DNA methylation patterns associate with genetic and gene expression variation in HapMap cell lines

Predicting male fertility from the sperm methylome: application to 120 bulls with hundreds of artificial insemination records

BACKGROUND

Conflicting results regarding alterations to sperm DNA methylation in cases of spermatogenesis defects, male infertility and poor developmental outcomes have been reported in humans. Bulls used for artificial insemination represent a relevant model in this field, as the broad dissemination of bull semen considerably alleviates confounding factors and enables the precise assessment of male fertility. This study was therefore designed to assess the potential for sperm DNA methylation to predict bull fertility.

RESULTS

A unique collection of 100 sperm samples was constituted by pooling 2-5 ejaculates per bull from 100 Montbéliarde bulls of comparable ages, assessed as fertile (n = 57) or subfertile (n = 43) based on non-return rates 56 days after insemination. The DNA methylation profiles of these samples were obtained using reduced representation bisulfite sequencing. After excluding putative sequence polymorphisms, 490 fertility-related differentially methylated cytosines (DMCs) were identified, most of which were hypermethylated in subfertile bulls. Interestingly, 46 genes targeted by DMCs are involved in embryonic and fetal development, sperm function and maturation, or have been related to fertility in genome-wide association studies; five of these were further analyzed by pyrosequencing. In order to evaluate the prognostic value of fertility-related DMCs, the sperm samples were split between training (n = 67) and testing (n = 33) sets. Using a Random Forest approach, a predictive model was built from the methylation values obtained on the training set. The predictive accuracy of this model was 72% on the testing set and 72% on individual ejaculates collected from an independent cohort of 20 bulls.

CONCLUSION

This study, conducted on the largest set of bull sperm samples so far examined in epigenetic analyses, demonstrated that the sperm methylome is a valuable source of male fertility biomarkers. The next challenge is to combine these results with other data on the same sperm samples in order to improve the quality of the model and better understand the interplay between DNA methylation and other molecular features in the regulation of fertility. This research may have potential applications in human medicine, where infertility affects the interaction between a male and a female, thus making it difficult to isolate the male factor.

Bisphenol A replacement chemicals, BPF and BPS, induce protumorigenic changes in human mammary gland organoid morphology and proteome

SignificanceBisphenol A (BPA), found in many plastic products, has weak estrogenic effects that can be harmful to human health. Thus, structurally related replacements-bisphenol S (BPS) and bisphenol F (BPF)-are coming into wider use with very few data about their biological activities. Here, we compared the effects of BPA, BPS, and BPF on human mammary organoids established from normal breast tissue. BPS disrupted organoid architecture and induced supernumerary branching. At a proteomic level, the bisphenols altered the abundance of common targets and those that were unique to each compound. The latter included proteins linked to tumor-promoting processes. These data highlighted the importance of testing the human health effects of replacements that are structurally related to chemicals of concern.

Evidence for differences in DNA methylation between Germans and Japanese

As a contribution to the discussion about the possible effects of ethnicity/ancestry on age estimation based on DNA methylation (DNAm) patterns, we directly compared age-associated DNAm in German and Japanese donors in one laboratory under identical conditions. DNAm was analyzed by pyrosequencing for 22 CpG sites (CpGs) in the genes PDE4C, RPA2, ELOVL2, DDO, and EDARADD in buccal mucosa samples from German and Japanese donors (N = 368 and N = 89, respectively).Twenty of these CpGs revealed a very high correlation with age and were subsequently tested for differences between German and Japanese donors aged between 10 and 65 years (N = 287 and N = 83, respectively). ANCOVA was performed by testing the Japanese samples against age- and sex-matched German subsamples (N = 83 each; extracted 500 times from the German total sample). The median p values suggest a strong evidence for significant differences (p < 0.05) at least for two CpGs (EDARADD, CpG 2, and PDE4C, CpG 2) and no differences for 11 CpGs (p > 0.3).Age prediction models based on DNAm data from all 20 CpGs from German training data did not reveal relevant differences between the Japanese test samples and German subsamples. Obviously, the high number of included "robust CpGs" prevented relevant effects of differences in DNAm at two CpGs.Nevertheless, the presented data demonstrates the need for further research regarding the impact of confounding factors on DNAm in the context of ethnicity/ancestry to ensure a high quality of age estimation. One approach may be the search for "robust" CpG markers-which requires the targeted investigation of different populations, at best by collaborative research with coordinated research strategies.

Investigation of promoter methylation patterns association with genes expression profile of ISL1, MGMT and DMNT3b in tissue of breast cancer patients

BACKGROUND AND OBJECTIVES

Cancer initiation and progression could influenced by both genetic and epigenetic events revealing of the overlap between epigenetic and genetic alteration can give important insights into cancer biology.

METHODS AND RESULTS

In this experiment ISL1, MGMT, DMNT3b genes were candidate to investigate both methylation status and expression profile by using methylation-specific PCR and real time PCR in 40 breast cancer patients, respectively, also we have assessed relation of the promoter methylation status and expression variation of the target genes. The mean level of methylation of ISL1 and MGMT in tumor tissues were significantly greater than normal tissues. In Contrast, DMNT3b gene was showed lower mean level of methylation in tumor tissue compared to normal tissues, however, this was not statistically significant. Relative expression analysis was displayed a significant reduction in expression level of ISL1 and MGMT in tumor tissues. Furthermore, there was a meaningful association between down expression of ISL1 with histological grade, Her2 and ER status. Moreover, MGMT down expression was significantly associated with tumor sizes. Any remarkable relation was not observed between DMNT3b expression level and clinic pathological features. At the end, significant relation between methylation status and expression level has been revealed.

CONCLUSIONS

In this study all observed results were exactly in line with the results were obtained from articles which were based on the methylation research and illustrate that the real-time PCR and methylation methods are in correlated with each other, furthermore, selected genes are capable to use as a potential biomarkers, however, more research on extended cases are needed.

Quantification Methods for Methylation Levels in Illumina Arrays

The genome-wide patterns of methylation levels and identifications of differentially methylated genetic loci or regions of CpG sites are being important, because the methylome has the potential for large effects in disease etiology. There are several quantification methods of methylation level at each CpG site for a given sample, which include β-value, M-value, and N-value. The performance of three quantification methods of methylation levels has been examined with simulation study and 27K Illumina array data for obesity.

Accelerated Epigenetic Aging Mediates the Association between Vitamin D Levels and Knee Pain in Community-Dwelling Individuals

OBJECTIVES

To examine the relationship between Vitamin D status and pain intensity and disability in individuals with and without knee pain, and to examine the role of epigenetics in this relationship.

DESIGN

Cross-sectional analysis of data from the UPLOAD-2 study (Understanding Pain and Limitations in OsteoArthritic Disease-2).

PARTICIPANTS

189 individuals aged 45-65 years and older.

MEASUREMENTS

Serum Vitamin D levels, pain related interference and characteristic pain intensity measures, and the epigenetic clock GrimAge derived from blood analyses.

RESULTS

Lower Vitamin D was associated with advanced epigenetic aging (AgeAccelGrim), greater pain and disability and that (AgeAccelGrim) mediated the relationship between Vitamin D status and self-reported pain (ab = -0.0799; CI [-0.1492, -0.0237]) and disability (ab = -0.0669; CI [-0.1365, -0.0149]) outcomes.

CONCLUSION

These data support the notion that lifestyle factors such as nutrition status play a key role in aging process, as well as the development and maintenance of age-related diseases such as pain. Modifying nutrition status could help promote healthy aging and reduce pain.

An Introduction to the Callithrix Genus and Overview of Recent Advances in Marmoset Research

We provide here a current overview of marmoset (Callithrix) evolution, hybridization, species biology, basic/biomedical research, and conservation initiatives. Composed of 2 subgroups, the aurita group (C aurita and C flaviceps) and the jacchus group (C geoffroyi, C jacchus, C kuhlii, and C penicillata), this relatively young primate radiation is endemic to the Brazilian Cerrado, Caatinga, and Atlantic Forest biomes. Significant impacts on Callithrix within these biomes resulting from anthropogenic activity include (1) population declines, particularly for the aurita group; (2) widespread geographic displacement, biological invasions, and range expansions of C jacchus and C penicillata; (3) anthropogenic hybridization; and (4) epizootic Yellow Fever and Zika viral outbreaks. A number of Brazilian legal and conservation initiatives are now in place to protect the threatened aurita group and increase research about them. Due to their small size and rapid life history, marmosets are prized biomedical models. As a result, there are increasingly sophisticated genomic Callithrix resources available and burgeoning marmoset functional, immuno-, and epigenomic research. In both the laboratory and the wild, marmosets have given us insight into cognition, social group dynamics, human disease, and pregnancy. Callithrix jacchus and C penicillata are emerging neotropical primate models for arbovirus disease, including Dengue and Zika. Wild marmoset populations are helping us understand sylvatic transmission and human spillover of Zika and Yellow Fever viruses. All of these factors are positioning marmosets as preeminent models to facilitate understanding of facets of evolution, hybridization, conservation, human disease, and emerging infectious diseases.

CUT&Tag-BS for simultaneous profiling of histone modification and DNA methylation with high efficiency and low cost

It remains a challenge to decipher the complex relationship between DNA methylation, histone modification, and the underlying DNA sequence with limited input material. Here, we developed an efficient, low-input, and low-cost method for the simultaneous profiling of genomic localization of histone modification and methylation status of the underlying DNA at single-base resolution from the same cells in a single experiment by integrating cleavage under targets and tagmentation (CUT&Tag) with tagmentation-based bisulfite sequencing (CUT&Tag-BS). We demonstrated the validity of our method using representative histone modifications of euchromatin and constitutive and facultative heterochromatin (H3K4me1, H3K9me3, and H3K27me3, respectively). Similar histone modification enrichment patterns were observed in CUT&Tag-BS compared with non-bisulfite-treated control, and H3K4me1-marked regions were found to mostly be CpG poor, lack methylation concordance, and exhibit prevalent DNA methylation heterogeneity among mouse embryonic stem cells (mESCs). We anticipate that CUT&Tag-BS will be widely applied to directly address the genomic relationship between DNA methylation and histone modification, especially in low-input scenarios with precious biological samples.

Deciphering DNA Methylation in HIV Infection

With approximately 38 million people living with HIV/AIDS globally, and a further 1.5 million new global infections per year, it is imperative that we advance our understanding of all factors contributing to HIV infection. While most studies have focused on the influence of host genetic factors on HIV pathogenesis, epigenetic factors are gaining attention. Epigenetics involves alterations in gene expression without altering the DNA sequence. DNA methylation is a critical epigenetic mechanism that influences both viral and host factors. This review has five focal points, which examines (i) fluctuations in the expression of methylation modifying factors upon HIV infection (ii) the effect of DNA methylation on HIV viral genes and (iii) host genome (iv) inferences from other infectious and non-communicable diseases, we provide a list of HIV-associated host genes that are regulated by methylation in other disease models (v) the potential of DNA methylation as an epi-therapeutic strategy and biomarker. DNA methylation has also been shown to serve as a robust therapeutic strategy and precision medicine biomarker against diseases such as cancer and autoimmune conditions. Despite new drugs being discovered for HIV, drug resistance is a problem in high disease burden settings such as Sub-Saharan Africa. Furthermore, genetic therapies that are under investigation are irreversible and may have off target effects. Alternative therapies that are nongenetic are essential. In this review, we discuss the potential role of DNA methylation as a novel therapeutic intervention against HIV.

Integrated analysis of probability of type 2 diabetes mellitus with polymorphisms and methylation of KCNQ1 gene: A nested case-control study

BACKGROUND

To estimate the associations between single-nucleotide polymorphisms (SNPs) and methylation of KCNQ1 gene and type 2 diabetes mellitus (T2DM) risk and the interactions among SNPs, methylation, and environmental factors on T2DM risk.

METHODS

We genotyped five SNPs and tested methylation at 39 CpG loci of KCNQ1 in 290 T2DM cases and 290 matched controls nested in the Rural Chinese Cohort Study. Conditional logistic regression model was used to estimate the associations between SNPs and KCNQ1 methylation and T2DM risk. Multifactor dimensionality reduction (MDR) analysis was used to estimate the effect of the interactions SNPs-SNPs, SNPs-methylation, methylation-methylation and SNPs, and methylation-environment on T2DM risk.

RESULTS

Probability of T2DM was decreased with rs2283228 of KCNQ1 (CA vs AA, odds ratio [OR] = 0.65, 95% confidence interval [CI] 0.42-0.99). T2DM probability was significantly increased with rs2237895 combined with hypertriglyceridemia (OR_eg  = 2.76, 95% CI 1.35-5.62), with hypertension (OR_eg  = 2.23, 95% CI 1.25-3.98), and with body mass index (BMI; OR_eg  = 1.93, 95% CI 1.12-3.34). T2DM probability was associated with methylation of CG11 and CG41 (OR = 1.89, 95% CI 1.23-2.89, P = .003). It was significantly associated with the interaction between BMI, hypertriglyceridemia, and CG5 methylation (P = .028 and .028), and the combined effects of CG11 with hypertriglyceridemia and hypertension. On MDR analysis, no significant interaction was observed.

CONCLUSION

T2DM probability was reduced 35% with rs2283228 polymorphism. It was associated with rs2237895 combined with hypertension, with BMI and with hypertriglyceridemia. The methylation at two CpG loci of KCNQ1 significantly increased T2DM risk by 89%.

Detecting methylation quantitative trait loci using a methylation random field method

DNA methylation may be regulated by genetic variants within a genomic region, referred to as methylation quantitative trait loci (mQTLs). The changes of methylation levels can further lead to alterations of gene expression, and influence the risk of various complex human diseases. Detecting mQTLs may provide insights into the underlying mechanism of how genotypic variations may influence the disease risk. In this article, we propose a methylation random field (MRF) method to detect mQTLs by testing the association between the methylation level of a CpG site and a set of genetic variants within a genomic region. The proposed MRF has two major advantages over existing approaches. First, it uses a beta distribution to characterize the bimodal and interval properties of the methylation trait at a CpG site. Second, it considers multiple common and rare genetic variants within a genomic region to identify mQTLs. Through simulations, we demonstrated that the MRF had improved power over other existing methods in detecting rare variants of relatively large effect, especially when the sample size is small. We further applied our method to a study of congenital heart defects with 83 cardiac tissue samples and identified two mQTL regions, MRPS10 and PSORS1C1, which were colocalized with expression QTL in cardiac tissue. In conclusion, the proposed MRF is a useful tool to identify novel mQTLs, especially for studies with limited sample sizes.

Maternal LINE-1 DNA Methylation in Early Spontaneous Preterm Birth

Despite considerable effort aimed at decreasing the incidence of spontaneous preterm birth (SPTB), it remains the leading cause of infant mortality and morbidity. The aim of this study was to evaluate maternal LINE-1 DNA methylation (DNAm), along with DNMT polymorphisms and factors proposed to modulate DNAm, in patients who delivered early preterm. This case-control study included women who delivered spontaneously early preterm (23-33^6/7 weeks of gestation), and control women. DNAm was analyzed in peripheral blood lymphocytes by quantification of LINE-1 DNAm using the MethyLight method. There was no significant difference in LINE-1 DNAm between patients with early PTB and controls. Among the investigated predictors, only the history of previous PTB was significantly associated with LINE-1 DNAm in PTB patients (β = -0.407; R² = 0.131; p = 0.011). The regression analysis showed the effect of DNMT3B rs1569686 TT+TG genotypes on LINE-1 DNAm in patients with familial PTB (β = -0.524; R² = 0.275; p = 0.037). Our findings suggest novel associations of maternal LINE-1 DNA hypomethylation with DNMT3B rs1569686 T allele. These results also contribute to the understanding of a complex (epi)genetic and environmental relationship underlying the early PTB.

Integrating Genome and Methylome Data to Identify Candidate DNA Methylation Biomarkers for Pancreatic Cancer Risk

BACKGROUND

The role of methylation in pancreatic cancer risk remains unclear. We integrated genome and methylome data to identify CpG sites (CpG) with the genetically predicted methylation to be associated with pancreatic cancer risk. We also studied gene expression to understand the identified associations.

METHODS

Using genetic data and white blood cell methylation data from 1,595 subjects of European descent, we built genetic models to predict DNA methylation levels. After internal and external validation, we applied prediction models with satisfactory performance to the genetic data of 8,280 pancreatic cancer cases and 6,728 controls of European ancestry to investigate the associations of predicted methylation with pancreatic cancer risk. For associated CpGs, we compared their measured levels in pancreatic tumor versus benign tissue.

RESULTS

We identified 45 CpGs at nine loci showing an association with pancreatic cancer risk, including 15 CpGs showing an association independent from identified risk variants. We observed significant correlations between predicted methylation of 16 of the 45 CpGs and predicted expression of eight adjacent genes, of which six genes showed associations with pancreatic cancer risk. Of the 45 CpGs, we were able to compare measured methylation of 16 in pancreatic tumor versus benign pancreatic tissue. Of them, six showed differentiated methylation.

CONCLUSIONS

We identified methylation biomarker candidates associated with pancreatic cancer using genetic instruments and added additional insights into the role of methylation in regulating gene expression in pancreatic cancer development.

IMPACT

A comprehensive study using genetic instruments identifies 45 CpG sites at nine genomic loci for pancreatic cancer risk.

From genetics to systems biology of stress-related mental disorders

Many individuals will be exposed to some form of traumatic stress in their lifetime which, in turn, increases the likelihood of developing stress-related disorders such as post-traumatic stress disorder (PTSD), major depressive disorder (MDD) and anxiety disorders (ANX). The development of these disorders is also influenced by genetics and have heritability estimates ranging between ∼30 and 70%. In this review, we provide an overview of the findings of genome-wide association studies for PTSD, depression and ANX, and we observe a clear genetic overlap between these three diagnostic categories. We go on to highlight the results from transcriptomic and epigenomic studies, and, given the multifactorial nature of stress-related disorders, we provide an overview of the gene-environment studies that have been conducted to date. Finally, we discuss systems biology approaches that are now seeing wider utility in determining a more holistic view of these complex disorders.

Harnessing the power of multi-omics data for predicting climate change response

Predicting how species will respond to future climate change is of central importance in the midst of the global biodiversity crisis, and recent work has demonstrated the utility of population genomics for improving these predictions. Here, we suggest a broadening of the approach to include other types of genomic variants that play an important role in adaptation, like structural (e.g. copy number variants) and epigenetic variants (e.g. DNA methylation). These data could provide additional power for forecasting response, especially in weakly structured or panmictic species. Incorporating structural and epigenetic variation into estimates of climate change vulnerability, or maladaptation, may not only improve prediction power but also provide insight into the molecular mechanisms underpinning species' response to climate change.

Hepatic glycogenolysis is determined by maternal high-calorie diet via methylation of Pygl and it is modified by oteocalcin administration in mice

Objective

Accumulating evidence indicates that an adverse perinatal environment contributes to a higher risk of metabolic disorders in the later life of the offspring. However, the underlying molecular mechanisms remain largely unknown. Thus, we investigated the contribution of maternal high-calorie diet and osteocalcin to metabolic homeostasis in the offspring.

Methods

Eight-week-old C57Bl/6N female mice were mated with age-matched males and allocated randomly to three groups: a normal-diet (ND) or a high-fat, high-sucrose diet group, which was administered either saline (control) or GluOC (10 ng/g body mass) from the day of mating to that of delivery, and the dams were fed a ND after the delivery. Pups weaned at 24 days after birth were analyzed.

Results

A maternal high-fat, high-sucrose diet during pregnancy causes metabolic disorders in the liver of the offspring via hypermethylation of the Pygl gene, encoding glycogen phosphorylase L, which mediates hepatic glycogenolysis. The reduced expression of Pygl induced by the maternal diet causes the hepatic accumulation of glycogen and triglyceride in the offspring, which remains in adulthood. In addition, the administration of uncarboxylated osteocalcin during pregnancy upregulates Pygl expression via both direct CREBH and ATF4 and indirect epigenomic pathways, mitigating the maternal diet-induced obesity and abnormal glucose and lipid metabolism in adulthood.

Conclusions

We propose that maternal energy status is reflected in the hepatic glycogenolysis capacity of the offspring via epigenetic modification of Pygl and uncarboxylated osteocalcin regulates glycogenolysis.

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A high-calorie diet during pregnancy causes metabolic disorders in mouse offspring.

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These are mediated by low liver expression of Pygl encoding glycogen phosphorylase.

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Hypermethylation of the Pygl promoter in utero suppresses subsequent gene expression.

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Modification and phenotypic changes are prevented by GluOC administration during pregnancy.

AI applications in functional genomics

We review the current applications of artificial intelligence (AI) in functional genomics. The recent explosion of AI follows the remarkable achievements made possible by "deep learning", along with a burst of "big data" that can meet its hunger. Biology is about to overthrow astronomy as the paradigmatic representative of big data producer. This has been made possible by huge advancements in the field of high throughput technologies, applied to determine how the individual components of a biological system work together to accomplish different processes. The disciplines contributing to this bulk of data are collectively known as functional genomics. They consist in studies of: i) the information contained in the DNA (genomics); ii) the modifications that DNA can reversibly undergo (epigenomics); iii) the RNA transcripts originated by a genome (transcriptomics); iv) the ensemble of chemical modifications decorating different types of RNA transcripts (epitranscriptomics); v) the products of protein-coding transcripts (proteomics); and vi) the small molecules produced from cell metabolism (metabolomics) present in an organism or system at a given time, in physiological or pathological conditions. After reviewing main applications of AI in functional genomics, we discuss important accompanying issues, including ethical, legal and economic issues and the importance of explainability.

ANK3 Gene Polymorphism Rs10994336 Influences Executive Functions by Modulating Methylation in Patients With Bipolar Disorder

Background: A large body of evidence suggests that epigenetic modification including DNA methylation plays a critical role in BD's pathogenesis while the identification of methylation quantitative trait loci (meQTLs) shed light on the interpretation of the function of genetic variants in non-coding regions. The intronic single nucleotide polymorphism (SNP) rs10994336 within the ANK3 has emerged as one of the most replicated risk variants for bipolar disorder (BD) in genome-wide association studies. Whether rs10994336 functions as a meQTL to mediate the association between genotype and phenotype remains unclear.

Method: A total of 154 patients with BD and 181 healthy controls (HC) were recruited. The genotypes of rs10994336 and methylation levels of CpG sites within ANK3 were tested. Executive functions were assessed using a computerized version of the Wisconsin Card Sorting Test (WCST).

Results: Bipolar disorder patients with the risk-T allele of rs10994336 scored lower on tests of executive function compared to homozygous CC carriers, after controlling for age, gender, and education level. No significant difference was found in HC individuals. The risk-T allele is associated with a lower methylation level of CpG site cg02172182 in HC after multiple corrections and replicated in the BD group in the same direction. Further mediation analysis revealed that the cg02172182 methylation significantly mediated the association between the polymorphism rs10994336 and PE index of WCST in patients with BD.

Conclusion: Our study suggests that BD-related genetic variant rs10994336 in ANK3 impacts executive functions by modulating ANK3 methylation, supporting the theory that methylation acts as a mediator between genotype and phenotype.

Blood CDKN2A Gene Expression in Aging and Neurodegenerative Diseases

BACKGROUND

Cyclin-dependent kinase inhibitor 2A (CDKN2A) is an important gene in cellular senescence and aging.

OBJECTIVE

This study assessed the utility of blood CDKN2A mRNA expression levels and methylation status as a potential biomarker for aging and the pathogenesis of Alzheimer's disease (AD).

METHODS

The correlation between CDKN2A mRNA expression levels and age was examined in 45 healthy subjects, after which mRNA expression levels were compared among 46 AD patients, 20 mild cognitive impairment due to AD patients, 21 Parkinson's disease patients, 21 dementia with Lewy bodies patients, and 55 older healthy controls. The methylation rates of the second exon of the CDKN2A gene, known to influence its expression levels, was also examined.

RESULTS

A significant correlation between CDKN2A mRNA expression levels and age was found (Spearman's rank correlation coefficient: r = 0.407, p = 0.005). CDKN2A mRNA expression levels in blood were significantly decreased in AD patients, although those of healthy controls were significantly increased with age. Further, only in AD patients were CDKN2A mRNA expression levels significantly and positively correlated with methylation rates.

CONCLUSION

Although further research with a larger sample size is needed to elucidate the relationships between CDKN2A gene expression in blood and the development of other neurodegenerative diseases, CDKN2A mRNA expression in blood may be a biomarker for differentiating AD from normal aging and other neurodegenerative diseases.

Memorable Food: Fighting Age-Related Neurodegeneration by Precision Nutrition

Healthcare systems worldwide are seriously challenged by a rising prevalence of neurodegenerative diseases (NDDs), which mostly, but not exclusively, affect the ever-growing population of the elderly. The most known neurodegenerative diseases are Alzheimer's (AD) and Parkinson's disease, multiple sclerosis, and amyotrophic lateral sclerosis, but some viral infections of the brain and traumatic brain injury may also cause NDD. Typical for NDD are the malfunctioning of neurons and their irreversible loss, which often progress irreversibly to dementia and ultimately to death. Numerous factors are involved in the pathogenesis of NDD: genetic variability, epigenetic changes, extent of oxidative/nitrosative stress, mitochondrial dysfunction, and DNA damage. The complex interplay of all the above-mentioned factors may be a fingerprint of neurodegeneration, with different diseases being affected to different extents by particular factors. There is a voluminous body of evidence showing the benefits of regular exercise to brain health and cognitive functions. Moreover, the importance of a healthy diet, balanced in macro- and micro-nutrients, in preventing neurodegeneration and slowing down a progression to full-blown disease is evident. Individuals affected by NDD almost inevitably have low-grade inflammation and anomalies in lipid metabolism. Metabolic and lipid profiles in NDD can be improved by the Mediterranean diet. Many studies have associated the Mediterranean diet with a decreased risk of dementia and AD, but a cause-and-effect relationship has not been deduced. Studies with caloric restriction showed neuroprotective effects in animal models, but the results in humans are inconsistent. The pathologies of NDD are complex and there is a great inter-individual (epi)genetic variance within any population. Furthermore, the gut microbiome, being deeply involved in nutrient uptake and lipid metabolism, also represents a pillar of the gut microbiome-brain axis and is linked with the pathogenesis of NDD. Numerous studies on the role of different micronutrients (omega-3 fatty acids, bioactive polyphenols from fruit and medicinal plants) in the prevention, prediction, and treatment of NDD have been conducted, but we are still far away from a personalized diet plan for individual NDD patients. For this to be realized, large-scale cohorts that would include the precise monitoring of food intake, mapping of genetic variants, epigenetic data, microbiome studies, and metabolome, lipidome, and transcriptome data are needed.

Paternal adverse childhood experiences: Associations with infant DNA methylation

Adverse childhood experiences (ACEs), or cumulative childhood stress exposures, such as abuse, neglect, and household dysfunction, predict later health problems in both the exposed individuals and their offspring. One potential explanation suggests exposure to early adversity predicts epigenetic modification, especially DNA methylation (DNAm), linked to later health. Stress experienced preconception by mothers may associate with DNAm in the next generation. We hypothesized that fathers' exposure to ACEs also associates with their offspring DNAm, which, to our knowledge, has not been previously explored. An epigenome-wide association study (EWAS) of blood DNAm (n = 45) from 3-month-old infants was regressed onto fathers' retrospective ACEs at multiple Cytosine-phosphate-Guanosine (CpG) sites to discover associations. This accounted for infants' sex, age, ethnicity, cell type proportion, and genetic variability. Higher ACE scores associated with methylation values at eight CpGs. Post-hoc analysis found no contribution of paternal education, income, marital status, and parental postpartum depression, but did with paternal smoking and BMI along with infant sleep latency. These same CpGs also contributed to the association between paternal ACEs and offspring attention problems at 3 years. Collectively, these findings suggested there were biological associations with paternal early life adversity and offspring DNAm in infancy, potentially affecting offspring later childhood outcomes.

A machine learning approach to brain epigenetic analysis reveals kinases associated with Alzheimer's disease

Alzheimer's disease (AD) is influenced by both genetic and environmental factors; thus, brain epigenomic alterations may provide insights into AD pathogenesis. Multiple array-based Epigenome-Wide Association Studies (EWASs) have identified robust brain methylation changes in AD; however, array-based assays only test about 2% of all CpG sites in the genome. Here, we develop EWASplus, a computational method that uses a supervised machine learning strategy to extend EWAS coverage to the entire genome. Application to six AD-related traits predicts hundreds of new significant brain CpGs associated with AD, some of which are further validated experimentally. EWASplus also performs well on data collected from independent cohorts and different brain regions. Genes found near top EWASplus loci are enriched for kinases and for genes with evidence for physical interactions with known AD genes. In this work, we show that EWASplus implicates additional epigenetic loci for AD that are not found using array-based AD EWASs.

Cell-type-specific effects of genetic variation on chromatin accessibility during human neuronal differentiation

Common genetic risk for neuropsychiatric disorders is enriched in regulatory elements active during cortical neurogenesis. However, it remains poorly understood as to how these variants influence gene regulation. To model the functional impact of common genetic variation on the noncoding genome during human cortical development, we performed the assay for transposase accessible chromatin using sequencing (ATAC-seq) and analyzed chromatin accessibility quantitative trait loci (QTL) in cultured human neural progenitor cells and their differentiated neuronal progeny from 87 donors. We identified significant genetic effects on 988/1,839 neuron/progenitor regulatory elements, with highly cell-type and temporally specific effects. A subset (roughly 30%) of chromatin accessibility-QTL were also associated with changes in gene expression. Motif-disrupting alleles of transcriptional activators generally led to decreases in chromatin accessibility, whereas motif-disrupting alleles of repressors led to increases in chromatin accessibility. By integrating cell-type-specific chromatin accessibility-QTL and brain-relevant genome-wide association data, we were able to fine-map and identify regulatory mechanisms underlying noncoding neuropsychiatric disorder risk loci.

Elevation of DNA Methylation in the Promoter Regions of the Brain-Derived Neurotrophic Factor Gene is Associated with Heroin Addiction

To study the potential role of brain-derived neurotrophic factor (BDNF) methylation in heroin addiction, we first detected the methylation level of seven CpG islands that included 106 CpG sites in the promoter regions of BDNF from 120 people addicted to heroin and 113 controls. Methylation quantitative trait locus (mQTL) analysis was then employed to determine the association between the single-nucleotide polymorphism rs6265, a well-known locus shown to be correlated with heroin addiction, and the methylation levels of these CpG sites. Finally, we used the JASPAR database to predict whether transcription factors could bind to these CpG sites. We found that the methylation levels of CpG islands 6 and 7 and the methylation levels of BDNF_45 and BDNF_80 were significantly higher in the heroin addiction group than in the control group. We also found that rs6265 was an mQTL and was associated with the methylation level of BDNF_58. Using the JASPAR database, we found that ALX homeobox 3 (ALX3), achaete-scute family bHLH transcription factor 1 (ASCL1) and aryl hydrocarbon receptor nuclear translocator 2 (ARNT2) could bind to CpG island 6, and ALX3 could bind to CpG island 7. In summary, we showed that increased DNA methylation in the promoter regions of the BDNF gene was associated with heroin addiction in Han Chinese.

Wavelet Screening identifies regions highly enriched for differentially methylated loci for orofacial clefts

DNA methylation is the most widely studied epigenetic mark in humans and plays an essential role in normal biological processes as well as in disease development. More focus has recently been placed on understanding functional aspects of methylation, prompting the development of methods to investigate the relationship between heterogeneity in methylation patterns and disease risk. However, most of these methods are limited in that they use simplified models that may rely on arbitrarily chosen parameters, they can only detect differentially methylated regions (DMRs) one at a time, or they are computationally intensive. To address these shortcomings, we present a wavelet-based method called 'Wavelet Screening' (WS) that can perform an epigenome-wide association study (EWAS) of thousands of individuals on a single CPU in only a matter of hours. By detecting multiple DMRs located near each other, WS identifies more complex patterns that can differentiate between different methylation profiles. We performed an extensive set of simulations to demonstrate the robustness and high power of WS, before applying it to a previously published EWAS dataset of orofacial clefts (OFCs). WS identified 82 associated regions containing several known genes and loci for OFCs, while other findings are novel and warrant replication in other OFCs cohorts.

Longitudinal data reveal strong genetic and weak non-genetic components of ethnicity-dependent blood DNA methylation levels

Epigenetic architecture is influenced by genetic and environmental factors, but little is known about their relative contributions or longitudinal dynamics. Here, we studied DNA methylation (DNAm) at over 750,000 CpG sites in mononuclear blood cells collected at birth and age 7 from 196 children of primarily self-reported Black and Hispanic ethnicities to study race-associated DNAm patterns. We developed a novel Bayesian method for high-dimensional longitudinal data and showed that race-associated DNAm patterns at birth and age 7 are nearly identical. Additionally, we estimated that up to 51% of all self-reported race-associated CpGs had race-dependent DNAm levels that were mediated through local genotype and, quite surprisingly, found that genetic factors explained an overwhelming majority of the variation in DNAm levels at other, previously identified, environmentally-associated CpGs. These results indicate that race-associated blood DNAm patterns in particular, and blood DNAm levels in general, are primarily driven by genetic factors, and are not as sensitive to environmental exposures as previously suggested, at least during the first 7 years of life.

17β-Estradiol alleviates cardiac aging induced by d-galactose by downregulating the methylation of autophagy-related genes

Intrinsic cardiac aging increases cardiovascular mortality and morbidity in the elderly. Estrogen helps reduce the risk of cardiovascular disease in women, with 17β-estradiol (17β-E2) activating the autophagy pathway and inhibiting vascular aging, mainly through estrogen receptor alpha (ER α) to prevent atherosclerosis. Abnormal methylation of autophagy-related genes can impact autophagic regulation. We hypothesized that 17β-E2, specifically 17β-E2 α, downregulates the methylation of autophagy factors and delays cardiac aging. Here, we used d-galactose, 17β-E2, and ER α receptor antagonist methyl-piperidino-pyrazole (MPP) to establish different aging models in mice divided into four groups, namely negative control, D.gal, D.gal + 17β-E2, and D.gal + 17β-E2 + MPP groups. Echocardiography showed that compared with the D.gal group group, the D.gal + 17β-E2 showed substantially increased cardiac function. The level of cardiac aging markers in mice in the D.gal + 17β-E2 group was lower than that in mice in the D.gal group. Beclin1, LC3, and Atg5 mRNA and protein expression levels in mice in the D.gal + 17β-E2 group were significantly increased compared with those in the D.gal group. Additionally, Beclin1, LC3, and Atg5 methylation levels were significantly decreased in the D.gal + 17β-E2 group. All the above values of the D.gal + 17β-E2 + MPP group were between those of the D.gal and D.gal + 17β-E2 groups. The expression of Dnmt1, Dnmt2, and Dnmt3A genes was the highest in the D.gal group. In summary, our results suggest that 17β-E2, specifically 17β-E2 α, promotes autophagy by downregulating the methylation of autophagy factors, thereby inhibiting galactose-induced cardiac aging in mice. 17β-E2 may be a potential therapeutic target to mitigate the effects of cardiac aging.

Exploring the use of a Comic for Education about Expanded Carrier Screening among a Diverse Group of Mothers

Purpose

Expanded carrier screening (ECS) during prenatal care is an important test for identifying prospective parents' risk of inherited genetic diseases. However, barriers remain for effectively educating patients about ECS. Graphic medicine (i.e. comics) has grown as a mechanism for patient education. The purpose of this study was to explore attitudes and opinions of a comic to educate about ECS during prental care.

Methods

Focus groups were conducted with pregnant women or women who recently gave birth (6 groups, n=54). The participants were all female, 44.4% Latino/Hispanic, 16.7% Bi-Racial/Other, and 43.3% reporting some college education or high school degree.

Results

Most participants reported high enjoyment with the comic due to their relatability to the characters, simplicity of the story, description of medical outcomes in everyday terms and the exploration of multiple outcomes possible with ECS. In addition, participants reported that during pregnancy their reading habits increase as well as emotional reactions to the content and some participants stated they avoided reading information that may cause stress or anxiety.

Conclusion

More research is needed to assess what features of the comic promote understanding and how that influences decisions and pre-test patient education for ECS. The use of graphic narratives may enable individuals to better understand medical information in general.

Harsh Parenting Predicts Novel HPA Receptor Gene Methylation and NR3C1 Methylation Predicts Cortisol Daily Slope in Middle Childhood

Adverse experiences in childhood are associated with altered hypothalamic-pituitary-adrenal (HPA) axis function and negative health outcomes throughout life. It is now commonly accepted that abuse and neglect can alter epigenetic regulation of HPA genes. Accumulated evidence suggests harsh parenting practices such as spanking are also strong predictors of negative health outcomes. We predicted harsh parenting at 2.5 years old would predict HPA gene DNA methylation similarly to abuse and neglect, and cortisol output at 8.5 years old. Saliva samples were collected three times a day across 3 days to estimate cortisol diurnal slopes. Methylation was quantified using the Illumina Infinium MethylationEPIC array BeadChip (850 K) with DNA collected from buccal cells. We used principal components analysis to compute a summary statistic for CpG sites across candidate genes. The first and second components were used as outcome variables in mixed linear regression analyses with harsh parenting as a predictor variable. We found harsh parenting significantly predicted methylation of several HPA axis genes, including novel gene associations with AVPRB1, CRHR1, CRHR2, and MC2R (FDR corrected p < 0.05). Further, we found NR3C1 methylation predicted a steeper diurnal cortisol slope. Our results extend the current literature by demonstrating harsh parenting may influence DNA methylation similarly to more extreme early life experiences such as abuse and neglect. Further, we show NR3C1 methylation is associated with diurnal HPA function. Elucidating the molecular consequences of harsh parenting on health can inform best parenting practices and provide potential treatment targets for common complex disorders.

Genetic impacts on DNA methylation: research findings and future perspectives

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

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

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

Hypomethylation mediates genetic association with the major histocompatibility complex genes in Sjögren's syndrome

Differential methylation of immune genes has been a consistent theme observed in Sjögren's syndrome (SS) in CD4+ T cells, CD19+ B cells, whole blood, and labial salivary glands (LSGs). Multiple studies have found associations supporting genetic control of DNA methylation in SS, which in the absence of reverse causation, has positive implications for the potential of epigenetic therapy. However, a formal study of the causal relationship between genetic variation, DNA methylation, and disease status is lacking. We performed a causal mediation analysis of DNA methylation as a mediator of nearby genetic association with SS using LSGs and genotype data collected from 131 female members of the Sjögren's International Collaborative Clinical Alliance registry, comprising of 64 SS cases and 67 non-cases. Bumphunter was used to first identify differentially-methylated regions (DMRs), then the causal inference test (CIT) was applied to identify DMRs mediating the association of nearby methylation quantitative trait loci (MeQTL) with SS. Bumphunter discovered 215 DMRs, with the majority located in the major histocompatibility complex (MHC) on chromosome 6p21.3. Consistent with previous findings, regions hypomethylated in SS cases were enriched for gene sets associated with immune processes. Using the CIT, we observed a total of 19 DMR-MeQTL pairs that exhibited strong evidence for a causal mediation relationship. Close to half of these DMRs reside in the MHC and their corresponding meQTLs are in the region spanning the HLA-DQA1, HLA-DQB1, and HLA-DQA2 loci. The risk of SS conferred by these corresponding MeQTLs in the MHC was further substantiated by previous genome-wide association study results, with modest evidence for independent effects. By validating the presence of causal mediation, our findings suggest both genetic and epigenetic factors contribute to disease susceptibility, and inform the development of targeted epigenetic modification as a therapeutic approach for SS.

Differential DNA Methylation by Hispanic Ethnicity Among Firefighters in the United States

Firefighters are exposed to a variety of environmental hazards and are at increased risk for multiple cancers. There is evidence that risks differ by ethnicity, yet the biological or environmental differences underlying these differences are not known. DNA methylation is one type of epigenetic regulation that is altered in cancers. In this pilot study, we profiled DNA methylation with the Infinium MethylationEPIC in blood leukocytes from 31 Hispanic white and 163 non-Hispanic white firefighters. We compared DNA methylation (1) at 12 xenobiotic metabolizing genes and (2) at all loci on the array (>740 000), adjusting for confounders. Five of the xenobiotic metabolizing genes were differentially methylated at a raw P-value <.05 when comparing the 2 ethnic groups, yet were not statistically significant at a 5% false discovery rate (q-value <.05). In the epigenome-wide analysis, 76 loci exhibited DNA methylation differences at q < .05. Among these, 3 CpG sites in the promoter region of the biotransformation gene SULT1C2 had lower methylation in Hispanic compared to non-Hispanic firefighters. Other differentially methylated loci included genes that have been implicated in carcinogenesis in published studies (FOXK2, GYLTL1B, ZBTB16, ARHGEF10, and more). In this pilot study, we report differential DNA methylation between Hispanic and non-Hispanic firefighters in xenobiotic metabolism genes and other genes with functions related to cancer. Epigenetic susceptibility by ethnicity merits further study as this may alter risk for cancers linked to toxic exposures.

Integrative analysis of DNA methylation and gene expression profiles identified potential breast cancer-specific diagnostic markers

Breast cancer is a common malignant tumor among women whose prognosis is largely determined by the period and accuracy of diagnosis. We here propose to identify a robust DNA methylation-based breast cancer-specific diagnostic signature. Genome-wide DNA methylation and gene expression profiles of breast cancer patients along with their adjacent normal tissues from the Cancer Genome Atlas (TCGA) were obtained as the training set. CpGs that with significantly elevated methylation level in breast cancer than not only their adjacent normal tissues and the other ten common cancers from TCGA but also the healthy breast tissues from the Gene Expression Omnibus (GEO) were finally remained for logistic regression analysis. Another independent breast cancer DNA methylation dataset from GEO was used as the testing set. Lots of CpGs were hyper-methylated in breast cancer samples compared with adjacent normal tissues, which tend to be negatively correlated with gene expressions. Eight CpGs located at RIIAD1, ENPP2, ESPN, and ETS1, were finally retained. The diagnostic model was reliable in separating BRCA from normal samples. Besides, chromatin accessibility status of RIIAD1, ENPP2, ESPN and ETS1 showed great differences between MCF-7 and MDA-MB-231 cell lines. In conclusion, the present study should be helpful for breast cancer early and accurate diagnosis.

Landscape of epigenetically regulated lncRNAs and DNA methylation in smokers with lung adenocarcinoma

In this study, we identified long non-coding RNAs (lncRNAs) associated with DNA methylation in lung adenocarcinoma (LUAD) using clinical and methylation/expression data from 184 qualified LUAD tissue samples and 21 normal lung-tissue samples from The Cancer Genome Atlas (TCGA). We identified 1865 differentially expressed genes that correlated negatively with the methylation profiles of normal lung tissues, never-smoker LUAD tissues and smoker LUAD tissues, while 1079 differentially expressed lncRNAs were identified using the same criteria. These transcripts were integrated using ingenuity pathway analysis to determine significant pathways directly related to cancer, suggesting that lncRNAs play a crucial role in carcinogenesis. When comparing normal lung tissues and smoker LUAD tissues, 86 candidate genes were identified, including six lncRNAs. Of the 43 candidate genes revealed by comparing never-smoker LUAD tissues and smoker LUAD tissues, 13 were also different when compared to normal lung tissues. We then investigated the expression of these genes using the Gene Expression of Normal and Tumor Tissues (GENT) and Methylation and Expression Database of Normal and Tumor Tissues (MENT) databases. We observed an inverse correlation between the expression of 13 genes in normal lung tissues and smoker LUAD tissues, and the expression of five genes between the never-smoker and smoker LUAD tissues. These findings were further validated in clinical specimens using bisulfite sequencing, revealing that AGR2, AURKB, FOXP3, and HMGA1 displayed borderline differences in methylation. Finally, we explored the functional connections between DNA methylation, lncRNAs, and gene expression to identify possible targets that may contribute toward the pathogenesis of cigarette smoking-associated LUAD. Together, our findings suggested that differentially expressed lncRNAs and their target transcripts could serve as potential biomarkers for LUAD.

Bipartite graph-based approach for clustering of cell lines by gene expression-drug response associations

MOTIVATION

In pharmacogenomic studies, the biological context of cell lines influences the predictive ability of drug-response models and the discovery of biomarkers. Thus, similar cell lines are often studied together based on prior knowledge of biological annotations. However, this selection approach is not scalable with the number of annotations, and the relationship between gene-drug association patterns and biological context may not be obvious.

RESULTS

We present a procedure to compare cell lines based on their gene-drug association patterns. Starting with a grouping of cell lines from biological annotation, we model gene-drug association patterns for each group as a bipartite graph between genes and drugs. This is accomplished by applying sparse canonical correlation analysis (SCCA) to extract the gene-drug associations, and using the canonical vectors to construct the edge weights. Then, we introduce a nuclear norm-based dissimilarity measure to compare the bipartite graphs. Accompanying our procedure is a permutation test to evaluate the significance of similarity of cell line groups in terms of gene-drug associations. In the pharmacogenomics datasets CTRP2, GDSC2, and CCLE, hierarchical clustering of carcinoma groups based on this dissimilarity measure uniquely reveals clustering patterns driven by carcinoma subtype rather than primary site. Next, we show that the top associated drugs or genes from SCCA can be used to characterize the clustering patterns of haematopoietic and lymphoid malignancies. Finally, we confirm by simulation that when drug responses are linearly-dependent on expression, our approach is the only one that can effectively infer the true hierarchy compared to existing approaches.

AVAILABILITY

Bipartite graph-based hierarchical clustering is implemented in R and can be obtained from CRAN: https://CRAN.R-project.org/package=hierBipartite. The source code is available at https://github.com/CalvinTChi/hierBipartite.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

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

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

Association between COMT methylation and response to treatment in children with ADHD

BACKGROUND

COMT had been considered a promising candidate gene in pharmacogenetic studies in ADHD; yet the findings from these studies have been inconsistent. Part of these inconsistencies could be related to epigenetic mechanisms (including DNA methylation). Here we investigated the role of genetic variants of the COMT gene on the methylation levels of CpG sites in the same gene and explored the effect of methylation on methylphenidate (MPH) and placebo (PBO) response in children with ADHD.

METHODS

Two hundred and thirty children with ADHD (6-12 years) participated in a randomized, double-blind, placebo-controlled crossover trial with MPH. Univariate analysis was performed to examine the associations between genotypes in the COMT gene and DNA methylation in the same genetic loci. Association between the DNA methylation of 11 CpG sites and PBO/MPH responses were then assessed using spearman's correlation analysis in 212 children. Multiple linear regression analyses were performed to test the interaction between these factors while accounting for sex.

RESULTS

Associations were observed between specific genetic variants and methylation level of cg20709110. Homozygous genotypes of GG (rs6269), CC (rs4633), GG (rs4818), Val/Val (rs4680) and the haplotype (ACCVal/GCGVal) were significantly associated with higher level of methylation. This CpG showed a significant correlation with placebo response (r = -0.15, P = 0.045) according to the teachers' evaluation, and a close-to significance correlation with response to MPH according to parents' evaluation (r = -0.134, p = 0.051). Regression analysis showed that in the model including rs4818, sex and DNA methylation of cg20709110 contributed significantly to treatment response.

CONCLUSIONS

These preliminary results could provide evidence for the effect of genetic variations on methylation level and the involvement of the epigenetic variation of COMT loci in modulating the response to treatment in ADHD.

TRIAL REGISTRATION

clinicaltrials.gov, number NCT00483106.

Multi-omics analysis to identify susceptibility genes for colorectal cancer

Most genetic variants for colorectal cancer (CRC) identified in genome-wide association studies (GWAS) are located in intergenic regions, implying pathogenic dysregulations of gene expression. However, comprehensive assessments of target genes in CRC remain to be explored. We conducted a multi-omics analysis using transcriptome and/or DNA methylation data from the Genotype-Tissue Expression, The Cancer Genome Atlas and the Colonomics projects. We identified 116 putative target genes for 45 GWAS-identified variants. Using summary-data-based Mendelian randomization approach (SMR), we demonstrated that the CRC susceptibility for 29 out of the 45 CRC variants may be mediated by cis-effects on gene regulation. At a cutoff of the Bonferroni-corrected PSMR < 0.05, we determined 66 putative susceptibility genes, including 39 genes that have not been previously reported. We further performed in vitro assays for two selected genes, DIP2B and SFMBT1, and provide functional evidence that they play a vital role in colorectal carcinogenesis via disrupting cell behavior, including migration, invasion and epithelial-mesenchymal transition. Our study reveals a large number of putative novel susceptibility genes and provides additional insight into the underlying mechanisms for CRC genetic risk loci.

Cellular Heterogeneity-Adjusted cLonal Methylation (CHALM) improves prediction of gene expression

Promoter DNA methylation is a well-established mechanism of transcription repression, though its global correlation with gene expression is weak. This weak correlation can be attributed to the failure of current methylation quantification methods to consider the heterogeneity among sequenced bulk cells. Here, we introduce Cell Heterogeneity-Adjusted cLonal Methylation (CHALM) as a methylation quantification method. CHALM improves understanding of the functional consequences of DNA methylation, including its correlations with gene expression and H3K4me3. When applied to different methylation datasets, the CHALM method enables detection of differentially methylated genes that exhibit distinct biological functions supporting underlying mechanisms.

Specific Differentially Methylated and Expressed Genes in People with Longevity Family History

Background

We attempt to identify specific differentially methylated and expressed genes in people with longevity family history, it will contribute to discover significant features about human longevity.

Methods

A prevalence study was conducted during October 2017 to January 2019 in Bama County of Guangxi, China and individuals were recruited and grouped into longevity family (n=60) and non-longevity family (n=60) to identify differentially methylated genes (DMGs). The expression profile dataset GSE16717 was downloaded from the GEO database in which individuals were divided into 3 groups, namely longevity (n=50), longevity offspring (n=50) and control (n=50) for identifying differentially expressed genes (DEGs). It was considered significantly different when P or adjusted P≤0.05.

Results

In total, 117 longevity-related hypermethylated genes enriched in interleukin secretion/production regulation, chemokine signaling pathway and natural killer cell-mediated cytotoxicity. Another 296 significant key longevity-related DEGs primarily involved in protein binding, nucleus, cytoplasm, T cell receptor signaling pathway and Metabolic pathway, H19 and PFKFB4 were found to be both methylated and downregulated in people with longevity family history.

Conclusion

Human longevity-specific genes involve in many immunity regulations and cellular immunity pathways, H19 and PFKFB4 show hypermethylated and suppressed status in people with longevity family history and might serve as longevity candidate genes.

Role of DNA Methylation in Mediating Genetic Risk of Psychiatric Disorders

Psychiatric disorders are common, complex, and heritable conditions estimated to be the leading cause of disability worldwide. The last decade of research in genomics of psychiatry, performed by multinational, and multicenter collaborative efforts on hundreds of thousands of mental disorder cases and controls, provided invaluable insight into the genetic risk variants of these conditions. With increasing cohort sizes, more risk variants are predicted to be identified in the near future, but there appears to be a knowledge gap in understanding how these variants contribute to the pathophysiology of psychiatric disorders. Majority of the identified common risk single-nucleotide polymorphisms (SNPs) are non-coding but are enriched in regulatory regions of the genome. It is therefore of great interest to study the impact of identified psychiatric disorders' risk SNPs on DNA methylation, the best studied epigenetic modification, playing a pivotal role in the regulation of transcriptomic processes, brain development, and functioning. This work outlines the mechanisms through which risk SNPs can impact DNA methylation levels and provides a summary of current evidence on the role of DNA methylation in mediating the genetic risk of psychiatric disorders.

Integrative analysis identifies potential causal methylation-mRNA regulation chains for rheumatoid arthritis

Genome-wide association studies have identified many genetic loci for rheumatoid arthritis (RA). However, causal factors underlying these loci were largely unknown. The aim of this study was to identify potential causal methylation-mRNA regulation chains for RA. We identified differentially expressed mRNAs and methylations and conducted summary statistic data-based Mendelian randomization (SMR) analysis to detect potential causal mRNAs and methylations for RA. Then causal inference test (CIT) was performed to determine if the methylation-mRNA pairs formed causal chains. We identified 11,170 mRNAs and 24,065 methylations that were nominally associated with RA. Among them, 197 mRNAs and 104 methylations passed the SMR test. According to physical positions, we defined 16 cis methylation-mRNA pairs and inferred 5 chains containing 4 methylations and 4 genes (BACH2, MBP, MX1 and SYNGR1) to be methylation→mRNA→RA causal chains. The effect of SYNGR1 expression in peripheral blood mononuclear cells on RA risk was found to be consistent in both the in-house and public data. The identified methylations located in CpG Islands that overlap promoters in the 5' region of the genes. The promoter regions showed long-range interactions with other enhancers and promoters, suggesting a regulatory potential of these methylations. Therefore, the present study provided a new integrative analysis strategy and highlighted potential causal methylation-mRNA chains for RA. Taking the evidences together, SYNGR1 promoter methylations most probably affect mRNA expressions and then affect RA risk.

The methylation landscape and its role in domestication and gene regulation in the chicken

Domestication is one of the strongest examples of artificial selection and has produced some of the most extreme within-species phenotypic variation known. In the case of the chicken, it has been hypothesized that DNA methylation may play a mechanistic role in the domestication response. By inter-crossing wild-derived red junglefowl with domestic chickens, we mapped quantitative trait loci for hypothalamic methylation (methQTL), gene expression (eQTL) and behaviour. We find large, stable methylation differences, with 6,179 cis and 2,973 trans methQTL identified. Over 46% of the trans effects were genotypically controlled by five loci, mainly associated with increased methylation in the junglefowl genotype. In a third of eQTL, we find that there is a correlation between gene expression and methylation, while statistical causality analysis reveals multiple instances where methylation is driving gene expression, as well as the reverse. We also show that methylation is correlated with some aspects of behavioural variation in the inter-cross. In conclusion, our data suggest a role for methylation in the regulation of gene expression underlying the domesticated phenotype of the chicken.

Vitamin D and its Effects on DNA Methylation in Development, Aging, and Disease

DNA methylation is increasingly being recognized as a mechanism through which environmental exposures confer disease risk. Several studies have examined the association between vitamin D and changes in DNA methylation in areas as diverse as human and animal development, genomic stability, chronic disease risk, and malignancy. In many cases, they have demonstrated clear associations between vitamin D and DNA methylation in candidate disease pathways. Despite this, a clear understanding of the mechanisms by which these factors interact is unclear. This paper reviews the current understanding of the effects of vitamin D on DNA methylation. In light of current knowledge in the field, the potential mechanisms mediating vitamin D effects on DNA methylation are discussed, as are the limiting factors and future avenues for research into this exciting area.

'There and Back Again'-Forward Genetics and Reverse Phenotyping in Pulmonary Arterial Hypertension

Although the invention of right heart catheterisation in the 1950s enabled accurate clinical diagnosis of pulmonary arterial hypertension (PAH), it was not until 2000 when the landmark discovery of the causative role of bone morphogenetic protein receptor type II (BMPR2) mutations shed new light on the pathogenesis of PAH. Since then several genes have been discovered, which now account for around 25% of cases with the clinical diagnosis of idiopathic PAH. Despite the ongoing efforts, in the majority of patients the cause of the disease remains elusive, a phenomenon often referred to as "missing heritability". In this review, we discuss research approaches to uncover the genetic architecture of PAH starting with forward phenotyping, which in a research setting should focus on stable intermediate phenotypes, forward and reverse genetics, and finally reverse phenotyping. We then discuss potential sources of "missing heritability" and how functional genomics and multi-omics methods are employed to tackle this problem.

Genome-Wide Epigenetic Signatures of Adaptive Developmental Plasticity in the Andes

High-altitude adaptation is a classic example of natural selection operating on the human genome. Physiological and genetic adaptations have been documented in populations with a history of living at high altitude. However, the role of epigenetic gene regulation, including DNA methylation, in high-altitude adaptation is not well understood. We performed an epigenome-wide DNA methylation association study based on whole blood from 113 Peruvian Quechua with differential lifetime exposures to high altitude (>2,500) and recruited based on a migrant study design. We identified two significant differentially methylated positions (DMPs) and 62 differentially methylated regions (DMRs) associated with high-altitude developmental and lifelong exposure statuses. DMPs and DMRs were found in genes associated with hypoxia-inducible factor pathway, red blood cell production, blood pressure, and others. DMPs and DMRs associated with fractional exhaled nitric oxide also were identified. We found a significant association between EPAS1 methylation and EPAS1 SNP genotypes, suggesting that local genetic variation influences patterns of methylation. Our findings demonstrate that DNA methylation is associated with early developmental and lifelong high-altitude exposures among Peruvian Quechua as well as altitude-adaptive phenotypes. Together these findings suggest that epigenetic mechanisms might be involved in adaptive developmental plasticity to high altitude. Moreover, we show that local genetic variation is associated with DNA methylation levels, suggesting that methylation associated SNPs could be a potential avenue for research on genetic adaptation to hypoxia in Andeans.

Leveraging functional annotation to identify genes associated with complex diseases

To increase statistical power to identify genes associated with complex traits, a number of transcriptome-wide association study (TWAS) methods have been proposed using gene expression as a mediating trait linking genetic variations and diseases. These methods first predict expression levels based on inferred expression quantitative trait loci (eQTLs) and then identify expression-mediated genetic effects on diseases by associating phenotypes with predicted expression levels. The success of these methods critically depends on the identification of eQTLs, which may not be functional in the corresponding tissue, due to linkage disequilibrium (LD) and the correlation of gene expression between tissues. Here, we introduce a new method called T-GEN (Transcriptome-mediated identification of disease-associated Genes with Epigenetic aNnotation) to identify disease-associated genes leveraging epigenetic information. Through prioritizing SNPs with tissue-specific epigenetic annotation, T-GEN can better identify SNPs that are both statistically predictive and biologically functional. We found that a significantly higher percentage (an increase of 18.7% to 47.2%) of eQTLs identified by T-GEN are inferred to be functional by ChromHMM and more are deleterious based on their Combined Annotation Dependent Depletion (CADD) scores. Applying T-GEN to 207 complex traits, we were able to identify more trait-associated genes (ranging from 7.7% to 102%) than those from existing methods. Among the identified genes associated with these traits, T-GEN can better identify genes with high (>0.99) pLI scores compared to other methods. When T-GEN was applied to late-onset Alzheimer's disease, we identified 96 genes located at 15 loci, including two novel loci not implicated in previous GWAS. We further replicated 50 genes in an independent GWAS, including one of the two novel loci.