Blood-derived DNA Methylation Research Articles

Blood-based multivariate methylation risk score for cognitive impairment and dementia.

The established link between DNA methylation and pathophysiology of dementia, along with its potential role as a molecular mediator of lifestyle and environmental influences, positions blood-derived DNA methylation as a promising tool for early dementia risk detection. In conjunction with an extensive array of machine learning techniques, we employed whole blood genome-wide DNA methylation data as a surrogate for 14 modifiable and non-modifiable factors in the assessment of dementia risk in independent dementia cohorts. We established a multivariate methylation risk score (MMRS) for identifying mild cognitive impairment cross-sectionally, independent of age and sex (P=2.0×10-3). This score significantly predicted the prospective development of cognitive impairments in independent studies of Alzheimer's disease (hazard ratio for Rey's Auditory Verbal Learning Test (RAVLT)-Learning=2.47) and Parkinson's disease (hazard ratio for MCI/dementia=2.59). Our work shows the potential of employing blood-derived DNA methylation data in the assessment of dementia risk. We used whole blood DNA methylation as a surrogate for 14 dementia risk factors. Created a multivariate methylation risk score for predicting cognitive impairment. Emphasized the role of machine learning and omics data in predicting dementia. The score predicts cognitive impairment development at the population level.

Blood-based DNA methylation and exposure risk scores predict PTSD with high accuracy in military and civilian cohorts

BackgroundIncorporating genomic data into risk prediction has become an increasingly popular approach for rapid identification of individuals most at risk for complex disorders such as PTSD. Our goal was to develop and validate Methylation Risk Scores (MRS) using machine learning to distinguish individuals who have PTSD from those who do not.MethodsElastic Net was used to develop three risk score models using a discovery dataset (n = 1226; 314 cases, 912 controls) comprised of 5 diverse cohorts with available blood-derived DNA methylation (DNAm) measured on the Illumina Epic BeadChip. The first risk score, exposure and methylation risk score (eMRS) used cumulative and childhood trauma exposure and DNAm variables; the second, methylation-only risk score (MoRS) was based solely on DNAm data; the third, methylation-only risk scores with adjusted exposure variables (MoRSAE) utilized DNAm data adjusted for the two exposure variables. The potential of these risk scores to predict future PTSD based on pre-deployment data was also assessed. External validation of risk scores was conducted in four independent cohorts.ResultsThe eMRS model showed the highest accuracy (92%), precision (91%), recall (87%), and f1-score (89%) in classifying PTSD using 3730 features. While still highly accurate, the MoRS (accuracy = 89%) using 3728 features and MoRSAE (accuracy = 84%) using 4150 features showed a decline in classification power. eMRS significantly predicted PTSD in one of the four independent cohorts, the BEAR cohort (beta = 0.6839, p=0.006), but not in the remaining three cohorts. Pre-deployment risk scores from all models (eMRS, beta = 1.92; MoRS, beta = 1.99 and MoRSAE, beta = 1.77) displayed a significant (p < 0.001) predictive power for post-deployment PTSD.ConclusionThe inclusion of exposure variables adds to the predictive power of MRS. Classification-based MRS may be useful in predicting risk of future PTSD in populations with anticipated trauma exposure. As more data become available, including additional molecular, environmental, and psychosocial factors in these scores may enhance their accuracy in predicting PTSD and, relatedly, improve their performance in independent cohorts.

A Common OXTR Risk Variant Alters Regulation of Gene Expression by DNA Hydroxymethylation in Pregnant Human Myometrium

Postpartum hemorrhage, or excessive bleeding after birth, is a leading cause of maternal morbidity. A major cause of postpartum hemorrhage is uterine atony, tiring of the uterus which leads to ineffective contractions. Uterine contractions depend on oxytocin signaling in the myometrium, which in turn depends on expression of the oxytocin receptor (OXTR). Both genetic and epigenetic factors related to the oxytocin receptor are associated with risk of postpartum hemorrhage, but a mechanism relating these factors to oxytocin receptor activity in myometrium remains unclear. We report a genetic by epigenetic interaction whereby the relationship between DNA hydroxymethylation and OXTR gene expression depends on a common OXTR gene variant (rs53576). We also provide evidence that a similar genetic by epigenetic interaction using blood-derived DNA methylation is associated with relevant clinical outcomes: quantity of oxytocin administration and odds for postpartum hemorrhage. These results provide new avenues for predicting how women will respond to pharmacological agents in the prevention and treatment of postpartum hemorrhage.

Sex effects on DNA methylation affect discovery in epigenome-wide association study of schizophrenia

Sex differences in the epidemiology and clinical characteristics of schizophrenia are well-known; however, the molecular mechanisms underlying these differences remain unclear. Further, the potential advantages of sex-stratified meta-analyses of epigenome-wide association studies (EWAS) of schizophrenia have not been investigated. Here, we performed sex-stratified EWAS meta-analyses to investigate whether sex stratification improves discovery, and to identify differentially methylated regions (DMRs) in schizophrenia. Peripheral blood-derived DNA methylation data from 1519 cases of schizophrenia (male n = 989, female n = 530) and 1723 controls (male n = 997, female n = 726) from three publicly available datasets, and the TOP cohort were meta-analyzed to compare sex-specific, sex-stratified, and sex-adjusted EWAS. The predictive power of each model was assessed by polymethylation score (PMS). The number of schizophrenia-associated differentially methylated positions identified was higher for the sex-stratified model than for the sex-adjusted one. We identified 20 schizophrenia-associated DMRs in the sex-stratified analysis. PMS from sex-stratified analysis outperformed that from sex-adjusted analysis in predicting schizophrenia. Notably, PMSs from the sex-stratified and female-only analyses, but not those from sex-adjusted or the male-only analyses, significantly predicted schizophrenia in males. The findings suggest that sex-stratified EWAS meta-analyses improve the identification of schizophrenia-associated epigenetic changes and highlight an interaction between sex and schizophrenia status on DNA methylation. Sex-specific DNA methylation may have potential implications for precision psychiatry and the development of stratified treatments for schizophrenia.

Epigenome-wide association study on ambient PM2.5 exposure in Han Chinese, the NSPT study

Ambient PM2.5 exposure has been recognized as a major health risk and related to aging, cardiovascular, respiratory and neurologic diseases, and cancer. However, underlying mechanism of epigenetic alteration and regulated pathways still remained unclear. The study on methylome effect of PM2.5 exposure was quite limited in Chinese population, and cohort-based study was absent. The study included blood-derived DNA methylation for 3365 Chinese participants from the NSPT cohort. We estimated individual PM2.5 exposure level of short-medium-, medium- and long-term, based on a validated prediction model. We preformed epigenome-wide association studies to estimate the links between PM2.5 exposure and DNA methylation change, as well as stratification and sensitive analysis to examined the robustness of the association models. A systematic review was conducted to obtain the previously published CpGs and examined for replication. We also conducted comparison on the DNA methylation variation corresponding to different time windows. We further conducted gene function analysis and pathway enrichment analysis to reveal related biological response. We identified a total of 177 CpGs and 107 DMRs associated with short-medium-term PM2.5 exposure, at a strict genome-wide significance (P < 5 × 10−8). The effect sizes on most CpGs tended to cease with the exposure of extended time scale. Associated markers and aligned genes were related to aging, immunity, inflammation and carcinogenesis. Enriched pathways were mostly involved in cell cycle and cell division, signal transduction, inflammatory pathway. Our study is the first EWAS on PM2.5 exposure conducted in large-scale Han Chinese cohort and identified associated DNA methylation change on CpGs and regions, as well as related gene functions and pathways.

Epigenome-wide association study on short-, intermediate- and long-term ozone exposure in Han Chinese, the NSPT study

Epidemiological and epigenetic studies have acknowledged ambient ozone exposure associated with inflammatory and cardiovascular disease. However, the molecular mechanisms still remained unclear, and epigenome-wide analysis in cohort were lacking, especially in Chinese. We included blood-derived DNA methylation for 3365 Chinese participants from the NSPT cohort and estimated individual ozone exposure level of short-, intermediate- and long-term, based on a validated prediction model. We performed epigenome-wide association studies which identified 59 CpGs and 30 DMRs at a strict genome-wide significance (P < 5 ×10−8). We also conducted comparison on the DNA methylation alteration corresponding to different time windows, and observed an enhanced differentiated methylation trend for intermediate- and long-term exposure, while the short-term exposure associated methylation changes did not retain. The targeted genes of methylation alteration were involved in mechanism related to aging, inflammation disease, metabolic syndrome, neurodevelopmental disorders, and oncogenesis. Underlying pathways were enriched in biological activities including telomere maintenance process, DNA damage response and megakaryocyte differentiation. In conclusion, our study is the first EWAS on ozone exposure conducted in large-scale Han Chinese cohort and identified associated DNA methylation change on CpGs and regions, as well as related gene functions and pathways.

Epigenome-wide meta-analysis identifies DNA methylation biomarkers associated with diabetic kidney disease

Type 1 diabetes affects over nine million individuals globally, with approximately 40% developing diabetic kidney disease. Emerging evidence suggests that epigenetic alterations, such as DNA methylation, are involved in diabetic kidney disease. Here we assess differences in blood-derived genome-wide DNA methylation associated with diabetic kidney disease in 1304 carefully characterised individuals with type 1 diabetes and known renal status from two cohorts in the United Kingdom-Republic of Ireland and Finland. In the meta-analysis, we identify 32 differentially methylated CpGs in diabetic kidney disease in type 1 diabetes, 18 of which are located within genes differentially expressed in kidneys or correlated with pathological traits in diabetic kidney disease. We show that methylation at 21 of the 32 CpGs predict the development of kidney failure, extending the knowledge and potentially identifying individuals at greater risk for diabetic kidney disease in type 1 diabetes.

Wildfire-related PM2.5 and DNA methylation: An Australian twin and family study

BackgroundWildfire-related fine particulate matter (PM2.5) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM2.5. MethodsWe studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant’s home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate. ResultsThe 3-year average wildfire-related PM2.5 (range: 0.3 to 7.6 µg/m3, mean: 1.6 µg/m3) was negatively, but not significantly (p-values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM2.5 (Bonferroni adjusted p-value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM2.5. ConclusionsLong-term exposure to wildfire-related PM2.5 was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM2.5.

Blood-based DNA methylation profiling for the detection of ovarian cancer

ObjectivesOvarian cancer is a fatal gynecological cancer due to the lack of effective screening strategies at early stage. This study explored the utility of DNA methylation profiling of blood samples for the detection of ovarian cancer. MethodsTargeted bisulfite sequencing was performed on tissue (n = 152) and blood samples (n = 373) obtained from healthy women, women with benign ovarian tumors, or malignant epithelial ovarian tumors. Based on the tissue-derived differentially-methylated regions, a supervised machine learning algorithm was implemented and cross-validated using the blood-derived DNA methylation profiles of the training cohort (n = 178) to predict and classify each blood sample as malignant or non-malignant. The model was further evaluated using an independent test cohort (n = 184). ResultsComparison of the DNA methylation profiles of normal/benign and malignant tumor samples identified 1272 differentially-methylated regions, with 49.4% hypermethylated regions and 50.6% hypomethylated regions. Five-fold cross-validation of the model using the training dataset yielded an area under the curve of 0.94. Using the test dataset, the model accurately predicted non-malignancy in 96.2% of healthy women (n = 53) and 93.5% of women with benign tumors (n = 46). For patients with malignant tumors, the model accurately predicted malignancy in 44.4% of stage I-II (n = 9), 86.4% of stage III (n = 59), 100.0% of stage IV tumors (n = 6), and 81.8% of tumors with unknown stage (n = 11). Overall, the model yielded a predictive accuracy of 89.5%. ConclusionsOur study demonstrates the potential clinical application of blood-based DNA methylation profiling for the detection of ovarian cancer.

Associations of Heavy Metals with Activities of Daily Living Disability: An Epigenome-Wide View of DNA Methylation and Mediation Analysis.

Background:Exposure to heavy metals has been reported to be associated with multiple diseases. However, direct associations and potential mechanisms of heavy metals with physical disability remain unclear.Objectives:We aimed to quantify associations of heavy metals with physical disability and further explore the potential mechanisms of DNA methylation on the genome scale.Methods:A cross-sectional study of 4,391 older adults was conducted and activities of daily living (ADL) disability were identified using a 14-item scale questionnaire including basic and instrumental activities to assess the presence of disability (yes or no) rated on a scale of dependence. Odds ratios (ORs) and 95% confidence intervals (CI) were estimated to quantify associations between heavy metals and ADL disability prevalence using multivariate logistic regression and Bayesian kernel machine regression (BKMR) models. Whole blood–derived DNA methylation was measured using the HumanMethylationEPIC BeadChip array. An ADL disability-related epigenome-wide DNA methylation association study (EWAS) was performed among 212 sex-matched ADL disability cases and controls, and mediation analysis was further applied to explore potential mediators of DNA methylation.Results:Each 1-standard deviation (SD) higher difference in -transformed manganese, copper, arsenic, and cadmium level was significantly associated with a 14% (95% CI: 1.05, 1.24), 16% (95% CI:1.07, 1.26), 22% (95% CI:1.13, 1.33), and 15% (95% CI:1.06, 1.26) higher odds of ADL disability, which remained significant in the multiple-metal and BKMR models. A total of 85 differential DNA methylation sites were identified to be associated with ADL disability prevalence, among which methylation level at cg220000984 and cg23012519 (annotated to IRGM and PKP3) mediated 31.0% and 31.2% of manganese-associated ADL disability prevalence, cg06723863 (annotated to ESRP2) mediated 32.4% of copper-associated ADL disability prevalence, cg24433124 (nearest to IER3) mediated 15.8% of arsenic-associated ADL disability prevalence, and cg07905190 and cg17485717 (annotated to FREM1 and TCP11L1) mediated 21.5% and 30.5% of cadmium-associated ADL disability prevalence (all ).Discussion:Our findings suggested that heavy metals contributed to higher prevalence of ADL disability and that locus-specific DNA methylation are partial mediators, providing potential biomarkers for further cellular mechanism studies. https://doi.org/10.1289/EHP10602

Residential surrounding greenness and DNA methylation: an epigenome-wide association study

BACKGROUND AND AIM: DNA methylation is a potential biological mechanism through which residential greenness affects health, but little is known about its association with greenness and whether the association could be modified by genetic background. We aimed to evaluate the association between surrounding greenness and genome-wide DNA methylation and potential gene-greenness interaction effects on DNA methylation. METHODS: We measured blood-derived DNA methylation using the HumanMethylation450 BeadChip array (Illumina) for 479 Australian women, including 66 monozygotic, 66 dizygotic twin pairs, and 215 sisters of these twins. Surrounding greenness was represented by Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) within 300, 500, 1000 or 2000 metres surrounding participants’ home addresses. For each cytosine-guanine dinucleotide (CpG), the association between its methylation level and NDVI or EVI were evaluated by generalized estimating equations, adjusting for age, education, marital status, area-level socioeconomic status, smoking behavior, cell-type proportions and familial clustering. We used comb-p and DMRcate to identify significant differentially methylated regions (DMRs). For each significant CpG, we evaluated the interaction effects of greenness and single-nucleotide polymorphisms (SNPs) within ±1Mb window on its methylation level. RESULTS:We found associations between surrounding greenness and blood DNA methylation for one CpG (cg04720477, mapped to the promoter region of CNP gene) with false discovery rate [FDR]0.05, and for another 9 CpGs with 0.05≤FDR0.10. For two of these CpGs, we found 33 SNPs significantly (FDR0.05) modified the greenness-methylation association. There were 35 significant DMRs related to surrounding greenness that were identified by both comb-p (Sidak p-value0.01) and DMRcate (FDR0.01). Those CpGs and DMRs were mapped to genes related to many human diseases, such as mental health disorders and neoplasms as well as nutritional and metabolic diseases. CONCLUSIONS:Surrounding greenness was associated with blood DNA methylation of many loci across human genome, and this association could be modified by genetic variations. KEYWORDS: Green space, Epigenomics, Molecular epidemiology, Environmental epidemiology

Ambient temperature and genome-wide DNA methylation: A twin and family study in Australia

Little is known about the association between ambient temperature and DNA methylation, which is a potential biological process through which ambient temperature affects health. This study aimed to evaluate the association between ambient temperature and DNA methylation across human genome. We included 479 Australian women, including 132 twin pairs and 215 sisters of these twins. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on average ambient temperature during eight different exposure windows [lag0d (the blood draw day), lag0-7d (the current day and previous seven days prior to blood draw), lag0-14d, lag0-21d, lag0-28d, lag0-90d, lag0-180d, and lag0-365d)] was linked to each participant's home address. For each cytosine-guanine dinucleotide (CpG), we evaluated the association between its methylation level and temperature using generalized estimating equations (GEE), adjusting for important covariates. We used comb-p and DMRcate to identify differentially methylated regions (DMRs). We identified 31 CpGs at which blood DNA methylation were significantly associated with ambient temperature with false discovery rate [FDR] < 0.05. There were 82 significant DMRs identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Most of these CpGs and DMRs only showed association with temperature during one specific exposure window. These CpGs and DMRs were mapped to 85 genes. These related genes have been related to many human chronic diseases or phenotypes (e.g., diabetes, arthritis, breast cancer, depression, asthma, body height) in previous studies. The signals of short-term windows (lag0d and lag0-21d) showed enrichment in biological processes related to cell adhesion. In conclusion, short-, medium-, and long-term exposures to ambient temperature were all associated with blood DNA methylation, but the target genomic loci varied by exposure window. These differential methylation signals may serve as potential biomarkers to understand the health impacts of temperature.

Hypothalamus volume and DNA methylation of stress axis genes in major depressive disorder: A CAN-BIND study report

Dysfunction of the hypothalamic-pituitary-adrenal (HPA) axis is considered one of the mechanisms underlying the development of major depressive disorder (MDD), but the exact nature of this dysfunction is unknown. We investigated the relationship between hypothalamus volume (HV) and blood-derived DNA methylation in MDD. We obtained brain MRI, clinical and molecular data from 181 unmedicated MDD and 90 healthy control (HC) participants. MDD participants received a 16-week standardized antidepressant treatment protocol, as part of the first Canadian Biomarker Integration Network in Depression (CAN-BIND) study. We collected bilateral HV measures via manual segmentation by two independent raters. DNA methylation and RNA sequencing were performed for three key HPA axis-regulating genes coding for the corticotropin-binding protein (CRHBP), glucocorticoid receptor (NR3C1) and FK506 binding protein 5 (FKBP5). We used elastic net regression to perform variable selection and assess predictive ability of methylation variables on HV. Left HV was negatively associated with duration of current episode (ρ = −0.17, p = 0.035). We did not observe significant differences in HV between MDD and HC or any associations between HV and treatment response at weeks 8 or 16, overall depression severity, illness duration or childhood maltreatment. We also did not observe any differentially methylated CpG sites between MDD and HC groups. After assessing functionality by correlating methylation levels with RNA expression of the respective genes, we observed that the number of functionally relevant CpG sites differed between MDD and HC groups in FKBP5 (χ2 = 77.25, p < 0.0001) and NR3C1 (χ2 = 7.29, p = 0.007). Cross-referencing functionally relevant CpG sites to those that were highly ranked in predicting HV in elastic net modeling identified one site from FKBP5 (cg03591753) and one from NR3C1 (cg20728768) within the MDD group. Stronger associations between DNA methylation, gene expression and HV in MDD suggest a novel putative molecular pathway of stress-related sensitivity in depression. Future studies should consider utilizing the epigenome and ultra-high field MR data which would allow the investigation of HV sub-fields.

Association of ZNF331 and WIF1 methylation in peripheral blood leukocytes with the risk and prognosis of gastric cancer

BackgroundPeripheral blood leukocyte (PBL) DNA methylation may serve as a surrogate marker to evaluate the susceptibility to and prognosis of gastric cancer (GC). In this study, blood-derived DNA methylation levels of two tumour-related genes, namely, ZNF331 and WIF1, and their impacts on the risk and prognosis of GC were evaluated.MethodsIn total, 398 GC cases and 397 controls were recruited for the study. Then, all cases were followed up for 5 years. ZNF331 and WIF1 promoter methylation status in PBLs was measured using a methylation-sensitive high-resolution melting method. Logistic and Cox regression models were used to analyse the correlation between gene methylation and the risk and prognosis of GC. Confounders were balanced through propensity score (PS) matching.ResultsHigh ZNF331 methylation significantly decreased GC risk after PS adjustment (OR = 0.580, 95% CI: 0.375–0.898, P = 0.015), which also presented in males (OR = 0.577, 95% CI: 0.343–0.970, P = 0.038). However, WIF1 methylation was not associated with GC risk. Additionally, significant combined effects between ZNF331 methylation and the intake of green vegetables and garlic were observed (OR = 0.073, 95% CI: 0.027–0.196, P < 0.001 and OR = 0.138, 95% CI: 0.080–0.238, P < 0.001, respectively). Furthermore, ZNF331 and WIF1 methylation had no impact on the prognosis of GC.ConclusionZNF331 methylation in PBLs may affect GC risk in combination with the consumption of green vegetables and garlic and may act as a potential biomarker of GC.

Assessment of differentially methylated loci in individuals with end-stage kidney disease attributed to diabetic kidney disease: an exploratory study

BackgroundA subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina’s Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10–8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM.ResultsTop-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation.ConclusionsEpigenetic alterations provide a dynamic link between an individual’s genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.

Residential surrounding greenness and DNA methylation: An epigenome-wide association study

BackgroundDNA methylation is a potential biological mechanism through which residential greenness affects health, but little is known about its association with greenness and whether the association could be modified by genetic background. We aimed to evaluate the association between surrounding greenness and genome-wide DNA methylation and potential gene-greenness interaction effects on DNA methylation. MethodsWe measured blood-derived DNA methylation using the HumanMethylation450 BeadChip array (Illumina) for 479 Australian women, including 66 monozygotic, 66 dizygotic twin pairs, and 215 sisters of these twins. Surrounding greenness was represented by Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) within 300, 500, 1000 or 2000 m surrounding participants’ home addresses. For each cytosine-guanine dinucleotide (CpG), the associations between its methylation level and NDVI or EVI were evaluated by generalized estimating equations, after adjusting for age, education, marital status, area-level socioeconomic status, smoking behavior, cell-type proportions, and familial clustering. We used comb-p and DMRcate to identify significant differentially methylated regions (DMRs). For each significant CpG, we evaluated the interaction effects of greenness and single-nucleotide polymorphisms (SNPs) within ±1 Mb window on its methylation level. ResultsWe found associations between surrounding greenness and blood DNA methylation for one CpG (cg04720477, mapped to the promoter region of CNP gene) with false discovery rate [FDR] < 0.05, and for another 9 CpGs with 0.05 ≤ FDR < 0.10. For two of these CpGs, we found 33 SNPs significantly (FDR < 0.05) modified the greenness-methylation association. There were 35 significant DMRs related to surrounding greenness that were identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Those CpGs and DMRs were mapped to genes related to many human diseases, such as mental health disorders and neoplasms as well as nutritional and metabolic diseases. ConclusionsSurrounding greenness was associated with blood DNA methylation of many loci across human genome, and this association could be modified by genetic variations.

Epigenome-wide meta-analysis of PTSD across 10 military and civilian cohorts identifies methylation changes in AHRR

Epigenetic differences may help to distinguish between PTSD cases and trauma-exposed controls. Here, we describe the results of the largest DNA methylation meta-analysis of PTSD to date. Ten cohorts, military and civilian, contribute blood-derived DNA methylation data from 1,896 PTSD cases and trauma-exposed controls. Four CpG sites within the aryl-hydrocarbon receptor repressor (AHRR) associate with PTSD after adjustment for multiple comparisons, with lower DNA methylation in PTSD cases relative to controls. Although AHRR methylation is known to associate with smoking, the AHRR association with PTSD is most pronounced in non-smokers, suggesting the result was independent of smoking status. Evaluation of metabolomics data reveals that AHRR methylation associated with kynurenine levels, which are lower among subjects with PTSD. This study supports epigenetic differences in those with PTSD and suggests a role for decreased kynurenine as a contributor to immune dysregulation in PTSD.

Epigenome-wide DNA methylation and risk of breast cancer: a systematic review

BackgroundDNA methylation is a potential biomarker for early detection of breast cancer. However, robust evidence of a prospective relationship between DNA methylation patterns and breast cancer risk is still lacking. The objective of this study is to provide a systematic analysis of the findings of epigenome-wide DNA methylation studies on breast cancer risk, in light of their methodological strengths and weaknesses.MethodsWe searched major databases (MEDLINE, EMBASE, Web of Science, CENTRAL) from inception up to 30th June 2019, for observational or intervention studies investigating the association between epigenome-wide DNA methylation (using the HM450k or EPIC BeadChip), measured in any type of human sample, and breast cancer risk. A pre-established protocol was drawn up following the Cochrane Reviews rigorous methodology. Study selection, data abstraction, and risk of bias assessment were performed by at least two investigators. A qualitative synthesis and systematic comparison of the strengths and weaknesses of studies was performed.ResultsOverall, 20 studies using the HM450k BeadChip were included, 17 of which had measured blood-derived DNA methylation. There was a consistent trend toward an association of global blood-derived DNA hypomethylation and higher epigenetic age with higher risk of breast cancer. The strength of associations was modest for global hypomethylation and relatively weak for most of epigenetic age algorithms. Differences in length of follow-up periods may have influenced the ability to detect associations, as studies reporting follow-up periods shorter than 10 years were more likely to observe an association with global DNA methylation. Probe-wise differential methylation analyses identified between one and 806 differentially methylated CpGs positions in 10 studies. None of the identified differentially methylated sites overlapped between studies. Three studies used breast tissue DNA and suffered major methodological issues that precludes any conclusion. Overall risk of bias was critical mainly because of incomplete control of confounding. Important issues relative to data preprocessing could have limited the consistency of results.ConclusionsGlobal DNA methylation may be a short-term predictor of breast cancer risk. Further studies with rigorous methodology are needed to determine spatial distribution of DNA hypomethylation and identify differentially methylated sites associated with risk of breast cancer.Prospero registration numberCRD42020147244

Statistical challenges in the analysis of blood-derived DNA methylation data from environmental epidemiology studies

Title: Statistical challenges in the analysis of blood-derived DNA methylation data from environmental epidemiology studiesAbstract: One of the foremost challenges in the analysis and interpretation of epigenomic data is the issue of cellular heterogeneity and its potential confounding effects on studies that aim to understand the relationship between DNA methylation and some phenotype or exposure. This is especially true of whole blood, which represents one of the most commonly used tissue types for environmental epigenomic studies due to its relatively easy accessibility, and because of a heightened interest in the immonomethylomic effects of environmental insults. Whole blood is a heterogenous and complex mixture of many different cell types each with distinct functions and roles. The cellular landscape of whole blood may be sensitive to certain environmental insults and such insults may impact patterns of DNA methylation in a cell-specific manner. Thus, in addition to the well-recognized potential for confounding, environmental exposures may elicit cell-specific effects, the detection of which represents a major challenge in the analysis whole-blood methylation signatures. The identification of cell-specific effects of methylation based on bulk-tissue methylation signatures is an ongoing area of research with important implications for environmental epidemiology studies of DNA methylation. This talk will orient the audience to the above challenges and will include a discussion of recent work that aims to address these challenges. Insight into the application of such methods for environmental epidemiology studies of DNA methylation will be given.

Derivation of poly-methylomic profile scores for schizophrenia

Schizophrenia and bipolar disorder share biological features and environmental risk factors that may be associated with altered DNA methylation. In this study we sought to: 1) construct a novel ‘Poly-Methylomic Profile Score (PMPS)’ by transforming schizophrenia-associated epigenome-wide methylation from a previously published epigenome-wide association study (EWAS) into a single quantitative metric; and 2) examine associations between the PMPS and clinical status in an independent sample of 57 schizophrenia (SZ) cases, 59 bipolar disorder (BD) cases and 55 healthy controls (HC) for whom blood-derived DNA methylation was quantified using the Illumina 450 K methylation beadchip. We constructed five PMPSs at different p-value thresholds by summing methylation beta-values weighted by individual-CpG effect sizes from the meta-analysis of a previously published schizophrenia EWAS (comprising three separate cohorts with 675 [353 SZ and 322 HC] discovery cohort participants, 847 [414 SZ and 433 HC] replication cohort participants, and 96 monozygotic twin-pairs discordant for SZ). All SZ PMPSs were elevated in SZ participants relative to HCs, with the score calculated at a p-value threshold of 1 × 10−5 accounting for the greatest amount of variance. All PMPSs were elevated in SZ relative to BD and none of the PMPSs were increased in BD, or in a combined cohort of BD and SZ cases, relative to HCs. PMPSs were also not associated with positive or negative symptom severity. That this SZ-derived PMPSs was elevated in SZ, but not BD, suggests that epigenome-wide methylation patterns may represent distinct pathophysiology that is yet to be elucidated.