Smoking-associated MGAT3 hypomethylation was associated with severe disease course only in UC, while IER3 hypomethylation was associated with worse course only in CD. Smoking downregulated several inflammatory pathways in UC. Current smoking in CD but not in UC was associated with upregulation of several genes mediating Paneth cell function. Genes with opposite direction of effects in CD and UC include HSD3B2 and GSTA1.

CONCLUSIONS

Our findings suggest both common and differential effects of cigarette smoking on CD and UC. Paneth cell dysfunction may mediate adverse impact of smoking on CD. Bile acid and oxidative stress pathways may be relevant for the differential effect of smoking on CD and UC.

Serotonin Transporter (SLC6A4) and FK506-Binding Protein 5 (FKBP5) Genotype and Methylation Relationships with Response to Meditation in Veterans with PTSD

Meditation-based interventions are novel and effective non-pharmacologic treatments for veterans with PTSD. We examined relationships between treatment response, early life trauma exposure, DNA polymorphisms, and methylation in the serotonin transporter (SLC6A4) and FK506-binding protein 5 (FKBP5) genes. DNA samples and clinical outcomes were examined in 72 veterans with PTSD who received meditation-based therapy in two separate studies of mindfulness-based stress reduction (MBSR) and Transcendental Meditation (TM). The PTSD Checklist was administered to assess symptoms at baseline and after 9 weeks of meditation intervention. We examined the SLC6A4 promoter (5HTTLPR_L/S insertion/deletion + rs25531_A/G) polymorphisms according to previously defined gene expression groups, and the FKBP5 variant rs1360780 previously associated with PTSD disease risk. Methylation for CpG sites of SLC6A4 (28 sites) and FKBP5 (45 sites) genes was quantified in DNA samples collected before and after treatment. The 5HTTLPR LALA high expression genotype was associated with greater symptom improvement in participants exposed to early life trauma (p = 0.015). Separately, pre to post-treatment change of DNA methylation in a group of nine FKBP5 CpG sites was associated with greater symptom improvement (OR = 2.8, 95% CI 1.1-7.1, p = 0.027). These findings build on a wealth of existing knowledge regarding epigenetic and genetic relationships with PTSD disease risk to highlight the potential importance of SLC6A4 and FKBP5 for treatment mechanisms and as biomarkers of symptom improvement.

A higher dysregulation burden of brain DNA methylation in female patients implicated in the sex bias of Schizophrenia

Sex differences are pervasive in schizophrenia (SCZ), but the extent and magnitude of DNA methylation (DNAm) changes underlying these differences remain uncharacterized. In this study, sex-stratified differential DNAm analysis was performed in postmortem brain samples from 117 SCZ and 137 controls, partitioned into discovery and replication datasets. Three differentially methylated positions (DMPs) were identified (adj.p < 0.05) in females and 29 DMPs in males without overlap between them. Over 81% of these sex-stratified DMPs were directionally consistent between sexes but with different effect sizes. Females experienced larger magnitude of DNAm changes and more DMPs (based on data of equal sample size) than males, contributing to a higher dysregulation burden of DNAm in females SCZ. Additionally, despite similar proportions of female-related DMPs (fDMPs, 8%) being under genetic control compared with males (10%), significant enrichment of DMP-related single nucleotide polymorphisms (SNPs) in signals of genome-wide association studies was identified only in fDMPs. One DMP in each sex connected the SNPs and gene expression of CALHM1 in females and CCDC149 in males. PPI subnetworks revealed that both female- and male-related differential DNAm interacted with synapse-related dysregulation. Immune-related pathways were unique for females and neuron-related pathways were associated with males. This study reveals remarkable quantitative differences in DNAm-related sexual dimorphism in SCZ and that females have a higher dysregulation burden of SCZ-associated DNAm than males.

Expression quantitative trait methylation analysis elucidates gene regulatory effects of DNA methylation: the Framingham Heart Study

Expression quantitative trait methylation (eQTM) analysis identifies DNA CpG sites at which methylation is associated with gene expression. The present study describes an eQTM resource of CpG-transcript pairs derived from whole blood DNA methylation and RNA sequencing gene expression data in 2115 Framingham Heart Study participants. We identified 70,047 significant cis CpG-transcript pairs at p < 1E-7 where the top most significant eGenes (i.e., gene transcripts associated with a CpG) were enriched in biological pathways related to cell signaling, and for 1208 clinical traits (enrichment false discovery rate [FDR] ≤ 0.05). We also identified 246,667 significant trans CpG-transcript pairs at p < 1E-14 where the top most significant eGenes were enriched in biological pathways related to activation of the immune response, and for 1191 clinical traits (enrichment FDR ≤ 0.05). Independent and external replication of the top 1000 significant cis and trans CpG-transcript pairs was completed in the Women's Health Initiative and Jackson Heart Study cohorts. Using significant cis CpG-transcript pairs, we identified significant mediation of the association between CpG sites and cardiometabolic traits through gene expression and identified shared genetic regulation between CpGs and transcripts associated with cardiometabolic traits. In conclusion, we developed a robust and powerful resource of whole blood eQTM CpG-transcript pairs that can help inform future functional studies that seek to understand the molecular basis of disease.

Propensity scores as a novel method to guide sample allocation and minimize batch effects during the design of high throughput experiments

BACKGROUND

We developed a novel approach to minimize batch effects when assigning samples to batches. Our algorithm selects a batch allocation, among all possible ways of assigning samples to batches, that minimizes differences in average propensity score between batches. This strategy was compared to randomization and stratified randomization in a case-control study (30 per group) with a covariate (case vs control, represented as β1, set to be null) and two biologically relevant confounding variables (age, represented as β2, and hemoglobin A1c (HbA1c), represented as β3). Gene expression values were obtained from a publicly available dataset of expression data obtained from pancreas islet cells. Batch effects were simulated as twice the median biological variation across the gene expression dataset and were added to the publicly available dataset to simulate a batch effect condition. Bias was calculated as the absolute difference between observed betas under the batch allocation strategies and the true beta (no batch effects). Bias was also evaluated after adjustment for batch effects using ComBat as well as a linear regression model. In order to understand performance of our optimal allocation strategy under the alternative hypothesis, we also evaluated bias at a single gene associated with both age and HbA1c levels in the 'true' dataset (CAPN13 gene).

RESULTS

Pre-batch correction, under the null hypothesis (β1), maximum absolute bias and root mean square (RMS) of maximum absolute bias, were minimized using the optimal allocation strategy. Under the alternative hypothesis (β2 and β3 for the CAPN13 gene), maximum absolute bias and RMS of maximum absolute bias were also consistently lower using the optimal allocation strategy. ComBat and the regression batch adjustment methods performed well as the bias estimates moved towards the true values in all conditions under both the null and alternative hypotheses. Although the differences between methods were less pronounced following batch correction, estimates of bias (average and RMS) were consistently lower using the optimal allocation strategy under both the null and alternative hypotheses.

CONCLUSIONS

Our algorithm provides an extremely flexible and effective method for assigning samples to batches by exploiting knowledge of covariates prior to sample allocation.

A Higher Dysregulation Burden of Brain DNA Methylation in Female Patients Implicated in the Sex Bias of Schizophrenia

Sex differences are pervasive in schizophrenia (SCZ), but the extent and magnitude of DNA methylation (DNAm) changes underlying these differences remain uncharacterized. In this study, sex-stratified differential DNAm analysis was performed in postmortem brain samples from 117 SCZ and 137 controls, partitioned into discovery and replication datasets. Three differentially methylated positions (DMPs) were identified (adj. p  < 0.05) in females and 29 DMPs in males without overlap between them. Over 81% of these sex-stratified DMPs were directionally consistent between sexes but with different effect sizes. Down-sampling analysis revealed more DMPs in females than in males when the sample sizes matched. Females had higher DNAm levels in healthy individuals and larger magnitude of DNAm changes in patients than males. Despite similar proportions of female-related DMPs (fDMPs, 8%) being under genetic control compared with males (10%), significant enrichment of DMP-related SNPs in signals of genome-wide association studies was identified only in fDMPs. One DMP in each sex connected the SNPs and gene expression of CALHM1 in females and CCDC149 in males. PPI subnetworks revealed that both female- and male-related differential DNAm interacted with synapse-related dysregulation. Immune-related pathways were unique for females and neuron-related pathways were associated with males. This study reveals remarkable quantitative differences in DNAm-related sexual dimorphism in SCZ and that females have a higher dysregulation burden of SCZ-associated DNAm than males.

Epigenetic mechanisms underlying the association between maternal climate stress and child growth: characterizing severe drought and its impact on a Kenyan community engaging in a climate change-sensitive livelihood

Pastoralists in East Africa are among the world's most vulnerable communities to climate change, already living near their upper thermal limits and engaging in a climate-sensitive livelihood in a climate change global hot spot. Pregnant women and children are even more at risk. Here, we report the findings of a study characterizing Samburu pastoralist women's experiences of severe drought and outcomes in their children (N = 213, 1.8-9.6 y). First, we examined potential DNA methylation (DNAm) differences between children exposed to severe drought in utero and same-sex unexposed siblings. Next, we performed a high-dimensional mediation analysis to test whether DNAm mediated associations of exposure to severe drought with body weight and adiposity. DNAm was measured using the Infinium MethylationEPIC BeadChip array. After quality control; batch, chip, and genomic inflation corrections; covariate adjustment; and multiple testing correction, 16 CpG sites were differentially methylated between exposed and unexposed children, predominantly in metabolism and immune function pathways. We found a significant indirect effect of drought exposure on child body weight through cg03771070. Our results are the first to identify biological mediators linking severe drought to child growth in a low-income global hot spot for climate change. A better understanding of the mechanisms underlying the association between drought exposure and child growth is important to increasing climate change resilience by identifying targets for intervention.

Risperidone-induced changes in DNA methylation in peripheral blood from first-episode schizophrenia patients parallel changes in neuroimaging and cognitive phenotypes

BACKGROUND

Second generation antipsychotics such as risperidone are first-line pharmacotherapy treatment choices for schizophrenia. However, our ability to reliably predict and monitor treatment reaction is impeded by the lack of relevant biomarkers. As a biomarker for the susceptibility of schizophrenia and clozapine treatment response, DNA methylation (DNAm) has been studied, but the impact of antipsychotics on DNAm has not been explored in drug-naïve patients.

OBJECTIVE

The aim of the present study was to examine changes of DNAm after short-term antipsychotic therapy in first-episode drug-naïve schizophrenia (FES) to identify the beneficial and adverse effect of risperidone on DNAm and their relation to treatment outcome.

METHODS

Thirty-eight never treated schizophrenia patients and 38 demographically matched individuals (healthy controls) were assessed at baseline and at 8-week follow-up with symptom ratings, and cognitive and functional imaging procedures, at which time a blood draw for DNAm studies was performed. During the 8-week period, patients received treatment with risperidone monotherapy. An independent data set was used as replication.

RESULTS

We identified brain related pathways enriched in 4,888 FES-associated CpG sites relative to controls. Risperidone administration in patients altered DNAm in 5,979 CpG sites relative to baseline. Significant group differences in DNAm at follow-up were seen in FES patients at 6,760 CpG sites versus healthy controls. Through comparison of effect size, we found 87.54% out of the risperidone-associated changes in DNAm showed possible beneficial effect, while only 12.46% showed potential adverse effect. There were 580 DNAm sites in which changes shifted methylation levels to be indistinguishable from controls after risperidone treatment. The DNAm changes of some sites that normalized after treatment were correlated with treatment-related changes in symptom severity, spontaneous neurophysiological activity, and cognition. We replicated our results in an independent data set.

CONCLUSION

The normalizing effect of risperidone monotherapy on gene DNAm, and its correlation with clinically relevant phenotypes, indicates that risperidone therapy is associated with DNAm changes that are related to changes in brain physiology, cognition and symptom severity.

Longitudinal change in blood DNA epigenetic signature after smoking cessation

Cigarette smoking is associated with epigenetic changes that may be reversible following smoking cessation. Whole blood DNA methylation was evaluated in Framingham Heart Study Offspring (n = 169) and Third Generation (n = 30) cohort participants at two study visits 6 years apart and in Atherosclerosis Risk in Communities (ARIC) study (n = 222) participants at two study visits 20 years apart. Changes in DNA methylation (delta β values) at 483,565 cytosine-phosphate-guanine (CpG) sites and differentially methylated regions (DMRs) were compared between participants who were current, former, or never smokers at both visits (current-current, former-former, never-never, respectively), versus those who quit in the interim (current-former). Interim quitters had more hypermethylation at four CpGs annotated to AHRR, one CpG annotated to F2RL3, and one intergenic CpG (cg21566642) compared with current-current smokers (FDR < 0.02 for all), and two significant DMRs were identified. While there were no significant differentially methylated CpGs in the comparison of interim quitters and former-former smokers, 106 DMRs overlapping with small nucleolar RNA were identified. As compared with all non-smokers, current-current smokers additionally had more hypermethylation at two CpG sites annotated to HIVEP3 and TMEM126A, respectively, and another intergenic CpG (cg14339116). Gene transcripts associated with smoking cessation were implicated in immune responses, cell homoeostasis, and apoptosis. Smoking cessation is associated with early reversion of blood DNA methylation changes at CpG sites annotated to AHRR and F2RL3 towards those of never smokers. Associated gene expression suggests a role of longitudinal smoking-related DNA methylation changes in immune response processes.

Parkinson's disease-associated, sex-specific changes in DNA methylation at PARK7 (DJ-1), SLC17A6 (VGLUT2), PTPRN2 (IA-2β), and NR4A2 (NURR1) in cortical neurons

Evidence for epigenetic regulation playing a role in Parkinson's disease (PD) is growing, particularly for DNA methylation. Approximately 90% of PD cases are due to a complex interaction between age, genes, and environmental factors, and epigenetic marks are thought to mediate the relationship between aging, genetics, the environment, and disease risk. To date, there are a small number of published genome-wide studies of DNA methylation in PD, but none accounted for cell type or sex in their analyses. Given the heterogeneity of bulk brain tissue samples and known sex differences in PD risk, progression, and severity, these are critical variables to account for. In this genome-wide analysis of DNA methylation in an enriched neuronal population from PD postmortem parietal cortex, we report sex-specific PD-associated methylation changes in PARK7 (DJ-1), SLC17A6 (VGLUT2), PTPRN2 (IA-2β), NR4A2 (NURR1), and other genes involved in developmental pathways, neurotransmitter packaging and release, and axon and neuron projection guidance.

Controlling Batch Effect in Epigenome-Wide Association Study

Methylation data, similar to other omics data, is susceptible to various technical issues that are potentially associated with unexplained or unrelated factors. Any difference in the measurement of DNA methylation, such as laboratory operation and sequencing platform, may lead to batch effects. With the accumulation of large-scale omics data, scientists are making joint efforts to generate and analyze omics data to answer various scientific questions. However, batch effects are inevitable in practice, and careful adjustment is needed. Multiple statistical methods for controlling bias and inflation between batches have been developed either by correcting based on known batch factors or by estimating directly from the output data. In this chapter, we will review and demonstrate several popular methods for batch effect correction and make practical recommendations in epigenome-wide association studies (EWAS).

Evaluating the challenges and reproducibility of studies investigating DNA methylation signatures of psychological stress

Psychological stress can increase the risk of a wide range of negative health outcomes. Studies have been completed to determine if DNA methylation changes occur in the human brain because of stress and are associated with long-term effects and disease, but results have been inconsistent. Human candidate gene studies (150) and epigenome-wide association studies (67) were systematically evaluated to assess how DNA methylation is impacted by stress during the prenatal period, early childhood and adulthood. The association between DNA methylation of NR3C1 exon 1F and child maltreatment and early life adversity was well demonstrated, but other genes did not exhibit a clear association. The reproducibility of individual CpG sites in epigenome-wide association studies was also poor. However, biological pathways, including stress response, brain development and immunity, have been consistently identified across different stressors throughout the life span. Future studies would benefit from the increased sample size, longitudinal design, standardized methodology, optimal quality control, and improved statistical procedures.

ImmuMethy, a database of DNA methylation plasticity at a single cytosine resolution in human blood and immune cells

Differential DNA methylation is a feature of numerous physiological and pathological processes. However, the extent to which single-base cytosine methylation modifies cellular responses to various stimuli has not been well characterized. In this study, we carried out a systematic analysis of methylome data derived from human blood and immune cells and constructed the ImmuMethy database. ImmuMethy allows interrogation of DNA methylation plasticity (MPL) at the single cytosine level. MPL, which refers to the variability of DNA methylation, is quantitatively measured in multiple ways, such as quartiles and standard deviations. ImmuMethy comprises over 36 000 samples from the Human Methylation450 and MethylationEPIC BeadChips platforms and provides multiple applications, such as an overview of methylation status and plasticity, differential methylation analysis, identification of methylation markers and sample stratification. An analysis of all datasets revealed that DNA methylation is generally stable, with minimal changes in beta values. This further supports the characteristics of DNA methylation homeostasis. Based on the beta value distribution, we identified three types of methylation sites: methylation tendency sites, unmethylation tendency sites and dual tendency or nonbiased methylation sites. These sites represent different methylation tendentiousness of DNA methylation across samples. The occurrence of multiple methylation tendencies in a site means split methylation, which generally corresponds to high MPL. Inverted methylation tendencies from methylation tendency sites to unmethylation tendency sites, or vice versa, represent strong differential methylation in response to conditions. All these sites can be identified in ImmuMethy, making it a useful tool for omics-based data-driven knowledge discovery.

Database URL: http://immudb.bjmu.edu.cn/immumethy/

Reproducibility of the Infinium methylationEPIC BeadChip assay using low DNA amounts

The Infinium MethylationEPIC BeadChip (EPIC) is a reliable method for measuring the DNA methylation of more than 850,000 CpG positions. In clinical and forensic settings, it is critical to be able to work with low DNA amounts without risking reduced reproducibility. We evaluated the EPIC for a range of DNA amounts using two-fold serial dilutions investigated on two different days. While the β-value distributions were generally unaffected by decreasing DNA amounts, the median squared Pearson’s correlation coefficient (R²) of between-days β-value comparisons decreased from 0.994 (500 ng DNA) to 0.957 (16 ng DNA). The median standard deviation of the β-values was 0.005 and up to 0.017 (median of medians: 0.014) for β-values around 0.6–0.7. With decreasing amounts of DNA from 500 ng to 16 ng, the percentage of probes with standard deviations ≤ 0.1 decreased from 99.9% to 99.4%. This study showed that high reproducibility results are obtained with DNA amounts in the range 125–500 ng DNA, while DNA amounts equal to 63 ng or below gave less reproducible results.

Prenatal stress leads to deficits in brain development, mood related behaviors and gut microbiota in offspring

Early exposure to stressful and adverse life events at fetal and neonatal stages is one of crucial risk factors for mood disorders such as anxiety and depressive disorder in adulthood. Intergenerational effects of prenatal stress on offspring are still not fully understood. We here uncover a significant negative impact of prenatal stress on brain development in embryos and newborns, and on mood-related behaviors and gut microbiota in adult offspring. Prenatal stress leads to reduced numbers in neural progenitors and newborn neurons, and altered gene expression profiles in the mouse embryonic cerebral cortex. Adult mouse offspring exposed to prenatal stress displays altered gene expression in the cortex and elevated responses in anxiety- and depression-like behaviors. Interestingly, prenatal stress has an enduring effect on gut microbiota, as specific microbial community structure is altered in adult F1 offspring treated with prenatal stress, compared to that of the control. Our results highlight the essential impact of prenatal stress on cortical neurogenesis, gene expression patterns, mood-related behaviors, and even gut microbiota in the next generation.

Reduction in Epigenetic Age Acceleration Is Related to Empathy in Mothers with Neglectful Caregiving

DNA methylation clocks are used as molecular estimators of epigenetic age, but with little evidence in mothers and none in neglectful mothering. We investigated differences in epigenetic age acceleration (EAA) and the role of empathy using the PhenoAge clock. We collected saliva samples from mothers with extreme disregard for their child's needs (50 in the neglect group, NG) and mothers with non-neglectful caregiving (87 in the control group, CG). Mothers completed an empathy scale, along with questionnaires of their own childhood maltreatment, adverse life events and psychiatric disorders. Sociodemographic variables potentially affecting EAA were also measured. The ANCOVA solution showed a significant increase in EAA in the NG compared to the CG, after adjustment for maternal age, number of pregnancies, financial assistance, adverse events, childhood maltreatment and psychiatric disorder. The group interaction effects showed a reduction in EAA for greater empathic concern and for a higher education level both as positive factors, and an increment in EAA for mothers living in a two-parent family as a risk factor, all in the NG. Our findings open the search for protective factors of EAA associated with caregiver behavior to reduce health vulnerabilities and poor social functioning, especially for mothers at risk of maladaptive caregiving.

SLC25A24 gene methylation and gray matter volume in females with and without conduct disorder: an exploratory epigenetic neuroimaging study

Conduct disorder (CD), a psychiatric disorder characterized by a repetitive pattern of antisocial behaviors, results from a complex interplay between genetic and environmental factors. The clinical presentation of CD varies both according to the individual's sex and level of callous-unemotional (CU) traits, but it remains unclear how genetic and environmental factors interact at the molecular level to produce these differences. Emerging evidence in males implicates methylation of genes associated with socio-affective processes. Here, we combined an epigenome-wide association study with structural neuroimaging in 51 females with CD and 59 typically developing (TD) females to examine DNA methylation in relation to CD, CU traits, and gray matter volume (GMV). We demonstrate an inverse pattern of correlation between CU traits and methylation of a chromosome 1 region in CD females (positive) as compared to TD females (negative). The identified region spans exon 1 of the SLC25A24 gene, central to energy metabolism due to its role in mitochondrial function. Increased SLC25A24 methylation was also related to lower GMV in multiple brain regions in the overall cohort. These included the superior frontal gyrus, prefrontal cortex, and supramarginal gyrus, secondary visual cortex and ventral posterior cingulate cortex, which are regions that have previously been implicated in CD and CU traits. While our findings are preliminary and need to be replicated in larger samples, they provide novel evidence that CU traits in females are associated with methylation levels in a fundamentally different way in CD and TD, which in turn may relate to observable variations in GMV across the brain.

An effective processing pipeline for harmonizing DNA methylation data from Illumina's 450K and EPIC platforms for epidemiological studies

OBJECTIVE

Illumina BeadChip arrays are commonly used to generate DNA methylation data for large epidemiological studies. Updates in technology over time create challenges for data harmonization within and between studies, many of which obtained data from the older 450K and newer EPIC platforms. The pre-processing pipeline for DNA methylation is not trivial, and influences the downstream analyses. Incorporating different platforms adds a new level of technical variability that has not yet been taken into account by recommended pipelines. Our study evaluated the performance of various tools on different versions of platform data harmonization at each step of pre-processing pipeline, including quality control (QC), normalization, batch effect adjustment, and genomic inflation. We illustrate our novel approach using 450K and EPIC data from the Diabetes Autoimmunity Study in the Young (DAISY) prospective cohort.

RESULTS

We found normalization and probe filtering had the biggest effect on data harmonization. Employing a meta-analysis was an effective and easily executable method for accounting for platform variability. Correcting for genomic inflation also helped with harmonization. We present guidelines for studies seeking to harmonize data from the 450K and EPIC platforms, which includes the use of technical replicates for evaluating numerous pre-processing steps, and employing a meta-analysis.

DNA methylation signature on phosphatidylethanol, not on self-reported alcohol consumption, predicts hazardous alcohol consumption in two distinct populations

The process of diagnosing hazardous alcohol drinking (HAD) is based on self-reported data and is thereby vulnerable to bias. There has been an interest in developing epigenetic biomarkers for HAD that might complement clinical assessment. Because alcohol consumption has been previously linked to DNA methylation (DNAm), we aimed to select DNAm signatures in blood to predict HAD from two demographically and clinically distinct populations (Ntotal = 1,549). We first separately conducted an epigenome-wide association study (EWAS) for phosphatidylethanol (PEth), an objective measure of alcohol consumption, and for self-reported alcohol consumption in Cohort 1. We identified 83 PEth-associated CpGs, including 23 CpGs previously associated with alcohol consumption or alcohol use disorder. In contrast, no CpG reached epigenome-wide significance on self-reported alcohol consumption. Using a machine learning approach, two CpG subsets from EWAS on PEth and on self-reported alcohol consumption from Cohort 1 were separately tested for the prediction of HAD in Cohort 2. We found that a subset of 143 CpGs selected from the EWAS on PEth showed an excellent prediction of HAD with the area under the receiver operating characteristic curve (AUC) of 89.4% in training set and 73.9% in validation set of Cohort 2. However, CpGs preselected from the EWAS on self-reported alcohol consumption showed a poor prediction of HAD with AUC 75.2% in training set and 57.6% in validation set. Our results demonstrate that an objective measure for alcohol consumption is a more informative phenotype than self-reported data for revealing epigenetic mechanisms. The PEth-associated DNAm signature in blood could serve as a robust biomarker for alcohol consumption.

Drug Response-Related DNA Methylation Changes in Schizophrenia, Bipolar Disorder, and Major Depressive Disorder

Pharmacotherapy is the most common treatment for schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD). Pharmacogenetic studies have achieved results with limited clinical utility. DNA methylation (DNAm), an epigenetic modification, has been proposed to be involved in both the pathology and drug treatment of these disorders. Emerging data indicates that DNAm could be used as a predictor of drug response for psychiatric disorders. In this study, we performed a systematic review to evaluate the reproducibility of published changes of drug response-related DNAm in SCZ, BD and MDD. A total of 37 publications were included. Since the studies involved patients of different treatment stages, we partitioned them into three groups based on their primary focuses: (1) medication-induced DNAm changes (n = 8); (2) the relationship between DNAm and clinical improvement (n = 24); and (3) comparison of DNAm status across different medications (n = 14). We found that only BDNF was consistent with the DNAm changes detected in four independent studies for MDD. It was positively correlated with clinical improvement in MDD. To develop better predictive DNAm factors for drug response, we also discussed future research strategies, including experimental, analytical procedures and statistical criteria. Our review shows promising possibilities for using BDNF DNAm as a predictor of antidepressant treatment response for MDD, while more pharmacoepigenetic studies are needed for treatments of various diseases. Future research should take advantage of a system-wide analysis with a strict and standard analytical procedure.

Genetic impacts on DNA methylation: research findings and future perspectives

Multiple recent studies highlight that genetic variants can have strong impacts on a significant proportion of the human DNA methylome. Methylation quantitative trait loci, or meQTLs, allow for the exploration of biological mechanisms that underlie complex human phenotypes, with potential insights for human disease onset and progression. In this review, we summarize recent milestones in characterizing the human genetic basis of DNA methylation variation over the last decade, including heritability findings and genome-wide identification of meQTLs. We also discuss challenges in this field and future areas of research geared to generate insights into molecular processes underlying human complex traits.

DNA methylation perturbations may link altered development and aging in the lung

Fetal perturbations in DNA methylation during lung development may reveal insights into the enduring impacts on adult lung health and disease during aging that have not been explored altogether before. We studied the association between genome-wide DNA-methylation and post-conception age in fetal-lung (n=78, 42 exposed to in-utero-smoke (IUS)) tissue and chronological age in adult-lung tissue (n=160, 114 with Chronic Obstructive Pulmonary Disease) using multi-variate linear regression models with covariate adjustment and tested for effect modification by phenotypes. Overlapping age-associations were evaluated for functional and tissue-specific enrichment using the Genotype-Tissue-Expression (GTEx) project. We identified 244 age-associated differentially methylated positions and 878 regions overlapping between fetal and adult-lung tissues. Hyper-methylated CpGs (96%) were enriched in transcription factor activity (FDR adjusted P=2x10-33) and implicated in developmental processes including embryonic organ morphogenesis, neurogenesis and growth delay. Hypo-methylated CpGs (2%) were enriched in oxido-reductase activity and VEGFA-VEGFR2 Signaling. Twenty-one age-by-sex and eleven age-by-pack-years interactions were statistically significant (FDR<0.05) in adult-lung tissue. DNA methylation in transcription factors during development in fetal lung recapitulates in adult-lung tissue with aging. These findings reveal molecular mechanisms and pathways that may link disrupted development in early-life and age-associated lung diseases.

INTEDE: interactome of drug-metabolizing enzymes

Drug-metabolizing enzymes (DMEs) are critical determinant of drug safety and efficacy, and the interactome of DMEs has attracted extensive attention. There are 3 major interaction types in an interactome: microbiome-DME interaction (MICBIO), xenobiotics-DME interaction (XEOTIC) and host protein-DME interaction (HOSPPI). The interaction data of each type are essential for drug metabolism, and the collective consideration of multiple types has implication for the future practice of precision medicine. However, no database was designed to systematically provide the data of all types of DME interactions. Here, a database of the Interactome of Drug-Metabolizing Enzymes (INTEDE) was therefore constructed to offer these interaction data. First, 1047 unique DMEs (448 host and 599 microbial) were confirmed, for the first time, using their metabolizing drugs. Second, for these newly confirmed DMEs, all types of their interactions (3359 MICBIOs between 225 microbial species and 185 DMEs; 47 778 XEOTICs between 4150 xenobiotics and 501 DMEs; 7849 HOSPPIs between 565 human proteins and 566 DMEs) were comprehensively collected and then provided, which enabled the crosstalk analysis among multiple types. Because of the huge amount of accumulated data, the INTEDE made it possible to generalize key features for revealing disease etiology and optimizing clinical treatment. INTEDE is freely accessible at: https://idrblab.org/intede/.

Sex-differential DNA methylation and associated regulation networks in human brain implicated in the sex-biased risks of psychiatric disorders

Many psychiatric disorders are characterized by a strong sex difference, but the mechanisms behind sex-bias are not fully understood. DNA methylation plays important roles in regulating gene expression, ultimately impacting sexually different characteristics of the human brain. Most previous literature focused on DNA methylation alone without considering the regulatory network and its contribution to sex-bias of psychiatric disorders. Since DNA methylation acts in a complex regulatory network to connect genetic and environmental factors with high-order brain functions, we investigated the regulatory networks associated with different DNA methylation and assessed their contribution to the risks of psychiatric disorders. We compiled data from 1408 postmortem brain samples in 3 collections to identify sex-differentially methylated positions (DMPs) and regions (DMRs). We identified and replicated thousands of DMPs and DMRs. The DMR genes were enriched in neuronal related pathways. We extended the regulatory networks related to sex-differential methylation and psychiatric disorders by integrating methylation quantitative trait loci (meQTLs), gene expression, and protein-protein interaction data. We observed significant enrichment of sex-associated genes in psychiatric disorder-associated gene sets. We prioritized 2080 genes that were sex-biased and associated with psychiatric disorders, such as NRXN1, NRXN2, NRXN3, FDE4A, and SHANK2. These genes are enriched in synapse-related pathways and signaling pathways, suggesting that sex-differential genes of these neuronal pathways may cause the sex-bias of psychiatric disorders.

Altered DNA methylation profiles in blood from patients with sporadic Creutzfeldt-Jakob disease

Prion diseases are fatal and transmissible neurodegenerative disorders caused by the misfolding and aggregation of prion protein. Although recent studies have implicated epigenetic variation in common neurodegenerative disorders, no study has yet explored their role in human prion diseases. Here we profiled genome-wide blood DNA methylation in the most common human prion disease, sporadic Creutzfeldt–Jakob disease (sCJD). Our case–control study (n = 219), when accounting for differences in cell type composition between individuals, identified 38 probes at genome-wide significance (p < 1.24 × 10^–7). Nine of these sites were taken forward in a replication study, performed in an independent case–control (n = 186) cohort using pyrosequencing. Sites in or close to FKBP5, AIM2 (2 probes), UHRF1, KCNAB2 successfully replicated. The blood-based DNA methylation signal was tissue- and disease-specific, in that the replicated probe signals were unchanged in case–control studies using sCJD frontal-cortex (n = 84), blood samples from patients with Alzheimer’s disease, and from inherited and acquired prion diseases. Machine learning algorithms using blood DNA methylation array profiles accurately distinguished sCJD patients and controls. Finally, we identified sites whose methylation levels associated with prolonged survival in sCJD patients. Altogether, this study has identified a peripheral DNA methylation signature of sCJD with a variety of potential biomarker applications.