Genomic and phenotypic insights from an atlas of genetic effects on DNA methylation

Comparative analysis of genome-scale, base-resolution DNA methylation profiles across 580 animal species

Methylation of cytosines is a prototypic epigenetic modification of the DNA. It has been implicated in various regulatory mechanisms across the animal kingdom and particularly in vertebrates. We mapped DNA methylation in 580 animal species (535 vertebrates, 45 invertebrates), resulting in 2443 genome-scale DNA methylation profiles of multiple organs. Bioinformatic analysis of this large dataset quantified the association of DNA methylation with the underlying genomic DNA sequence throughout vertebrate evolution. We observed a broadly conserved link with two major transitions-once in the first vertebrates and again with the emergence of reptiles. Cross-species comparisons focusing on individual organs supported a deeply conserved association of DNA methylation with tissue type, and cross-mapping analysis of DNA methylation at gene promoters revealed evolutionary changes for orthologous genes. In summary, this study establishes a large resource of vertebrate and invertebrate DNA methylomes, it showcases the power of reference-free epigenome analysis in species for which no reference genomes are available, and it contributes an epigenetic perspective to the study of vertebrate evolution.

Systemic interindividual epigenetic variation in humans is associated with transposable elements and under strong genetic control

BACKGROUND

Genetic variants can modulate phenotypic outcomes via epigenetic intermediates, for example at methylation quantitative trait loci (mQTL). We present the first large-scale assessment of mQTL at human genomic regions selected for interindividual variation in CpG methylation, which we call correlated regions of systemic interindividual variation (CoRSIVs). These can be assayed in blood DNA and do not reflect interindividual variation in cellular composition.

RESULTS

We use target-capture bisulfite sequencing to assess DNA methylation at 4086 CoRSIVs in multiple tissues from each of 188 donors in the NIH Gene-Tissue Expression (GTEx) program. At CoRSIVs, DNA methylation in peripheral blood correlates with methylation and gene expression in internal organs. We also discover unprecedented mQTL at these regions. Genetic influences on CoRSIV methylation are extremely strong (median R²=0.76), cumulatively comprising over 70-fold more human mQTL than detected in the most powerful previous study. Moreover, mQTL beta coefficients at CoRSIVs are highly skewed (i.e., the major allele predicts higher methylation). Both surprising findings are independently validated in a cohort of 47 non-GTEx individuals. Genomic regions flanking CoRSIVs show long-range enrichments for LINE-1 and LTR transposable elements; the skewed beta coefficients may therefore reflect evolutionary selection of genetic variants that promote their methylation and silencing. Analyses of GWAS summary statistics show that mQTL polymorphisms at CoRSIVs are associated with metabolic and other classes of disease.

CONCLUSIONS

A focus on systemic interindividual epigenetic variants, clearly enhanced in mQTL content, should likewise benefit studies attempting to link human epigenetic variation to the risk of disease.

An overview on neurobiology and therapeutics of attention-deficit/hyperactivity disorder

Attention-Deficit/Hyperactivity Disorder (ADHD) is a prevalent psychiatric condition characterized by developmentally inappropriate symptoms of inattention and/or hyperactivity/impulsivity, which leads to impairments in the social, academic, and professional contexts. ADHD diagnosis relies solely on clinical assessment based on symptom evaluation and is sometimes challenging due to the substantial heterogeneity of the disorder in terms of clinical and pathophysiological aspects. Despite the difficulties imposed by the high complexity of ADHD etiology, the growing body of research and technological advances provide good perspectives for understanding the neurobiology of the disorder. Such knowledge is essential to refining diagnosis and identifying new therapeutic options to optimize treatment outcomes and associated impairments, leading to improvements in all domains of patient care. This review is intended to be an updated outline that addresses the etiological and neurobiological aspects of ADHD and its treatment, considering the impact of the "omics" era on disentangling the multifactorial architecture of ADHD.

Differential DNA methylation associated with multiple sclerosis and disease modifying treatments in an underrepresented minority population

Black and Hispanic American patients frequently develop earlier onset of multiple sclerosis (MS) and a more severe disease course that can be resistant to disease modifying treatments. The objectives were to identify differential methylation of genomic DNA (gDNA) associated with disease susceptibility and treatment responses in a cohort of MS patients from underrepresented minority populations. Patients with MS and controls with non-inflammatory neurologic conditions were consented and enrolled under an IRB-approved protocol. Approximately 64% of donors identified as Black or African American and 30% as White, Hispanic-Latino. Infinium MethylationEPIC bead arrays were utilized to measure epigenome-wide gDNA methylation of whole blood. Data were analyzed in the presence and absence of adjustments for unknown covariates in the dataset, some of which corresponded to disease modifying treatments. Global patterns of differential methylation associated with MS were strongest for those probes that showed relative demethylation of loci with lower M values. Pathway analysis revealed unexpected associations with shigellosis and amoebiasis. Enrichment analysis revealed an over-representation of probes in enhancer regions and an under-representation in promoters. In the presence of adjustments for covariates that included disease modifying treatments, analysis revealed 10 differentially methylated regions (DMR's) with an FDR <1E-77. Five of these genes (ARID5B, BAZ2B, RABGAP1, SFRP2, WBP1L) are associated with cancer risk and cellular differentiation and have not been previously identified in MS studies. Hierarchical cluster and multi-dimensional scaling analysis of differential DNA methylation at 147 loci within those DMR's was sufficient to differentiate MS donors from controls. In the absence of corrections for disease modifying treatments, differential methylation in patients treated with dimethyl fumarate was associated with immune regulatory pathways that regulate cytokine and chemokine signaling, axon guidance, and adherens junctions. These results demonstrate possible associations of gastrointestinal pathogens and regulation of cellular differentiation with MS susceptibility in our patient cohort. This work further suggests that analyses can be performed in the presence and absence of corrections for immune therapies. Because of their high representation in our patient cohort, these results may be of specific relevance in the regulation of disease susceptibility and treatment responses in Black and Hispanic Americans.

TXNIP DNA methylation is associated with glycemic control over 28 years in type 1 diabetes: findings from the Pittsburgh Epidemiology of Diabetes Complications (EDC) study

INTRODUCTION

DNA methylation (DNAme) has been cross-sectionally associated with type 2 diabetes and hemoglobin A1c (HbA1c) in the general population. However, longitudinal data and data in type 1 diabetes are currently very limited. Thus, we performed an epigenome-wide association study (EWAS) in an observational type 1 diabetes cohort to identify loci with DNAme associated with concurrent and future HbA1cs, as well as other clinical risk factors, over 28 years.

RESEARCH DESIGN AND METHODS

Whole blood DNAme in 683 597 CpGs was analyzed in the Pittsburgh Epidemiology of Diabetes Complications study of childhood onset (<17 years) type 1 diabetes (n=411). An EWAS of DNAme beta values and concurrent HbA1c was performed using linear models adjusted for diabetes duration, sex, pack years of smoking, estimated cell type composition variables, and technical/batch covariates. A longitudinal EWAS of subsequent repeated HbA1c measures was performed using mixed models. We further identified methylation quantitative trait loci (meQTLs) for significant CpGs and conducted a Mendelian randomization.

RESULTS

DNAme at cg19693031 (Chr 1, Thioredoxin-Interacting Protein (TXNIP)) and cg21534330 (Chr 17, Casein Kinase 1 Isoform Delta) was significantly inversely associated with concurrent HbA1c. In longitudinal analyses, hypomethylation of cg19693031 was associated with consistently higher HbA1c over 28 years, and with higher triglycerides, pulse rate, and albumin:creatinine ratio (ACR) independently of HbA1c. We further identified 34 meQTLs in SLC2A1/SLC2A1-AS1 significantly associated with cg19693031 DNAme.

CONCLUSIONS

Our results extend prior findings that TXNIP hypomethylation relates to worse glycemic control in type 1 diabetes by demonstrating the association persists over the long term. Additionally, the associations with triglycerides, pulse rate, and ACR suggest TXNIP DNAme could play a role in vascular damage independent of HbA1c. These findings strengthen potential for interventions targeting TXNIP to improve glycemic control in type 1 diabetes through its role in SLC2A1/glucose transporter 1-mediated glucose regulation.

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.

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

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

A comparison of the genes and genesets identified by GWAS and EWAS of fifteen complex traits

Identifying genomic regions pertinent to complex traits is a common goal of genome-wide and epigenome-wide association studies (GWAS and EWAS). GWAS identify causal genetic variants, directly or via linkage disequilibrium, and EWAS identify variation in DNA methylation associated with a trait. While GWAS in principle will only detect variants due to causal genes, EWAS can also identify genes via confounding, or reverse causation. We systematically compare GWAS (N > 50,000) and EWAS (N > 4500) results of 15 complex traits. We evaluate if the genes or gene ontology terms flagged by GWAS and EWAS overlap, and find substantial overlap for diastolic blood pressure, (gene overlap P = 5.2 × 10^-6; term overlap P = 0.001). We superimpose our empirical findings against simulated models of varying genetic and epigenetic architectures and observe that in most cases GWAS and EWAS are likely capturing distinct genesets. Our results indicate that GWAS and EWAS are capturing different aspects of the biology of complex traits.

Maternal Glycaemic and Insulinemic Status and Newborn DNA Methylation: Findings in Women With Overweight and Obesity

CONTEXT

Maternal dysglycaemia and prepregnancy obesity are associated with adverse offspring outcomes. Epigenetic mechanisms such as DNA methylation (DNAm) could contribute.

OBJECTIVE

To examine relationships between maternal glycaemia, insulinemic status, and dietary glycemic indices during pregnancy and an antenatal behavioral-lifestyle intervention with newborn DNAm.

METHODS

We investigated 172 women from a randomized controlled trial of a lifestyle intervention in pregnant women who were overweight or obese. Fasting glucose and insulin concentrations and derived indices of insulin resistance (HOMA-IR), β-cell function (HOMA-%B), and insulin sensitivity were determined at baseline (15) and 28 weeks' gestation. Dietary glycemic load (GL) and index (GI) were calculated from 3-day food diaries. Newborn cord blood DNAm levels of 850K CpG sites were measured using the Illumina Infinium HumanMethylationEPIC array. Associations of each biomarker, dietary index and intervention with DNAm were examined.

RESULTS

Early pregnancy HOMA-IR and HOMA-%B were associated with lower DNAm at CpG sites cg03158092 and cg05985988, respectively. Early pregnancy insulin sensitivity was associated with higher DNAm at cg04976151. Higher late pregnancy insulin concentrations and GL scores were positively associated with DNAm at CpGs cg12082129 and cg11955198 and changes in maternal GI with lower DNAm at CpG cg03403995 (Bonferroni corrected P < 5.99 × 10-8). These later associations were located at genes previously implicated in growth or regulation of insulin processes. No effects of the intervention on cord blood DNAm were observed. None of our findings were replicated in previous studies.

CONCLUSION

Among women who were overweight or obese, maternal pregnancy dietary glycemic indices, glucose, and insulin homeostasis were associated with modest changes in their newborn methylome.

TRIAL REGISTRATION

ISRCTN29316280.

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.

Quantifying the role of transcript levels in mediating DNA methylation effects on complex traits and diseases

High-dimensional omics datasets provide valuable resources to determine the causal role of molecular traits in mediating the path from genotype to phenotype. Making use of molecular quantitative trait loci (QTL) and genome-wide association study (GWAS) summary statistics, we propose a multivariable Mendelian randomization (MVMR) framework to quantify the proportion of the impact of the DNA methylome (DNAm) on complex traits that is propagated through the assayed transcriptome. Evaluating 50 complex traits, we find that on average at least 28.3% (95% CI: [26.9%-29.8%]) of DNAm-to-trait effects are mediated through (typically multiple) transcripts in the cis-region. Several regulatory mechanisms are hypothesized, including methylation of the promoter probe cg10385390 (chr1:8'022'505) increasing the risk for inflammatory bowel disease by reducing PARK7 expression. The proposed integrative framework can be extended to other omics layers to identify causal molecular chains, providing a powerful tool to map and interpret GWAS signals.

Opioid medication use and blood DNA methylation: epigenome-wide association meta-analysis

Aim: To identify differential methylation related to prescribed opioid use. Methods: This study examined whether blood DNA methylation, measured using Illumina arrays, differs by recent opioid medication use in four population-based cohorts. We meta-analyzed results (282 users; 10,560 nonusers) using inverse-variance weighting. Results: Differential methylation (false discovery rate <0.05) was observed at six CpGs annotated to the following genes: KIAA0226, CPLX2, TDRP, RNF38, TTC23 and GPR179. Integrative epigenomic analyses linked implicated loci to regulatory elements in blood and/or brain. Additionally, 74 CpGs were differentially methylated in males or females. Methylation at significant CpGs correlated with gene expression in blood and/or brain. Conclusion: This study identified DNA methylation related to opioid medication use in general populations. The results could inform the development of blood methylation biomarkers of opioid use.

DNA methylation and aeroallergen sensitization: The chicken or the egg?

Background

DNA methylation (DNAm) is considered a plausible pathway through which genetic and environmental factors may influence the development of allergies. However, causality has yet to be determined as it is unknown whether DNAm is rather a cause or consequence of allergic sensitization. Here, we investigated the direction of the observed associations between well-known environmental and genetic determinants of allergy, DNAm, and aeroallergen sensitization using a combination of high-dimensional and causal mediation analyses.

Methods

Using prospectively collected data from the German LISA birth cohort from two time windows (6–10 years: N = 234; 10–15 years: N = 167), we tested whether DNAm is a cause or a consequence of aeroallergen sensitization (specific immunoglobulin E > 0.35kU/l) by conducting mediation analyses for both effect directions using maternal smoking during pregnancy, family history of allergies, and a polygenic risk score (PRS) for any allergic disease as exposure variables. We evaluated individual CpG sites (EPIC BeadChip) and allergy-related methylation risk scores (MRS) as potential mediators in the mediation analyses. We applied three high-dimensional mediation approaches (HIMA, DACT, gHMA) and validated results using causal mediation analyses. A replication of results was attempted in the Swedish BAMSE cohort.

Results

Using high-dimensional methods, we identified five CpGs as mediators of prenatal exposures to sensitization with significant (adjusted p < 0.05) indirect effects in the causal mediation analysis (maternal smoking: two CpGs, family history: one, PRS: two). None of these CpGs could be replicated in BAMSE. The effect of family history on allergy-related MRS was significantly mediated by aeroallergen sensitization (proportions mediated: 33.7–49.6%), suggesting changes in DNAm occurred post-sensitization.

Conclusion

The results indicate that DNAm may be a cause or consequence of aeroallergen sensitization depending on genomic location. Allergy-related MRS, identified as a potential cause of sensitization, can be considered as a cross-sectional biomarker of disease. Differential DNAm in individual CpGs, identified as mediators of the development of sensitization, could be used as clinical predictors of disease development.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13148-022-01332-5.

Incorporation of DNA methylation quantitative trait loci (mQTLs) in epigenome-wide association analysis: application to birthweight effects in neonatal whole blood

BACKGROUND

Epigenome-wide association studies (EWAS) have helped to define the associations between DNA methylation and many clinicopathologic and developmental traits. Since DNA methylation is affected by genetic variation at certain loci, EWAS associations may be potentially influenced by genetic effects. However, a formal assessment of the value of incorporating genetic variation in EWAS evaluations is lacking especially for multiethnic populations.

METHODS

Using single nucleotide polymorphism (SNP) from Illumina Omni Express or Affymetrix PMDA arrays and DNA methylation data from the Illumina 450 K or EPIC array from 1638 newborns of diverse genetic ancestries, we generated DNA methylation quantitative trait loci (mQTL) databases for both array types. We then investigated associations between neonatal DNA methylation and birthweight (incorporating gestational age) using EWAS modeling, and reported how EWAS results were influenced by controlling for mQTLs.

RESULTS

For CpGs on the 450 K array, an average of 15.4% CpGs were assigned as mQTLs, while on the EPIC array, 23.0% CpGs were matched to mQTLs (adjusted P value < 0.05). The CpGs associated with SNPs were enriched in the CpG island shore regions. Correcting for mQTLs in the EWAS model for birthweight helped to increase significance levels for top hits. For CpGs overlapping genes associated with birthweight-related pathways (nutrition metabolism, biosynthesis, for example), accounting for mQTLs changed their regression coefficients more dramatically (> 20%) than for other random CpGs.

CONCLUSION

DNA methylation levels at circa 20% CpGs in the genome were affected by common SNP genotypes. EWAS model fit significantly improved when taking these genetic effects into consideration. Genetic effects were stronger on CpGs overlapping genetic elements associated with control of gene expression.

Dynamic patterns of blood lipids and DNA methylation in response to statin therapy

INTRODUCTION

Statins are lipid-lowering drugs and starting treatment has been associated with DNA methylation changes at genes related to lipid metabolism. However, the longitudinal pattern of how statins affect DNA methylation in relation to lipid levels has not been well investigated.

METHODS

We conducted an epigenetic association study in a longitudinal Swedish twin sample in previously reported lipid-related CpGs (cg10177197, cg17901584 and cg27243685). First, we applied a mixed-effect model to assess the association between blood lipids (total cholesterol (TC), low-density lipoprotein cholesterol (LDL), high-density lipoprotein cholesterol (HDL), total triglyceride (TG)) and DNA methylation. Then, we performed a piecewise latent linear-linear growth curve model (LGCM) to explore the long-term changing pattern of lipids and methylation in response to statin treatment. Finally, we used a bivariate autoregressive latent trajectory model with structured residuals (ALT-SR) to analyze the cross-lagged effects in different lipid-CpG pairs in statin users and non-users.

RESULTS

We replicated the associations between TC, LDL, HDL and DNA methylation level in cg17901584 and cg27243685 (P values ranged from 4.70E-12 to 1.84E-04). From the piecewise LGCM, we showed that TC and LDL significantly decreased in statin users before treatment started and then remained stable. For non-statin users, we only found a slightly significant decreasing trend for TC and TG. We observed a similar dynamic pattern for methylation levels at cg27243685 and cg17901584. Before statin initiation, cg27243685 showed a significantly increasing trend and cg17901584 a decreasing trend, but post-treatment, there were no additional changes. From the ALT-SR model, we found TG levels to be significantly associated with the DNA methylation level of cg27243685 at the next measurement in statin users (estimate = 0.383, 95% CI: 0.173, 0.594, P value < 0.001).

CONCLUSIONS

Longitudinal blood lipid and DNA methylation levels change after statin treatment initiation, where the latter is mostly a response to alterations in lipid levels and not vice versa.

Why epigenetics is (not) a biosocial science and why that matters

Epigenetic modifications offer compelling evidence of the environmental etiology of complex diseases. Social and biographical conditions, as well as material exposures, all modulate our biology with consequences for risk predispositions and health conditions. Elucidating these complex biosocial loops is one of the main challenges animating epigenetics. Yet, research on the development of epigenetic biomarkers often pulls in a direction that departs from a view of biological determinants of health embedded in their social and material environment. Taking the example of the epigenetics of cardiovascular diseases, this paper illustrates how common understandings of epigenetic biomarkers strongly lean toward considering them as mere targets for molecular intervention, rather than as correlates of a complex biological and social patterning of disease. This reductionism about biosocial dynamics of disease, we argue, hampers the pursuit of the goals epigenetics has given itself (in cardiology and beyond). If epigenetic mechanisms point to the deep socio-environmental embeddedness of our health, we conclude, future designs and methods of this research may require an improved methodological consideration of a biosocial perspective.

Epigenetics and ADHD: Reflections on Current Knowledge, Research Priorities and Translational Potential

Attention-deficit/hyperactivity disorder (ADHD) is a common and debilitating neurodevelopmental disorder influenced by both genetic and environmental factors, typically identified in the school-age years but hypothesized to have developmental origins beginning in utero. To improve current strategies for prediction, prevention and treatment, a central challenge is to delineate how, at a molecular level, genetic and environmental influences jointly shape ADHD risk, phenotypic presentation, and developmental course. Epigenetic processes that regulate gene expression, such as DNA methylation, have emerged as a promising molecular system in the search for both biomarkers and mechanisms to address this challenge. In this Current Opinion, we discuss the relevance of epigenetics (specifically DNA methylation) for ADHD research and clinical practice, starting with the current state of knowledge, what challenges we have yet to overcome, and what the future may hold in terms of methylation-based applications for personalized medicine in ADHD. We conclude that the field of epigenetics and ADHD is promising but is still in its infancy, and the potential for transformative translational applications remains a distant goal. Nevertheless, rapid methodological advances, together with the rise of collaborative science and increased availability of high-quality, longitudinal data make this a thriving research area that in future may contribute to the development of new tools for improved prediction, management, and treatment of ADHD.

Maternal Mediterranean diet in pregnancy and newborn DNA methylation: a meta-analysis in the PACE Consortium

Higher adherence to the Mediterranean diet during pregnancy is related to a lower risk of preterm birth and to better offspring cardiometabolic health. DNA methylation may be an underlying biological mechanism. We evaluated whether maternal adherence to the Mediterranean diet was associated with offspring cord blood DNA methylation.We meta-analysed epigenome-wide association studies (EWAS) of maternal adherence to the Mediterranean diet during pregnancy and offspring cord blood DNA methylation in 2802 mother-child pairs from five cohorts. We calculated the relative Mediterranean diet (rMED) score with range 0-18 and an adjusted rMED excluding alcohol (rMEDp, range 0-16). DNA methylation was measured using Illumina 450K arrays. We used robust linear regression modelling adjusted for child sex, maternal education, age, smoking, body mass index, energy intake, batch, and cell types. We performed several functional analyses and examined the persistence of differential DNA methylation into childhood (4.5-7.8 y).rMEDp was associated with cord blood DNA methylation at cg23757341 (0.064% increase in DNA methylation per 1-point increase in the rMEDp score, SE = 0.011, P = 2.41 × 10-8). This cytosine-phosphate-guanine (CpG) site maps to WNT5B, associated with adipogenesis and glycaemic phenotypes. We did not identify associations with childhood gene expression, nor did we find enriched biological pathways. The association did not persist into childhood.In this meta-analysis, maternal adherence to the Mediterranean diet (excluding alcohol) during pregnancy was associated with cord blood DNA methylation level at cg23757341. Potential mediation of DNA methylation in associations with offspring health requires further study.

Allergies to food and airborne allergens in children and adolescents: role of epigenetics in a changing environment

Allergic diseases affect millions of children and adolescents worldwide. In this Review, we focus on allergies to food and airborne allergens and provide examples of prevalence trends during a time when climate change is of increasing concern. Profound environmental changes have affected natural systems in terms of biodiversity loss, air pollution, and climate. We discuss the potential links between these changes and allergic diseases in children, and the clinical implications. Several exposures of relevance for allergic disease also correlate with epigenetic changes such as DNA methylation. We propose that epigenetics could be a promising tool by which exposures and hazards related to a changing environment can be captured. Epigenetics might also provide promising biomarkers and help to elucidate the mechanisms related to allergic disease initiation and progress.

Temporal associations between leukocytes DNA methylation and blood lipids: a longitudinal study

BACKGROUND

The associations between blood lipids and DNA methylation have been investigated in epigenome-wide association studies mainly among European ancestry populations. Several studies have explored the direction of the association using cross-sectional data, while evidence of longitudinal data is still lacking.

RESULTS

We tested the associations between peripheral blood leukocytes DNA methylation and four lipid measures from Illumina 450 K or EPIC arrays in 1084 participants from the Chinese National Twin Registry and replicated the result in 988 participants from the China Kadoorie Biobank. A total of 23 associations of 19 CpG sites were identified, with 4 CpG sites located in or adjacent to 3 genes (TMEM49, SNX5/SNORD17 and CCDC7) being novel. Among the validated associations, we conducted a cross-lagged analysis to explore the temporal sequence and found temporal associations of methylation levels of 2 CpG sites with triglyceride and 2 CpG sites with high-density lipoprotein-cholesterol (HDL-C) in all twins. In addition, methylation levels of cg11024682 located in SREBF1 at baseline were temporally associated with triglyceride at follow-up in only monozygotic twins. We then performed a mediation analysis with the longitudinal data and the result showed that the association between body mass index and HDL-C was partially mediated by the methylation level of cg06500161 (ABCG1), with a mediation proportion of 10.1%.

CONCLUSIONS

Our study indicated that the DNA methylation levels of ABCG1, AKAP1 and SREBF1 may be involved in lipid metabolism and provided evidence for elucidating the regulatory mechanism of lipid homeostasis.

Genome-wide discovery for diabetes-dependent triglycerides-associated loci

PURPOSE

We aimed to discover loci associated with triglyceride (TG) levels in the context of type 2 diabetes (T2D). We conducted a genome-wide association study (GWAS) in 424,120 genotyped participants of the UK Biobank (UKB) with T2D status and TG levels.

METHODS

We stratified the cohort based on T2D status and conducted association analyses of TG levels for genetic variants with minor allele count (MAC) at least 20 in each stratum. Effect differences of genetic variants by T2D status were determined by Cochran's Q-test and we validated the significantly associated variants in the Mass General Brigham Biobank (MGBB).

RESULTS

Among 21,176 T2D and 402,944 non-T2D samples from UKB, stratified GWAS identified 19 and 315 genomic risk loci significantly associated with TG levels, respectively. Only chr6p21.32 exhibited genome-wide significant heterogeneity (I2 = 98.4%; pheterogeneity = 2.1x10-15), with log(TG) effect estimates of -0.066 (95%CI: -0.082, -0.050) and 0.002 (95%CI: -0.002, 0.006) for T2D and non-T2D, respectively. The lead variant rs9274619:A (allele frequency 0.095) is located 2Kb upstream of the HLA-DQB1 gene, between HLA-DQB1 and HLA-DQA2 genes. We replicated this finding among 25,137 participants (6,951 T2D cases) of MGBB (pheterogeneity = 9.5x10-3). Phenome-wide interaction association analyses showed that the lead variant was strongly associated with a concomitant diagnosis of type 1 diabetes (T1D) as well as diabetes-associated complications.

CONCLUSION

In conclusion, we identified an intergenic variant near HLA-DQB1/DQA2 significantly associates with decreased triglycerides only among those with T2D and highlights an immune overlap with T1D.

Local CpG density affects the trajectory and variance of age-associated DNA methylation changes

BACKGROUND

DNA methylation is an epigenetic mark associated with the repression of gene promoters. Its pattern in the genome is disrupted with age and these changes can be used to statistically predict age with epigenetic clocks. Altered rates of aging inferred from these clocks are observed in human disease. However, the molecular mechanisms underpinning age-associated DNA methylation changes remain unknown. Local DNA sequence can program steady-state DNA methylation levels, but how it influences age-associated methylation changes is unknown.

RESULTS

We analyze longitudinal human DNA methylation trajectories at 345,895 CpGs from 600 individuals aged between 67 and 80 to understand the factors responsible for age-associated epigenetic changes at individual CpGs. We show that changes in methylation with age occur at 182,760 loci largely independently of variation in cell type proportions. These changes are especially apparent at 8322 low CpG density loci. Using SNP data from the same individuals, we demonstrate that methylation trajectories are affected by local sequence polymorphisms at 1487 low CpG density loci. More generally, we find that low CpG density regions are particularly prone to change and do so variably between individuals in people aged over 65. This differs from the behavior of these regions in younger individuals where they predominantly lose methylation.

CONCLUSIONS

Our results, which we reproduce in two independent groups of individuals, demonstrate that local DNA sequence influences age-associated DNA methylation changes in humans in vivo. We suggest that this occurs because interactions between CpGs reinforce maintenance of methylation patterns in CpG dense regions.

RABC: Rheumatoid Arthritis Bioinformatics Center

Advances in sequencing technologies have led to the rapid growth of multi-omics data on rheumatoid arthritis (RA). However, a comprehensive database that systematically collects and classifies the scattered data is still lacking. Here, we developed the Rheumatoid Arthritis Bioinformatics Center (RABC, http://www.onethird-lab.com/RABC/), the first multi-omics data resource platform (data hub) for RA. There are four categories of data in RABC: (i) 175 multi-omics sample sets covering transcriptome, epigenome, genome, and proteome; (ii) 175 209 differentially expressed genes (DEGs), 105 differentially expressed microRNAs (DEMs), 18 464 differentially DNA methylated (DNAm) genes, 1 764 KEGG pathways, 30 488 GO terms, 74 334 SNPs, 242 779 eQTLs, 105 m6A-SNPs and 18 491 669 meta-mQTLs; (iii) prior knowledge on seven types of RA molecular markers from nine public and credible databases; (iv) 127 073 literature information from PubMed (from 1972 to March 2022). RABC provides a user-friendly interface for browsing, searching and downloading these data. In addition, a visualization module also supports users to generate graphs of analysis results by inputting personalized parameters. We believe that RABC will become a valuable resource and make a significant contribution to the study of RA.

Characterisation of ethnic differences in DNA methylation between UK-resident South Asians and Europeans

Ethnic differences in non-communicable disease risk have been described between individuals of South Asian and European ethnicity that are only partially explained by genetics and other known risk factors. DNA methylation is one underexplored mechanism that may explain differences in disease risk. Currently, there is little knowledge of how DNA methylation varies between South Asian and European ethnicities. This study characterised differences in blood DNA methylation between individuals of self-reported European and South Asian ethnicity from two UK-based cohorts: Southall and Brent Revisited and Born in Bradford. DNA methylation differences between ethnicities were widespread throughout the genome (n = 16,433 CpG sites, 3.4% sites tested). Specifically, 76% of associations were attributable to ethnic differences in cell composition with fewer effects attributable to smoking and genetic variation. Ethnicity-associated CpG sites were enriched for EWAS Catalog phenotypes including metabolites. This work highlights the need to consider ethnic diversity in epigenetic research.

The immune factors driving DNA methylation variation in human blood

Epigenetic changes are required for normal development, yet the nature and respective contribution of factors that drive epigenetic variation in humans remain to be fully characterized. Here, we assessed how the blood DNA methylome of 884 adults is affected by DNA sequence variation, age, sex and 139 factors relating to life habits and immunity. Furthermore, we investigated whether these effects are mediated or not by changes in cellular composition, measured by deep immunophenotyping. We show that DNA methylation differs substantially between naïve and memory T cells, supporting the need for adjustment on these cell-types. By doing so, we find that latent cytomegalovirus infection drives DNA methylation variation and provide further support that the increased dispersion of DNA methylation with aging is due to epigenetic drift. Finally, our results indicate that cellular composition and DNA sequence variation are the strongest predictors of DNA methylation, highlighting critical factors for medical epigenomics studies.

Methylation status of VTRNA2-1/nc886 is stable across populations, monozygotic twin pairs and in majority of tissues

Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.

DNA methylation as a potential mediator of the association between prenatal tobacco and alcohol exposure and child neurodevelopment in a South African birth cohort

Prenatal tobacco exposure (PTE) and prenatal alcohol exposure (PAE) have been associated with an increased risk of delayed neurodevelopment in children as well as differential newborn DNA methylation (DNAm). However, the biological mechanisms connecting PTE and PAE, DNAm, and neurodevelopment are largely unknown. Here we aim to determine whether differential DNAm mediates the association between PTE and PAE and neurodevelopment at 6 (N = 112) and 24 months (N = 184) in children from the South African Drakenstein Child Health Study. PTE and PAE were assessed antenatally using urine cotinine measurements and the ASSIST questionnaire, respectively. Cord blood DNAm was measured using the EPIC and 450 K BeadChips. Neurodevelopment (cognitive, language, motor, adaptive behavior, socioemotional) was measured using the Bayley Scales of Infant and Toddler Development, Third Edition. We constructed methylation risk scores (MRS) for PTE and PAE and conducted causal mediation analysis (CMA) with these MRS as mediators. Next, we conducted a high-dimensional mediation analysis to identify individual CpG sites as potential mediators, followed by a CMA to estimate the average causal mediation effects (ACME) and total effect (TE). PTE and PAE were associated with neurodevelopment at 6 but not at 24 months. PTE MRS reached a prediction accuracy (R2) of 0.23 but did not significantly mediate the association between PTE and neurodevelopment. PAE MRS was not predictive of PAE (R2 = 0.006). For PTE, 31 CpG sites and eight CpG sites were identified as significant mediators (ACME and TE P < 0.05) for the cognitive and motor domains at 6 months, respectively. For PAE, 16 CpG sites and 1 CpG site were significant mediators for the motor and adaptive behavior domains at 6 months, respectively. Several of the associated genes, including MAD1L1, CAMTA1, and ALDH1A2 have been implicated in neurodevelopmental delay, suggesting that differential DNAm may partly explain the biological mechanisms underlying the relationship between PTE and PAE and child neurodevelopment.

Distinct sex-specific DNA methylation differences in Alzheimer's disease

BACKGROUND

Sex is increasingly recognized as a significant factor contributing to the biological and clinical heterogeneity in AD. There is also growing evidence for the prominent role of DNA methylation (DNAm) in Alzheimer's disease (AD).

METHODS

We studied sex-specific DNA methylation differences in the blood samples of AD subjects compared to cognitively normal subjects, by performing sex-specific meta-analyses of two large blood-based epigenome-wide association studies (ADNI and AIBL), which included DNA methylation data for a total of 1284 whole blood samples (632 females and 652 males). Within each dataset, we used two complementary analytical strategies, a sex-stratified analysis that examined methylation to AD associations in male and female samples separately, and a methylation-by-sex interaction analysis that compared the magnitude of these associations between different sexes. After adjusting for age, estimated immune cell type proportions, batch effects, and correcting for inflation, the inverse-variance fixed-effects meta-analysis model was used to identify the most consistent DNAm differences across datasets. In addition, we also evaluated the performance of the sex-specific methylation-based risk prediction models for AD diagnosis using an independent external dataset.

RESULTS

In the sex-stratified analysis, we identified 2 CpGs, mapped to the PRRC2A and RPS8 genes, significantly associated with AD in females at a 5% false discovery rate, and an additional 25 significant CpGs (21 in females, 4 in males) at P-value < 1×10^-5. In methylation-by-sex interaction analysis, we identified 5 significant CpGs at P-value < 10^-5. Out-of-sample validations using the AddNeuroMed dataset showed in females, the best logistic prediction model included age, estimated immune cell-type proportions, and methylation risk scores (MRS) computed from 9 of the 23 CpGs identified in AD vs. CN analysis that are also available in AddNeuroMed dataset (AUC = 0.74, 95% CI: 0.65-0.83). In males, the best logistic prediction model included only age and MRS computed from 2 of the 5 CpGs identified in methylation-by-sex interaction analysis that are also available in the AddNeuroMed dataset (AUC = 0.70, 95% CI: 0.56-0.82).

CONCLUSIONS

Overall, our results show that the DNA methylation differences in AD are largely distinct between males and females. Our best-performing sex-specific methylation-based prediction model in females performed better than that for males and additionally included estimated cell-type proportions. The significant discriminatory classification of AD samples with our methylation-based prediction models demonstrates that sex-specific DNA methylation could be a predictive biomarker for AD. As sex is a strong factor underlying phenotypic variability in AD, the results of our study are particularly relevant for a better understanding of the epigenetic architecture that underlie AD and for promoting precision medicine in AD.

Clonal hematopoiesis of indeterminate potential, DNA methylation, and risk for coronary artery disease

Age-related changes to the genome-wide DNA methylation (DNAm) pattern observed in blood are well-documented. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by the age-related acquisition and expansion of leukemogenic mutations in hematopoietic stem cells (HSCs), is associated with blood cancer and coronary artery disease (CAD). Epigenetic regulators DNMT3A and TET2 are the two most frequently mutated CHIP genes. Here, we present results from an epigenome-wide association study for CHIP in 582 Cardiovascular Health Study (CHS) participants, with replication in 2655 Atherosclerosis Risk in Communities (ARIC) Study participants. We show that DNMT3A and TET2 CHIP have distinct and directionally opposing genome-wide DNAm association patterns consistent with their regulatory roles, albeit both promoting self-renewal of HSCs. Mendelian randomization analyses indicate that a subset of DNAm alterations associated with these two leading CHIP genes may promote the risk for CAD.

The potential of DNA methylation as a biomarker for obesity and smoking

DNA methylation is an epigenetic modification that has consistently been shown to be linked with a variety of human traits and diseases. Because DNA methylation is dynamic and potentially reversible in nature and can reflect environmental exposures and predict the onset of diseases, it has piqued interest as a potential disease biomarker. DNA methylation patterns are more stable than transcriptomic or proteomic patterns, and they are relatively easy to measure to track exposure to different environments and risk factors. Importantly, technologies for DNA methylation quantification have become increasingly cost effective-accelerating new research in the field-and have enabled the development of novel DNA methylation biomarkers. Quite a few DNA methylation-based predictors for a number of traits and diseases already exist. Such predictors show potential for being more accurate than self-reported or measured phenotypes (such as smoking behavior and body mass index) and may even hold potential for applications in clinics. In this review, we will first discuss the advantages and challenges of DNA methylation biomarkers in general. We will then review the current state and future potential of DNA methylation biomarkers in two human traits that show rather consistent alterations in methylome-obesity and smoking. Lastly, we will briefly speculate about the future prospects of DNA methylation biomarkers, and possible ways to achieve them.

Methylation risk scores for childhood aeroallergen sensitization: Results from the LISA birth cohort

BACKGROUND

Epigenomic (e.g., DNA methylation [DNAm]) changes have been hypothesized as intermediate step linking environmental exposures with allergic disease. Associations between individual DNAm at CpGs and allergic diseases have been reported, but their joint predictive capability is unknown.

METHODS

Data were obtained from 240 children of the German LISA cohort. DNAm was measured in blood clots at 6 (N = 234) and 10 years (N = 227) using the Illumina EPIC chip. Presence of aeroallergen sensitization was measured in blood at 6, 10, and 15 years. We calculated six methylation risk scores (MRS) for allergy-related phenotypes, like total and specific IgE, asthma, or any allergies, based on available publications and assessed their performances both cross-sectionally (biomarker) and prospectively (predictor of the disease). Dose-response associations between aeroallergen sensitization and MRS were evaluated.

RESULTS

All six allergy-related MRS were highly correlated (r > .86), and seven CpGs were included in more than one MRS. Cross-sectionally, we observed an 81% increased risk for aeroallergen sensitization at 6 years with an increased MRS by one standard deviation (best-performing MRS, 95% confidence interval = [43%; 227%]). Significant associations were also seen cross-sectionally at 10 years and prospectively, though the effect of the latter was attenuated when restricted to participants not sensitized at baseline. A clear dose-response relationship with levels of aeroallergen sensitization could be established cross-sectionally, but not prospectively.

CONCLUSION

We found good classification and prediction capabilities of calculated allergy-related MRS cross-sectionally, underlining the relevance of altered gene-regulation in allergic diseases and providing insights into potential DNAm biomarkers of aeroallergen sensitization.

Cross-tissue analysis of blood and brain epigenome-wide association studies in Alzheimer's disease

To better understand DNA methylation in Alzheimer's disease (AD) from both mechanistic and biomarker perspectives, we performed an epigenome-wide meta-analysis of blood DNA methylation in two large independent blood-based studies in AD, the ADNI and AIBL studies, and identified 5 CpGs, mapped to the SPIDR, CDH6 genes, and intergenic regions, that are significantly associated with AD diagnosis. A cross-tissue analysis that combined these blood DNA methylation datasets with four brain methylation datasets prioritized 97 CpGs and 10 genomic regions that are significantly associated with both AD neuropathology and AD diagnosis. An out-of-sample validation using the AddNeuroMed dataset showed the best performing logistic regression model includes age, sex, immune cell type proportions, and methylation risk score based on prioritized CpGs in cross-tissue analysis (AUC = 0.696, 95% CI: 0.616 - 0.770, P-value = 2.78 × 10^-5). Our study offers new insights into epigenetics in AD and provides a valuable resource for future AD biomarker discovery.

Design and experimental validation of OPERA_MET-A panel for deep methylation analysis by next generation sequencing

DNA methylation is the most recognized epigenetic mark that leads to a massive distortion in cancer cells. It has been observed that a large number of DNA aberrant methylation events occur simultaneously in a group of genes, thus providing a growth advantage to the cell in promoting cell differentiation and neoplastic transformation. Due to this reason, methylation profiles have been suggested as promising cancer biomarkers. Here, we designed and performed a first step of validation of a novel targeted next generation sequencing (NGS) panel for methylation analysis, which can simultaneously evaluate the methylation levels at CpG sites of multiple cancer-related genes. The OPERA_MET-A methylation panel was designed using the Ion AmpliSeq™ technology to amplify 155 regions with 125-175 bp mean length and covers a total of 1107 CpGs of 18 cancer-related genes. The performance of the panel was assessed by running commercially available fully methylated and unmethylated control human genomic DNA (gDNA) samples and a variable mixture of them. The libraries were run on Ion Torrent platform and the sequencing output was analyzed using the “methylation_analysis” plugin. DNA methylation calls on both Watson (W) and Crick (C) strands and methylated:unmethylated ratio for each CpG site were obtained. Cell lines, fresh frozen and formalin-fixed paraffin-embedded (FFPE) lung cancer tissues were tested. The OPERA_MET-A panel allows to run a minimum of 6 samples/530 chip to reach an observed mean target depth ≥2,500X (W and C strands) and an average number of mapped reads >750,000/sample. The conversion efficiency, determined by spiking-in unmethylated Lambda DNA into each sample before the bisulfite conversion process, was >97% for all samples. The observed percentage of global methylation for all CpGs was >95% and <5% for fully methylated and unmethylated gDNA samples, respectively, and the observed results for the variable mixtures were in agreement with what was expected. Methylation-specific NGS analysis represents a feasible method for a fast and multiplexed screening of cancer patients by a high-throughput approach. Moreover, it offers the opportunity to construct a more robust algorithm for disease prediction in cancer patients having a low quantity of biological material available.

Identification of influential probe types in epigenetic predictions of human traits: implications for microarray design

BACKGROUND

CpG methylation levels can help to explain inter-individual differences in phenotypic traits. Few studies have explored whether identifying probe subsets based on their biological and statistical properties can maximise predictions whilst minimising array content. Variance component analyses and penalised regression (epigenetic predictors) were used to test the influence of (i) the number of probes considered, (ii) mean probe variability and (iii) methylation QTL status on the variance captured in eighteen traits by blood DNA methylation. Training and test samples comprised ≤ 4450 and ≤ 2578 unrelated individuals from Generation Scotland, respectively.

RESULTS

As the number of probes under consideration decreased, so too did the estimates from variance components and prediction analyses. Methylation QTL status and mean probe variability did not influence variance components. However, relative effect sizes were 15% larger for epigenetic predictors based on probes with known or reported methylation QTLs compared to probes without reported methylation QTLs. Relative effect sizes were 45% larger for predictors based on probes with mean Beta-values between 10 and 90% compared to those based on hypo- or hypermethylated probes (Beta-value ≤ 10% or ≥ 90%).

CONCLUSIONS

Arrays with fewer probes could reduce costs, leading to increased sample sizes for analyses. Our results show that reducing array content can restrict prediction metrics and careful attention must be given to the biological and distribution properties of CpG probes in array content selection.

Integrated methylome and phenome study of the circulating proteome reveals markers pertinent to brain health

Characterising associations between the methylome, proteome and phenome may provide insight into biological pathways governing brain health. Here, we report an integrated DNA methylation and phenotypic study of the circulating proteome in relation to brain health. Methylome-wide association studies of 4058 plasma proteins are performed (N = 774), identifying 2928 CpG-protein associations after adjustment for multiple testing. These are independent of known genetic protein quantitative trait loci (pQTLs) and common lifestyle effects. Phenome-wide association studies of each protein are then performed in relation to 15 neurological traits (N = 1,065), identifying 405 associations between the levels of 191 proteins and cognitive scores, brain imaging measures or APOE e4 status. We uncover 35 previously unreported DNA methylation signatures for 17 protein markers of brain health. The epigenetic and proteomic markers we identify are pertinent to understanding and stratifying brain health.

Pulmonary Function and Blood DNA Methylation: A Multiancestry Epigenome-Wide Association Meta-analysis

Rationale: Methylation integrates factors present at birth and modifiable across the lifespan that can influence pulmonary function. Studies are limited in scope and replication. Objectives: To conduct large-scale epigenome-wide meta-analyses of blood DNA methylation and pulmonary function. Methods: Twelve cohorts analyzed associations of methylation at cytosine-phosphate-guanine probes (CpGs), using Illumina 450K or EPIC/850K arrays, with FEV1, FVC, and FEV1/FVC. We performed multiancestry epigenome-wide meta-analyses (total of 17,503 individuals; 14,761 European, 2,549 African, and 193 Hispanic/Latino ancestries) and interpreted results using integrative epigenomics. Measurements and Main Results: We identified 1,267 CpGs (1,042 genes) differentially methylated (false discovery rate, <0.025) in relation to FEV1, FVC, or FEV1/FVC, including 1,240 novel and 73 also related to chronic obstructive pulmonary disease (1,787 cases). We found 294 CpGs unique to European or African ancestry and 395 CpGs unique to never or ever smokers. The majority of significant CpGs correlated with nearby gene expression in blood. Findings were enriched in key regulatory elements for gene function, including accessible chromatin elements, in both blood and lung. Sixty-nine implicated genes are targets of investigational or approved drugs. One example novel gene highlighted by integrative epigenomic and druggable target analysis is TNFRSF4. Mendelian randomization and colocalization analyses suggest that epigenome-wide association study signals capture causal regulatory genomic loci. Conclusions: We identified numerous novel loci differentially methylated in relation to pulmonary function; few were detected in large genome-wide association studies. Integrative analyses highlight functional relevance and potential therapeutic targets. This comprehensive discovery of potentially modifiable, novel lung function loci expands knowledge gained from genetic studies, providing insights into lung pathogenesis.

Maternal Dietary Glycemic Index and Glycemic Load in Pregnancy and Offspring Cord Blood DNA Methylation

OBJECTIVE

Suboptimal nutrition in pregnancy is associated with worse offspring cardiometabolic health. DNA methylation may be an underlying mechanism. We meta-analyzed epigenome-wide association studies (EWAS) of maternal dietary glycemic index and load with cord blood DNA methylation.

RESEARCH DESIGN AND METHODS

We calculated maternal glycemic index and load from food frequency questionnaires and ran EWAS on cord blood DNA methylation in 2,003 mother-offspring pairs from three cohorts. Analyses were additionally stratified by maternal BMI categories. We looked-up the findings in EWAS of maternal glycemic traits and BMI as well as in EWAS of birth weight and child BMI. We examined associations with gene expression in child blood in the online Human Early Life Exposome eQTM catalog and in 223 adipose tissue samples.

RESULTS

Maternal glycemic index and load were associated with cord blood DNA methylation at 41 cytosine-phosphate-guanine sites (CpGs, P < 1.17 × 10-7), mostly in mothers with overweight/obesity. We did not observe overlap with CpGs associated with maternal glycemic traits, BMI, or child birth weight or BMI. Only DNA methylation at cg24458009 and cg23347399 was associated with expression of PCED1B and PCDHG, respectively, in child blood, and DNA methylation at cg27193519 was associated with expression of TFAP4, ZNF500, PPL, and ANKS3 in child subcutaneous adipose tissue.

CONCLUSIONS

We observed multiple associations of maternal glycemic index and load during pregnancy with cord blood DNA methylation, mostly in mothers with overweight/obesity; some of these CpGs were associated with gene expression. Additional studies are required to further explore functionality, uncover causality, and study pathways to offspring health.

Tissue- and ethnicity-independent hypervariable DNA methylation states show evidence of establishment in the early human embryo

We analysed DNA methylation data from 30 datasets comprising 3474 individuals, 19 tissues and 8 ethnicities at CpGs covered by the Illumina450K array. We identified 4143 hypervariable CpGs ('hvCpGs') with methylation in the top 5% most variable sites across multiple tissues and ethnicities. hvCpG methylation was influenced but not determined by genetic variation, and was not linked to probe reliability, epigenetic drift, age, sex or cell heterogeneity effects. hvCpG methylation tended to covary across tissues derived from different germ-layers and hvCpGs were enriched for proximity to ERV1 and ERVK retrovirus elements. hvCpGs were also enriched for loci previously associated with periconceptional environment, parent-of-origin-specific methylation, and distinctive methylation signatures in monozygotic twins. Together, these properties position hvCpGs as strong candidates for studying how stochastic and/or environmentally influenced DNA methylation states which are established in the early embryo and maintained stably thereafter can influence life-long health and disease.

An epigenome-wide view of osteoarthritis in primary tissues

Osteoarthritis is a complex degenerative joint disease. Here, we investigate matched genotype and methylation profiles of primary chondrocytes from macroscopically intact (low-grade) and degraded (high-grade) osteoarthritis cartilage and from synoviocytes collected from 98 osteoarthritis-affected individuals undergoing knee replacement surgery. We perform an epigenome-wide association study of knee cartilage degeneration and report robustly replicating methylation markers, which reveal an etiologic mechanism linked to the migration of epithelial cells. Using machine learning, we derive methylation models of cartilage degeneration, which we validate with 82% accuracy in independent data. We report a genome-wide methylation quantitative trait locus (mQTL) map of articular cartilage and synovium and identify 18 disease-grade-specific mQTLs in osteoarthritis cartilage. We resolve osteoarthritis GWAS loci through causal inference and colocalization analyses and decipher the epigenetic mechanisms that mediate the effect of genotype on disease risk. Together, our findings provide enhanced insights into epigenetic mechanisms underlying osteoarthritis in primary tissues.

Can epigenetics shine a light on the biological pathways underlying major mental disorders?

A significant proportion of the global burden of disease can be attributed to mental illness. Despite important advances in identifying risk factors for mental health conditions, the biological processing underlying causal pathways to disease onset remain poorly understood. This represents a limitation to implement effective prevention and the development of novel pharmacological treatments. Epigenetic mechanisms have emerged as mediators of environmental and genetic risk factors which might play a role in disease onset, including childhood adversity (CA) and cannabis use (CU). Particularly, human research exploring DNA methylation has provided new and promising insights into the role of biological pathways implicated in the aetio-pathogenesis of psychiatric conditions, including: monoaminergic (Serotonin and Dopamine), GABAergic, glutamatergic, neurogenesis, inflammatory and immune response and oxidative stress. While these epigenetic changes have been often studied as disease-specific, similarly to the investigation of environmental risk factors, they are often transdiagnostic. Therefore, we aim to review the existing literature on DNA methylation from human studies of psychiatric diseases (i) to identify epigenetic modifications mapping onto biological pathways either transdiagnostically or specifically related to psychiatric diseases such as Eating Disorders, Post-traumatic Stress Disorder, Bipolar and Psychotic Disorder, Depression, Autism Spectrum Disorder and Anxiety Disorder, and (ii) to investigate a convergence between some of these epigenetic modifications and the exposure to known risk factors for psychiatric disorders such as CA and CU, as well as to other epigenetic confounders in psychiatry research.

Prenatal Maternal Smoke, DNA Methylation, and Multi-omics of Tissues and Child Health

PURPOSE OF REVIEW

Maternal tobacco smoking during pregnancy is of public health concern, and understanding the biological mechanisms can help to promote smoking cessation campaigns. This non-systematic review focuses on the effects of maternal smoking during pregnancy on offspring's epigenome, consistent in chemical modifications of the genome that regulate gene expression.

RECENT FINDINGS

Recent meta-analyses of epigenome-wide association studies have shown that maternal smoking during pregnancy is consistently associated with offspring's DNA methylation changes, both in the placenta and blood. These studies indicate that effects on blood DNA methylation can persist for years, and that the longer the duration of the exposure and the higher the dose, the larger the effects. Hence, DNA methylation scores have been developed to estimate past exposure to maternal smoking during pregnancy as biomarkers. There is robust evidence for DNA methylation alterations associated with maternal smoking during pregnancy; however, the role of sex, ethnicity, and genetic background needs further exploration. Moreover, there are no conclusive studies about exposure to low doses or during the preconception period. Similarly, studies on tissues other than the placenta and blood are scarce, and cell-type specificity within tissues needs further investigation. In addition, biological interpretation of DNA methylation findings requires multi-omics data, poorly available in epidemiological settings. Finally, although several mediation analyses link DNA methylation changes with health outcomes, they do not allow causal inference. For this, a combination of data from multiple study designs will be essential in the future to better address this topic.

The missing diversity in human epigenomic studies

Recent work has highlighted a lack of diversity in genomic studies. However, less attention has been given to epigenomics. Here, we show that epigenomic studies are lacking in diversity and propose several solutions to address this problem.

A novel DNA methylation-driver gene signature for long-term survival prediction of hepatitis-positive hepatocellular carcinoma patients

BACKGROUND

Abnormal DNA methylation is one of the most general epigenetic modifications in hepatocellular carcinoma (HCC). Recent research showed that DNA methylation was a prognostic indicator of all-cause HCC and nonviral HCC. However, whether DNA methylation-driver genes could be used for predicting survival, the probability of hepatitis-positive HCC remains unclear.

METHODS

In this study, DNA methylation-driver genes (MDGs) were screened by a joint analysis of methylome and transcriptome data of 142 hepatitis-positive HCC patients. Subsequently, a prognostic risk score and nomogram were constructed. Finally, correlation analyses between the risk score and signaling pathways and immunity were conducted by GSVA and CIBERSORT.

RESULTS

Through random forest screening and Cox progression analysis, 10 prognostic methylation-driver genes (AC008271.1, C11orf53, CASP8, F2RL2, GBP5, LUCAT1, RP11-114B7.6, RP11-149I23.3, RP11-383 J24.1, and SLC35G2) were screened out. As a result, a prognostic risk score signature was constructed. The independent value of the risk score for prognosis prediction were addressed in the TCGA-HCC and the China-HCC cohorts. Next, clinicopathological features were analyzed and HBV status and histological grade were screened to construct a nomogram together with the risk score. The prognostic efficiency of the nomogram was validated by the calibration curves and the concordance index (C index: 0.829, 95% confidence interval: 0.794-0.864), while its clinical application ability was confirmed by decision curve analysis (DCA). At last, the relationship between the risk score and signaling pathways, as well as the correlations between immune cells were elucidated preliminary.

CONCLUSIONS

Taken together, our study explored a novel DNA methylation-driver gene risk score signature and an efficient nomogram for long-term survival prediction of hepatitis-positive HCC patients.

Smartphone-Based Electrochemiluminescence for Visual Simultaneous Detection of RASSF1A and SLC5A8 Tumor Suppressor Gene Methylation in Thyroid Cancer Patient Plasma

Visual one-step simultaneous detection of low-abundance methylation is a crucial challenge in early cancer diagnosis in a simple manner. Through the design of a closed split bipolar electrochemistry system (BE), detection of promoter methylation of tumor suppressor genes in papillary thyroid cancer, RASSF1A and SLC5A8, was achieved using electrochemiluminescence. For this purpose, electrochemiluminescence of luminol loaded into the Fe₃O₄@UiO-66 and gold nanorod-functionalized graphite-like carbon nitride nanosheet (AuNRs@C₃N₄ NS), separately, on the anodic and cathodic pole bipolar electrodes (BPEs) in two different chambers of a bipolar cell were recorded on a smartphone camera. To provide the same electric potential (ΔE_elec) through the BPEs to conduct simultaneous light emission, as well as to achieve higher sensitivity, anodic and cathodic poles BPEs were separately connected to ruthenium nanoparticles electrodeposited on nitrogen-doped graphene-coated Cu foam (fCu/N-GN/RuNPs) to provide a hydrogen evolution reaction (HER) and polycatechol-modified reduced graphene oxide/pencil graphite electrode (PC-rGO/PGE) to provide electrooxidation of hydrazine. Moreover, taking advantages of the strong cathodic ECL activity due to the roles of AuNRs, as well as the high density of capture probes on the UiO-66 and Fe₃O₄ roles in improving the signal-to-background ratio (S/B) in complicated plasma media, a sensitive visual ECL immunosensor was developed to detect two different genes as model target analytes in patient plasma samples. The ability of discrimination of methylation levels as low as 0.01% and above 90% clinical sensitivity in thyroid cancer patient plasma implies that the present strategy is able to diagnose cancer early, as well as monitor responses of patients to therapeutic agents.

Challenges in Analyzing Functional Epigenetic Data in Perspective of Adolescent Psychiatric Health

The formative period of adolescence plays a crucial role in the development of skills and abilities for adulthood. Adolescents who are affected by mental health conditions are at risk of suicide and social and academic impairments. Gene-environment complementary contributions to the molecular mechanisms involved in psychiatric disorders have emphasized the need to analyze epigenetic marks such as DNA methylation (DNAm) and non-coding RNAs. However, the large and diverse bioinformatic and statistical methods, referring to the confounders of the statistical models, application of multiple-testing adjustment methods, questions regarding the correlation of DNAm across tissues, and sex-dependent differences in results, have raised challenges regarding the interpretation of the results. Based on the example of generalized anxiety disorder (GAD) and depressive disorder (MDD), we shed light on the current knowledge and usage of methodological tools in analyzing epigenetics. Statistical robustness is an essential prerequisite for a better understanding and interpretation of epigenetic modifications and helps to find novel targets for personalized therapeutics in psychiatric diseases.

3D chromatin architecture and transcription regulation in cancer

Chromatin has distinct three-dimensional (3D) architectures important in key biological processes, such as cell cycle, replication, differentiation, and transcription regulation. In turn, aberrant 3D structures play a vital role in developing abnormalities and diseases such as cancer. This review discusses key 3D chromatin structures (topologically associating domain, lamina-associated domain, and enhancer-promoter interactions) and corresponding structural protein elements mediating 3D chromatin interactions [CCCTC-binding factor, polycomb group protein, cohesin, and Brother of the Regulator of Imprinted Sites (BORIS) protein] with a highlight of their associations with cancer. We also summarise the recent development of technologies and bioinformatics approaches to study the 3D chromatin interactions in gene expression regulation, including crosslinking and proximity ligation methods in the bulk cell population (ChIA-PET and HiChIP) or single-molecule resolution (ChIA-drop), and methods other than proximity ligation, such as GAM, SPRITE, and super-resolution microscopy techniques.

Molecular Quantitative Trait Locus Mapping in Human Complex Diseases

Mapping quantitative trait loci (QTLs) for molecular traits from chromatin to metabolites (i.e., xQTLs) provides insight into the locations and effect modes of genetic variants that influence these molecular phenotypes and the propagation of functional consequences of each variant. xQTL studies indirectly interrogate the functional landscape of the molecular basis of complex diseases, including the impact of non-coding regulatory variants, the tissue specificity of regulatory elements, and their contribution to disease by integrating with genome-wide association studies (GWAS). We summarize a variety of molecular xQTL studies in human tissues and cells. In addition, using the Alzheimer's Disease Sequencing Project (ADSP) as an example, we describe the ADSP xQTL project, a collaborative effort across the ADSP Functional Genomics Consortium (ADSP-FGC). The project's ultimate goal is a reference map of Alzheimer's-related QTLs using existing datasets from multiple omics layers to help us study the consequences of genetic variants identified in the ADSP. xQTL studies enable the identification of the causal genes and pathways in GWAS loci, which will likely aid in the discovery of novel biomarkers and therapeutic targets for complex diseases. © 2022 Wiley Periodicals LLC.

Genome- and epigenome-wide studies of plasma protein biomarkers for Alzheimer's disease implicate TBCA and TREM2 in disease risk

Introduction

The levels of many blood proteins are associated with Alzheimer's disease (AD) or its pathological hallmarks. Elucidating the molecular factors that control circulating levels of these proteins may help to identify proteins associated with disease risk mechanisms.

Methods

Genome-wide and epigenome-wide studies (nindividuals ≤1064) were performed on plasma levels of 282 AD-associated proteins, identified by a structured literature review. Bayesian penalized regression estimated contributions of genetic and epigenetic variation toward inter-individual differences in plasma protein levels. Mendelian randomization (MR) and co-localization tested associations between proteins and disease-related phenotypes.

Results

Sixty-four independent genetic and 26 epigenetic loci were associated with 45 proteins. Novel findings included an association between plasma triggering receptor expressed on myeloid cells 2 (TREM2) levels and a polymorphism and cytosine-phosphate-guanine (CpG) site within the MS4A4A locus. Higher plasma tubulin-specific chaperone A (TBCA) and TREM2 levels were significantly associated with lower AD risk.

Discussion

Our data inform the regulation of biomarker levels and their relationships with AD.