Mechanisms and Disease Associations of Haplotype-Dependent Allele-Specific DNA Methylation

FastQTLmapping: an ultra-fast and memory efficient package for mQTL-like analysis

BACKGROUND

FastQTLmapping addresses the need for an ultra-fast and memory-efficient solver capable of handling exhaustive multiple regression analysis with a vast number of dependent and explanatory variables, including covariates. This challenge is especially pronounced in methylation quantitative trait loci (mQTL)-like analysis, which typically involves high-dimensional genetic and epigenetic data.

RESULTS

FastQTLmapping is a precompiled C++ software solution accelerated by Intel MKL and GSL, freely available at https://github.com/Fun-Gene/fastQTLmapping . Compared to state-of-the-art methods (MatrixEQTL, FastQTL, and TensorQTL), fastQTLmapping demonstrated an order of magnitude speed improvement, coupled with a marked reduction in peak memory usage. In a large dataset consisting of 3500 individuals, 8 million SNPs, 0.8 million CpGs, and 20 covariates, fastQTLmapping completed the entire mQTL analysis in 4.5 h with only 13.1 GB peak memory usage.

CONCLUSIONS

FastQTLmapping effectively expedites comprehensive mQTL analyses by providing a robust and generic approach that accommodates large-scale genomic datasets with covariates. This solution has the potential to streamline mQTL-like studies and inform future method development for efficient computational genomics.

Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders

Increasing evidence supports the role of the placenta in neurodevelopment and in the onset of neuropsychiatric disorders. Recently, mQTL and iQTL maps have proven useful in understanding relationships between SNPs and GWAS that are not captured by eQTL. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation. We construct a public placental cis-mQTL database including 214,830 CpG sites calculated in 368 fetal placenta DNA samples from the INMA project, and run cell type-, gestational age- and sex-imQTL models. We combine these data with summary statistics of GWAS on ten neuropsychiatric disorders using summary-based Mendelian randomization and colocalization. We also evaluate the influence of identified DNA methylation sites on placental gene expression in the RICHS cohort. We find that placental cis-mQTLs are enriched in placenta-specific active chromatin regions, and establish that part of the genetic burden for schizophrenia, bipolar disorder, and major depressive disorder confers risk through placental DNA methylation. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, the involvement of cell type-imQTLs, and the correlation of identified DNA methylation sites with the expression levels of relevant genes in the placenta.

Genetic-epigenetic interactions (meQTLs) in orofacial clefts etiology

Objectives

Nonsyndromic orofacial clefts (OFCs) etiology involves multiple genetic and environmental factors with over 60 identified risk loci; however, they account for only a minority of the estimated risk. Epigenetic factors such as differential DNA methylation (DNAm) are also associated with OFCs risk and can alter risk for different cleft types and modify OFCs penetrance. DNAm is a covalent addition of a methyl (CH3) group to the nucleotide cytosine that can lead to changes in expression of the targeted gene. DNAm can be affected by environmental influences and genetic variation via methylation quantitative loci (meQTLs). We hypothesize that aberrant DNAm and the resulting alterations in gene expression play a key role in the etiology of OFCs, and that certain common genetic variants that affect OFCs risk do so by influencing DNAm.

Methods

We used genotype from 10 cleft-associated SNPs and genome-wide DNA methylation data (Illumina 450K array) for 409 cases with OFCs and 456 controls and identified 23 cleft-associated meQTLs. We then used an independent cohort of 362 cleft-discordant sib pairs for replication. We used methylation-specific qPCR to measure methylation levels of each CpG site and combined genotypic and methylation data for an interaction analysis of each SNP-CpG pair using the R package MatrixeQTL in a linear model. We also performed a Paired T-test to analyze differences in DNA methylation between each member of the sibling pairs.

Results

We replicated 9 meQTLs, showing interactions between rs13041247 (MAFB) - cg18347630 (PLCG1) (P=0.04); rs227731 (NOG) - cg08592707 (PPM1E) (P=0.01); rs227731 (NOG) - cg10303698 (CUEDC1) (P=0.001); rs3758249 (FOXE1) - cg20308679 (FRZB) (P=0.04); rs8001641 (SPRY2) - cg19191560 (LGR4) (P=0.04); rs987525(8q24) - cg16561172(MYC) (P=0.00000963); rs7590268(THADA) - cg06873343 (TTYH3) (P=0.04); rs7078160 (VAX1) - cg09487139 (P=0.05); rs560426 (ABCA4/ARHGAP29) - cg25196715 (ABCA4/ARHGAP29) (P=0,03). Paired T-test showed significant differences for cg06873343 (TTYH3) (P=0.04); cg17103269 (LPIN3) (P=0.002), and cg19191560 (LGR4) (P=0.05).

Conclusions

Our results confirm previous evidence that some of the common non-coding variants detected through GWAS studies can influence the risk of OFCs via epigenetic mechanisms, such as DNAm, which can ultimately affect and regulate gene expression. Given the large prevalence of non-coding SNPs in most OFCs genome wide association studies, our findings can potentially address major knowledge gaps, like missing heritability, reduced penetrance, and variable expressivity associated with OFCs phenotypes.

Haplotype-resolved genome assembly of Ficus carica L. reveals allele-specific expression in the fruit

In this study, we produced a haplotype-phased genome sequence of the fig tree (Ficus carica L.), a non-Rosaceae fruit tree model species, providing a systematic overview of the organization of a heterozygous diploid genome and, for the first time in a fruit tree, evidence of allelic expression direction-shifting among haplotypes. The genome was used for whole genome analysis of heterozygosis, allelic cytosine methylation, and expression profiles in peel and pulp fruit tissues. The two pseudo-haplotypes spanned approximately 355 and 346 Mbp, respectively, and 97% of the sequences were associated with 13 chromosome pairs of the fig tree. Overall, the methylation profile in peel and pulp tissues showed no variations between the homologous chromosomes. However, we detected differential DNA methylation within defined heterozygous allelic gene regions, particularly in upstream regions. Among 6768 heterozygous coding sequences identified, 4024 exhibited allele-specific expression, with approximately 18% specific to the peel and 14% to the pulp. Specifically, 2715 genes were consistent, with one allele always more expressed than the other in both peel and pulp. On the contrary, 22 allele-specific expressed genes switched allele expression among the fig fruit peel and pulp tissues, indicating evidence of overdominance and suggesting that the genome can express one of the two alleles higher or lower depending on developmental or environmental triggers. Notably, these genes were associated with key biological processes, including fruit maturation regulation, seed maturation, and stress response, highlighting their potential role in the plant's developmental and adaptive functions in view of gene editing-based breeding.

Expanding Upon Genomics in Rare Diseases: Epigenomic Insights

DNA methylation is an essential epigenetic modification that plays a crucial role in regulating gene expression and maintaining genomic stability. With the advancement in sequencing technology, methylation studies have provided valuable insights into the diagnosis of rare diseases through the various identification of episignatures, epivariation, epioutliers, and allele-specific methylation. However, current methylation studies are not without limitations. This mini-review explores the current understanding of DNA methylation in rare diseases, highlighting the key mechanisms and diagnostic potential, and emphasizing the need for advanced methodologies and integrative approaches to enhance the understanding of disease progression and design more personable treatment for patients, given the nature of rare diseases.

Single chromatin fiber profiling and nucleosome position mapping in the human brain

We apply a single-molecule chromatin fiber sequencing (Fiber-seq) protocol designed for amplification-free cell-type-specific mapping of the regulatory architecture at nucleosome resolution along extended ∼10-kb chromatin fibers to neuronal and non-neuronal nuclei sorted from human brain tissue. Specifically, application of this method enables the resolution of cell-selective promoter and enhancer architectures on single fibers, including transcription factor footprinting and position mapping, with sequence-specific fixation of nucleosome arrays flanking transcription start sites and regulatory motifs. We uncover haplotype-specific chromatin patterns, multiple regulatory elements cis-aligned on individual fibers, and accessible chromatin at 20,000 unique sites encompassing retrotransposons and other repeat sequences hitherto "unmappable" by short-read epigenomic sequencing. Overall, we show that Fiber-seq is applicable to human brain tissue, offering sharp demarcation of nucleosome-depleted regions at sites of open chromatin in conjunction with multi-kilobase nucleosomal positioning at single-fiber resolution on a genome-wide scale.

Cognitive benefits of folic acid supplementation during pregnancy track with epigenetic changes at an imprint regulator

BACKGROUND

The human ZFP57 gene is a major regulator of imprinted genes, maintaining DNA methylation marks that distinguish parent-of-origin-specific alleles. DNA methylation of the gene itself has shown sensitivity to environmental stimuli, particularly folate status. However, the role of DNA methylation in ZFP57's own regulation has not been fully investigated.

METHODS

We used samples and data from our previously described randomised controlled trial (RCT) in pregnancy called Folic Acid Supplementation in the Second and Third Trimester (FASSTT), including follow-up of the children at age 11. Biometric and blood biochemistry results were examined for mothers and children. Methylation of ZFP57 was analysed by EPIC arrays, pyrosequencing and clonal analysis, and transcription assessed by PCR-based methods. Functional consequences of altered methylation were examined in cultured cells with mutations or by inhibition of the main DNA methyltransferases. DNA variants were examined using pyrosequencing and Sanger sequencing, with results compared to published studies using bioinformatic approaches. Cognitive outcomes were assessed using the Wechsler Intelligence Scale for Children 4th UK Edition (WISC-IV), with neural activity during language tasks quantified using magnetoencephalography (MEG).

RESULTS

Here we show that methylation at an alternative upstream promoter of ZFP57 is controlled in part by a quantitative trait locus (QTL). By altering DNA methylation levels, we demonstrate that this in turn controls the expression of the ZFP57 isoforms. Methylation at this region is also sensitive to folate levels, as we have previously shown in this cohort. Fully methylated alleles were associated with poorer performance in the Symbol Search and Cancellation subtests of WISC-IV in the children at age 11 years. There were also differences in neural activity during language tasks, as measured by MEG. Analysis of published genome-wide studies indicated other SNPs in linkage disequilibrium with the mQTL were also associated with neurodevelopmental outcomes.

CONCLUSIONS

While numbers in the current RCT were small and require further validation in larger cohorts, the results nevertheless suggest a molecular mechanism by which maternal folic acid supplementation during pregnancy may help to counteract the effects of folate depletion and positively influence cognitive development in the offspring.

Long-read sequencing of an advanced cancer cohort resolves rearrangements, unravels haplotypes, and reveals methylation landscapes

The Long-Read Personalized OncoGenomics (POG) dataset comprises a cohort of 189 patient tumors and 41 matched normal samples sequenced using the Oxford Nanopore Technologies PromethION platform. This dataset from the POG program and the Marathon of Hope Cancer Centres Network includes DNA and RNA short-read sequence data, analytics, and clinical information. We show the potential of long-read sequencing for resolving complex cancer-related structural variants, viral integrations, and extrachromosomal circular DNA. Long-range phasing facilitates the discovery of allelically differentially methylated regions (aDMRs) and allele-specific expression, including recurrent aDMRs in the cancer genes RET and CDKN2A. Germline promoter methylation in MLH1 can be directly observed in Lynch syndrome. Promoter methylation in BRCA1 and RAD51C is a likely driver behind homologous recombination deficiency where no coding driver mutation was found. This dataset demonstrates applications for long-read sequencing in precision medicine and is available as a resource for developing analytical approaches using this technology.

Quantitative trait locus mapping in placenta: A comparative study of chorionic villus and birth placenta

The placenta, a pivotal player in the prenatal environment, holds crucial insights into early developmental pathways and future health outcomes. In this study, we explored genetic molecular regulation in chorionic villus samples (CVS) from the first trimester and placenta tissue at birth. We assessed quantitative trait locus (QTL) mapping on DNA methylation and gene expression data in a Finnish cohort of 574 individuals. We found more QTLs in birth placenta than in first-trimester placenta. Nevertheless, a substantial amount of associations overlapped in their effects and showed consistent direction in both tissues, with increasing molecular genetic effects from early pregnancy to birth placenta. The identified QTLs in birth placenta were most enriched in genes with placenta-specific expression. Conducting a phenome-wide-association study (PheWAS) on the associated SNPs, we observed numerous overlaps with genome-wide association study (GWAS) hits (spanning 57 distinct traits and 23 SNPs), with notable enrichments for immunological, skeletal, and respiratory traits. The QTL-SNP rs1737028 (chr6:29737993) presented with the highest number of GWAS hits. This SNP was related to HLA-G expression via DNA methylation and was associated with various immune, respiratory, and psychiatric traits. Our findings implicate increasing genetic molecular regulation during the course of pregnancy and support the involvement of placenta gene regulation, particularly in immunological traits. This study presents a framework for understanding placenta-specific gene regulation during pregnancy and its connection to health-related traits.

The correlation between CpG methylation and gene expression is driven by sequence variants

Gene promoter and enhancer sequences are bound by transcription factors and are depleted of methylated CpG sites (cytosines preceding guanines in DNA). The absence of methylated CpGs in these sequences typically correlates with increased gene expression, indicating a regulatory role for methylation. We used nanopore sequencing to determine haplotype-specific methylation rates of 15.3 million CpG units in 7,179 whole-blood genomes. We identified 189,178 methylation depleted sequences where three or more proximal CpGs were unmethylated on at least one haplotype. A total of 77,789 methylation depleted sequences (~41%) associated with 80,503 cis-acting sequence variants, which we termed allele-specific methylation quantitative trait loci (ASM-QTLs). RNA sequencing of 896 samples from the same blood draws used to perform nanopore sequencing showed that the ASM-QTL, that is, DNA sequence variability, drives most of the correlation found between gene expression and CpG methylation. ASM-QTLs were enriched 40.2-fold (95% confidence interval 32.2, 49.9) among sequence variants associating with hematological traits, demonstrating that ASM-QTLs are important functional units in the noncoding genome.

Epigenomic insights into common human disease pathology

The epigenome-the chemical modifications and chromatin-related packaging of the genome-enables the same genetic template to be activated or repressed in different cellular settings. This multi-layered mechanism facilitates cell-type specific function by setting the local sequence and 3D interactive activity level. Gene transcription is further modulated through the interplay with transcription factors and co-regulators. The human body requires this epigenomic apparatus to be precisely installed throughout development and then adequately maintained during the lifespan. The causal role of the epigenome in human pathology, beyond imprinting disorders and specific tumour suppressor genes, was further brought into the spotlight by large-scale sequencing projects identifying that mutations in epigenomic machinery genes could be critical drivers in both cancer and developmental disorders. Abrogation of this cellular mechanism is providing new molecular insights into pathogenesis. However, deciphering the full breadth and implications of these epigenomic changes remains challenging. Knowledge is accruing regarding disease mechanisms and clinical biomarkers, through pathogenically relevant and surrogate tissue analyses, respectively. Advances include consortia generated cell-type specific reference epigenomes, high-throughput DNA methylome association studies, as well as insights into ageing-related diseases from biological 'clocks' constructed by machine learning algorithms. Also, 3rd-generation sequencing is beginning to disentangle the complexity of genetic and DNA modification haplotypes. Cell-free DNA methylation as a cancer biomarker has clear clinical utility and further potential to assess organ damage across many disorders. Finally, molecular understanding of disease aetiology brings with it the opportunity for exact therapeutic alteration of the epigenome through CRISPR-activation or inhibition.

Sex-dependent placental methylation quantitative trait loci provide insight into the prenatal origins of childhood onset traits and conditions

Molecular quantitative trait loci (QTLs) allow us to understand the biology captured in genome-wide association studies (GWASs). The placenta regulates fetal development and shows sex differences in DNA methylation. We therefore hypothesized that placental methylation QTL (mQTL) explain variation in genetic risk for childhood onset traits, and that effects differ by sex. We analyzed 411 term placentas from two studies and found 49,252 methylation (CpG) sites with mQTL and 2,489 CpG sites with sex-dependent mQTL. All mQTL were enriched in regions that typically affect gene expression in prenatal tissues. All mQTL were also enriched in GWAS results for growth- and immune-related traits, but male- and female-specific mQTL were more enriched than cross-sex mQTL. mQTL colocalized with trait loci at 777 CpG sites, with 216 (28%) specific to males or females. Overall, mQTL specific to male and female placenta capture otherwise overlooked variation in childhood traits.

Association of clinical parameters and polygenic risk scores for body mass index, schizophrenia, and diabetes with antipsychotic-induced weight gain

Antipsychotic-induced weight gain (AIWG) is a common adverse event in schizophrenia. Genome-wide association studies (GWAS) and polygenic risk scores (PRS) for other diseases or traits are recent approaches to disentangling the genetic architecture of AIWG. 200 patients with schizophrenia treated monotherapeutically with antipsychotics were included in this study. A multiple linear regression analysis with ten-fold crossvalidation was performed to predict the percentage weight change after five weeks of treatment. Independent variables were sex, age, body mass index (BMI) at baseline, medication-associated risk, and PRSs (BMI, schizophrenia, diabetes, and metabolic syndrome). An explorative GWAS analysis was performed on the same subjects and traits. PRSs for BMI (β = 3.78; p = 0.0041), schizophrenia (β = 5.38; p = 0.021) and diabetes type 2 (β = 13.4; p = 0.046) were significantly associated with AIWG. Other significant factors were sex, baseline BMI and medication. Compared to the model without genetic factors, the addition of PRSs for BMI, schizophrenia, and diabetes type 2 increased the goodness of fit by 6.5 %. The GWAS identified the association of three variants (rs10668573, rs10249381 and rs1988834) with AIWG at a genome-wide level of p < 1 · 10-6. Using PRS for schizophrenia, BMI, and diabetes type 2 increased the explained variation of predicted weight gain, compared to a model without PRSs. For more precise results, PRSs derived from other traits (ideally AIWG) should be investigated. Potential risk variants identified in our GWAS need to be further investigated and replicated in independent samples.

Genetic impacts on DNA methylation help elucidate regulatory genomic processes

BACKGROUND

Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk.

RESULTS

We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites).

CONCLUSIONS

Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk .

ZFP57 promotes ovarian cancer progression by transcriptionally regulating BRCA1 and managing G1 checkpoint

Ovarian cancer (OC) which is one of the frequently-occurring gynecologic malignant tumors, endangers the health of women. The zinc finger protein 57 (ZFP57) plays crucial functions during the progression of cancer and is reported as a prognostic and therapeutic candidate in a variety of cancer. However, the biological function as well as the underlying mechanism of ZFP57 during OC progression remains unknown. Here, ZFP57 expression was found prominently increased in OC tissues and correlated with the prognosis of OC patients. Knock down of ZFP57 in OC cells inhibited the cell proliferation and migration, and also arrested the cells at G1 phase as well as accelerated the apoptosis. Additionally, ZFP57 transcriptionally regulated BRCA1 expression in OC, indicating that ZFP57 may affect BRCA1 mediated G1 checkpoint to regulate the cell cycle of OC cells and further influence the progression of OC. Taken together, our present study discovered a novel function of ZFP57 in OC, suggesting that ZFP57 could be potentially treated as a prognostic biomarker and therapeutic target for OC patients.

meQTL mapping in the GENOA study reveals genetic determinants of DNA methylation in African Americans

Identifying genetic variants that are associated with variation in DNA methylation, an analysis commonly referred to as methylation quantitative trait locus (meQTL) mapping, is an important first step towards understanding the genetic architecture underlying epigenetic variation. Most existing meQTL mapping studies have focused on individuals of European ancestry and are underrepresented in other populations, with a particular absence of large studies in populations with African ancestry. We fill this critical knowledge gap by performing a large-scale cis-meQTL mapping study in 961 African Americans from the Genetic Epidemiology Network of Arteriopathy (GENOA) study. We identify a total of 4,565,687 cis-acting meQTLs in 320,965 meCpGs. We find that 45% of meCpGs harbor multiple independent meQTLs, suggesting potential polygenic genetic architecture underlying methylation variation. A large percentage of the cis-meQTLs also colocalize with cis-expression QTLs (eQTLs) in the same population. Importantly, the identified cis-meQTLs explain a substantial proportion (median = 24.6%) of methylation variation. In addition, the cis-meQTL associated CpG sites mediate a substantial proportion (median = 24.9%) of SNP effects underlying gene expression. Overall, our results represent an important step toward revealing the co-regulation of methylation and gene expression, facilitating the functional interpretation of epigenetic and gene regulation underlying common diseases in African Americans.

An integrative framework and recommendations for the study of DNA methylation in the context of race and ethnicity

Human social epigenomics research is critical to elucidate the intersection of social and genetic influences underlying racial and ethnic differences in health and development. However, this field faces major challenges in both methodology and interpretation with regard to disentangling confounded social and biological aspects of race and ethnicity. To address these challenges, we discuss how these constructs have been approached in the past and how to move forward in studying DNA methylation (DNAm), one of the best-characterized epigenetic marks in humans, in a responsible and appropriately nuanced manner. We highlight self-reported racial and ethnic identity as the primary measure in this field, and discuss its implications in DNAm research. Racial and ethnic identity reflects the biological embedding of an individual's sociocultural experience and environmental exposures in combination with the underlying genetic architecture of the human population (i.e., genetic ancestry). Our integrative framework demonstrates how to examine DNAm in the context of race and ethnicity, while considering both intrinsic factors-including genetic ancestry-and extrinsic factors-including structural and sociocultural environment and developmental niches-when focusing on early-life experience. We reviewed DNAm research in relation to health disparities given its relevance to race and ethnicity as social constructs. Here, we provide recommendations for the study of DNAm addressing racial and ethnic differences, such as explicitly acknowledging the self-reported nature of racial and ethnic identity, empirically examining the effects of genetic variants and accounting for genetic ancestry, and investigating race-related and culturally regulated environmental exposures and experiences.

Supplementary Information

The online version contains supplementary material available at 10.1007/s44155-023-00039-z.

Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders

Increasing evidence supports the role of placenta in neurodevelopment and potentially, in the later onset of neuropsychiatric disorders. Recently, methylation quantitative trait loci (mQTL) and interaction QTL (iQTL) maps have proven useful to understand SNP-genome wide association study (GWAS) relationships, otherwise missed by conventional expression QTLs. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation (DNAm). We constructed the first public placental cis-mQTL database including nearly eight million mQTLs calculated in 368 fetal placenta DNA samples from the INMA project, ran cell type- and gestational age-imQTL models and combined those data with the summary statistics of the largest GWAS on 10 neuropsychiatric disorders using Summary-based Mendelian Randomization (SMR) and colocalization. Finally, we evaluated the influence of the DNAm sites identified on placental gene expression in the RICHS cohort. We found that placental cis-mQTLs are highly enriched in placenta-specific active chromatin regions, and useful to map the etiology of neuropsychiatric disorders at prenatal stages. Specifically, part of the genetic burden for schizophrenia, bipolar disorder and major depressive disorder confers risk through placental DNAm. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, regional pleiotropic methylation signals associated to the same disorder, and cell type-imQTLs, additionally associated to the expression levels of relevant immune genes in placenta. In conclusion, the genetic risk of several neuropsychiatric disorders could operate, at least in part, through DNAm and associated gene expression in placenta.

Hereditable variants of classical protein tyrosine phosphatase genes: Will they prove innocent or guilty?

Protein tyrosine phosphatases, together with protein tyrosine kinases, control many molecular signaling steps that control life at cellular and organismal levels. Impairing alterations in the genes encoding the involved proteins is expected to profoundly affect the quality of life-if compatible with life at all. Here, we review the current knowledge on the effects of germline variants that have been reported for genes encoding a subset of the protein tyrosine phosphatase superfamily; that of the thirty seven classical members. The conclusion must be that the newest genome research tools produced an avalanche of data that suggest 'guilt by association' for individual genes to specific disorders. Future research should face the challenge to investigate these accusations thoroughly and convincingly, to reach a mature genotype-phenotype map for this intriguing protein family.

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.

Kidney omics in hypertension: from statistical associations to biological mechanisms and clinical applications

Hypertension is a major cardiovascular disease risk factor and contributor to premature death globally. Family-based investigations confirmed a significant heritable component of blood pressure (BP), whereas genome-wide association studies revealed >1000 common and rare genetic variants associated with BP and/or hypertension. The kidney is not only an organ of key relevance to BP regulation and the development of hypertension, but it also acts as the tissue mediator of genetic predisposition to hypertension. The identity of kidney genes, pathways, and related mechanisms underlying the genetic associations with BP has started to emerge through integration of genomics with kidney transcriptomics, epigenomics, and other omics as well as through applications of causal inference, such as Mendelian randomization. Single-cell methods further enabled mapping of BP-associated kidney genes to cell types, and in conjunction with other omics, started to illuminate the biological mechanisms underpinning associations of BP-associated genetic variants and kidney genes. Polygenic risk scores derived from genome-wide association studies and refined on kidney omics hold the promise of enhanced diagnostic prediction, whereas kidney omics-informed drug discovery is likely to contribute new therapeutic opportunities for hypertension and hypertension-mediated kidney damage.

Systematic evaluation of cell-type deconvolution pipelines for sequencing-based bulk DNA methylomes

DNA methylation analysis by sequencing is becoming increasingly popular, yielding methylomes at single-base pair and single-molecule resolution. It has tremendous potential for cell-type heterogeneity analysis using intrinsic read-level information. Although diverse deconvolution methods were developed to infer cell-type composition based on bulk sequencing-based methylomes, systematic evaluation has not been performed yet. Here, we thoroughly benchmark six previously published methods: Bayesian epiallele detection, DXM, PRISM, csmFinder+coMethy, ClubCpG and MethylPurify, together with two array-based methods, MeDeCom and Houseman, as a comparison group. Sequencing-based deconvolution methods consist of two main steps, informative region selection and cell-type composition estimation, thus each was individually assessed. With this elaborate evaluation, we aimed to establish which method achieves the highest performance in different scenarios of synthetic bulk samples. We found that cell-type deconvolution performance is influenced by different factors depending on the number of cell types within the mixture. Finally, we propose a best-practice deconvolution strategy for sequencing data and point out limitations that need to be handled. Array-based methods-both reference-based and reference-free-generally outperformed sequencing-based methods, despite the absence of read-level information. This implies that the current sequencing-based methods still struggle with correctly identifying cell-type-specific signals and eliminating confounding methylation patterns, which needs to be handled in future studies.

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.

DNA methylation changes in glial cells of the normal-appearing white matter in Multiple Sclerosis patients

Multiple Sclerosis (MS), the leading cause of non-traumatic neurological disability in young adults, is a chronic inflammatory and neurodegenerative disease of the central nervous system (CNS). Due to the poor accessibility to the target organ, CNS-confined processes underpinning the later progressive form of MS remain elusive thereby limiting treatment options. We aimed to examine DNA methylation, a stable epigenetic mark of genome activity, in glial cells to capture relevant molecular changes underlying MS neuropathology. We profiled DNA methylation in nuclei of non-neuronal cells, isolated from 38 post-mortem normal-appearing white matter (NAWM) specimens of MS patients (n = 8) in comparison to white matter of control individuals (n = 14), using Infinium MethylationEPIC BeadChip. We identified 1,226 significant (genome-wide adjusted P-value < 0.05) differentially methylated positions (DMPs) between MS patients and controls. Functional annotation of the altered DMP-genes uncovered alterations of processes related to cellular motility, cytoskeleton dynamics, metabolic processes, synaptic support, neuroinflammation and signaling, such as Wnt and TGF-β pathways. A fraction of the affected genes displayed transcriptional differences in the brain of MS patients, as reported by publically available transcriptomic data. Cell type-restricted annotation of DMP-genes attributed alterations of cytoskeleton rearrangement and extracellular matrix remodelling to all glial cell types, while some processes, including ion transport, Wnt/TGF-β signaling and immune processes were more specifically linked to oligodendrocytes, astrocytes and microglial cells, respectively. Our findings strongly suggest that NAWM glial cells are highly altered, even in the absence of lesional insult, collectively exhibiting a multicellular reaction in response to diffuse inflammation.

Methylation quantitative trait locus rs5326 is associated with susceptibility and effective dosage of methadone maintenance treatment for heroin use disorder

RATIONALE

Opioid use disorder is a complicated brain disease with high heritability. The underlying mechanisms of the genetic underpinnings in the susceptibility and treatment response of opioid use disorder remain elusive.

OBJECTIVES

To reveal the potential associations of genotypes and gene methylations of dopaminergic system genes, as well as roles of them in opioid use disorder. In the present study, we detected the DNA methylation in the promoter regions of five representative dopaminergic system genes (DRD1, DRD2, SLC6A3, TH, and COMT) between 120 patients with heroin use disorder in methadone maintenance treatment (MMT) program and 111 healthy controls. The associations of 25 SNPs in the above genes and methylation of 237 CpG sites, known as methylation quantitative trait loci (mQTLs), were determined. Then, the correlations of the above mQTLs and traits of heroin use disorder were analyzed in a sample set of 801 patients with heroin use disorder and 930 healthy controls.

RESULTS

Our results demonstrated that several mQTLs in the DRD1 and DRD2 genes were identified both in the heroin use disorder and healthy control groups. Interestingly, rs4867798-CpG_174872884 and rs5326-CpG_174872884 in the DRD1 gene were the unique SNP-CpG pairs in the patients with heroin use disorder. Furthermore, mQTL rs5326 was associated with the susceptibility and effective dosage of MMT for heroin use disorder, and demonstrated allele-specific correlation with the expression of the DRD1 gene in the human caudate.

CONCLUSIONS

Our findings suggest that some mQTLs may be associated with traits of opioid use disorder by implicating the DNA methylation and gene expression.

Allele-specific DNA methylation maps in monozygotic twins discordant for psychiatric disorders reveal that disease-associated switching at the EIPR1 regulatory loci modulates neural function

The non-Mendelian features of phenotypic variations within monozygotic twins are likely complicated by environmental modifiers of genetic effects that have yet to be elucidated. Here, we performed methylome and genome analyses of blood DNA from psychiatric disorder-discordant monozygotic twins to study how allele-specific methylation (ASM) mediates phenotypic variations. We identified that thousands of genetic variants with ASM imbalances exhibit phenotypic variation-associated switching at regulatory loci. These ASMs have plausible causal associations with psychiatric disorders through effects on interactions between transcription factors, DNA methylations, and other epigenomic markers and then contribute to dysregulated gene expression, which eventually increases disease susceptibility. Moreover, we also experimentally validated the model that the rs4854158 alternative C allele at an ASM switching regulatory locus of EIPR1 encoding endosome-associated recycling protein-interacting protein 1, is associated with demethylation and higher RNA expression and shows lower TF binding affinities in unaffected controls. An epigenetic ASM switching induces C allele hypermethylation and then recruits repressive Polycomb repressive complex 2 (PRC2), reinforces trimethylation of lysine 27 on histone 3 and inhibits its transcriptional activity, thus leading to downregulation of EIPR1 in schizophrenia. Moreover, disruption of rs4854158 induces gain of EIPR1 function and promotes neural development and vesicle trafficking. Our study provides a powerful framework for identifying regulatory risk variants and contributes to our understanding of the interplay between genetic and epigenetic variants in mediating psychiatric disorder susceptibility.

Genetic and in utero environmental contributions to DNA methylation variation in placenta

Genetic and prenatal environmental factors shape fetal development and cardiometabolic health in later life. A key target of genetic and prenatal environmental factors is the epigenome of the placenta, an organ that is implicated in fetal growth and diseases in later life. This study had two aims: (1) to identify and functionally characterize placental variably methylated regions (VMRs), which are regions in the epigenome with high inter-individual methylation variability; and (2) to investigate the contributions of fetal genetic loci and 12 prenatal environmental factors (maternal cardiometabolic-,psychosocial-, demographic- and obstetric-related) on methylation at each VMR. Akaike's information criterion was used to select the best model out of four models [prenatal environment only, genotype only, additive effect of genotype and prenatal environment (G + E), and their interaction effect (G × E)]. We identified 5850 VMRs in placenta. Methylation at 70% of VMRs was best explained by G × E, followed by genotype only (17.7%), and G + E (12.3%). Prenatal environment alone best explained only 0.03% of VMRs. We observed that 95.4% of G × E models and 93.9% of G + E models included maternal age, parity, delivery mode, maternal depression or gestational weight gain. VMR methylation sites and their regulatory genetic variants were enriched (P < 0.05) for genomic regions that have known links with regulatory functions and complex traits. This study provided a genome-wide catalog of VMRs in placenta and highlighted that variation in placental DNA methylation at loci with regulatory and trait relevance is best elucidated by integrating genetic and prenatal environmental factors, and rarely by environmental factors alone.

Differential methylation of genes in the human placenta associated with bisphenol A exposure

Prenatal exposure to bisphenol A (BPA) is associated with numerous adverse health outcomes among offspring. Although DNA methylation is considered one of the underlying causes of these associations, few studies have focused on the association between prenatal BPA exposure and DNA methylation in the human placenta. In this study, we examined the association between prenatal BPA exposure and DNA methylation in the placenta of 146 mother-infant pairs from the Shanghai-Minhang Birth Cohort Study. BPA concentrations in maternal urine samples were measured using high-performance liquid chromatography. Six placenta samples were selected for whole-genome methylation analysis using Infinium Human Methylation 450K Beadchip, followed by pyrosequencing-based methylation analysis of three selected genes in 146 placentas. Among 282 differentially methylated CpGs, representing 208 genes, 127 were hypermethylated, and 155 were hypomethylated in the BPA exposure group. Prenatal BPA exposure was associated with a higher methylation level of HLA-DRB6 in individuals as determined using pyrosequencing, which was consistent with the whole-genome methylation analysis results. Compared with that subjects with low BPA exposure, the methylation level (ln-transformed) of HLA-DRB6 in placentas from those with high BPA exposure increased by 0.29% (95% confidence interval[CI]: 0.02%, 0.56%) at the CpG2 site, and the average methylation level (ln-transformed) of the three CpG sites increased by 0.30% (95%CI: -0.03%, 0.63%). Our findings provide evidence that prenatal BPA exposure might alter DNA methylation levels in the placenta.

Placental DNA methylation signatures of maternal smoking during pregnancy and potential impacts on fetal growth

Maternal smoking during pregnancy (MSDP) contributes to poor birth outcomes, in part through disrupted placental functions, which may be reflected in the placental epigenome. Here we present a meta-analysis of the associations between MSDP and placental DNA methylation (DNAm) and between DNAm and birth outcomes within the Pregnancy And Childhood Epigenetics (PACE) consortium (N = 1700, 344 with MSDP). We identify 443 CpGs that are associated with MSDP, of which 142 associated with birth outcomes, 40 associated with gene expression, and 13 CpGs are associated with all three. Only two CpGs have consistent associations from a prior meta-analysis of cord blood DNAm, demonstrating substantial tissue-specific responses to MSDP. The placental MSDP-associated CpGs are enriched for environmental response genes, growth-factor signaling, and inflammation, which play important roles in placental function. We demonstrate links between placental DNAm, MSDP and poor birth outcomes, which may better inform the mechanisms through which MSDP impacts placental function and fetal growth.

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.

p53-intact cancers escape tumor suppression through loss of long noncoding RNA Dino

Many long noncoding RNA (lncRNA) genes exist near cancer-associated loci, yet evidence connecting lncRNA functions to recurrent genetic alterations in cancer are lacking. Here, we report that DINO, the lncRNA transcribed from the cancer-associated DINO/CDKN1A locus, suppresses tumor formation independent of p21, the protein encoded at the locus. Loss of one or two alleles of Dino impairs p53 signaling and apoptosis, resulting in a haplo-insufficient tumor suppressor phenotype in genetically defined mouse models of tumorigenesis. A discrete region of the DINO/CDKN1A locus is recurrently hypermethylated in human cancers, silencing DINO but not CDKN1A, the gene encoding p21. Hypermethylation silences DINO, impairs p53 signaling pathway in trans, and is mutually exclusive with TP53 alterations, indicating that DINO and TP53 comprise a common tumor suppressor module. Therefore, DINO encodes a lncRNA essential for tumor suppression that is recurrently silenced in human cancers as a mechanism to escape p53-dependent tumor suppression.

Mapping methylation quantitative trait loci in cardiac tissues nominates risk loci and biological pathways in congenital heart disease

Background

Most congenital heart defects (CHDs) result from complex interactions among genetic susceptibilities, epigenetic modifications, and maternal environmental exposures. Characterizing the complex relationship between genetic, epigenetic, and transcriptomic variation will enhance our understanding of pathogenesis in this important type of congenital disorder. We investigated cis-acting effects of genetic single nucleotide polymorphisms (SNPs) on local DNA methylation patterns within 83 cardiac tissue samples and prioritized their contributions to CHD risk by leveraging results of CHD genome-wide association studies (GWAS) and their effects on cardiac gene expression.

Results

We identified 13,901 potential methylation quantitative trait loci (mQTLs) with a false discovery threshold of 5%. Further co-localization analyses and Mendelian randomization indicated that genetic variants near the HLA-DRB6 gene on chromosome 6 may contribute to CHD risk by regulating the methylation status of nearby CpG sites. Additional SNPs in genomic regions on chromosome 10 (TNKS2-AS1 gene) and chromosome 14 (LINC01629 gene) may simultaneously influence epigenetic and transcriptomic variations within cardiac tissues.

Conclusions

Our results support the hypothesis that genetic variants may influence the risk of CHDs through regulating the changes of DNA methylation and gene expression. Our results can serve as an important source of information that can be integrated with other genetic studies of heart diseases, especially CHDs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12863-021-00975-2.

Uncovering genetic mechanisms of hypertension through multi-omic analysis of the kidney

The kidney is an organ of key relevance to blood pressure (BP) regulation, hypertension and antihypertensive treatment. However, genetically mediated renal mechanisms underlying susceptibility to hypertension remain poorly understood. We integrated genotype, gene expression, alternative splicing and DNA methylation profiles of up to 430 human kidneys to characterize the effects of BP index variants from genome-wide association studies (GWASs) on renal transcriptome and epigenome. We uncovered kidney targets for 479 (58.3%) BP-GWAS variants and paired 49 BP-GWAS kidney genes with 210 licensed drugs. Our colocalization and Mendelian randomization analyses identified 179 unique kidney genes with evidence of putatively causal effects on BP. Through Mendelian randomization, we also uncovered effects of BP on renal outcomes commonly affecting patients with hypertension. Collectively, our studies identified genetic variants, kidney genes, molecular mechanisms and biological pathways of key relevance to the genetic regulation of BP and inherited susceptibility to hypertension.

Socioeconomic Deprivation Index Is Associated With Psychiatric Disorders: An Observational and Genome-wide Gene-by-Environment Interaction Analysis in the UK Biobank Cohort

BACKGROUND

Psychiatric disorders are among the largest and fastest-growing categories of the global disease burden. However, limited effort has been made to further elucidate associations between socioeconomic factors and psychiatric disorders from a genetic perspective.

METHODS

We randomly divided 501,882 participants in the UK Biobank cohort with socioeconomic Townsend deprivation index (TDI) data into a discovery cohort and a replication cohort. For both cohorts, we first conducted regression analyses to evaluate the associations between the TDI and common psychiatric disorders or traits, including anxiety, bipolar disorder, self-harm, and depression (based on self-reported depression and Patient Health Questionnaire scores). We then performed a genome-wide gene-by-environment interaction study using PLINK 2.0 with the TDI as an environmental factor to explore interaction effects.

RESULTS

In the discovery cohort, significant associations were observed between the TDI and psychiatric disorders (p < 4.00 × 10^-16), including anxiety (odds ratio [OR] = 1.08, 95% confidence interval [CI] = 1.07-1.10), bipolar disorder (OR = 1.42, 95% CI = 1.36-1.48), self-harm (OR = 1.21, 95% CI = 1.19-1.23), self-reported depression (OR = 1.22, 95% CI = 1.20-1.24), and Patient Health Questionnaire scores (β = .07, SE = 0.004). We observed similar significant associations in the replication cohort. In addition, multiple candidate loci were identified by the genome-wide gene-by-environment interaction study, including rs10886438 at 10q26.11 (GRK5) (p = 5.72 × 10^-11) for Patient Health Questionnaire scores and rs162553 at 2p22.2 (CYP1B1) (p = 2.25 × 10^-9) for self-harm.

CONCLUSIONS

Our findings suggest the relevance of the TDI to psychiatric disorders. The genome-wide gene-by-environment interaction study identified several candidate genes interacting with the TDI, providing novel clues for understanding the biological mechanism of associations between the TDI and psychiatric 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.

Crosstalk between microRNA expression and DNA methylation drives the hormone-dependent phenotype of breast cancer

BACKGROUND

Abnormal DNA methylation is observed as an early event in breast carcinogenesis. However, how such alterations arise is still poorly understood. microRNAs (miRNAs) regulate gene expression at the post-transcriptional level and play key roles in various biological processes. Here, we integrate miRNA expression and DNA methylation at CpGs to study how miRNAs may affect the breast cancer methylome and how DNA methylation may regulate miRNA expression.

METHODS

miRNA expression and DNA methylation data from two breast cancer cohorts, Oslo2 (n = 297) and The Cancer Genome Atlas (n = 439), were integrated through a correlation approach that we term miRNA-methylation Quantitative Trait Loci (mimQTL) analysis. Hierarchical clustering was used to identify clusters of miRNAs and CpGs that were further characterized through analysis of mRNA/protein expression, clinicopathological features, in silico deconvolution, chromatin state and accessibility, transcription factor binding, and long-range interaction data.

RESULTS

Clustering of the significant mimQTLs identified distinct groups of miRNAs and CpGs that reflect important biological processes associated with breast cancer pathogenesis. Notably, two major miRNA clusters were related to immune or fibroblast infiltration, hence identifying miRNAs associated with cells of the tumor microenvironment, while another large cluster was related to estrogen receptor (ER) signaling. Studying the chromatin landscape surrounding CpGs associated with the estrogen signaling cluster, we found that miRNAs from this cluster are likely to be regulated through DNA methylation of enhancers bound by FOXA1, GATA2, and ER-alpha. Further, at the hub of the estrogen cluster, we identified hsa-miR-29c-5p as negatively correlated with the mRNA and protein expression of DNA methyltransferase DNMT3A, a key enzyme regulating DNA methylation. We found deregulation of hsa-miR-29c-5p already present in pre-invasive breast lesions and postulate that hsa-miR-29c-5p may trigger early event abnormal DNA methylation in ER-positive breast cancer.

CONCLUSIONS

We describe how miRNA expression and DNA methylation interact and associate with distinct breast cancer phenotypes.

Human brain region-specific variably methylated regions are enriched for heritability of distinct neuropsychiatric traits

BACKGROUND

DNA methylation dynamics in the brain are associated with normal development and neuropsychiatric disease and differ across functionally distinct brain regions. Previous studies of genome-wide methylation differences among human brain regions focus on limited numbers of individuals and one to two brain regions.

RESULTS

Using GTEx samples, we generate a resource of DNA methylation in purified neuronal nuclei from 8 brain regions as well as lung and thyroid tissues from 12 to 23 donors. We identify differentially methylated regions between brain regions among neuronal nuclei in both CpG (181,146) and non-CpG (264,868) contexts, few of which were unique to a single pairwise comparison. This significantly expands the knowledge of differential methylation across the brain by 10-fold. In addition, we present the first differential methylation analysis among neuronal nuclei from basal ganglia tissues and identify unique CpG differentially methylated regions, many associated with ion transport. We also identify 81,130 regions of variably CpG methylated regions, i.e., variable methylation among individuals in the same brain region, which are enriched in regulatory regions and in CpG differentially methylated regions. Many variably methylated regions are unique to a specific brain region, with only 202 common across all brain regions, as well as lung and thyroid. Variably methylated regions identified in the amygdala, anterior cingulate cortex, and hippocampus are enriched for heritability of schizophrenia.

CONCLUSIONS

These data suggest that epigenetic variation in these particular human brain regions could be associated with the risk for this neuropsychiatric disorder.

Exploring allele specific methylation in drug dependence susceptibility

Drug dependence is a neuropsychiatric condition that involves genetic, epigenetic and environmental factors. Allele-specific methylation (ASM) is a common and stable epigenetic mechanism that involves genetic variants correlating with differential levels of methylation at CpG sites. We selected 182 single-nucleotide polymorphisms (SNPs) described to influence cis ASM in human brain regions to evaluate their possible contribution to drug dependence susceptibility. We performed a case-control association study in a discovery sample of 578 drug-dependent patients (including 428 cocaine-dependent subjects) and 656 controls from Spain, and then, we followed-up the significant associations in an independent sample of 1119 cases (including 589 cocaine-dependent subjects) and 1092 controls. In the discovery sample, we identified five nominal associations, one of them replicated in the follow-up sample (rs6020251). The pooled analysis revealed an association between drug dependence and rs6020251 but also rs11585570, both overcoming the Bonferroni correction for multiple testing. We performed the same analysis considering only cocaine-dependent patients and obtained similar results. The rs6020251 variant correlates with differential methylation levels of cg17974185 and lies in the first intron of the CTNNBL1 gene, in a genomic region with multiple histone marks related to enhancer and promoter regions in brain. Rs11585570 is an eQTL in brain and blood for the SCP2 and ECHDC2 genes and correlates with differential methylation of cg27535305 and cg13461509, located in the promoter regions of both genes. To conclude, using an approach that combines genetic and epigenetic data, we highlighted the CTNNBL1, SCP2 and ECHDC2 genes as potential contributors to drug dependence susceptibility.

Adipose Tissue Epigenetic Profile in Obesity-Related Dysglycemia - A Systematic Review

BACKGROUND

Obesity is a major risk factor for dysglycemic disorders, including type 2 diabetes (T2D). However, there is wide phenotypic variation in metabolic profiles. Tissue-specific epigenetic modifications could be partially accountable for the observed phenotypic variability.

SCOPE

The aim of this systematic review was to summarize the available data on epigenetic signatures in human adipose tissue (AT) that characterize overweight or obesity-related insulin resistance (IR) and dysglycemia states and to identify potential underlying mechanisms through the use of unbiased bioinformatics approaches.

METHODS

Original data published in the last decade concerning the comparison of epigenetic marks in human AT of individuals with metabolically unhealthy overweight/obesity (MUHO) versus normal weight individuals or individuals with metabolically healthy overweight/obesity (MHO) was assessed. Furthermore, association of these epigenetic marks with IR/dysglycemic traits, including T2D, was compiled.

RESULTS

We catalogued more than two thousand differentially methylated regions (DMRs; above the cut-off of 5%) in the AT of individuals with MUHO compared to individuals with MHO. These DNA methylation changes were less likely to occur around the promoter regions and were enriched at loci implicated in intracellular signaling (signal transduction mediated by small GTPases, ERK1/2 signaling and intracellular trafficking). We also identified a network of seven transcription factors that may play an important role in targeting DNA methylation changes to specific genes in the AT of subjects with MUHO, contributing to the pathogeny of obesity-related IR/T2D. Furthermore, we found differentially methylated CpG sites at 8 genes that were present in AT and whole blood, suggesting that DMRs in whole blood could be potentially used as accessible biomarkers of MUHO.

CONCLUSIONS

The overall evidence linking epigenetic alterations in key tissues such AT to metabolic complications in human obesity is still very limited, highlighting the need for further studies, particularly those focusing on epigenetic marks other than DNA methylation. Our initial analysis suggests that DNA methylation patterns can potentially discriminate between MUHO from MHO and provide new clues into why some people with obesity are less susceptible to dysglycemia. Identifying AT-specific epigenetic targets could also lead to novel approaches to modify the progression of individuals with obesity towards metabolic disease.

SYSTEMATIC REVIEW REGISTRATION

PROSPERO, identifier CRD42021227237.

The role of ZFP57 and additional KRAB-zinc finger proteins in the maintenance of human imprinted methylation and multi-locus imprinting disturbances

Genomic imprinting is an epigenetic process regulated by germline-derived DNA methylation that is resistant to embryonic reprogramming, resulting in parental origin-specific monoallelic gene expression. A subset of individuals affected by imprinting disorders (IDs) displays multi-locus imprinting disturbances (MLID), which may result from aberrant establishment of imprinted differentially methylated regions (DMRs) in gametes or their maintenance in early embryogenesis. Here we investigated the extent of MLID in a family harbouring a ZFP57 truncating variant and characterize the interactions between human ZFP57 and the KAP1 co-repressor complex. By ectopically targeting ZFP57 to reprogrammed loci in mouse embryos using a dCas9 approach, we confirm that ZFP57 recruitment is sufficient to protect oocyte-derived methylation from reprogramming. Expression profiling in human pre-implantation embryos and oocytes reveals that unlike in mice, ZFP57 is only expressed following embryonic-genome activation, implying that other KRAB-zinc finger proteins (KZNFs) recruit KAP1 prior to blastocyst formation. Furthermore, we uncover ZNF202 and ZNF445 as additional KZNFs likely to recruit KAP1 to imprinted loci during reprogramming in the absence of ZFP57. Together, these data confirm the perplexing link between KZFPs and imprint maintenance and highlight the differences between mouse and humans in this respect.

Deconvolution of cellular subsets in human tissue based on targeted DNA methylation analysis at individual CpG sites

Background

The complex composition of different cell types within a tissue can be estimated by deconvolution of bulk gene expression profiles or with various single-cell sequencing approaches. Alternatively, DNA methylation (DNAm) profiles have been used to establish an atlas for multiple human tissues and cell types. DNAm is particularly suitable for deconvolution of cell types because each CG dinucleotide (CpG site) has only two states per DNA strand—methylated or non-methylated—and these epigenetic modifications are very consistent during cellular differentiation. So far, deconvolution of DNAm profiles implies complex signatures of many CpGs that are often measured by genome-wide analysis with Illumina BeadChip microarrays. In this study, we investigated if the characterization of cell types in tissue is also feasible with individual cell type-specific CpG sites, which can be addressed by targeted analysis, such as pyrosequencing.

Results

We compiled and curated 579 Illumina 450k BeadChip DNAm profiles of 14 different non-malignant human cell types. A training and validation strategy was applied to identify and test for cell type-specific CpGs. We initially focused on estimating the relative amount of fibroblasts using two CpGs that were either hypermethylated or hypomethylated in fibroblasts. The combination of these two DNAm levels into a “FibroScore” correlated with the state of fibrosis and was associated with overall survival in various types of cancer. Furthermore, we identified hypomethylated CpGs for leukocytes, endothelial cells, epithelial cells, hepatocytes, glia, neurons, fibroblasts, and induced pluripotent stem cells. The accuracy of this eight CpG signature was tested in additional BeadChip datasets of defined cell mixtures and the results were comparable to previously published signatures based on several thousand CpGs. Finally, we established and validated pyrosequencing assays for the relevant CpGs that can be utilized for classification and deconvolution of cell types.

Conclusion

This proof of concept study demonstrates that DNAm analysis at individual CpGs reflects the cellular composition of cellular mixtures and different tissues. Targeted analysis of these genomic regions facilitates robust methods for application in basic research and clinical settings.

Epigenetics of Muscle- and Brain-Specific Expression of KLHL Family Genes

KLHL and the related KBTBD genes encode components of the Cullin-E3 ubiquitin ligase complex and typically target tissue-specific proteins for degradation, thereby affecting differentiation, homeostasis, metabolism, cell signaling, and the oxidative stress response. Despite their importance in cell function and disease (especially, KLHL40, KLHL41, KBTBD13, KEAP1, and ENC1), previous studies of epigenetic factors that affect transcription were predominantly limited to promoter DNA methylation. Using diverse tissue and cell culture whole-genome profiles, we examined 17 KLHL or KBTBD genes preferentially expressed in skeletal muscle or brain to identify tissue-specific enhancer and promoter chromatin, open chromatin (DNaseI hypersensitivity), and DNA hypomethylation. Sixteen of the 17 genes displayed muscle- or brain-specific enhancer chromatin in their gene bodies, and most exhibited specific intergenic enhancer chromatin as well. Seven genes were embedded in super-enhancers (particularly strong, tissue-specific clusters of enhancers). The enhancer chromatin regions typically displayed foci of DNA hypomethylation at peaks of open chromatin. In addition, we found evidence for an intragenic enhancer in one gene upregulating expression of its neighboring gene, specifically for KLHL40/HHATL and KLHL38/FBXO32 gene pairs. Many KLHL/KBTBD genes had tissue-specific promoter chromatin at their 5' ends, but surprisingly, two (KBTBD11 and KLHL31) had constitutively unmethylated promoter chromatin in their 3' exons that overlaps a retrotransposed KLHL gene. Our findings demonstrate the importance of expanding epigenetic analyses beyond the 5' ends of genes in studies of normal and abnormal gene regulation.

Rare genetic variation at transcription factor binding sites modulates local DNA methylation profiles

Although DNA methylation is the best characterized epigenetic mark, the mechanism by which it is targeted to specific regions in the genome remains unclear. Recent studies have revealed that local DNA methylation profiles might be dictated by cis-regulatory DNA sequences that mainly operate via DNA-binding factors. Consistent with this finding, we have recently shown that disruption of CTCF-binding sites by rare single nucleotide variants (SNVs) can underlie cis-linked DNA methylation changes in patients with congenital anomalies. These data raise the hypothesis that rare genetic variation at transcription factor binding sites (TFBSs) might contribute to local DNA methylation patterning. In this work, by combining blood genome-wide DNA methylation profiles, whole genome sequencing-derived SNVs from 247 unrelated individuals along with 133 predicted TFBS motifs derived from ENCODE ChIP-Seq data, we observed an association between the disruption of binding sites for multiple TFs by rare SNVs and extreme DNA methylation values at both local and, to a lesser extent, distant CpGs. While the majority of these changes affected only single CpGs, 24% were associated with multiple outlier CpGs within ±1kb of the disrupted TFBS. Interestingly, disruption of functionally constrained sites within TF motifs lead to larger DNA methylation changes at nearby CpG sites. Altogether, these findings suggest that rare SNVs at TFBS negatively influence TF-DNA binding, which can lead to an altered local DNA methylation profile. Furthermore, subsequent integration of DNA methylation and RNA-Seq profiles from cardiac tissues enabled us to observe an association between rare SNV-directed DNA methylation and outlier expression of nearby genes. In conclusion, our findings not only provide insights into the effect of rare genetic variation at TFBS on shaping local DNA methylation and its consequences on genome regulation, but also provide a rationale to incorporate DNA methylation data to interpret the functional role of rare variants.

Detection of haplotype-dependent allele-specific DNA methylation in WGBS data

In heterozygous genomes, allele-specific measurements can reveal biologically significant differences in DNA methylation between homologous alleles associated with local changes in genetic sequence. Current approaches for detecting such events from whole-genome bisulfite sequencing (WGBS) data perform statistically independent marginal analysis at individual cytosine-phosphate-guanine (CpG) sites, thus ignoring correlations in the methylation state, or carry-out a joint statistical analysis of methylation patterns at four CpG sites producing unreliable statistical evidence. Here, we employ the one-dimensional Ising model of statistical physics and develop a method for detecting allele-specific methylation (ASM) events within segments of DNA containing clusters of linked single-nucleotide polymorphisms (SNPs), called haplotypes. Comparisons with existing approaches using simulated and real WGBS data show that our method provides an improved fit to data, especially when considering large haplotypes. Importantly, the method employs robust hypothesis testing for detecting statistically significant imbalances in mean methylation level and methylation entropy, as well as for identifying haplotypes for which the genetic variant carries significant information about the methylation state. As such, our ASM analysis approach can potentially lead to biological discoveries with important implications for the genetics of complex human diseases.

MethHaplo: combining allele-specific DNA methylation and SNPs for haplotype region identification

Background

DNA methylation is an important epigenetic modification that plays a critical role in most eukaryotic organisms. Parental alleles in haploid genomes may exhibit different methylation patterns, which can lead to different phenotypes and even different therapeutic and drug responses to diseases. However, to our knowledge, no software is available for the identification of DNA methylation haplotype regions with combined allele-specific DNA methylation, single nucleotide polymorphisms (SNPs) and high-throughput chromosome conformation capture (Hi-C) data.

Results

In this paper, we developed a new method, MethHaplo, that identify DNA methylation haplotype regions with allele-specific DNA methylation and SNPs from whole-genome bisulfite sequencing (WGBS) data. Our results showed that methylation haplotype regions were ten times longer than haplotypes with SNPs only. When we integrate WGBS and Hi-C data, MethHaplo could call even longer haplotypes.

Conclusions

This study illustrates the usefulness of methylation haplotypes. By constructing methylation haplotypes for various cell lines, we provide a clearer picture of the effect of DNA methylation on gene expression, histone modification and three-dimensional chromosome structure at the haplotype level. Our method could benefit the study of parental inheritance-related disease and hybrid vigor in agriculture.

The fusiform gyrus exhibits an epigenetic signature for Alzheimer's disease

Background

Alzheimer’s disease (AD) is the most common type of dementia, and patients with advanced AD frequently lose the ability to identify family members. The fusiform gyrus (FUS) of the brain is critical in facial recognition. However, AD etiology in the FUS of AD patients is poorly understood. New analytical strategies are needed to reveal the genetic and epigenetic basis of AD in FUS.

Results

A complex of new analytical paradigms that integrates an array of transcriptomes and methylomes of normal controls, AD patients, and “AD-in-dish” models were used to identify genetic and epigenetic signatures of AD in FUS. Here we identified changes in gene expression that are specific to the FUS in brains of AD patients. These changes are closely linked to key genes in the AD network. Profiling of the methylome (5mC/5hmC/5fC/5caC) at base resolution identified 5 signature genes (COL2A1, CAPN3, COL14A1, STAT5A, SPOCK3) that exhibit perturbed expression, specifically in the FUS and display altered DNA methylome profiles that are common across AD-associated brain regions. Moreover, we demonstrate proof-of-principle that AD-associated methylome changes in these genes effectively predict the disease prognosis with enhanced sensitivity compared to presently used clinical criteria.

Conclusions

This study identified a set of previously unexplored FUS-specific AD genes and their epigenetic characteristics, which may provide new insights into the molecular pathology of AD, attributing the genetic and epigenetic basis of FUS to AD development.

CGGBP1-regulated cytosine methylation at CTCF-binding motifs resists stochasticity

Background

The human CGGBP1 binds to GC-rich regions and interspersed repeats, maintains homeostasis of stochastic cytosine methylation and determines DNA-binding of CTCF. Interdependence between regulation of cytosine methylation and CTCF occupancy by CGGBP1 remains unknown.

Results

By analyzing methylated DNA-sequencing data obtained from CGGBP1-depleted cells, we report that some transcription factor-binding sites, including CTCF, resist stochastic changes in cytosine methylation. By analysing CTCF-binding sites we show that cytosine methylation changes at CTCF motifs caused by CGGBP1 depletion resist stochastic changes. These CTCF-binding sites are positioned at locations where the spread of cytosine methylation in cis depends on the levels of CGGBP1.

Conclusion

Our findings suggest that CTCF occupancy and functions are determined by CGGBP1-regulated cytosine methylation patterns.

Concentrations of persistent organic pollutants in maternal plasma and epigenome-wide placental DNA methylation

Background

Prenatal maternal plasma persistent organic pollutant (POP) concentrations have been associated with neonatal outcomes. However, the underlying mechanisms remain unknown. Placental epigenetic mechanisms may be involved, but no prior epigenome-wide studies have investigated the impact of maternal POPs on placental DNA methylation. We studied the association between maternal plasma POP concentration in early pregnancy and epigenome-wide placental DNA methylation among 260 pregnant women from the NICHD Fetal Growth Studies.

Results

Our analysis focused on POPs with more than 80% plasma concentrations above the limit of quantification, including 3 organochlorine pesticides (hexachlorobenzene, trans-nonachlor, p,p’-dichlorodiphenyldichloroethylene), 1 polybrominated diphenyl ether (PBDE 47), 3 polychlorinated biphenyls (138/158, 153, 180), and 6 poly- and perfluorinated alkyl substances (PFASs) (perfluorodecanoic acid, perfluorohexanesulfonic acid, perfluorononanoic acid, perfluorooctanesulfonic acid, perfluoroundecanoic acid (PFUnDA)). Using 5% false discovery rate, POPs were associated with a total of 214 differentially methylated CpG sites (nominal p values ranging from 2.61 × 10⁻²¹ to 2.11 × 10⁻⁷). Out of the 214 CpG sites, 24 (11%) were significantly correlated with placental expression of 21 genes. Notably, higher PFUnDA was associated with increased methylation at 3 CpG sites (cg13996963, cg12089439, cg18145877) annotated to TUSC3, and increased methylation at those 3 CpG sites was correlated with decreased expression of TUSC3 in the placenta. Increased methylation at cg18145877 (TUSC3) and decreased expression of TUSC3 were correlated with shorter birth length. Out of the 214 CpG sites, methylation at 44 CpG sites was correlated (p value < 0.10) with at least one neonatal anthropometry measure (i.e., birth weight, birth length, and head circumference). Seven CpG sites mediated (p value < 0.05) the association between PBDE 47 and neonatal anthropometry measures. Genes annotating the top differentially methylated CpG sites were enriched in pathways related to differentiation of embryonic cells (PBDE 47) and in pathways related to brain size and brain morphology (PFASs).

Conclusions

DNA methylation changes in the placenta were significantly associated with maternal plasma POPs concentration. The findings suggest that placental DNA methylation and gene expression mechanism may be involved in the prenatal toxicity of POPs and their association with neonatal anthropometry measures.

Epigenetic Vulnerability of Insulator CTCF Motifs at Parkinson's Disease-Associated Genes in Response to Neurotoxicant Rotenone

CCCTC-binding factor (CTCF) is a regulatory protein that binds DNA to control spatial organization and transcription. The sequence-specific binding of CTCF is variable and is impacted by nearby epigenetic patterns. It has been demonstrated that non-coding genetic variants cluster with CTCF sites in topological associating domains and thus can affect CTCF activity on gene expression. Therefore, environmental factors that alter epigenetic patterns at CTCF binding sites may dictate the interaction of non-coding genetic variants with regulatory proteins. To test this mechanism, we treated human cell line HEK293 with rotenone for 24 h and characterized its effect on global epigenetic patterns specifically at regulatory regions of Parkinson's disease (PD) risk loci. We used RNA sequencing to examine changes in global transcription and identified over 2000 differentially expressed genes (DEGs, >1.5-fold change, FDR < 0.05). Among these DEGs, 13 were identified as PD-associated genes according to Genome-wide association studies meta-data. We focused on eight genes that have non-coding risk variants and a prominent CTCF binding site. We analyzed methylation of a total of 165 CGs surrounding CTCF binding sites and detected differential methylation (|>1%|, q < 0.05) in 45 CGs at 7 PD-associated genes. Of these 45 CGs, 47% were hypomethylated and 53% were hypermethylated. Interestingly, 5 out of the 7 genes had correlated gene upregulation with CG hypermethylation at CTCF and gene downregulation with CG hypomethylation at CTCF. We also investigated active H3K27ac surrounding the same CTCF binding sites within these seven genes. We observed a significant increase in H3K27ac in four genes (FDR < 0.05). Three genes (PARK2, GPRIN3, FER) showed increased CTCF binding in response to rotenone. Our data indicate that rotenone alters regulatory regions of PD-associated genes through changes in epigenetic patterns, and these changes impact high-order chromatin organization to increase the influence of non-coding variants on genome integrity and cellular survival.

Epigenetics in Lewy Body Diseases: Impact on Gene Expression, Utility as a Biomarker, and Possibilities for Therapy

Lewy body disorders (LBD) include Parkinson's disease (PD) and dementia with Lewy bodies (DLB). They are synucleinopathies with a heterogeneous clinical manifestation. As a cause of neuropathological overlap with other neurodegenerative diseases, the establishment of a correct clinical diagnosis is still challenging, and clinical management may be difficult. The combination of genetic variation and epigenetic changes comprising gene expression-modulating DNA methylation and histone alterations modifies the phenotype, disease course, and susceptibility to disease. In this review, we summarize the results achieved in the deciphering of the LBD epigenome. To provide an appropriate context, first LBD genetics is briefly outlined. Afterwards, a detailed review of epigenetic modifications identified for LBD in human cells, postmortem, and peripheral tissues is provided. We also focus on the difficulty of identifying epigenome-related biomarker candidates and discuss the results obtained so far. Additionally, epigenetic changes as therapeutic targets, as well as different epigenome-based treatments, are revised. The number of studies focusing on PD is relatively limited and practically inexistent for DLB. There is a lack of replication studies, and some results are even contradictory, probably due to differences in sample collection and analytical techniques. In summary, we show the current achievements and directions for future research.