Identifying mislabeled and contaminated DNA methylation microarray data: an extended quality control toolset with examples from GEO

Epigenome-wide DNA methylation in leukocytes and toenail metals: The normative aging study

BACKGROUND

Environmental metal exposures have been associated with multiple deleterious health endpoints. DNA methylation (DNAm) may provide insight into the mechanisms underlying these relationships. Toenail metals are non-invasive biomarkers, reflecting a medium-term time exposure window.

OBJECTIVES

This study examined variation in leukocyte DNAm and toenail arsenic (As), cadmium (Cd), lead (Pb), manganese (Mn), and mercury (Hg) among elderly men in the Normative Aging Study, a longitudinal cohort.

METHODS

We repeatedly collected samples of blood and toenail clippings. We measured DNAm in leukocytes with the Illumina HumanMethylation450 K BeadChip. We first performed median regression to evaluate the effects of each individual toenail metal on DNAm at three levels: individual cytosine-phosphate-guanine (CpG) sites, regions, and pathways. Then, we applied a Bayesian kernel machine regression (BKMR) to assess the joint and individual effects of metal mixtures on DNAm. Significant CpGs were identified using a multiple testing correction based on the independent degrees of freedom approach for correlated outcomes. The approach considers the effective degrees of freedom in the DNAm data using the principal components that explain >95% variation of the data.

RESULTS

We included 564 subjects (754 visits) between 1999 and 2013. The numbers of significantly differentially methylated CpG sites, regions, and pathways varied by metals. For example, we found six significant pathways for As, three for Cd, and one for Mn. The As-associated pathways were associated with cancer (e.g., skin cancer) and cardiovascular disease, whereas the Cd-associated pathways were related to lung cancer. Metal mixtures were also associated with 47 significant CpG sites, as well as pathways, mainly related to cancer and cardiovascular disease.

CONCLUSIONS

This study provides an approach to understanding the potential epigenetic mechanisms underlying observed relations between toenail metals and adverse health endpoints.

Epigenome-Wide Analysis of DNA Methylation and Optimism in Women and Men

OBJECTIVE

Higher optimism is associated with reduced mortality and a lower risk of age-related chronic diseases. DNA methylation (DNAm) may provide insight into mechanisms underlying these relationships. We hypothesized that DNAm would differ among older individuals who are more versus less optimistic.

METHODS

Using cross-sectional data from two population-based cohorts of women with diverse races/ethnicities ( n = 3816) and men (only White, n = 667), we investigated the associations of optimism with epigenome-wide leukocyte DNAm. Random-effects meta-analyses were subsequently used to pool the individual results. Significantly differentially methylated cytosine-phosphate-guanines (CpGs) were identified by the "number of independent degrees of freedom" approach: effective degrees of freedom correction using the number of principal components (PCs), explaining >95% of the variation of the DNAm data (PC-correction). We performed regional analyses using comb-p and pathway analyses using the Ingenuity Pathway Analysis software.

RESULTS

We found that essentially all CpGs (total probe N = 359,862) were homogeneous across sex and race/ethnicity in the DNAm-optimism association. In the single CpG site analyses based on homogeneous CpGs, we identified 13 significantly differentially methylated probes using PC-correction. We found four significantly differentially methylated regions and two significantly differentially methylated pathways. The annotated genes from the single CpG site and regional analyses are involved in psychiatric disorders, cardiovascular disease, cognitive impairment, and cancer. Identified pathways were related to cancer, and neurodevelopmental and neurodegenerative disorders.

CONCLUSION

Our findings provide new insights into possible mechanisms underlying optimism and health.

Polymethylation scores for prenatal maternal smoke exposure persist until age 15 and are detected in saliva in the Fragile Families and Child Wellbeing cohort

Prenatal maternal smoking is associated with low birthweight, neurological disorders, and asthma in exposed children. DNA methylation signatures can function as biomarkers of prenatal smoke exposure. However, the robustness of DNA methylation signatures across child ages, genetic ancestry groups, or tissues is not clear. Using coefficients from a meta-analysis of prenatal smoke exposure and DNA methylation in newborn cord blood, we created polymethylation scores of saliva DNA methylation from children at ages 9 and 15 in the Fragile Families and Child Wellbeing study. In the full sample at age 9 (n = 753), prenatal smoke exposure was associated with a 0.51 (95%CI: 0.35, 0.66) standard deviation higher polymethylation score. The direction and magnitude of the association was consistent in European and African genetic ancestry samples. In the full sample at age 15 (n = 747), prenatal smoke exposure was associated with a 0.48 (95%CI: 0.32, 0.63) standard deviation higher polymethylation score, and the association was attenuated among the European and Admixed-Latin genetic ancestry samples. The polymethylation score classified prenatal smoke exposure accurately (AUC age 9 = 0.77, age 15 = 0.76). Including the polymethylation score increased the AUC of base model covariates by 5 (95% CI: (2.1, 7.2)) percentage points, while including a single candidate site in the AHRR gene did not (P-value = 0.19). Polymethylation scores for prenatal smoking were portable across genetic ancestries and more accurate than an individual DNA methylation site. Polymethylation scores from saliva samples could serve as robust and practical biomarkers of prenatal smoke exposure.

Epigenome-wide association of neonatal methylation and trimester-specific prenatal PM2.5 exposure

Exposure to particulate matter with an aerodynamic diameter smaller than 2.5 microns (PM2.5) can affect birth outcomes through physiological pathways such as inflammation. One potential way PM2.5 affects physiology could be through altering DNA methylation (DNAm). Considering that exposures during specific windows of gestation may have unique effects on DNAm, we hypothesized a timing-specific association between PM2.5 exposure during pregnancy and DNAm in the neonatal epithelial-cell epigenome.

Methods

After collecting salivary samples from a cohort of 91 neonates, DNAm was assessed at over 850,000 cytosine-guanine dinucleotide (CpG) methylation sites on the epigenome using the MethylationEPIC array. Daily ambient PM2.5 concentrations were estimated based on the mother's address of primary residence during pregnancy. PM2.5 was averaged over the first two trimesters, separately and combined, and tested for association with DNAm through an epigenome-wide association (EWA) analysis. For each EWA, false discovery rate (FDR)-corrected P < 0.05 constituted a significant finding and every CpG site with uncorrected P < 0.0001 was selected to undergo pathway and network analysis to identify molecular functions enriched by them.

Results

Our analysis showed that cg18705808 was associated with the combined average of PM2.5. Pathway and network analysis revealed little similarity between the first two trimesters. Previous studies reported that TMEM184A, the gene regulated by cg18705808, has a putative role in inflammatory pathways.

Conclusions

The differences in pathway and network analyses could potentially indicate trimester-specific effects of PM2.5 on DNAm. Further analysis with greater temporal resolution would be valuable to fully characterize the effect of PM2.5 on DNAm and child development.

Serum lead, mercury, manganese, and copper and DNA methylation age among adults in Detroit, Michigan

Although the effects of lead, mercury, manganese, and copper on individual disease processes are well understood, estimating the health effects of long-term exposure to these metals at the low concentrations often observed in the general population is difficult. In addition, the health effects of joint exposure to multiple metals are difficult to estimate. Biological aging refers to the integrative progression of multiple physiologic and molecular changes that make individuals more at risk of disease. Biomarkers of biological aging may be useful to estimate the population-level effects of metal exposure prior to the development of disease in the population. We used data from 290 participants in the Detroit Neighborhood Health Study to estimate the effect of serum lead, mercury, manganese, and copper on three DNA methylation-based biomarkers of biological aging (Horvath Age, PhenoAge, and GrimAge). We used mixed models and Bayesian kernel machine regression and controlled for participant sex, race, ethnicity, cigarette use, income, educational attainment, and block group poverty. We observed consistently positive estimates of the effects between lead and GrimAge acceleration and mercury and PhenoAge acceleration. In contrast, we observed consistently negative associations between manganese and PhenoAge acceleration and mercury and Horvath Age acceleration. We also observed curvilinear relationships between copper and both PhenoAge and GrimAge acceleration. Increasing total exposure to the observed mixture of metals was associated with increased PhenoAge and GrimAge acceleration and decreased Horvath Age acceleration. These findings indicate that an increase in serum lead or mercury from the 25th to 75th percentile is associated with a ∼0.25-year increase in two epigenetic markers of all-cause mortality in a population of adults in Detroit, Michigan. While few of the findings were statistically significant, their consistency and novelty warrant interest.

Association between prenatal cadmium exposure and cord blood DNA methylation

Prenatal cadmium exposure is known to affect infant growth and organ development. Nonetheless, the role of DNA methylation in cadmium-related health effects has yet to be determined. To this end, we investigated the relationship between prenatal cadmium exposure and cord blood DNA methylation in Korean infants through an epigenome-wide association study. Cadmium concentrations in maternal blood during early and late pregnancy and in cord blood collected from newborns were measured using atomic adsorption spectrometry and DNA methylation analysis was conducted using HumanMethylationEPIC BeadChip kits. After adjusting for infant sex, maternal pregnancy body mass index, smoking status, and estimated leukocyte composition, we analyzed the association between CpG methylation and cadmium concentration in 364 samples. Among 835,252 CpG sites, maternal blood cadmium concentration in early pregnancy was significantly associated with two differentially methylated CpG sites, cg05537752 and cg24904393, which were annotated ATP9A and no gene, respectively. The study findings indicate that prenatal cadmium exposure is significantly associated with methylation statuses of several CpG sites and regions in Korean infants, especially during early pregnancy.

The shared mother-child epigenetic signature of neglect is related to maternal adverse events

Studies of DNA methylation have revealed the biological mechanisms by which life adversity confers risk for later physical and mental health problems. What remains unknown is the “biologically embedding” of maternal adverse experiences resulting in maladaptive parenting and whether these epigenetic effects are transmitted to the next generation. This study focuses on neglectful mothering indexed by a severe disregard for the basic and psychological needs of the child. Using the Illumina Human Methylation EPIC BeadChip in saliva samples, we identified genes with differentially methylated regions (DMRs) in those mothers with (n = 51), versus those without (n = 87), neglectful behavior that present similar DMRs patterns in their children being neglected versus non-neglected (n = 40 vs. 75). Mothers reported the emotional intensity of adverse life events. After covariate adjustment and multiple testing corrections, we identified 69 DMRs in the mother epigenome and 42 DMRs in the child epigenome that were simultaneously above the α = 0.01 threshold. The common set of nine DMRs contained genes related to childhood adversity, neonatal and infant diabetes, child neurobehavioral development and other health problems such as obesity, hypertension, cancer, posttraumatic stress, and the Alzheimer’s disease; four of the genes were associated with maternal life adversity. Identifying a shared epigenetic signature of neglect linked to maternal life adversity is an essential step in breaking the intergenerational transmission of one of the most common forms of childhood maltreatment.

Digital methylation assessments of alcohol and cigarette consumption account for common variance in accelerated epigenetic ageing

Smoking and Heavy Alcohol Consumption (HAC) are established risk factors for myriad complex disorders of ageing. Yet many prior studies of Epigenetic Ageing (EA) have shown only modest effects of smoking and drinking on accelerated ageing. One potential reason for this conundrum might be the reliance of some prior EA studies on self-reported substance use, which may be unreliable in many samples. To test whether novel, non-self-reported indices would show a stronger association of smoking and HAC to EA, we used methylation sensitive digital PCR (MSdPCR) and data from 437 African American subjects from Wave 7 of the Family and Community Health Study Offspring Cohort to examine the effects of subjective and objective measures of smoking and HAC on 7 indices of EA. Because of limited overall correlations between the various EA indices, we examined patterns of association separately for each index. Consistent with expectations, MSdPCR assessments of smoking and HAC, but not self-reported alcohol consumption, were strongly correlated with accelerated EA. MSdPCR assessments of smoking and HAC accounted for 57% of GrimAge acceleration and the shared variance in GrimAge and DunedinPOAM accelerated EA. We conclude that MSdPCR assessments of smoking and HAC are valuable tools for understanding EA, represent directly targetable conditions for the prevention of premature ageing, and substantially improve upon self-reported assessment of smoking and HAC.

Associations between perceived discrimination and immune cell composition in the Jackson Heart Study

African American adults suffer disproportionately from several non-communicable and infectious diseases. Among numerous contributing factors, perceived discrimination is considered a stressor for members of historically marginalized groups that contributes to health risk, although biological pathways are incompletely understood. Previous studies have reported associations between stress and both an up-regulation of non-specific (innate) inflammation and down-regulation of specific (adaptive) immunity. While associations between perceived discrimination and markers of inflammation have been explored, it is unclear if this is part of an overall shift that also includes down-regulated adaptive immunity. Relying on a large cross-section of African American adults (n = 3,319) from the Jackson Heart Study (JHS) in Jackson, Mississippi, we tested whether perceived everyday and lifetime discrimination as well as perceived burden from lifetime discrimination were associated with counts of neutrophils (innate), monocytes (innate), lymphocytes (adaptive), and the neutrophil-to-lymphocyte ratio (NLR), derived from complete white blood cell counts with differential. In addition, DNA methylation (DNAm) was measured on the EPIC array in a sub-sample (n = 1,023) of participants, allowing estimation of CD4T, CD8T and B lymphocyte proportions. Unexpectedly, high lifetime discrimination compared to low was significantly associated with lower neutrophils (b : -0.14, [95% CI: -0.24, -0.04]) and a lower NLR (b : -0.15, [95% CI: -0.25, -0.05]) after controlling for confounders. However, high perceived burden from lifetime discrimination was significantly associated with higher neutrophils (b : 0.17, [95% CI: 0.05, 0.30]) and a higher NLR (b : 0.16, [95% CI: 0.03, 0.29]). High perceived burden was also associated with lower lymphocytes among older men, which our analysis suggested might have been attributable to differences in CD4T cells. These findings highlight immune function as a potentially important pathway linking perceived discrimination to health outcomes.

Association between DNA methylation variability and self-reported exposure to heavy metals

Individuals encounter varying environmental exposures throughout their lifetimes. Some exposures such as smoking are readily observed and have high personal recall; others are more indirect or sporadic and might only be inferred from long occupational histories or lifestyles. We evaluated the utility of using lifetime-long self-reported exposures for identifying differential methylation in an amyotrophic lateral sclerosis cases-control cohort of 855 individuals. Individuals submitted paper-based surveys on exposure and occupational histories as well as whole blood samples. Genome-wide DNA methylation levels were quantified using the Illumina Infinium Human Methylation450 array. We analyzed 15 environmental exposures using the OSCA software linear and MOA models, where we regressed exposures individually by methylation adjusted for batch effects and disease status as well as predicted scores for age, sex, cell count, and smoking status. We also regressed on the first principal components on clustered environmental exposures to detect DNA methylation changes associated with a more generalised definition of environmental exposure. Five DNA methylation probes across three environmental exposures (cadmium, mercury and metalwork) were significantly associated using the MOA models and seven through the linear models, with one additionally across a principal component representing chemical exposures. Methylome-wide significance for four of these markers was driven by extreme hyper/hypo-methylation in small numbers of individuals. The results indicate the potential for using self-reported exposure histories in detecting DNA methylation changes in response to the environment, but also highlight the confounded nature of environmental exposure in cohort studies.

Prenatal lead exposure, telomere length in cord blood, and DNA methylation age in the PROGRESS prenatal cohort

BACKGROUND

Lead is a ubiquitous pollutant with deleterious effects on human health and remains a major current public health concern in developing countries. This heavy metal may interfere with nucleic acids via oxidative stress or epigenetic changes that affect biological markers of aging, e.g., telomere length and DNA methylation (DNAm). Telomere shortening associates with biological age in newborns, and DNA methylation at specific CpG sites can be used to calculate "epigenetic clocks".

OBJECTIVE

The aim of this study was to examine the associations of prenatal lead exposures with telomere length and DNA-methylation-based predictors of age in cord blood.

DESIGN

The study included 507 mother-child pairs from the Programming Research in Obesity, Growth, Environment and Social Stressors (PROGRESS) study, a birth cohort in Mexico City. Maternal blood (second trimester, third trimester and at delivery) and bone lead levels (one month postpartum) were measured using inductively coupled plasma-mass spectrometry and X-ray fluorescence, respectively. Cord blood leukocyte telomere length was measured using quantitative PCR and apparent age by DNA methylation biomarkers, i.e., Horvath's DNA methylation age and the Knight's predictor of gestational age.

RESULTS

Average maternal age was 28.5 ± 5.5 years, and 51.5% reported low socioeconomic status. Children's mean telomere length was 1.2 ± 1.3 relative units, and mean DNA methylation ages using the Horvath's and Knight's clocks were -2.6 ± 0.1 years and 37.9 ± 1.4 weeks (mean ± SD), respectively. No significant associations were found between maternal blood and bone lead concentrations with telomere length and DNAm age in newborns.

CONCLUSION

We found no associations of prenatal lead exposure with telomere length and DNA methylation age biomarkers.

Prenatal Exposure to Traffic-Related Air Pollution and the DNA Methylation in Cord Blood Cells: MOCEH Study

Particulate matter with a diameter of ≤10 µm (PM₁₀) and nitrogen dioxide (NO₂) affect the DNA methylation in the fetus, but epigenetic studies regarding prenatal exposure to air pollution in Asia are lacking. Therefore, this study aimed to assess whether there is any association between the ambient concentrations of PM₁₀ and NO₂ and CpG methylation in the cord blood DNA by using a Korean birth cohort. The concentrations of the air pollutants were incorporated into the final LUR model by using the maternal address data. The methylation level was determined using HumanMethylationEPIC BeadChip and a linear regression analysis model. A multipollutant model including both PM₁₀ and NO₂ and models with single pollutants were used for each trimester exposure. The number of differentially methylated positions was the largest for midpregnancy exposure in both the single pollutant models and the multipollutant regression analysis. Additionally, gene-set analysis regarding midpregnancy exposure revealed four gene ontology terms (cellular response to staurosporine, positive regulation of cytoskeleton organization, neurotransmitter transport, and execution phase of apoptosis). In conclusion, these findings show an association between prenatal PM₁₀ and NO₂ exposure and DNA methylation in several CpG sites in cord blood cells, especially for midpregnancy exposure.

Navigating the hydroxymethylome: experimental biases and quality control tools for the tandem bisulfite and oxidative bisulfite Illumina microarrays

Aim: Tandem bisulfite (BS) and oxidative bisulfite (oxBS) conversion on DNA followed by hybridization to Infinium HumanMethylation BeadChips allows nucleotide resolution of 5-hydroxymethylcytosine genome-wide. Here, the authors compared data quality acquired from BS-treated and oxBS-treated samples. Materials & methods: Raw BeadArray data from 417 pairs of samples across 12 independent datasets were included in the study. Probe call rates were compared between paired BS and oxBS treatments controlling for technical variables. Results: oxBS-treated samples had a significantly lower call rate. Among technical variables, DNA-specific extraction kits performed better with higher call rates after oxBS conversion. Conclusion: The authors emphasize the importance of quality control during oxBS conversion to minimize information loss and recommend using a DNA-specific extraction kit for DNA extraction and an oxBSQC package for data preprocessing.

Association of Epigenetic Differences Screened in a Few Cases of Monozygotic Twins Discordant for Attention-Deficit Hyperactivity Disorder With Brain Structures

The present study examined the relationship between DNA methylation differences and variations in brain structures involved in the development of attention-deficit hyperactivity disorder (ADHD). First, we used monozygotic (MZ) twins discordant (2 pairs of 4 individuals, 2 boys, mean age 12.5 years) for ADHD to identify candidate DNA methylation sites involved in the development of ADHD. Next, we tried to replicate these candidates in a case-control study (ADHD: N = 18, 15 boys, mean age 10.0 years; Controls: N = 62, 40 boys, mean age 13.9 years). Finally, we examined how methylation rates at those sites relate to the degree of local structural alterations where significant differences were observed between cases and controls. As a result, we identified 61 candidate DNA methylation sites involved in ADHD development in two pairs of discordant MZ twins, among which elevated methylation at a site in the sortilin-related Vps10p domain containing receptor 2 (SorCS2) gene was replicated in the case-control study. We also observed that the ADHD group had significantly reduced gray matter volume (GMV) in the precentral and posterior orbital gyri compared to the control group and that this volume reduction was positively associated with SorCS2 methylation. Furthermore, the reduced GMV regions in children with ADHD are involved in language processing and emotional control, while SorCS2 methylation is also negatively associated with emotional behavioral problems in children. These results indicate that SorCS2 methylation might mediate a reduced GMV in the precentral and posterior orbital gyri and therefore influence the pathology of children with ADHD.

Short- and intermediate-term exposure to ambient fine particulate elements and leukocyte epigenome-wide DNA methylation in older men: the Normative Aging Study

BACKGROUND

Several epigenome-wide association studies (EWAS) of ambient particulate matter with aerodynamic diameter ≤ 2.5 µm (PM_2.5) have been reported. However, EWAS of PM_2.5 elements (PEs), reflecting different emission sources, are very limited.

OBJECTIVES

We performed EWAS of short- and intermediate-term exposure to PM_2.5 and 13 PEs. We hypothesized that significant changes in DNAm may vary by PM_2.5 mass and its elements.

METHODS

We repeatedly collected blood samples in the Normative Aging Study and measured leukocyte DNA methylation (DNAm) with the Illumina HumanMethylation450K BeadChip. We collected daily PM_2.5 and 13 PEs at a fixed central site. To estimate the associations between each PE and DNAm at individual cytosine-phosphate-guanine (CpG) sites, we incorporated a distributed-lag (0-27 d) term in the setting of median regression with subject-specific intercept and examined cumulative lag associations. We also accounted for selection bias due to loss to follow-up and mortality prior to enrollment. Significantly differentially methylated probes (DMPs) were identified using Bonferroni correction for multiple testing. We further conducted regional and pathway analyses to identify significantly differentially methylated regions (DMRs) and pathways.

RESULTS

We included 695 men with 1,266 visits between 1999 and 2013. The subjects had a mean age of 75 years. The significant DMPs, DMRs, and pathways varied by to PM_2.5 total mass and PEs. For example, PM_2.5 total mass was associated with 2,717 DMPs and 10,470 DMRs whereas Pb was associated with 3,173 DMPs and 637 DMRs. The identified pathways by PM_2.5 mass were mostly involved in mood disorders, neuroplasticity, immunity, and inflammation, whereas the pathways associated with motor vehicles (BC, Cu, Pb, and Zn) were related with cardiovascular disease and cancer (e.g., "PPARs signaling").

CONCLUSIONS

PM_2.5 and PE were associated with methylation changes at multiple probes and along multiple pathways, in ways that varied by particle components.

The SEQC2 epigenomics quality control (EpiQC) study

BACKGROUND

Cytosine modifications in DNA such as 5-methylcytosine (5mC) underlie a broad range of developmental processes, maintain cellular lineage specification, and can define or stratify types of cancer and other diseases. However, the wide variety of approaches available to interrogate these modifications has created a need for harmonized materials, methods, and rigorous benchmarking to improve genome-wide methylome sequencing applications in clinical and basic research. Here, we present a multi-platform assessment and cross-validated resource for epigenetics research from the FDA's Epigenomics Quality Control Group.

RESULTS

Each sample is processed in multiple replicates by three whole-genome bisulfite sequencing (WGBS) protocols (TruSeq DNA methylation, Accel-NGS MethylSeq, and SPLAT), oxidative bisulfite sequencing (TrueMethyl), enzymatic deamination method (EMSeq), targeted methylation sequencing (Illumina Methyl Capture EPIC), single-molecule long-read nanopore sequencing from Oxford Nanopore Technologies, and 850k Illumina methylation arrays. After rigorous quality assessment and comparison to Illumina EPIC methylation microarrays and testing on a range of algorithms (Bismark, BitmapperBS, bwa-meth, and BitMapperBS), we find overall high concordance between assays, but also differences in efficiency of read mapping, CpG capture, coverage, and platform performance, and variable performance across 26 microarray normalization algorithms.

CONCLUSIONS

The data provided herein can guide the use of these DNA reference materials in epigenomics research, as well as provide best practices for experimental design in future studies. By leveraging seven human cell lines that are designated as publicly available reference materials, these data can be used as a baseline to advance epigenomics research.

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.

Prenatal Particulate Matter Exposure Is Associated with Saliva DNA Methylation at Age 15: Applying Cumulative DNA Methylation Scores as an Exposure Biomarker

Exposure in utero to particulate matter (PM2.5 and PM10) is associated with maladaptive health outcomes. Although exposure to prenatal PM2.5 and PM10 has cord blood DNA methylation signatures at birth, signature persistence into childhood and saliva cross-tissue applicability has not been tested. In the Fragile Families and Child Wellbeing Study, a United States 20-city birth cohort, average residential PM2.5 and PM10 during the three months prior to birth was estimated using air quality monitors with inverse distance weighting. Saliva DNA methylation at ages 9 (n = 749) and 15 (n = 793) was measured using the Illumina HumanMethylation 450 k BeadArray. Cumulative DNA methylation scores for particulate matter were estimated by weighting participant DNA methylation at each site by independent meta-analysis effect estimates and standardizing the sums. Using a mixed-effects regression analysis, we tested the associations between cumulative DNA methylation scores at ages 9 and 15 and PM exposure during pregnancy, adjusted for child sex, age, race/ethnicity, maternal income-to-needs ratio, nonmartial birth status, and saliva cell-type proportions. Our study sample was 50.5% male, 56.3% non-Hispanic Black, and 19.8% Hispanic, with a median income-to-needs ratio of 1.4. Mean exposure levels for PM2.5 were 27.9 μg/m³/day (standard deviation: 7.0; 23.7% of observations exceeded safety standards) and for PM10 were 15.0 μg/m³/day (standard deviation: 3.1). An interquartile range increase in PM2.5 exposure (10.73 μg/m³/day) was associated with a −0.0287 standard deviation lower cumulative DNA methylation score for PM2.5 (95% CI: −0.0732, 0.0158, p = 0.20) across all participants. An interquartile range increase in PM10 exposure (3.20 μg/m³/day) was associated with a −0.1472 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: −0.3038, 0.0095, p = 0.06) across all participants. The PM10 findings were driven by the age 15 subset where an interquartile range increase in PM10 exposure was associated with a −0.024 standard deviation lower cumulative DNA methylation score for PM10 (95% CI: −0.043, −0.005, p = 0.012). Findings were robust to adjustment for PM exposure at ages 1 and 3. In utero PM10-associated DNA methylation differences were identified at age 15 in saliva. Benchmarking the timing and cell-type generalizability is critical for epigenetic exposure biomarker assessment.

DNA methylation-based sex classifier to predict sex and identify sex chromosome aneuploidy

BACKGROUND

Sex is an important covariate of epigenome-wide association studies due to its strong influence on DNA methylation patterns across numerous genomic positions. Nevertheless, many samples on the Gene Expression Omnibus (GEO) frequently lack a sex annotation or are incorrectly labelled. Considering the influence that sex imposes on DNA methylation patterns, it is necessary to ensure that methods for filtering poor samples and checking of sex assignment are accurate and widely applicable.

RESULTS

Here we presented a novel method to predict sex using only DNA methylation beta values, which can be readily applied to almost all DNA methylation datasets of different formats (raw IDATs or text files with only signal intensities) uploaded to GEO. We identified 4345 significantly (p<0.01) sex-associated CpG sites present on both 450K and EPIC arrays, and constructed a sex classifier based on the two first principal components of the DNA methylation data of sex-associated probes mapped on sex chromosomes. The proposed method is constructed using whole blood samples and exhibits good performance across a wide range of tissues. We further demonstrated that our method can be used to identify samples with sex chromosome aneuploidy, this function is validated by five Turner syndrome cases and one Klinefelter syndrome case.

CONCLUSIONS

This proposed sex classifier not only can be used for sex predictions but also applied to identify samples with sex chromosome aneuploidy, and it is freely and easily accessible by calling the 'estimateSex' function from the newest wateRmelon Bioconductor package ( https://github.com/schalkwyk/wateRmelon ).

A cross-cohort analysis of autosomal DNA methylation sex differences in the term placenta

BACKGROUND

Human placental DNA methylation (DNAme) data is a valuable resource for studying sex differences during gestation, as DNAme profiles after delivery reflect the cumulative effects of gene expression patterns and exposures across gestation. Here, we present an analysis of sex differences in autosomal DNAme in the uncomplicated term placenta (n = 343) using the Illumina 450K array.

RESULTS

At a false discovery rate < 0.05 and a mean sex difference in DNAme beta value of > 0.10, we identified 162 autosomal CpG sites that were differentially methylated by sex and replicated in an independent cohort of samples (n = 293). Several of these differentially methylated CpG sites were part of larger correlated regions of sex differential DNAme. Although global DNAme levels did not differ by sex, the majority of significantly differentially methylated CpGs were more highly methylated in male placentae, the opposite of what is seen in differential methylation analyses of somatic tissues. Patterns of autosomal DNAme at these 162 CpGs were significantly associated with maternal age (in males) and newborn birthweight standard deviation (in females).

CONCLUSIONS

Our results provide a comprehensive analysis of sex differences in autosomal DNAme in the term human placenta. We report a list of high-confidence autosomal sex-associated differentially methylated CpGs and identify several key features of these loci that suggest their relevance to sex differences observed in normative and complicated pregnancies.

DNA methylation patterns in juvenile systemic sclerosis and localized scleroderma

Scleroderma refers to a group of chronic fibrotic immune-mediated diseases of unknown etiology. Characterizing epigenetic changes in childhood-onset scleroderma, systemic sclerosis or localized scleroderma, has not been previously performed. The aim of this study was to assess DNA methylation differences and similarities between juvenile systemic sclerosis (jSSc) and juvenile localized scleroderma (jLS) compared to matched healthy controls. Genome-wide DNA methylation changes in peripheral blood mononuclear cell samples were assessed using the MethylationEPIC array followed by bioinformatic analysis and limited functional assessment. We identified a total of 105 and 144 differentially methylated sites compared to healthy controls in jSSc and jLS, respectively. The majority of differentially methylated sites and genes represented were unique to either jSSc or jLS suggesting a different underlying epigenetic pattern in both diseases. Among shared differentially methylated genes, methylation levels in a CpG site in FGFR2 can distinguish between LS and healthy PBMCs with a high accuracy. Canonical pathway analysis revealed that inflammatory pathways were enriched in genes differentially methylated in jSSc, including STAT3, NF-κB, and IL-15 pathways. In contrast, the HIPPO signaling pathway was enriched in jLS. Our data also suggest a potential role for NOTCH3 in both jSSc and jLS, and revealed a number of transcription factors unique to each of the two diseases. In summary, our data revealed important insights into jSSc and jLS and suggest a potentially novel epigenetic diagnostic biomarker for LS.

Human methylome variation across Infinium 450K data on the Gene Expression Omnibus

While DNA methylation (DNAm) is the most-studied epigenetic mark, few recent studies probe the breadth of publicly available DNAm array samples. We collectively analyzed 35 360 Illumina Infinium HumanMethylation450K DNAm array samples published on the Gene Expression Omnibus. We learned a controlled vocabulary of sample labels by applying regular expressions to metadata and used existing models to predict various sample properties including epigenetic age. We found approximately two-thirds of samples were from blood, one-quarter were from brain and one-third were from cancer patients. About 19% of samples failed at least one of Illumina's 17 prescribed quality assessments; signal distributions across samples suggest modifying manufacturer-recommended thresholds for failure would make these assessments more informative. We further analyzed DNAm variances in seven tissues (adipose, nasal, blood, brain, buccal, sperm and liver) and characterized specific probes distinguishing them. Finally, we compiled DNAm array data and metadata, including our learned and predicted sample labels, into database files accessible via the recountmethylation R/Bioconductor companion package. Its vignettes walk the user through some analyses contained in this paper.

Prenatal lead exposure and cord blood DNA methylation in the Korean Exposome Study

BACKGROUND

Prenatal lead exposure has been reported to affect infant growth and nervous system development, as well as to influence DNA methylation. We conducted an epigenome-wide association study to identify associations between prenatal lead exposure and cord blood DNA methylation in Korean infants.

METHODS

Cord blood samples were assayed with the Illumina HumanMethylationEPIC BeadChip kits, and maternal blood lead levels during early and late pregnancy, as well as cord blood lead level, were measured. The association between CpG methylation and lead level was analyzed using the limma package, with adjusting for infant sex, maternal pre-pregnancy body mass index, and estimated leukocyte composition.

RESULTS

Among 364 blood samples (182 males and 182 females), those for which maternal and cord blood lead concentrations during early and later pregnancy was known were used for analysis. Maternal lead concentration in blood during early pregnancy was significantly associated with the methylation status of specific positions. After data stratification by infant sex, we found that, in males, the level of maternal blood lead was associated with 18 CpG sites during early pregnancy, and with one CpG site near the NBAS gene, during late pregnancy. In female samples, there was no significant association between DNA methylation and lead concentrations.

CONCLUSIONS

Prenatal lead exposure was associated with altered, gender-specific patterns of DNA methylation in Korean infants.

The impact of psychopathology, social adversity and stress-relevant DNA methylation on prospective risk for post-traumatic stress: A machine learning approach

BACKGROUND

A range of factors have been identified that contribute to greater incidence, severity, and prolonged course of post-traumatic stress disorder (PTSD), including: comorbid and/or prior psychopathology; social adversity such as low socioeconomic position, perceived discrimination, and isolation; and biological factors such as genomic variation at glucocorticoid receptor regulatory network (GRRN) genes. This complex etiology and clinical course make identification of people at higher risk of PTSD challenging. Here we leverage machine learning (ML) approaches to identify a core set of factors that may together predispose persons to PTSD.

METHODS

We used multiple ML approaches to assess the relationship among DNA methylation (DNAm) at GRRN genes, prior psychopathology, social adversity, and prospective risk for PTS severity (PTSS).

RESULTS

ML models predicted prospective risk of PTSS with high accuracy. The Gradient Boost approach was the top-performing model with mean absolute error of 0.135, mean square error of 0.047, root mean square error of 0.217, and R2 of 95.29%. Prior PTSS ranked highest in predicting the prospective risk of PTSS, accounting for >88% of the prediction. The top ranked GRRN CpG site was cg05616442, in AKT1, and the top ranked social adversity feature was loneliness.

CONCLUSION

Multiple factors including prior PTSS, social adversity, and DNAm play a role in predicting prospective risk of PTSS. ML models identified factors accounting for increased PTSS risk with high accuracy, which may help to target risk factors that reduce the likelihood or course of PTSD, potentially pointing to approaches that can lead to early intervention.

LIMITATION

One of the limitations of this study is small sample size.

Saliva cell type DNA methylation reference panel for epidemiological studies in children

Saliva is a widely used biological sample, especially in pediatric research, containing a heterogenous mixture of immune and epithelial cells. Associations of exposure or disease with saliva DNA methylation can be influenced by cell-type proportions. Here, we developed a saliva cell-type DNA methylation reference panel to estimate interindividual cell-type heterogeneity in whole saliva studies. Saliva was collected from 22 children (7-16 years) and sorted into immune and epithelial cells, using size exclusion filtration and magnetic bead sorting. DNA methylation was measured using the Illumina MethylationEPIC BeadChip. We assessed cell-type differences in DNA methylation profiles and tested for enriched biological pathways. Immune and epithelial cells differed at 181,577 (22.8%) DNA methylation sites (t-test p < 6.28 × 10^-8). Immune cell hypomethylated sites are mapped to genes enriched for immune pathways (p < 3.2 × 10^-5). Epithelial cell hypomethylated sites were enriched for cornification (p = 5.2 × 10^-4), a key process for hard palette formation. Saliva immune and epithelial cells have distinct DNA methylation profiles which can drive whole-saliva DNA methylation measures. A primary saliva DNA methylation reference panel, easily implemented with an R package, will allow estimates of cell proportions from whole saliva samples and improve epigenetic epidemiology studies by accounting for measurement heterogeneity by cell-type proportions.

Cell-specific characterization of the placental methylome

BACKGROUND

DNA methylation (DNAm) profiling has emerged as a powerful tool for characterizing the placental methylome. However, previous studies have focused primarily on whole placental tissue, which is a mixture of epigenetically distinct cell populations. Here, we present the first methylome-wide analysis of first trimester (n = 9) and term (n = 19) human placental samples of four cell populations: trophoblasts, Hofbauer cells, endothelial cells, and stromal cells, using the Illumina EPIC methylation array, which quantifies DNAm at > 850,000 CpGs.

RESULTS

The most distinct DNAm profiles were those of placental trophoblasts, which are central to many pregnancy-essential functions, and Hofbauer cells, which are a rare fetal-derived macrophage population. Cell-specific DNAm occurs at functionally-relevant genes, including genes associated with placental development and preeclampsia. Known placental-specific methylation marks, such as those associated with genomic imprinting, repetitive element hypomethylation, and placental partially methylated domains, were found to be more pronounced in trophoblasts and often absent in Hofbauer cells. Lastly, we characterize the cell composition and cell-specific DNAm dynamics across gestation.

CONCLUSIONS

Our results provide a comprehensive analysis of DNAm in human placental cell types from first trimester and term pregnancies. This data will serve as a useful DNAm reference for future placental studies, and we provide access to this data via download from GEO (GSE159526), through interactive exploration from the web browser ( https://robinsonlab.shinyapps.io/Placental_Methylome_Browser/ ), and through the R package planet, which allows estimation of cell composition directly from placental DNAm data.

DNA methylation-based biomarkers of age acceleration and all-cause death, myocardial infarction, stroke, and cancer in two cohorts: The NAS, and KORA F4

Background

DNA methylation (DNAm) may play a role in age-related outcomes. It is not yet known which DNAm-based biomarkers of age acceleration (BoAA) has the strongest association with age-related endpoints.

Methods

We collected the blood samples from two independent cohorts: the Normative Ageing Study, and the Cooperative Health Research in the Region of Augsburg cohort. We measured epigenome-wide DNAm level, and generated five DNAm BoAA at baseline. We used Cox proportional hazards model to analyze the relationships between BoAA and all-cause death. We applied the Fine and Gray competing risk model to estimate the risk of BoAA on myocardial infarction (MI), stroke, and cancer, accounting for death of other reasons as the competing risks. We used random-effects meta-analyses to pool the individual results, with adjustment for multiple testing.

Findings

The mean chronological ages in the two cohorts were 74, and 61, respectively. Baseline GrimAgeAccel, and DNAm-related mortality risk score (DNAmRS) both had strong associations with all-cause death, MI, and stroke, independent from chronological age. For example, a one standard deviation (SD) increment in GrimAgeAccel was significantly associated with increased risk of all-cause death [hazard ratio (HR): 2.01; 95% confidence interval (CI), 1.15, 3.50], higher risk of MI (HR: 1.44; 95% CI, 1.16, 1.79), and elevated risk of stroke (HR: 1.42; 95% CI, 1.06, 1.91). There were no associations between any BoAA and cancer.

Interpretation

From the public health perspective, GrimAgeAccel is the most useful tool for identifying at-risk elderly, and evaluating the efficacy of anti-aging interventions.

Funding

National Institute of Environmental Health Sciences of U.S., Harvard Chan-NIEHS Center for Environmental Health, German Federal Ministry of Education and Research, and the State of Bavaria in Germany.

Genome-wide DNA methylation profiling in human breast tissue by Illumina TruSeq methyl capture EPIC sequencing and infinium methylationEPIC beadchip microarray

A newly-developed platform, the Illumina TruSeq Methyl Capture EPIC library prep (TruSeq EPIC), builds on the content of the Infinium MethylationEPIC Beadchip Microarray (EPIC-array) and leverages the power of next-generation sequencing for targeted bisulphite sequencing. We empirically examined the performance of TruSeq EPIC and EPIC-array in assessing genome-wide DNA methylation in breast tissue samples. TruSeq EPIC provided data with a much higher density in the regions when compared to EPIC-array (~2.74 million CpGs with at least 10X coverage vs ~752 K CpGs, respectively). Approximately 398 K CpGs were common and measured across the two platforms in every sample. Overall, there was high concordance in methylation levels between the two platforms (Pearson correlation r = 0.98, P < 0.0001). However, we observed that TruSeq EPIC measurements provided a wider dynamic range and likely a higher quantitative sensitivity for CpGs that were either hypo- or hyper-methylated (β close to 0 or 1, respectively). In addition, when comparing different breast tissue types TruSeq EPIC identified more differentially methylated CpGs than EPIC-array, not only out of additional sites interrogated by TruSeq EPIC alone, but also out of common sites interrogated by both platforms. Our results suggest that both platforms show high reproducibility and reliability in genome-wide DNA methylation profiling, while TruSeq EPIC had a significant improvement over EPIC-array regarding genomic resolution and coverage. The wider dynamic range and likely higher precision of the estimates by the TruSeq EPIC may lead to the identification of novel differentially methylated markers that are associated with disease risk.

EWAS Data Hub: a resource of DNA methylation array data and metadata

Epigenome-Wide Association Study (EWAS) has become an effective strategy to explore epigenetic basis of complex traits. Over the past decade, a large amount of epigenetic data, especially those sourced from DNA methylation array, has been accumulated as the result of numerous EWAS projects. We present EWAS Data Hub (https://bigd.big.ac.cn/ewas/datahub), a resource for collecting and normalizing DNA methylation array data as well as archiving associated metadata. The current release of EWAS Data Hub integrates a comprehensive collection of DNA methylation array data from 75 344 samples and employs an effective normalization method to remove batch effects among different datasets. Accordingly, taking advantages of both massive high-quality DNA methylation data and standardized metadata, EWAS Data Hub provides reference DNA methylation profiles under different contexts, involving 81 tissues/cell types (that contain 25 brain parts and 25 blood cell types), six ancestry categories, and 67 diseases (including 39 cancers). In summary, EWAS Data Hub bears great promise to aid the retrieval and discovery of methylation-based biomarkers for phenotype characterization, clinical treatment and health care.

DNA methylation biomarkers for nasopharyngeal carcinoma

Background

Aberrant methylation of DNA plays an important role in the pathogenesis of nasopharyngeal carcinoma (NPC). In the current study, we aimed to integrate three cohorts profile datasets to identify abnormally methylated-differentially expressed genes and pathways associated with NPC.

Methods

Data of gene expression microarrays (GSE53819, GSE412452) and gene methylation microarrays (GSE52068) obtained from the GEO database. Aberrantly methylated differentially expressed genes (DEGs) were obtained by GEO2R. The David database was utilized to perform enrichment and functional analysis regarding selected genes. To create a protein-protein interaction (PPI), STRING and Cytoscape software were utilized. The MCODE was used for module analysis of the PPI network.

Results

In total, 181 hypomethylation-high expression genes were identified, which were enriched in the biological mechanisms involved in the differentiation of endodermal cell, mitotic nuclear division, mitotic cell cycle process, chromosome segregation and cell cycle phase transition, etc. Pathway enrichment showed ECM-receptor interaction, PI3K-Akt signaling pathway, Focal adhesion, Protein digestion and absorption and Amoebiasis, etc. The top 3 hub genes of PPI network were FANCI, POSTN, and IFIH1. Additionally, 210 hypermethylation-low expression genes were identified, and our data revealed enrichment in biological processes including axoneme assembly, micro tubular formation, assembly of axonemal dynein complex, cilium movement and cilium organization, etc. Pathway analysis indicated enrichment in B cell receptor signaling pathway, Hematopoietic cell lineage, Leukocyte transendothelial migration, Complement and coagulation cascades and Fc gamma R-mediated phagocytosis, etc. The ZMYND10, PACRG and POU2AF1 were identified as the top three hub genes of PPI network. After validation in TCGA and GEPIA database, most hub genes remained significant. Patients with high expression of POSTN found to have shorter overall survival, while in patients with high expression of ZMYND10 and POU2AF1 longer overall survival was identified.

Conclusions

The data revealed novel aberrantly methylated-differentially expressed genes and pathways in NPC by bioinformatics analysis, potentially providing novel insights for the molecular mechanisms governing NPC progression. Hub genes including FANCI, POSTN, IFIH1, ZMYND10, PACRG and POU2AF1 might serve as novel biomarkers for precision diagnosis and providing medical treatment for patient with NPC.

Prenatal lead exposure and cord blood DNA methylation in PROGRESS: an epigenome-wide association study

The effects of prenatal lead exposure on child development include impaired growth and cognitive function. DNA methylation might be involved in the underlying mechanisms and previous epigenome-wide association studies reported associations between lead exposure during pregnancy and cord blood methylation levels. However, it is unclear during which developmental stage lead exposure is most harmful. Cord blood methylation levels were assayed in 420 children from a Mexican pre-birth cohort using the Illumina Infinium MethylationEPIC microarray. Lead concentrations were measured in umbilical cord blood as well as in blood samples from the mothers collected at 2nd and 3rd trimester and delivery using inductively coupled plasma-mass spectrometry. In addition, maternal bone lead levels were measured in tibia and patella using X-ray fluorescence. Comprehensive quality control and preprocessing of microarray data was followed by an unbiased restriction to methylation sites with substantial variance. Methylation levels at 202 111 cytosine-phosphate-guanine sites were regressed on each exposure adjusting for child sex, leukocyte composition, batch variables, gestational age, birthweight-for-gestational-age, maternal age, maternal education and mode of delivery. We find no association between prenatal lead exposure and cord blood methylation. This null result is strengthened by a sensitivity analysis showing that in the same dataset known biomarkers for birthweight-for-gestational-age can be recovered and the fact that phenotypic associations with lead exposure have been described in the same cohort.

Methylomic profiling in trisomy 21 identifies cognition- and Alzheimer's disease-related dysregulation

Abstract

Background

Trisomy 21 (T21) is associated with intellectual disability that ranges from mild to profound with an average intellectual quotient of around 50. Furthermore, T21 patients have a high risk of developing Alzheimer’s disease (AD) early in life, characterized by the presence of senile plaques of amyloid protein and neurofibrillary tangles, leading to neuronal loss and cognitive decline. We postulate that epigenetic factors contribute to the observed variability in intellectual disability, as well as at the level of neurodegeneration seen in T21 individuals.

Materials and Methods

A genome-wide DNA methylation study was performed using Illumina Infinium® MethylationEPIC BeadChips on whole blood DNA of 3 male T21 patients with low IQ, 8 T21 patients with high IQ (4 males and 4 females), and 21 age- and sex-matched control samples (12 males and 9 females) in order to determine whether DNA methylation alterations could help explain variation in cognitive impairment between individuals with T21. In view of the increased risk of developing AD in T21 individuals, we additionally investigated the T21-associated sites in published blood DNA methylation data from the AgeCoDe cohort (German study on Ageing, Cognition, and Dementia). AgeCoDe represents a prospective longitudinal study including non-demented individuals at baseline of which a part develops AD dementia at follow-up.

Results

Two thousand seven hundred sixteen differentially methylated sites and regions discriminating T21 and healthy individuals were identified. In the T21 high and low IQ comparison, a single CpG located in the promoter of PELI1 was differentially methylated after multiple testing adjustment. For the same contrast, 69 differentially methylated regions were identified. Performing a targeted association analysis for the significant T21-associated CpG sites in the AgeCoDe cohort, we found that 9 showed significant methylation differences related to AD dementia, including one in the ADAM10 gene. This gene has previously been shown to play a role in the prevention of amyloid plaque formation in the brain.

Conclusion

The differentially methylated regions may help understand the interaction between methylation alterations and cognitive function. In addition, ADAM10 might be a valuable blood-based biomarker for at least the early detection of AD.

Alzheimer's disease-associated (hydroxy)methylomic changes in the brain and blood

BACKGROUND

Late-onset Alzheimer's disease (AD) is a complex multifactorial affliction, the pathogenesis of which is thought to involve gene-environment interactions that might be captured in the epigenome. The present study investigated epigenome-wide patterns of DNA methylation (5-methylcytosine, 5mC) and hydroxymethylation (5-hydroxymethylcytosine, 5hmC), as well as the abundance of unmodified cytosine (UC), in relation to AD.

RESULTS

We identified epigenetic differences in AD patients (n = 45) as compared to age-matched controls (n = 35) in the middle temporal gyrus, pertaining to genomic regions close to or overlapping with genes such as OXT (- 3.76% 5mC, pŠidák = 1.07E-06), CHRNB1 (+ 1.46% 5hmC, pŠidák = 4.01E-04), RHBDF2 (- 3.45% UC, pŠidák = 4.85E-06), and C3 (- 1.20% UC, pŠidák = 1.57E-03). In parallel, in an independent cohort, we compared the blood methylome of converters to AD dementia (n = 54) and non-converters (n = 42), at a preclinical stage. DNA methylation in the same region of the OXT promoter as found in the brain was found to be associated with subsequent conversion to AD dementia in the blood of elderly, non-demented individuals (+ 3.43% 5mC, pŠidák = 7.14E-04).

CONCLUSIONS

The implication of genome-wide significant differential methylation of OXT, encoding oxytocin, in two independent cohorts indicates it is a promising target for future studies on early biomarkers and novel therapeutic strategies in AD.

The Personal Genome Project-UK, an open access resource of human multi-omics data

Integrative analysis of multi-omics data is a powerful approach for gaining functional insights into biological and medical processes. Conducting these multifaceted analyses on human samples is often complicated by the fact that the raw sequencing output is rarely available under open access. The Personal Genome Project UK (PGP-UK) is one of few resources that recruits its participants under open consent and makes the resulting multi-omics data freely and openly available. As part of this resource, we describe the PGP-UK multi-omics reference panel consisting of ten genomic, methylomic and transcriptomic data. Specifically, we outline the data processing, quality control and validation procedures which were implemented to ensure data integrity and exclude sample mix-ups. In addition, we provide a REST API to facilitate the download of the entire PGP-UK dataset. The data are also available from two cloud-based environments, providing platforms for free integrated analysis. In conclusion, the genotype-validated PGP-UK multi-omics human reference panel described here provides a valuable new open access resource for integrated analyses in support of personal and medical genomics.

Battle of epigenetic proportions: comparing Illumina's EPIC methylation microarrays and TruSeq targeted bisulfite sequencing

DNA methylation microarrays have been the platform of choice for epigenome-wide association studies in epidemiology, but declining costs have rendered targeted bisulphite sequencing a feasible alternative. Nonetheless, the literature for researchers seeking guidance on which platform to choose is sparse. To fill this gap, we conducted a comparison study in which we processed cord blood samples from four newborns in duplicates using both the Illumina HumanMethylationEPIC BeadChip and the Illumina TruSeq Methyl Capture EPIC Kit, and evaluated both platforms in regard to coverage, reproducibility, and identification of differential methylation. We conclude that with current analytic goals microarrays still outperform bisulphite sequencing for precise quantification of DNA methylation.

Estimation of DNA contamination and its sources in genotyped samples

Array genotyping is a cost-effective and widely used tool that enables assessment of up to millions of genetic markers in hundreds of thousands of individuals. Genotyping array data are typically highly accurate but sensitive to mixing of DNA samples from multiple individuals before or during genotyping. Contaminated samples can lead to genotyping errors and consequently cause false positive signals or reduce power of association analyses. Here, we propose a new method to identify contaminated samples and the sources of contamination within a genotyping batch. Through analysis of array intensity and genotype data from intentionally mixed samples and 22,366 samples of the Michigan Genomics Initiative, an ongoing biobank-based study, we show that our method can reliably estimate contamination. We also show that identifying sources of contamination can implicate problematic sample processing steps and guide process improvements. Compared to existing methods, our approach can estimate the proportion of contaminating DNA more accurately, eliminate the need for external databases of allele frequencies, and provide contamination estimates that are more robust to the ancestral origin of the contaminating sample.

DNA methylation changes associated with Parkinson's disease progression: outcomes from the first longitudinal genome-wide methylation analysis in blood

Parkinson's Disease (PD) is a common neurodegenerative disorder currently diagnosed based on the presentation of characteristic movement symptoms. Unfortunately, patients exhibiting these symptoms have already undergone significant dopaminergic neuronal loss. Earlier diagnosis, aided by molecular biomarkers specific to PD, would improve overall patient care. Epigenetic mechanisms, which are modified by both environment and disease pathophysiology, are emerging as important components of neurodegeneration. Alterations to the PD methylome have been reported in epigenome-wide association studies. However, the extent to which methylation changes correlate with disease progression has not yet been reported; nor the degree to which methylation is affected by PD medication. We performed a longitudinal genome-wide methylation study surveying ~850,000 CpG sites in whole blood from 189 well-characterized PD patients and 191 control individuals obtained at baseline and at a follow-up visit ~2 y later. We identified distinct patterns of methylation in PD cases versus controls. Importantly, we identified genomic sites where methylation changes longitudinally as the disease progresses. Moreover, we identified methylation changes associated with PD pathology through the analysis of PD cases that were not exposed to anti-parkinsonian therapy. In addition, we identified methylation sites modulated by exposure to dopamine replacement drugs. These results indicate that DNA methylation is dynamic in PD and changes over time during disease progression. To the best of our knowledge, this is the first longitudinal epigenome-wide methylation analysis for Parkinson's disease and reveals changes associated with disease progression and in response to dopaminergic medications in the blood methylome.

Improved filtering of DNA methylation microarray data by detection p values and its impact on downstream analyses

Background

DNA methylation microarrays are popular for epigenome-wide association studies (EWAS), but spurious values complicate downstream analysis and threaten replication. Conventional cut-offs for detection p values for filtering out undetected probes were demonstrated in a single previous study as insufficient leading to many apparent methylation calls in samples from females in probes targeting the Y-chromosome. We present an alternative approach to calculate more accurate detection p values utilizing non-specific background fluorescence. We evaluate and compare our proposed approach of filtering observations with conventional ones by assessing the detection of Y-chromosome probes among males and females in 2755 samples from 17 studies on the 450K microarray and masking of large outliers between technical replicates and their impact downstream via an EWAS reanalysis.

Results

In contrast to conventional approaches, ours marks most Y-chromosome probes in females as undetected while removing a median of only 0.14% of the data per sample, catches more (30% vs. 6%) of large outliers (more than 20 percentage point difference between technical replicates), and helps to identify strong associations previously obfuscated by outliers between whole blood DNA methylation and chronological age in a well-powered EWAS (n = 729).

Conclusions

We provide guidance for filtering both 450K and EPIC microarrays as an essential preprocessing step to reduce spurious values. An implementation (including a function compatible with objects from the popular minfi package) was added to ewastools, an R package for comprehensive quality control of DNA methylation microarrays. Scripts to reproduce all analyses are available at doi.org/10.5281/zenodo.1443561.

Functional Transcriptomics for Bacterial Gene Detectives

Developments in transcriptomic technology and the availability of whole-genome-level expression profiles for many bacterial model organisms have accelerated the assignment of gene function. However, the deluge of transcriptomic data is making the analysis of gene expression a challenging task for biologists. Online resources for global bacterial gene expression analysis are not available for the majority of published data sets, impeding access and hindering data exploration. Here, we show the value of preexisting transcriptomic data sets for hypothesis generation. We describe the use of accessible online resources, such as SalComMac and SalComRegulon, to visualize and analyze expression profiles of coding genes and small RNAs. This approach arms a new generation of "gene detectives" with powerful new tools for understanding the transcriptional networks of Salmonella, a bacterium that has become an important model organism for the study of gene regulation. To demonstrate the value of integrating different online platforms, and to show the simplicity of the approach, we used well-characterized small RNAs that respond to envelope stress, oxidative stress, osmotic stress, or iron limitation as examples. We hope to provide impetus for the development of more online resources to allow the scientific community to work intuitively with transcriptomic data.