Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling

Who's afraid of the X? Incorporating the X and Y chromosomes into the analysis of DNA methylation array data

BACKGROUND

Many human disease phenotypes manifest differently by sex, making the development of methods for incorporating X and Y-chromosome data into analyses vital. Unfortunately, X and Y chromosome data are frequently excluded from large-scale analyses of the human genome and epigenome due to analytical complexity associated with sex chromosome dosage differences between XX and XY individuals, and the impact of X-chromosome inactivation (XCI) on the epigenome. As such, little attention has been given to considering the methods by which sex chromosome data may be included in analyses of DNA methylation (DNAme) array data.

RESULTS

With Illumina Infinium HumanMethylation450 DNAme array data from 634 placental samples, we investigated the effects of probe filtering, normalization, and batch correction on DNAme data from the X and Y chromosomes. Processing steps were evaluated in both mixed-sex and sex-stratified subsets of the analysis cohort to identify whether including both sexes impacted processing results. We found that identification of probes that have a high detection p-value, or that are non-variable, should be performed in sex-stratified data subsets to avoid over- and under-estimation of the quantity of probes eligible for removal, respectively. All normalization techniques investigated returned X and Y DNAme data that were highly correlated with the raw data from the same samples. We found no difference in batch correction results after application to mixed-sex or sex-stratified cohorts. Additionally, we identify two analytical methods suitable for XY chromosome data, the choice between which should be guided by the research question of interest, and we performed a proof-of-concept analysis studying differential DNAme on the X and Y chromosome in the context of placental acute chorioamnionitis. Finally, we provide an annotation of probe types that may be desirable to filter in X and Y chromosome analyses, including probes in repetitive elements, the X-transposed region, and cancer-testis gene promoters.

CONCLUSION

While there may be no single "best" approach for analyzing DNAme array data from the X and Y chromosome, analysts must consider key factors during processing and analysis of sex chromosome data to accommodate the underlying biology of these chromosomes, and the technical limitations of DNA methylation arrays.

MethylC-analyzer: a comprehensive downstream pipeline for the analysis of genome-wide DNA methylation

DNA methylation is a crucial epigenetic modification involved in multiple biological processes and diseases. Current approaches for measuring genome-wide DNA methylation via bisulfite sequencing (BS-seq) include whole-genome bisulfite sequencing (WGBS), reduced representation bisulfite sequencing (RRBS), and enzymatic methyl-seq (EM-seq). The computational analysis tools available for BS-seq data include customized aligners for mapping bisulfite-converted reads and computational pipelines for downstream data analysis. Current post-alignment methylation tools are specialized for the interpretation of CG methylation, which is known to dominate mammalian genomes, however, non-CG methylation (CHG and CHH, where H refers to A, C, or T) is commonly observed in plants and fungi and is closely associated with gene regulation, transposon silencing, and plant development. Thus, we have developed a MethylC-analyzer to analyze and visualize post-alignment WGBS, RRBS, and EM-seq data focusing on CG. The tool is able to also analyze non-CG sites to enhance deciphering genomes of plants and fungi. By processing aligned data and gene location files, MethylC-analyzer generates a genome-wide view of methylation levels and methylation in user-specified genomic regions. The meta-plot, for example, allows the investigation of DNA methylation within specific genomic elements. Moreover, our tool identifies differentially methylated regions (DMRs) and investigates the enrichment of genomic features associated with variable methylation. MethylC-analyzer functionality is not limited to specific genomes, and we demonstrated its performance on both plant and human BS-seq data. MethylC-analyzer is a Python- and R-based program designed to perform comprehensive downstream analyses of methylation data, providing an intuitive analysis platform for scientists unfamiliar with DNA methylation analysis. It is available as either a standalone version for command-line uses or a graphical user interface (GUI) and is publicly accessible at https://github.com/RitataLU/MethylC-analyzer .

Methylation in MAD1L1 is associated with the severity of suicide attempt and phenotypes of depression

Depression is a multifactorial disorder representing a significant public health burden. Previous studies have linked multiple single nucleotide polymorphisms with depressive phenotypes and suicidal behavior. MAD1L1 is a mitosis metaphase checkpoint protein that has been linked to depression in GWAS. Using a longitudinal EWAS approach in an adolescent cohort at two time points (n = 216 and n = 154), we identified differentially methylated sites that were associated with depression-related genetic variants in MAD1L1. Three methylation loci (cg02825527, cg18302629, and cg19624444) were consistently hypomethylated in the minor allele carriers, being cross-dependent on several SNPs. We further investigated whether DNA methylation at these CpGs is associated with depressive psychiatric phenotypes in independent cohorts. The first site (cg02825527) was hypomethylated in blood (exp(β) = 84.521, p value ~ 0.003) in participants with severe suicide attempts (n = 88). The same locus showed increased methylation in glial cells (exp(β) = 0.041, p value ~ 0.004) in the validation cohort, involving 29 depressed patients and 29 controls, and showed a trend for association with suicide (n = 40, p value ~ 0.089) and trend for association with depression treatment (n = 377, p value ~ 0.075). The second CpG (cg18302629) was significantly hypomethylated in depressed participants (exp(β) = 56.374, p value ~ 0.023) in glial cells, but did not show associations in the discovery cohorts. The last methylation site (cg19624444) was hypomethylated in the whole blood of severe suicide attempters; however, this association was at the borderline for statistical significance (p value ~ 0.061). This locus, however, showed a strong association with depression treatment in the validation cohort (exp(β) = 2.237, p value ~ 0.003) with 377 participants. The direction of associations between psychiatric phenotypes appeared to be different in the whole blood in comparison with brain samples for cg02825527 and cg19624444. The association analysis between methylation at cg18302629 and cg19624444 and MAD1L1 transcript levels in CD¹⁴⁺ cells shows a potential link between methylation at these CpGs and MAD1L1 expression. This study suggests evidence that methylation at MAD1L1 is important for psychiatric health as supported by several independent cohorts.

State-of-the-art techniques to study epigenetics

The epigenome consists of all the epigenetic alterations like DNA methylation, the histone modifications and non-coding RNAs which change the gene expression and have a role in diseases like cancer and other processes. Epigenetic modifications can control gene expression through variable gene activity at various levels which affects various cellular phenomenon such as cell differentiations, variability, morphogenesis, and the adaptability of an organism. Various factors such as food, pollutants, drugs, stress etc., impact the epigenome. Epigenetic mechanisms mainly involve various post-translational alteration of histones and DNA methylation. Numerous methods have been utilized to study these epigenetic marks. Various histone modifications and binding of histone modifier proteins can be analyzed using chromatin immunoprecipitation (ChIP) which is one of broadly utilized method. Other modified forms of the ChIP have been developed such as reverse chromatin immunoprecipitation (R-ChIP); sequential ChIP (ChIP-re-ChIP) and some high-throughput modified forms of ChIP such as ChIP-seq and ChIP-on-chip. Another epigenetic mechanism is DNA methylation, in which DNA methyltransferases (DNMTs) add a methyl group to the C-5 position of the cytosine. Bisulfite sequencing is the oldest and usually utilized method to measure the DNA methylation status. Other techniques have been established are whole genome bisulfite sequencing (WGBS), methylated DNA immune-precipitation based methods (MeDIP), methylation sensitive restriction enzyme digestion followed by sequencing (MRE-seq) and methylation BeadChip to study the methylome. This chapter briefly discusses the key principles and methods used to study epigenetics in health and disease conditions.

Epigenome-wide analysis of maternal exposure to green space during gestation and cord blood DNA methylation in the ENVIRONAGE cohort

BACKGROUND

DNA methylation programming is sensitive to prenatal life environmental influences, but the impact of maternal exposure to green space on newborns DNA methylation has not been studied yet.

METHODS

We conducted a meta-epigenome-wide association study (EWAS) of maternal exposure to green space during gestation with cord blood DNA methylation in two subsets of the ENVIRONAGE cohort (N = 538). Cord blood DNA methylation was measured by Illumina HumanMethylation 450K in one subset (N = 189) and EPICarray in another (N = 349). High (vegetation height>3 m (m)), low (vegetation height<3 m) and total (including both) high-resolution green space exposures during pregnancy were estimated within 100 m and 1000 m distance around maternal residence. In each subset, we sought cytosine-phosphate-guanine (CpG) sites via linear mixed models adjusted on newborns' sex, ethnicity, gestational age, season at delivery, sampling day, maternal parity, age, smoking, education, and estimated blood cell proportions. EWASs results were meta-analysed via fixed-effects meta-analyses. Differentially methylated regions (DMRs) were identified via ENmix-combp and DMRcate algorithms. Sensitivity analyses were additionally adjusted on PM_2.5, distance to major roads, urbanicity and neighborhood income. In the 450K subset, cord blood expression of differentially methylated genes was measured by Agilent microarrays and associated with green space.

RESULTS

147 DMRs were identified, 85 of which were still significant upon adjustment for PM_2.5, distance to major roads, urbanicity and neighborhood income, including HLA-DRB5, RPTOR, KCNQ1DN, A1BG-AS1, HTR2A, ZNF274, COL11A1 and PRSS36 DMRs. One CpG reached genome-wide significance, while 54 CpGs were suggestive significant (p-values<1e-05). Among them, a CpG, hypermethylated with 100 m buffer total green space, was annotated to PAQR9, whose expression decreased with 1000 m buffer low green space (p-value = 1.45e-05).

CONCLUSIONS

Our results demonstrate that maternal exposure to green space during pregnancy is associated with cord blood DNA methylation, mainly at loci organized in regions, in genes playing important roles in neurological development (e.g., HTR2A).

Sixteen-Year Longitudinal Evaluation of Blood-Based DNA Methylation Biomarkers for Early Prediction of Alzheimer's Disease

BACKGROUND

DNA methylation (DNAm), an epigenetic mark reflecting both inherited and environmental influences, has shown promise for Alzheimer's disease (AD) prediction.

OBJECTIVE

Testing long-term predictive ability (>15 years) of existing DNAm-based epigenetic age acceleration (EAA) measures and identifying novel early blood-based DNAm AD-prediction biomarkers.

METHODS

EAA measures calculated from Illumina EPIC data from blood were tested with linear mixed-effects models (LMMs) in a longitudinal case-control sample (50 late-onset AD cases; 51 matched controls) with prospective data up to 16 years before clinical onset, and post-onset follow-up. Novel DNAm biomarkers were generated with epigenome-wide LMMs, and Sparse Partial Least Squares Discriminant Analysis applied at pre- (10-16 years), and post-AD-onset time-points.

RESULTS

EAA did not differentiate cases from controls during the follow-up time (p > 0.05). Three new DNA biomarkers showed in-sample predictive ability on average 8 years pre-onset, after adjustment for age, sex, and white blood cell proportions (p-values: 0.022-<0.00001). Our longitudinally-derived panel replicated nominally (p = 0.012) in an external cohort (n = 146 cases, 324 controls). However, its effect size and discriminatory accuracy were limited compared to APOEɛ4-carriership (OR = 1.38 per 1 SD DNAm score increase versus OR = 13.58 for ɛ4-allele carriage; AUCs = 77.2% versus 87.0%). Literature review showed low overlap (n = 4) across 3275 AD-associated CpGs from 8 published studies, and no overlap with our identified CpGs.

Aerobic exercise training resets the human skeletal muscle methylome 10 years after breast cancer treatment and survival

Cancer survivors suffer impairments in skeletal muscle in terms of reduced mass and function. Interestingly, human skeletal muscle possesses an epigenetic memory of earlier stimuli, such as exercise. Long-term retention of epigenetic changes in skeletal muscle following cancer survival and/or exercise training has not yet been studied. We, therefore, investigated genome-wide DNA methylation (methylome) in skeletal muscle following a 5-month, 3/week aerobic-training intervention in breast cancer survivors 10-14 years after diagnosis and treatment. These results were compared to breast cancer survivors who remained untrained and to age-matched controls with no history of cancer, who undertook the same training intervention. Skeletal muscle biopsies were obtained from 23 females before(pre) and after(post) the 5-month training period. InfiniumEPIC 850K DNA methylation arrays and RT-PCR for gene expression were performed. The breast cancer survivors displayed a significant retention of increased DNA methylation (i.e., hypermethylation) at a larger number of differentially methylated positions (DMPs) compared with healthy age-matched controls pre training. Training in cancer survivors led to an exaggerated number of DMPs with a hypermethylated signature occurring at non-regulatory regions compared with training in healthy age-matched controls. However, the opposite occurred in important gene regulatory regions, where training in cancer survivors elicited a considerable reduction in methylation (i.e., hypomethylation) in 99% of the DMPs located in CpG islands within promoter regions. Importantly, training was able to reverse the hypermethylation identified in cancer survivors back toward a hypomethylated signature that was observed pre training in healthy age-matched controls at 300 (out of 881) of these island/promoter-associated CpGs. Pathway enrichment analysis identified training in cancer survivors evoked a predominantly hypomethylated signature in pathways associated with cell cycle, DNA replication/repair, transcription, translation, mTOR signaling, and the proteosome. Differentially methylated region (DMR) analysis also identified genes: BAG1, BTG2, CHP1, KIFC1, MKL2, MTR, PEX11B, POLD2, S100A6, SNORD104, and SPG7 as hypermethylated in breast cancer survivors, with training reversing these CpG island/promoter-associated DMRs toward a hypomethylated signature. Training also elicited a largely different epigenetic response in healthy individuals than that observed in cancer survivors, with very few overlapping changes. Only one gene, SIRT2, was identified as having altered methylation in cancer survivors at baseline and after training in both the cancer survivors and healthy controls. Overall, human skeletal muscle may retain a hypermethylated signature as long as 10-14 years after breast cancer treatment/survival. Five months of aerobic training reset the skeletal muscle methylome toward signatures identified in healthy age-matched individuals in gene regulatory regions.

Reverse inflammaging: Long-term effects of HCV cure on biological age

BACKGROUND & AIMS

Chronic hepatitis C virus (HCV) infection can be cured with direct-acting antivirals (DAAs). However, not all sequelae of chronic hepatitis C appear to be completely reversible after sustained virologic response (SVR). Recently, chronic viral infections have been shown to be associated with biological age acceleration defined by the epigenetic clock. The aim of this study was to investigate whether chronic HCV infection is associated with epigenetic changes and biological age acceleration and whether this is reversible after SVR.

METHODS

We included 54 well-characterized individuals with chronic hepatitis C who achieved SVR after DAA therapy at three time points: DAA treatment initiation, end of treatment, and long-term follow-up (median 96 weeks after end of treatment). Genome-wide DNA methylation status was determined in peripheral blood mononuclear cells (PBMCs) and used to calculate epigenetic age acceleration (EAA) using Horvath's clock.

RESULTS

Individuals with HCV had an overall significant EAA of 3.12 years at baseline compared with -2.61 years in the age- and sex-matched reference group (p <0.00003). HCV elimination resulted in a significant long-term increase in DNA methylation dominated by hypermethylated CpGs in all patient groups. Accordingly, EAA decreased to 1.37 years at long-term follow-up. The decrease in EAA was significant only between the end of treatment and follow-up (p = 0.01). Interestingly, eight individuals who developed hepatocellular carcinoma after SVR had the highest EAA and showed no evidence of reversal after SVR.

CONCLUSIONS

Our data contribute to the understanding of the biological impact of HCV elimination after DAA therapy and demonstrate that HCV elimination can lead to "reverse inflammaging". In addition, our data support the potential use of biological age as a biomarker for HCV sequelae after SVR.

IMPACT AND IMPLICATIONS

Chronic hepatitis C virus infection is now curable with direct-acting antivirals, but it remains unclear whether hepatitis C sequelae are fully reversible after viral elimination. Our results suggest that epigenetic changes or acceleration of biological age are reversible in principle, but this requires time, while a lack of reversibility appears to be associated with the development of hepatocellular carcinoma. While most clinical risk scores now take chronological age into account, it may be worthwhile to explore how biological age might improve these scores in the future. Biological age may be a cornerstone for the individualized clinical assessment of patients in the future, as it better reflects patients' lifestyle and environmental exposures over decades.

The discovery of the DNA methylation episignature for Duchenne muscular dystrophy

Duchenne Muscular Dystrophy (DMD) is an X-linked recessive neuromuscular disorder characterized by progressive muscle weakness due to loss of function mutations in the dystrophin gene. Variation in clinical presentation, the rate of disease progression, and treatment responsiveness have been observed amongst DMD patients, suggesting that factors beyond the loss of dystrophin may contribute to DMD pathophysiology. Epigenetic mechanisms are becoming recognized as important factors implicated in the etiology and progression of various diseases. A growing number of genetic syndromes have been associated with unique genomic DNA methylation patterns (called "episignatures") that can be used for diagnostic testing and as disease biomarkers. To further investigate DMD pathophysiology, we assessed the genome-wide DNA methylation profiles of peripheral blood from 36 patients with DMD using the combination of Illumina Infinium Methylation EPIC bead chip array and EpiSign technology. We identified a unique episignature for DMD that whose specificity was confirmed in relation other neurodevelopmental disorders with known episignatures. By modeling the DMD episignature, we developed a new DMD episignature biomarker and provided novel insights into the molecular pathogenesis of this disorder, which have the potential to advance more effective, personalized approaches to DMD care.

Epigenome-wide association study of serum folate in maternal peripheral blood leukocytes

Aim: To perform an epigenome-wide association study (EWAS) of serum folate in maternal blood. Methods: Cross-ancestry (Europeans = 302, South Asians = 161) and ancestry-specific EWAS in the EPIPREG cohort were performed, followed by methyl quantitative trait loci analysis and association with cardiometabolic phenotypes. Replication was attempted using maternal folate intake and blood methylation data from the MoBa study and verified if the findings were significant in a previous EWAS of maternal serum folate in cord blood. Results & conclusion: cg19888088 (cross-ancestry) in EBF3, cg01952260 (Europeans) and cg07077240 (South Asians) in HERC3 were associated with serum folate. cg19888088 and cg01952260 were associated with diastolic blood pressure. cg07077240 was associated with variants in CASC15. The findings were not replicated and were not significant in cord blood.

DNA methylation QTL mapping across diverse human tissues provides molecular links between genetic variation and complex traits

Studies of DNA methylation (DNAm) in solid human tissues are relatively scarce; tissue-specific characterization of DNAm is needed to understand its role in gene regulation and its relevance to complex traits. We generated array-based DNAm profiles for 987 human samples from the Genotype-Tissue Expression (GTEx) project, representing 9 tissue types and 424 subjects. We characterized methylome and transcriptome correlations (eQTMs), genetic regulation in cis (mQTLs and eQTLs) across tissues and e/mQTLs links to complex traits. We identified mQTLs for 286,152 CpG sites, many of which (>5%) show tissue specificity, and mQTL colocalizations with 2,254 distinct GWAS hits across 83 traits. For 91% of these loci, a candidate gene link was identified by integration of functional maps, including eQTMs, and/or eQTL colocalization, but only 33% of loci involved an eQTL and mQTL present in the same tissue type. With this DNAm-focused integrative analysis, we contribute to the understanding of molecular regulatory mechanisms in human tissues and their impact on complex traits.

Life-course socioeconomic factors are associated with markers of epigenetic aging in a population-based study

Adverse socioeconomic circumstances negatively affect the functioning of biological systems, but the underlying mechanisms remain only partially understood. Here, we explore the associations between life-course socioeconomic factors and four markers of epigenetic aging in a population-based setting. We included 684 participants (52 % women, mean age 52.6 ± 15.5 years) from a population and family-based Swiss study. We used nine life-course socioeconomic indicators as the main exposure variables, and four blood-derived, second generation markers of epigenetic aging as the outcome variables (Levine's DNAmPhenoAge, DunedinPoAm38, GrimAge epigenetic age acceleration (EAA), and the mortality risk score (MS)). First, we investigated the associations between socioeconomic indicators and markers of epigenetic aging via mixed-effect linear regression models, adjusting for age, sex, participant's recruitment center, familial structure (random-effect covariate), seasonality of blood sampling, and technical covariates. Second, we implemented counterfactual mediation analysis to investigate life-course and intermediate mechanisms underlying the socioeconomic gradient in epigenetic aging. Effect-size estimates were assessed using regression coefficients and counterfactual mediation parameters, along with their respective 95 % confidence intervals. Individuals reporting a low father's occupation, adverse financial conditions in childhood, a low income, having financial difficulties, or experiencing unfavorable socioeconomic trajectories were epigenetically older and had a higher mortality risk score than their more advantaged counterparts. Specifically, this corresponded to an average increase of 1.1-1.5 years for Levine's epigenetic age (β and 95 %CI range, β (minimum and maximum): 1.1-1.5 95 %CI[0.0-0.2; 2.3-3.0]), 1.1-1.5 additional years for GrimAge (β: 1.1-1.5 95 %CI[0.2-0.6; 1.9-3.0]), a 1-3 % higher DunedinPoAm38 age acceleration (β: 0.01-0.03 95 %CI[0.00; 0.03-0.04]), and a 10-50 % higher MS score (β: 0.1-0.4 95 %CI[0.0-0.2; 0.3-0.4]) for the aforementioned socioeconomic indicators. By exploring the life-course mechanisms underlying the socioeconomic gradient in epigenetic aging, we found that both childhood and adulthood socioeconomic factors contributed to epigenetic aging, and that detrimental lifestyle factors mediated the relation between socioeconomic circumstances in adulthood and EAA (31-89 % mediated proportion). This study provides emerging evidence for an association between disadvantaged life-course socioeconomic circumstances and detrimental epigenetic aging patterns, supporting the "sensitive-period" life-course model. Counterfactual mediation analyses further indicated that the effect of socioeconomic factors in adulthood operates through detrimental lifestyle factors, whereas associations involving early-life socioeconomic factors were less clear.

DNA methylation episignature for Witteveen-Kolk syndrome due to SIN3A haploinsufficiency

PURPOSE

Witteveen-Kolk syndrome (WITKOS) is a rare, autosomal dominant neurodevelopmental disorder caused by heterozygous loss-of-function alterations in the SIN3A gene. WITKOS has variable expressivity that commonly overlaps with other neurodevelopmental disorders. In this study, we characterized a distinct DNA methylation epigenetic signature (episignature) distinguishing WITKOS from unaffected individuals as well as individuals with other neurodevelopmental disorders with episignatures and described 9 previously unpublished individuals with SIN3A haploinsufficiency.

METHODS

We studied the phenotypic characteristics and the genome-wide DNA methylation in the peripheral blood samples of 20 individuals with heterozygous alterations in SIN3A. A total of 14 samples were used for the identification of the episignature and building of a predictive diagnostic biomarker, whereas the diagnostic model was used to investigate the methylation pattern of the remaining 6 samples.

RESULTS

A predominantly hypomethylated DNA methylation profile specific to WITKOS was identified, and the classifier model was able to diagnose a previously unresolved test case. The episignature was sensitive enough to detect individuals with varying degrees of phenotypic severity carrying SIN3A haploinsufficient variants.

CONCLUSION

We identified a novel, robust episignature in WITKOS due to SIN3A haploinsufficiency. This episignature has the potential to aid identification and diagnosis of individuals with WITKOS.

Genome-wide placental DNA methylations in fetal overgrowth and associations with leptin, adiponectin and fetal growth factors

BACKGROUND

Fetal overgrowth "programs" an elevated risk of type 2 diabetes in adulthood. Epigenetic alterations may be a mechanism in programming the vulnerability. We sought to characterize genome-wide alterations in placental gene methylations in fetal overgrowth and the associations with metabolic health biomarkers including leptin, adiponectin and fetal growth factors.

RESULTS

Comparing genome-wide placental gene DNA methylations in large-for-gestational-age (LGA, an indicator of fetal overgrowth, n = 30) versus optimal-for-gestational-age (OGA, control, n = 30) infants using the Illumina Infinium Human Methylation-EPIC BeadChip, we identified 543 differential methylation positions (DMPs; 397 hypermethylated, 146 hypomethylated) at false discovery rate < 5% and absolute methylation difference > 0.05 after adjusting for placental cell-type heterogeneity, maternal age, pre-pregnancy BMI and HbA1c levels during pregnancy. Twenty-five DMPs annotated to 20 genes (QSOX1, FCHSD2, LOC101928162, ADGRB3, GCNT1, TAP1, MYO16, NAV1, ATP8A2, LBXCOR1, EN2, INCA1, CAMTA2, SORCS2, SLC4A4, RPA3, UMAD1,USP53, OR2L13 and NR3C2) could explain 80% of the birth weight variations. Pathway analyses did not detect any statistically significant pathways after correcting for multiple tests. We validated a newly discovered differentially (hyper-)methylated gene-visual system homeobox 1 (VSX1) in an independent pyrosequencing study sample (LGA 47, OGA 47). Our data confirmed a hypermethylated gene-cadherin 13 (CDH13) reported in a previous epigenome-wide association study. Adiponectin in cord blood was correlated with its gene methylation in the placenta, while leptin and fetal growth factors (insulin, IGF-1, IGF-2) were not.

CONCLUSIONS

Fetal overgrowth may be associated with a large number of altered placental gene methylations. Placental VSX1 and CDH13 genes are hypermethylated in fetal overgrowth. Placental ADIPOQ gene methylations and fetal circulating adiponectin levels were correlated, suggesting the contribution of placenta-originated adiponectin to cord blood adiponectin.

Whole-blood methylation signatures are associated with and accurately classify multiple sclerosis disease severity

BACKGROUND

The variation in multiple sclerosis (MS) disease severity is incompletely explained by genetics, suggesting genetic and environmental interactions are involved. Moreover, the lack of prognostic biomarkers makes it difficult for clinicians to optimise care. DNA methylation is one epigenetic mechanism by which gene-environment interactions can be assessed. Here, we aimed to identify DNA methylation patterns associated with mild and severe relapse-onset MS (RMS) and to test the utility of methylation as a predictive biomarker.

METHODS

We conducted an epigenome-wide association study between 235 females with mild (n = 119) or severe (n = 116) with RMS. Methylation was measured with the Illumina methylationEPIC array and analysed using logistic regression. To generate hypotheses about the functional consequence of differential methylation, we conducted gene set enrichment analysis using ToppGene. We compared the accuracy of three machine learning models in classifying disease severity: (1) clinical data available at baseline (age at onset and first symptoms) built using elastic net (EN) regression, (2) methylation data using EN regression and (3) a weighted methylation risk score of differentially methylated positions (DMPs) from the main analysis using logistic regression. We used a conservative 70:30 test:train split for classification modelling. A false discovery rate threshold of 0.05 was used to assess statistical significance.

RESULTS

Females with mild or severe RMS had 1472 DMPs in whole blood (839 hypermethylated, 633 hypomethylated in the severe group). Differential methylation was enriched in genes related to neuronal cellular compartments and processes, and B-cell receptor signalling. Whole-blood methylation levels at 1708 correlated CpG sites classified disease severity more accurately (machine learning model 2, AUC = 0.91) than clinical data (model 1, AUC = 0.74) or the wMRS (model 3, AUC = 0.77). Of the 1708 selected CpGs, 100 overlapped with DMPs from the main analysis at the gene level. These overlapping genes were enriched in neuron projection and dendrite extension, lending support to our finding that neuronal processes, rather than immune processes, are implicated in disease severity.

CONCLUSION

RMS disease severity is associated with whole-blood methylation at genes related to neuronal structure and function. Moreover, correlated whole-blood methylation patterns can assign disease severity in females with RMS more accurately than clinical data available at diagnosis.

Periconceptional folate intake influences DNA methylation at birth based on dietary source in an analysis of pediatric acute lymphoblastic leukemia cases and controls

BACKGROUND

Periconceptional folate intake is associated with the establishment of DNA methylation in offspring; however, variations in this relation by food sources compared with folic acid supplements are not described. Also, maternal folate intake is associated with decreased risk of pediatric acute lymphoblastic leukemia (ALL), but the mechanism is not known.

OBJECTIVES

We evaluated the relation between periconceptional folate intake by source and DNA methylation at birth in a cohort of pediatric ALL cases and controls in an epigenome-wide association study.

METHODS

Genome-wide DNA methylation status obtained from archived neonatal blood spots from pediatric ALL cases (n = 189) and controls (n = 205) in the California Childhood Leukemia Study (CCLS) from 1995-2008 was compared with periconceptional folate from total, food, and supplemental sources using multivariable linear regression. Further stratification was performed by income, education, ethnicity, and total folate intake. We evaluated variable DNA methylation response to periconceptional folate by ALL case status through an interaction term.

RESULTS

Two significant differentially methylated probes (DMPs) were associated with food and supplemental periconceptional folate intake in all subjects (n = 394). The top differentially methylated region at the promoter region of DUSP22(dual specificity phosphatase 22) demonstrated DNA hypermethylation in ALL cases but not in controls in response to total and food folate intake. We further identified 8 interaction term DMPs with variable DNA methylation response to folate intake by ALL case status. Further stratification of the cohort by education and ethnicity revealed a substantially higher number of DMPs associated with supplemental folic acid intake in Hispanic subjects with lower income and educational level.

CONCLUSIONS

We identified modest associations between periconceptional folate intake and DNA methylation differing by source, including variation by ALL case status. Hispanic subjects of lower income and education appear uniquely responsive to periconceptional folate supplementation.

Genome-wide DNA methylation pattern in whole blood of patients with coal-burning arsenic poisoning

Exposure to coal-burning arsenic leads to an increased risk of cancer, multi-systems damage and chronic diseases, with DNA methylation one potential mechanism of arsenic toxicity. There are few studies on genome-wide methylation in the coal-burning arsenic poisoning population. Illumina 850 K methylation beadchip is the most suitable technology for DNA methylation of epigenome-wide association analysis. This study used 850 K to detect changes in Genome-wide DNA methylation in whole blood samples of 12 patients with coal-burning arsenic poisoning ( Arsenic poisoning group) and four healthy control participants (Healthy control group). There is clearly abnormal genome-wide DNA methylation in coal-burning arsenic poisoning, with 647 significantly different methylation positions, 524 different methylation regions and 335 significantly different methylation genes in arsenic poisoning patients compared with healthy controls. Further functional analysis of Gene ontology (GO) and Kyoto encyclopedia of genes (KEGG) found 592 GO items and 131 KEGG pathways between patients of coal-burning arsenic poisoning and healthy control. Then, analysis of gene degree and combined-score identified NAPRT1, NT5C3B, NEDD4L, SLC22A3 and RAB11B as target genes. Further validation by qRT-PCR indicates that mRNA expression of five genes changes significantly in the arsenic poisoning group (n = 72) compared to the healthy control group (n = 72). These results showed the genome-wide methylation pattern and highlighted five critical genes within the coal-burning arsenic poisoning population that involve Nicotinate and nicotinamide metabolism, Choline metabolism in cancer, and Ubiquitin mediated proteolysis. Next, the methylation profile of coal burning arsenic poisoning will be further excavation and the mechanism of coal burning arsenic poisoning will be further explored from five genes related pathways and functions.

Hypermethylation of nc886 in HPV-positive oropharyngeal cancer and its clinical implications: An epigenome-wide association study

The incidence of oropharyngeal squamous cell carcinoma (OPSCC) has increased rapidly in the United States, driven by rising human papillomavirus (HPV) infections in the U.S. population. HPV-positive OPSCC patients have a better prognosis than HPV-negative patients. To gain insights into the unique biology of HPV(+) OPSCC that may contribute to its clinical behaviors, we performed a multi-stage epigenome-wide methylation profiling of leukocyte and tumor DNA in OPSCC patients and compared the methylation levels of CpG sites between HPV(+) and HPV(-) OPSCC patients. We identified and validated a significantly differentially methylated region (DMR) of 1,355 bp encompassing non-coding RNA 886 (nc886) gene and its promoter region. Nc886 is hypermethylated in both leukocytes and tumor DNA of HPV(+) OPSCC patients. Homozygous knockout of nc886 by CRISPR-Cas9 in head and neck cell lines was lethal, but nc886 could be knocked out on the background of protein kinase R (PKR) knockout. Our data suggest that HPV induces nc886 hypermethylation, and nc886 acts as both a viral sensor and a tumor sensor in OPSCC patients and contribute to the better prognosis of HPV(+) OPSCC patients. Nc886 may become a therapeutic target in OPSCC.

Integrating methylome and transcriptome signatures expands the molecular classification of the pituitary tumors

PURPOSE

To explore pituitary tumors by methylome and transcriptome signatures in a heterogeneous ethnic population.

DESIGN

Retrospective cross-sectional study.

PATIENTS AND METHODS

Clinicopathological features, methylome and transcriptome were evaluated in pituitary tumors from 77 patients (61% women, age: 12-72 years) followed due to functioning (FPT: GH-secreting n = 18, ACTH-secreting n = 14) and non-functioning pituitary tumors (NFPT, n = 45) at Ribeirao Preto Medical School, University of Sao Paulo.

RESULTS

Unsupervised hierarchical clustering analysis (UHCA) of methylome (n = 77) and transcriptome (n = 65 out of 77) revealed three clusters each: one enriched by FPT, other by NFPT, and another by ACTH-secreting and NFPT. Comparison between each omics-derived clusters identified 3,568 and 5,994 differentially methylated and expressed genes, respectively, which were associated with each other, with tumor clinical presentation, and with 2017 and 2022 WHO classifications. UHCA considering 11 transcripts related to pituitary development/differentiation also supported three clusters: POU1F1-driven somatotroph, TBX19-driven corticotroph, and NR5A1-driven gonadotroph adenomas, with rare exceptions (NR5A1 expressed in few GH-secreting and corticotroph-silent adenomas; POU1F1 in few ACTH-secreting adenomas; and TBX19 in few NFPTs).

CONCLUSIONS

This large heterogenic ethnic Brazilian cohort confirms that integrated methylome and transcriptome signatures classify FPT and NFPT, which are associated with clinical presentation and tumor invasiveness. Moreover, the cluster NFPT/ACTH-secreting adenomas raises interest regarding tumor heterogeneity, supporting the challenge raised by the 2017 and 2022 WHO definition regarding the discrepancy, in rare cases, between clinical presentation and pituitary lineage markers. Finally, making our data publicly available enables further studies to validate genes/pathways involved in pituitary tumor pathogenesis and prognosis.

Promoter-Adjacent DNA Hypermethylation Can Downmodulate Gene Expression: TBX15 in the Muscle Lineage

TBX15, which encodes a differentiation-related transcription factor, displays promoter-adjacent DNA hypermethylation in myoblasts and skeletal muscle (psoas) that is absent from non-expressing cells in other lineages. By whole-genome bisulfite sequencing (WGBS) and enzymatic methyl-seq (EM-seq), these hypermethylated regions were found to border both sides of a constitutively unmethylated promoter. To understand the functionality of this DNA hypermethylation, we cloned the differentially methylated sequences (DMRs) in CpG-free reporter vectors and tested them for promoter or enhancer activity upon transient transfection. These cloned regions exhibited strong promoter activity and, when placed upstream of a weak promoter, strong enhancer activity specifically in myoblast host cells. In vitro CpG methylation targeted to the DMR sequences in the plasmids resulted in 86−100% loss of promoter or enhancer activity, depending on the insert sequence. These results as well as chromatin epigenetic and transcription profiles for this gene in various cell types support the hypothesis that DNA hypermethylation immediately upstream and downstream of the unmethylated promoter region suppresses enhancer/extended promoter activity, thereby downmodulating, but not silencing, expression in myoblasts and certain kinds of skeletal muscle. This promoter-border hypermethylation was not found in cell types with a silent TBX15 gene, and these cells, instead, exhibit repressive chromatin in and around the promoter. TBX18, TBX2, TBX3 and TBX1 display TBX15-like hypermethylated DMRs at their promoter borders and preferential expression in myoblasts. Therefore, promoter-adjacent DNA hypermethylation for downmodulating transcription to prevent overexpression may be used more frequently for transcription regulation than currently appreciated.

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

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

Complex molecular profile of DNA repair genes in epithelial ovarian carcinoma patients with different sensitivity to platinum-based therapy

Epithelial ovarian carcinoma (EOC) is known for high mortality due to diagnosis at advanced stages and frequent therapy resistance. Previous findings suggested that the DNA repair system is involved in the therapeutic response of cancer patients and DNA repair genes are promising targets for novel therapies. This study aimed to address complex inter-relations among gene expression levels, methylation profiles, and somatic mutations in DNA repair genes and EOC prognosis and therapy resistance status. We found significant associations of DUT expression with the presence of peritoneal metastases in EOC patients. The high-grade serous EOC subtype was enriched with TP53 mutations compared to other subtypes. Furthermore, somatic mutations in XPC and PRKDC were significantly associated with worse overall survival of EOC patients, and higher FAAP20 expression in platinum-resistant than platinum-sensitive patients was observed. We found higher methylation of RAD50 in platinum-resistant than in platinum-sensitive patients. Somatic mutations in BRCA1 and RAD9A were significantly associated with higher RBBP8 methylation in platinum-sensitive compared to platinum-resistant EOC patients. In conclusion, we discovered associations of several candidate genes from the DNA repair pathway with the prognosis and platinum resistance status of EOC patients, which deserve further validation as potential predictive biomarkers.

Grandmaternal smoking during pregnancy is associated with differential DNA methylation in peripheral blood of their grandchildren

The idea that information can be transmitted to subsequent generation(s) by epigenetic means has been studied for decades but remains controversial in humans. Epidemiological studies have established that grandparental exposures are associated with health outcomes in their grandchildren, often with sex-specific effects; however, the mechanism of transmission is still unclear. We conducted Epigenome Wide Association Studies (EWAS) to test whether grandmaternal smoking during pregnancy is associated with altered DNA methylation (DNAm) in peripheral blood from their adolescent grandchildren. We used data from a birth cohort, with discovery and replication datasets of up to 1225 and 708 individuals (respectively, for the maternal line), aged 15-17 years, and tested replication in the same individuals at birth and 7 years. We show for the first time that DNAm at a small number of loci in cord blood is associated with grandmaternal smoking in humans. In adolescents we see suggestive associations in regions of the genome which we hypothesised a priori could be involved in transgenerational transmission - we observe sex-specific associations at two sites on the X chromosome and one in an imprinting control region. All are within transcription factor binding sites (TFBSs), and we observe enrichment for TFBS among the CpG sites with the strongest associations; however, there is limited evidence that the associations we see replicate between timepoints. The implication of this work is that effects of smoking during pregnancy may induce DNAm changes in later generations and that these changes are often sex-specific, in line with epidemiological associations.

Genomic targets and selective inhibition of DNA methyltransferase isoforms

Background

DNA methylation in the human genome is established and maintained by DNA methyltransferases (DNMTs). DNMT isoforms show differential expression by cell lineage and during development, but much remains to be elucidated about their shared and unique genomic targets.

Results

We examined changes in the epigenome following overexpression of 13 DNMT isoforms in HEK293T cells. We observed increased methylation (Δβ > 0.2) at 43,405 CpG sites, with expression of DNMT3A2, DNMTΔ3B4 and DNMTΔ3B2 associated with the greatest impact. De novo methylation occurred primarily within open sea regions and at loci with intermediate methylation levels (β: 0.2–0.6). 53% of differentially methylated loci showed specificity towards a single DNMT subfamily, primarily DNMTΔ3B and DNMT3A and 39% towards a single isoform. These loci were significantly enriched for pathways related to neuronal development (DNMTΔ3B4), calcium homeostasis (DNMTΔ3B3) and ion transport (DNMT3L). Repetitive elements did not display differential sensitivity to overexpressed DNMTs, but hypermethylation of Alu elements was associated with their evolutionary age following overexpression of DNMT3A2, DNMT3B1, DNMT3B2 and DNMT3L. Differential methylation (Δβ > 0.1) was observed at 121 of the 353 loci associated with the Horvath ‘epigenetic clock’ model of ageing, with 51 showing isoform specificity, and was associated with reduction of epigenetic age by 5–15 years following overexpression of seven isoforms. Finally, we demonstrate the potential for dietary constituents to modify epigenetic marks through isoform-specific inhibition of methylation activity.

Conclusions

Our results provide insight into regions of the genome methylated uniquely by specific DNMT isoforms and demonstrate the potential for dietary intervention to modify the epigenome.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01325-4.

Maternal prenatal immunity, neonatal trained immunity, and early airway microbiota shape childhood asthma development

BACKGROUND

The path to childhood asthma is thought to initiate in utero and be further promoted by postnatal exposures. However, the underlying mechanisms remain underexplored. We hypothesized that prenatal maternal immune dysfunction associated with increased childhood asthma risk (revealed by low IFN-γ:IL-13 secretion during the third trimester of pregnancy) alters neonatal immune training through epigenetic mechanisms and promotes early-life airway colonization by asthmagenic microbiota.

METHODS

We examined epigenetic, immunologic, and microbial features potentially related to maternal prenatal immunity (IFN-γ:IL-13 ratio) and childhood asthma in a birth cohort of mother-child dyads sampled pre-, peri-, and postnatally (N = 155). Epigenome-wide DNA methylation and cytokine production were assessed in cord blood mononuclear cells (CBMC) by array profiling and ELISA, respectively. Nasopharyngeal microbiome composition was characterized at age 2-36 months by 16S rRNA sequencing.

RESULTS

Maternal prenatal immune status related to methylome profiles in neonates born to non-asthmatic mothers. A module of differentially methylated CpG sites enriched for microbe-responsive elements was associated with childhood asthma. In vitro responsiveness to microbial products was impaired in CBMCs from neonates born to mothers with the lowest IFN-γ:IL-13 ratio, suggesting defective neonatal innate immunity in those who developed asthma during childhood. These infants exhibited a distinct pattern of upper airway microbiota development characterized by early-life colonization by Haemophilus that transitioned to a Moraxella-dominated microbiota by age 36 months.

CONCLUSIONS

Maternal prenatal immune status shapes asthma development in her child by altering the epigenome and trained innate immunity at birth, and is associated with pathologic upper airway microbial colonization in early life.

Sex-specific DNA methylation and associations with in utero tobacco smoke exposure at nuclear-encoded mitochondrial genes

Sex-linked differences in mitochondrial ATP production, enzyme activities, and reactive oxygen species generation have been reported in multiple tissue and cell types. While the effects of reproductive hormones underlie many of these differences, regulation of sexually dimorphic mitochondrial function has not been fully characterized. We hypothesized that sex-specific DNA methylation contributes to sex-specific expression of nuclear genes that influence mitochondrial function. Herein, we analysed DNA methylation data specifically focused on nuclear-encoded mitochondrial genes in 191 males and 190 females. We found 596 differentially methylated sites (DMSs) (FDR p < 0.05), corresponding to 324 genes, with at least a 1% difference in methylation between sexes. To investigate the potential functional significance, we utilized gene expression microarray data. Of the 324 genes containing DMSs, 17 showed differences in gene expression by sex. Particularly striking was that ATP5G2, encoding subunit C of ATP synthase, contains seven DMSs and exhibits a sex difference in expression (p = 0.04). Finally, we also found that alterations in DNA methylation associated with in utero tobacco smoke exposure were sex-specific in these nuclear-encoded mitochondrial genes. Interestingly, the level of sex differences in DNA methylation at nuclear-encoded mitochondrial genes and the level of methylation changes associated with smoke exposure were less prominent than that of other genes. This suggests more conservative regulation of DNA methylation at these nuclear-encoded mitochondrial genes as compared to others. Overall, our findings suggest that sex-specific DNA methylation may help establish sex differences in expression and function and that sex-specific alterations in DNA methylation in response to exposures could contribute to sex-variable toxicological responses.

Longitudinal Association of DNA Methylation With Type 2 Diabetes and Glycemic Traits: A 5-Year Cross-Lagged Twin Study

Investigators of previous cross-sectional epigenome-wide association studies (EWAS) in adults have reported hundreds of 5'-cytosine-phosphate-guanine-3' (CpG) sites associated with type 2 diabetes mellitus (T2DM) and glycemic traits. However, the results from EWAS have been inconsistent, and longitudinal observations of these associations are scarce. Furthermore, few studies have investigated whether DNA methylation (DNAm) could be modified by smoking, drinking, and glycemic traits, which have broad impacts on genome-wide DNAm and result in altering the risk of T2DM. Twin studies provide a valuable tool for epigenetic studies, as twins are naturally matched for genetic information. In this study, we conducted a systematic literature search in PubMed and Embase for EWAS, and 214, 33, and 117 candidate CpG sites were selected for T2DM, HbA1c, and fasting blood glucose (FBG). Based on 1,070 twins from the Chinese National Twin Registry, 67, 17, and 16 CpG sites from previous studies were validated for T2DM, HbA1c, and FBG. Longitudinal review and blood sampling for phenotypic information and DNAm were conducted twice in 2013 and 2018 for 308 twins. A cross-lagged analysis was performed to examine the temporal relationship between DNAm and T2DM or glycemic traits in the longitudinal data. A total of 11 significant paths from T2DM to subsequent DNAm and 15 paths from DNAm to subsequent T2DM were detected, suggesting both directions of associations. For glycemic traits, we detected 17 cross-lagged associations from baseline glycemic traits to subsequent DNAm, and none were from the other cross-lagged direction, indicating that CpG sites may be the consequences, not the causes, of glycemic traits. Finally, a longitudinal mediation analysis was performed to explore the mediation effects of DNAm on the associations of smoking, drinking, and glycemic traits with T2DM. No significant mediations of DNAm in the associations linking smoking and drinking with T2DM were found. In contrast, our study suggested a potential role of DNAm of cg19693031, cg00574958, and cg04816311 in mediating the effect of altered glycemic traits on T2DM.

An evaluation of the genome-wide false positive rates of common methods for identifying differentially methylated regions using illumina methylation arrays

Differentially methylated regions (DMRs) are genomic regions with specific methylation patterns across multiple loci that are associated with a phenotype. We examined the genome-wide false positive (GFP) rates of five widely used DMR methods: comb-p, Bumphunter, DMRcate, mCSEA and coMethDMR using both Illumina HumanMethylation450 (450 K) and MethylationEPIC (EPIC) data and simulated continuous and dichotomous null phenotypes (i.e., generated independently of methylation data). coMethDMR provided well-controlled GFP rates (~5%) except when analysing skewed continuous phenotypes. DMRcate generally had well-controlled GFP rates when applied to 450 K data except for the skewed continuous phenotype and EPIC data only for the normally distributed continuous phenotype. GFP rates for mCSEA were at least 0.096 and comb-p yielded GFP rates above 0.34. Bumphunter had high GFP rates of at least 0.35 across conditions, reaching as high as 0.95. Analysis of the performance of these methods in specific regions of the genome found that regions with higher correlation across loci had higher regional false positive rates on average across methods. Based on the false positive rates, coMethDMR is the most recommended analysis method, and DMRcate had acceptable performance when analysing 450 K data. However, as both could display higher levels of FPs for skewed continuous distributions, a normalizing transformation of skewed continuous phenotypes is suggested. This study highlights the importance of genome-wide simulations when evaluating the performance of DMR-analysis methods.

EpiVisR: exploratory data analysis and visualization in epigenome-wide association analyses

Background

With the widespread availability of microarray technology for epigenetic research, methods for calling differentially methylated probes or differentially methylated regions have become effective tools to analyze this type of data. Furthermore, visualization is usually employed for quality check of results and for further insights. Expert knowledge is required to leverage capabilities of these methods. To overcome this limitation and make visualization in epigenetic research available to the public, we designed EpiVisR.

Results

The EpiVisR tool allows to select and visualize combinations of traits (i.e., concentrations of chemical compounds) and differentially methylated probes/regions. It supports various modes of enriched presentation to get the most knowledge out of existing data: (1) enriched Manhattan plot and enriched volcano plot for selection of probes, (2) trait-methylation plot for visualization of selected trait values against methylation values, (3) methylation profile plot for visualization of a selected range of probes against selected trait values as well as, (4) correlation profile plot for selection and visualization of further probes that are correlated to the selected probe. EpiVisR additionally allows exporting selected data to external tools for tasks such as network analysis.

Conclusion

The key advantage of EpiVisR is the annotation of data in the enriched plots (and tied tables) as well as linking to external data sources for further integrated data analysis. Using the EpiVisR approach will allow users to integrate data from traits with epigenetic analyses that are connected by belonging to the same individuals. Merging data from various data sources among the same cohort and visualizing them will enable users to gain more insights from existing data.

The Interaction of Trauma Exposure and DNA Methylation on Blood Pressure Among Black Women in the InterGEN Study

Objective

Despite evidence that trauma exposure is linked to higher risk of hypertension, epigenetic mechanisms (such as DNA methylation) by which trauma potentially influences hypertension risk among Black adults remain understudied.

Methods

Data from a longitudinal study of Black mothers were used to test the hypothesis that direct childhood trauma (ie, personal exposure) and vicarious trauma (ie, childhood trauma experienced by their children) would interact with DNA methylation to increase blood pressure (BP). Separate linear mixed effects models were fitted at each CpG site with the DNA methylation beta-value and direct and vicarious trauma as predictors and systolic and diastolic BP modeled as dependent variables adjusted for age, cigarette smoking, and body mass index. Interaction terms between DNA methylation beta-values with direct and vicarious trauma were added.

Results

The sample included 244 Black mothers with a mean age of 31.2 years (SD = ±5.8). Approximately 45% of participants reported at least one form of direct childhood trauma and 49% reported at least one form of vicarious trauma. Epigenome-wide interaction analyses found that no CpG sites passed the epigenome-wide significance level indicating the interaction between direct or vicarious trauma with DNAm did not influence systolic or diastolic BP.

Conclusions

This is one of the first studies to simultaneously examine whether direct or vicarious exposure to trauma interact with DNAm to influence BP. Although findings were null, this study highlights directions for future research that investigates epigenetic mechanisms that may link trauma exposure with hypertension risk in Black women.

Methylation differences in Alzheimer's disease neuropathologic change in the aged human brain

Alzheimer's disease (AD) is the most common cause of dementia with advancing age as its strongest risk factor. AD neuropathologic change (ADNC) is known to be associated with numerous DNA methylation changes in the human brain, but the oldest old (> 90 years) have so far been underrepresented in epigenetic studies of ADNC. Our study participants were individuals aged over 90 years (n = 47) from The 90+ Study. We analyzed DNA methylation from bulk samples in eight precisely dissected regions of the human brain: middle frontal gyrus, cingulate gyrus, entorhinal cortex, dentate gyrus, CA1, substantia nigra, locus coeruleus and cerebellar cortex. We deconvolved our bulk data into cell-type-specific (CTS) signals using computational methods. CTS methylation differences were analyzed across different levels of ADNC. The highest amount of ADNC related methylation differences was found in the dentate gyrus, a region that has so far been underrepresented in large scale multi-omic studies. In neurons of the dentate gyrus, DNA methylation significantly differed with increased burden of amyloid beta (Aβ) plaques at 5897 promoter regions of protein-coding genes. Amongst these, higher Aβ plaque burden was associated with promoter hypomethylation of the Presenilin enhancer 2 (PEN-2) gene, one of the rate limiting genes in the formation of gamma-secretase, a multicomponent complex that is responsible in part for the endoproteolytic cleavage of amyloid precursor protein into Aβ peptides. In addition to novel ADNC related DNA methylation changes, we present the most detailed array-based methylation survey of the old aged human brain to date. Our open-sourced dataset can serve as a brain region reference panel for future studies and help advance research in aging and neurodegenerative diseases.

An examination of mediation by DNA methylation on birthweight differences induced by assisted reproductive technologies

BACKGROUND

Children born after assisted reproductive technologies (ART) differ in birthweight from those naturally conceived. It has been hypothesized that this might be explained by epigenetic mechanisms. We examined whether cord blood DNA methylation mediated the birthweight difference between 890 newborns conceived by ART (764 by fresh embryo transfer and 126 frozen thawed embryo transfer) and 983 naturally conceived newborns from the Norwegian Mother, Father, and Child Cohort Study (MoBa). DNA methylation was measured by the Illumina Infinium MethylationEPIC array. We conducted mediation analyses to assess whether differentially methylated CpGs mediated the differences in birthweight observed between: (1) fresh embryo transfer and natural conception and (2) frozen and fresh embryo transfer.

RESULTS

We observed a difference in birthweight between fresh embryo transfer and naturally conceived offspring of - 120 g. 44% (95% confidence interval [CI] 26% to 81%) of this difference in birthweight between fresh embryo transfer and naturally conceived offspring was explained by differences in methylation levels at four CpGs near LOXL1, CDH20, and DRC1. DNA methylation differences at two CpGs near PTGS1 and RASGRP4 jointly mediated 22% (95% CI 8.1% to 50.3%) of the birthweight differences between fresh and frozen embryo transfer.

CONCLUSION

Our findings suggest that DNA methylation is an important mechanism in explaining birthweight differences according to the mode of conception. Further research should examine how gene regulation at these loci influences fetal growth.

Sex differences in epigenetic age in Mediterranean high longevity regions

Sex differences in aging manifest in disparities in disease prevalence, physical health, and lifespan, where women tend to have greater longevity relative to men. However, in the Mediterranean Blue Zones of Sardinia (Italy) and Ikaria (Greece) are regions of centenarian abundance, male-female centenarian ratios are approximately one, diverging from the typical trend and making these useful regions in which to study sex differences of the oldest old. Additionally, these regions can be investigated as examples of healthy aging relative to other populations. DNA methylation (DNAm)-based predictors have been developed to assess various health biomarkers, including biological age, Pace of Aging, serum interleukin-6 (IL-6), and telomere length. Epigenetic clocks are biological age predictors whose deviation from chronological age has been indicative of relative health differences between individuals, making these useful tools for interrogating these differences in aging. We assessed sex differences between the Horvath, Hannum, GrimAge, PhenoAge, Skin and Blood, and Pace of Aging predictors from individuals in two Mediterranean Blue Zones and found that men displayed positive epigenetic age acceleration (EAA) compared to women according to all clocks, with significantly greater rates according to GrimAge (β = 3.55; p = 1.22 × 10^-12), Horvath (β = 1.07; p = 0.00378) and the Pace of Aging (β = 0.0344; p = 1.77 × 10^-08). Other DNAm-based biomarkers findings indicated that men had lower DNAm-predicted serum IL-6 scores (β = -0.00301, p = 2.84 × 10^-12), while women displayed higher DNAm-predicted proportions of regulatory T cells than men from the Blue Zone (p = 0.0150, 95% Confidence Interval [0.00131, 0.0117], Cohen's d = 0.517). All clocks showed better correlations with chronological age in women from the Blue Zones than men, but all clocks showed large mean absolute errors (MAE >30 years) in both sexes, except for PhenoAge (MAE <5 years). Thus, despite their equal survival to older ages in these Mediterranean Blue Zones, men in these regions remain biologically older by most measured DNAm-derived metrics than women, with the exception of the IL-6 score and proportion of regulatory T cells.

Dementia with Lewy bodies post-mortem brains reveal differentially methylated CpG sites with biomarker potential

Dementia with Lewy bodies (DLB) is a common form of dementia with known genetic and environmental interactions. However, the underlying epigenetic mechanisms which reflect these gene-environment interactions are poorly studied. Herein, we measure genome-wide DNA methylation profiles of post-mortem brain tissue (Broadmann area 7) from 15 pathologically confirmed DLB brains and compare them with 16 cognitively normal controls using Illumina MethylationEPIC arrays. We identify 17 significantly differentially methylated CpGs (DMCs) and 17 differentially methylated regions (DMRs) between the groups. The DMCs are mainly located at the CpG islands, promoter and first exon regions. Genes associated with the DMCs are linked to "Parkinson's disease" and "metabolic pathway", as well as the diseases of "severe intellectual disability" and "mood disorders". Overall, our study highlights previously unreported DMCs offering insights into DLB pathogenesis with the possibility that some of these could be used as biomarkers of DLB in the future.

Comparative analysis of Illumina Mouse Methylation BeadChip and reduced-representation bisulfite sequencing for routine DNA methylation analysis

Researching the murine epigenome in disease models has been hampered by the lack of appropriate and cost-effective DNA methylation arrays. Here we perform a comprehensive, comparative analysis between the Mouse Methylation BeadChip (MMB) and reduced-representation bisulfite sequencing (RRBS) in two murine models of colorectal carcinogenesis. We evaluate the coverage, variability, and ability to identify differential DNA methylation of RRBS and MMB. We show that MMB is an effective tool for profiling the murine methylome that performs comparably with RRBS, identifying similar differentially methylated pathways. Although choice of technology is experiment dependent and will be predicated on the underlying biology being probed, these analyses provide insights into the relative strengths and weaknesses of each approach.

DNA methylation predicts the outcome of COVID-19 patients with acute respiratory distress syndrome

BACKGROUND

COVID-19 infections could be complicated by acute respiratory distress syndrome (ARDS), increasing mortality risk. We sought to assess the methylome of peripheral blood mononuclear cells in COVID-19 with ARDS.

METHODS

We recruited 100 COVID-19 patients with ARDS under mechanical ventilation and 33 non-COVID-19 controls between April and July 2020. COVID-19 patients were followed at four time points for 60 days. DNA methylation and immune cell populations were measured at each time point. A multivariate cox proportional risk regression analysis was conducted to identify predictive signatures according to survival.

RESULTS

The comparison of COVID-19 to controls at inclusion revealed the presence of a 14.4% difference in promoter-associated CpGs in genes that control immune-related pathways such as interferon-gamma and interferon-alpha responses. On day 60, 24% of patients died. The inter-comparison of baseline DNA methylation to the last recorded time point in both COVID-19 groups or the intra-comparison between inclusion and the end of follow-up in every group showed that most changes occurred as the disease progressed, mainly in the AIM gene, which is associated with an intensified immune response in those who recovered. The multivariate Cox proportional risk regression analysis showed that higher methylation of the "Apoptotic execution Pathway" genes (ROC1, ZNF789, and H1F0) at inclusion increases mortality risk by over twofold.

CONCLUSION

We observed an epigenetic signature of immune-related genes in COVID-19 patients with ARDS. Further, Hypermethylation of the apoptotic execution pathway genes predicts the outcome.

TRIAL REGISTRATION

IMRPOVIE study, NCT04473131.

Methylation microarray-based detection of clinical copy-number aberrations in CLL benchmarked to standard FISH analysis

Copy-number aberrations (CNAs) are assessed using FISH analysis in diagnostics of chronic lymphocytic leukemia (CLL), but CNAs can also be extrapolated from Illumina BeadChips developed for genome-wide methylation microarray screening. Increasing numbers of microarray data-sets are available from diagnostic samples, making it useful to assess the potential in CNA diagnostics. We benchmarked the limitations of CNA testing from two Illumina BeadChips (EPIC and 450k) and using two common packages for analysis (conumee and ChAMP) to FISH-based assessment of 11q, 13q, and 17p deletions in 202 CLL samples. Overall, the two packages predicted CNAs with similar accuracy regardless of the microarray type, but lower than FISH-based assessment. We showed that the bioinformatics analysis needs to be adjusted to the specific CNA, as no general settings were identified. Altogether, we were able to predict CNAs using methylation microarray data, however, with limited accuracy, making FISH-based assessment of deletions the superior diagnostic choice.

Epigenome-Wide Study Identifies Epigenetic Outliers in Normal Mucosa of Patients with Colorectal Cancer

Nongenetic predisposition to colorectal cancer continues to be difficult to measure precisely, hampering efforts in targeted prevention and screening. Epigenetic changes in the normal mucosa of patients with colorectal cancer can serve as a tool in predicting colorectal cancer outcomes. We identified epigenetic changes affecting the normal mucosa of patients with colorectal cancer. DNA methylation profiling on normal colon mucosa from 77 patients with colorectal cancer and 68 controls identified a distinct subgroup of normally-appearing mucosa with markedly disrupted DNA methylation at a large number of CpGs, termed as "Outlier Methylation Phenotype" (OMP) and are present in 15 of 77 patients with cancer versus 0 of 68 controls (P < 0.001). Similar findings were also seen in publicly available datasets. Comparison of normal colon mucosa transcription profiles of patients with OMP cancer with those of patients with non-OMP cancer indicates genes whose promoters are hypermethylated in the OMP patients are also transcriptionally downregulated, and that many of the genes most affected are involved in interactions between epithelial cells, the mucus layer, and the microbiome. Analysis of 16S rRNA profiles suggests that normal colon mucosa of OMPs are enriched in bacterial genera associated with colorectal cancer risk, advanced tumor stage, chronic intestinal inflammation, malignant transformation, nosocomial infections, and KRAS mutations. In conclusion, our study identifies an epigenetically distinct OMP group in the normal mucosa of patients with colorectal cancer that is characterized by a disrupted methylome, altered gene expression, and microbial dysbiosis. Prospective studies are needed to determine whether OMP could serve as a biomarker for an elevated epigenetic risk for colorectal cancer development.

PREVENTION RELEVANCE

Our study identifies an epigenetically distinct OMP group in the normal mucosa of patients with colorectal cancer that is characterized by a disrupted methylome, altered gene expression, and microbial dysbiosis. Identification of OMPs in healthy controls and patients with colorectal cancer will lead to prevention and better prognosis, respectively.

Genetic and methylation profiles distinguish benign, malignant and spitzoid melanocytic tumors

Accurate classification of melanocytic tumors is important for prognostic evaluation, treatment and follow-up protocols of patients. The majority of melanocytic proliferations can be classified solely based on clinical and pathological criteria, however in select cases a definitive diagnostic assessment remains challenging and additional diagnostic biomarkers would be advantageous. We analyzed melanomas, nevi, Spitz nevi and atypical spitzoid tumors using parallel sequencing (exons of 611 genes and 507 gene translocation analysis) and methylation arrays (850k Illumina EPIC). By combining detailed genetic and epigenetic analysis with reference-based and reference-free DNA methylome deconvolution we compared Spitz nevi to nevi and melanoma and assessed the potential for these methods in classifying challenging spitzoid tumors. Results were correlated with clinical and histologic features. Spitz nevi were found to cluster independently of nevi and melanoma and demonstrated a different mutation profile. Multiple copy number alterations and TERT promoter mutations were identified only in melanomas. Genome-wide methylation in Spitz nevi was comparable to benign nevi while the Leukocytes UnMethylation for Purity (LUMP) algorithm in Spitz nevi was comparable to melanoma. Histologically difficult to classify Spitz tumor cases were assessed which, based on methylation arrays, clustered between Spitz nevi and melanoma and in terms of genetic profile or copy number variations demonstrated worrisome features suggesting a malignant neoplasm. Comprehensive sequencing and methylation analysis verify Spitz nevi as an independent melanocytic entity distinct from both nevi and melanoma. Combined genetic and methylation assays can offer additional insights in diagnosing difficult to classify Spitzoid tumors.

Immuno-epigenomic analysis identifies attenuated interferon responses in naïve CD4 T cells of adolescents with peanut and multi-food allergy

BACKGROUND

IgE-mediated food allergies have been linked to suboptimal naïve CD4 T (nCD4T) cell activation in infancy, underlined by epigenetic and transcriptomic variation. Similar attenuated nCD4T cell activation in adolescents with food allergy have also been reported, but these are yet to be linked to specific epigenetic or transcriptional changes.

METHODS

We generated genome-wide DNA methylation data in purified nCD4 T cells at quiescence and following activation in a cohort of adolescents (aged 10-15 years old) with peanut allergy (peanut only or peanut + ≥1 additional food allergy) (FA, n = 29), and age-matched non-food allergic controls (NA, n = 18). Additionally, we assessed transcriptome-wide gene expression and cytokine production in these cells following activation.

RESULTS

We found widespread changes in DNA methylation in both NA and FA nCD4T cells in response to activation, associated with the T cell receptor signaling pathway. Adolescents with FA exhibit unique DNA methylation signatures at quiescence and post-activation at key genes involved in Th1/Th2 differentiation (RUNX3, RXRA, NFKB1A, IL4R), including a differentially methylated region (DMR) at the TNFRSF6B promoter, linked to Th1 proliferation. Combined analysis of DNA methylation, transcriptomic data and cytokine output in the same samples identified an attenuated interferon response in nCD4T cells from FA individuals following activation, with decreased expression of several interferon genes, including IFN-γ and a DMR at a key downstream gene, BST2.

CONCLUSION

We find that attenuated nCD4T cell responses from adolescents with food allergy are associated with specific epigenetic variation, including disruption of interferon responses, indicating dysregulation of key immune pathways that may contribute to a persistent FA phenotype. However, we recognize the small sample size, and the consequent restraint on reporting adjusted p-value statistics as limitations of the study. Further study is required to validate these findings.

Investigating DNA methylation as a mediator of genetic risk in childhood acute lymphoblastic leukemia

Genome-wide association studies have identified a growing number of single nucleotide polymorphisms (SNPs) associated with childhood acute lymphoblastic leukemia (ALL), yet the functional roles of most SNPs are unclear. Multiple lines of evidence suggest that epigenetic mechanisms may mediate the impact of heritable genetic variation on phenotypes. Here, we investigated whether DNA methylation mediates the effect of genetic risk loci for childhood ALL. We performed an epigenome-wide association study (EWAS) including 808 childhood ALL cases and 919 controls from California-based studies using neonatal blood DNA. For differentially methylated CpG positions (DMPs), we next conducted association analysis with 23 known ALL risk SNPs followed by causal mediation analyses addressing the significant SNP-DMP pairs. DNA methylation at CpG cg01139861, in the promoter region of IKZF1, mediated the effects of the intronic IKZF1 risk SNP rs78396808, with the average causal mediation effect (ACME) explaining ~30% of the total effect (ACME P = 0.0031). In analyses stratified by self-reported race/ethnicity, the mediation effect was only significant in Latinos, explaining ~41% of the total effect of rs78396808 on ALL risk (ACME P = 0.0037). Conditional analyses confirmed the presence of at least three independent genetic risk loci for childhood ALL at IKZF1, with rs78396808 unique to non-European populations. We also demonstrated that the most significant DMP in the EWAS, CpG cg13344587 at gene ARID5B (P = 8.61 × 10-10), was entirely confounded by the ARID5B ALL risk SNP rs7090445. Our findings provide new insights into the functional pathways of ALL risk SNPs and the DNA methylation differences associated with risk of childhood ALL.

Significant variation in the performance of DNA methylation predictors across data preprocessing and normalization strategies

Background

DNA methylation (DNAm)-based predictors hold great promise to serve as clinical tools for health interventions and disease management. While these algorithms often have high prediction accuracy, the consistency of their performance remains to be determined. We therefore conduct a systematic evaluation across 101 different DNAm data preprocessing and normalization strategies and assess how each analytical strategy affects the consistency of 41 DNAm-based predictors.

Results

Our analyses are conducted in a large EPIC DNAm array dataset from the Jackson Heart Study (N = 2053) that included 146 pairs of technical replicate samples. By estimating the average absolute agreement between replicate pairs, we show that 32 out of 41 predictors (78%) demonstrate excellent consistency when appropriate data processing and normalization steps are implemented. Across all pairs of predictors, we find a moderate correlation in performance across analytical strategies (mean rho = 0.40, SD = 0.27), highlighting significant heterogeneity in performance across algorithms. Successful or unsuccessful removal of technical variation furthermore significantly impacts downstream phenotypic association analysis, such as all-cause mortality risk associations.

Conclusions

We show that DNAm-based algorithms are sensitive to technical variation. The right choice of data processing strategy is important to achieve reproducible estimates and improve prediction accuracy in downstream phenotypic association analyses. For each of the 41 DNAm predictors, we report its degree of consistency and provide the best performing analytical strategy as a guideline for the research community. As DNAm-based predictors become more and more widely used, our work helps improve their performance and standardize their implementation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13059-022-02793-w.

The WID-CIN test identifies women with, and at risk of, cervical intraepithelial neoplasia grade 3 and invasive cervical cancer

Background

Cervical screening is transitioning from primary cytology to primary human papillomavirus (HPV) testing. HPV testing is highly sensitive but there is currently no high-specificity triage method for colposcopy referral to detect cervical intraepithelial neoplasia grade 3 or above (CIN3+) in women positive for high-risk (hr) HPV subtypes. An objective, automatable test that could accurately perform triage, independently of sample heterogeneity and age, is urgently required.

Methods

We analyzed DNA methylation at ~850,000 CpG sites across the genome in a total of 1254 cervical liquid-based cytology (LBC) samples from cases of screen-detected histologically verified CIN1-3+ (98% hrHPV-positive) and population-based control women free from any cervical disease (100% hrHPV-positive). Samples were provided by a state-of-the-art population-based cohort biobank and consisted of (i) a discovery set of 170 CIN3+ cases and 202 hrHPV-positive/cytology-negative controls; (ii) a diagnostic validation set of 87 CIN3+, 90 CIN2, 166 CIN1, and 111 hrHPV-positive/cytology-negative controls; and (iii) a predictive validation set of 428 cytology-negative samples (418 hrHPV-positive) of which 210 were diagnosed with CIN3+ in the upcoming 1–4 years and 218 remained disease-free.

Results

We developed the WID-CIN (Women’s cancer risk IDentification-Cervical Intraepithelial Neoplasia) test, a DNA methylation signature consisting of 5000 CpG sites. The receiver operating characteristic area under the curve (AUC) in the independent diagnostic validation set was 0.92 (95% CI 0.88–0.96). At 75% specificity (≤CIN1), the overall sensitivity to detect CIN3+ is 89.7% (83.3–96.1) in all and 92.7% (85.9–99.6) and 65.6% (49.2–82.1) in women aged ≥30 and <30. In hrHPV-positive/cytology-negative samples in the predictive validation set, the WID-CIN detected 54.8% (48.0–61.5) cases developing 1–4 years after sample donation in all ages or 56.9% (47.6–66.2) and 53.5% (43.7–63.2) in ≥30 and <30-year-old women, at a specificity of 75%.

Conclusions

The WID-CIN test identifies the vast majority of hrHPV-positive women with current CIN3+ lesions. In the absence of cytologic abnormalities, a positive WID-CIN test result is likely to indicate a significantly increased risk of developing CIN3+ in the near future.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01116-9.

Epigenetic and Proteomic Biomarkers of Elevated Alcohol Use Predict Epigenetic Aging and Cell-Type variation Better Than Self-Report

Excessive alcohol consumption (EAC) has a generally accepted effect on morbidity and mortality, outcomes thought to be reflected in measures of epigenetic aging (EA). As the association of self-reported EAC with EA has not been consistent with these expectations, underscoring the need for readily employable non-self-report tools for accurately assessing and monitoring the contribution of EAC to accelerated EA, newly developed alcohol consumption DNA methylation indices, such as the Alcohol T Score (ATS) and Methyl DetectR (MDR), may be helpful. To test that hypothesis, we used these new indices along with the carbohydrate deficient transferrin (CDT), concurrent as well as past self-reports of EAC, and well-established measures of cigarette smoking to examine the relationship of EAC to both accelerated EA and immune cell counts in a cohort of 437 young Black American adults. We found that MDR, CDT, and ATS were intercorrelated, even after controlling for gender and cotinine effects. Correlations between EA and self-reported EAC were low or non-significant, replicating prior research, whereas correlations with non-self-report indices were significant and more substantial. Comparing non-self-report indices showed that the ATS predicted more than four times as much variance in EA, CDT4 cells and B-cells as for both the MDR and CDT, and better predicted indices of accelerated EA. We conclude that each of the non-self-report indices have differing predictive capacities with respect to key alcohol-related health outcomes, and that the ATS may be particularly useful for clinicians seeking to understand and prevent accelerated EA. The results also underscore the likelihood of substantial underestimates of problematic use when self-report is used and a reduction in correlations with EA and variance in cell-types.

Short-Term Exposure of PM2.5 and Epigenetic Aging: A Quasi-Experimental Study

Epigenetic age (EA) is an emerging DNA methylation-based biomarker of biological aging, but whether EA is causally associated with short-term PM_2.5 exposure remains unknown. We conducted a quasi-experimental study of 26 healthy adults to test whether short-term PM_2.5 exposure accelerates seven EAs with three health examinations performed before, during, and after multiple PM_2.5 pollution waves. Seven EAs were derived from the DNA methylation profiles of the Illumina HumanMethylationEPIC BeadChip from CD4+ T-helper cells. We found that an increase of 10 μg/m³ in the 0-24 h personal PM_2.5 exposure prior to health examinations was associated with a 0.035, 0.035, 0.050, 0.055, 0.052, and 0.037-unit increase in the changes of z-scored DNA methylation age acceleration (AA,Horvath), AA (Hannum), AA (GrimAge), DunedinPoAm, mortality risk score (MS), and epiTOC, respectively (p-values < 0.05). The same increase in the 24-48 h average personal PM_2.5 exposure yielded smaller effects but was still robustly associated with the changes in AA (GrimAge), DunedinPoAm, and MS. Such acute aging effects of PM_2.5 were mediated by the changes in several circulating biomarkers, including EC-SOD and sCD40L, with up to ∼28% mediated proportions. Our findings demonstrated that short-term PM_2.5 exposure could accelerate aging reflected by DNA methylation profiles via blood coagulation, oxidative stress, and systematic inflammation.

Do Loneliness and Per Capita Income Combine to Increase the Pace of Biological Aging for Black Adults across Late Middle Age?

In a sample of 685 late middle-aged Black adults (M age at 2019 = 57.17 years), we examined the effects of loneliness and per capita income on accelerated aging using a newly developed DNA-methylation based index: the DunedinPACE. First, using linear, mixed effects regression in a growth curve framework, we found that change in DunedinPACE was dependent on age, with a linear model best fitting the data (b = 0.004, p < 0.001), indicating that average pace of change increased among older participants. A quadratic effect was also tested, but was non-significant. Beyond the effect of age, both change in loneliness (b = 0.009, p < 0.05) and change in per capita income (b = -0.016, p < 0.001) were significantly associated with change in DunedinPACE across an 11-year period, accounting for significant between person variability observed in the unconditional model. Including non-self-report indices of smoking and alcohol use did not reduce the association of loneliness or per capita income with DunedinPACE. However, change in smoking was strongly associated with change in DunedinPACE such that those reducing their smoking aged less rapidly than those continuing to smoke. In addition, both loneliness and per capita income were associated with DunedinPACE after controlling for variation in cell-types.

Aclust2.0: a revamped unsupervised R tool for Infinium methylation beadchips data analyses

MOTIVATION

A wide range of computational packages has been developed for regional DNA methylation analyses of Illumina's Infinium array data. Aclust, one of the first unsupervised algorithms, was originally designed to analyze regional methylation of Infinium's 27K and 450K arrays by clustering neighboring methylation sites prior to downstream analyses. However, Aclust relied on outdated packages that rendered it largely non-operational especially with the newer Infinium EPIC and mouse arrays.

RESULTS

We have created Aclust2.0, a streamlined pipeline that involves five steps for the analyses of human (450K and EPIC) and mouse array data. Aclust2.0 provides a user-friendly pipeline and versatile for regional DNA methylation analyses for molecular epidemiological and mouse studies.

AVAILABILITY AND IMPLEMENTATION

Aclust2.0 is freely available on Github (https://github.com/OluwayioseOA/Alcust2.0.git).

The Role of Dynamic DNA Methylation in Liver Transplant Rejection in Children

Transcriptional regulation of liver transplant (LT) rejection may reveal novel predictive and therapeutic targets. The purpose of this article is to test the role of differential DNA methylation in children with biopsy-proven acute cellular rejection after LT.

Genetic regulation of newborn telomere length is mediated and modified by DNA methylation

Telomere length at birth determines later life telomere length and potentially predicts ageing-related diseases. However, the genetic and epigenetic settings of telomere length in newborns have not been analyzed. In addition, no study yet has reported how the interplay between genetic variants and genome-wide cytosine methylation explains the variation in early-life telomere length. In this study based on 281 mother-newborn pairs from the ENVIRONAGE birth cohort, telomere length and whole-genome DNA methylation were assessed in cord blood and 26 candidate single nucleotide polymorphism related to ageing or telomere length were genotyped. We identified three genetic variants associated with cord blood telomere length and 57 cis methylation quantitative trait loci (cis-mQTLs) of which 22 mQTLs confirmed previous findings and 35 were newly identified. Five SNPs were found to have significant indirect effects on cord blood telomere length via the mediating CpGs. The association between rs911874 (SOD2) and newborn telomere length was modified by nearby DNA methylation indicated by a significant statistical interaction. Our results suggest that DNA methylation in cis might have a mediation or modification effect on the genetic difference in newborn telomere length. This novel approach warrants future follow-up studies that are needed to further confirm and extend these findings.