Genetic impacts on DNA methylation: research findings and future perspectives

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.

The Epigenetics of Animal Personality

Animal personality, consistent individual differences in behaviour, is an important concept for understanding how individuals vary in how they cope with environmental challenges. In order to understand the evolutionary significance of animal personality, it is crucial to understand the underlying regulatory mechanisms. Epigenetic marks such as DNA methylation are hypothesised to play a major role in explaining variation in phenotypic changes in response to environmental alterations. Several characteristics of DNA methylation also align well with the concept of animal personality. In this review paper, we summarise the current literature on the role that molecular epigenetic mechanisms may have in explaining personality variation. We elaborate on the potential for epigenetic mechanisms to explain behavioural variation, behavioural development and temporal consistency in behaviour. We then suggest future routes for this emerging field and point to potential pitfalls that may be encountered. We conclude that a more inclusive approach is needed for studying the epigenetics of animal personality and that epigenetic mechanisms cannot be studied without considering the genetic background.

Analysis of Y-STR diversity and DNA methylation variation among Black and Indian males from KwaZulu-Natal, South Africa

Y-chromosome short tandem repeats (Y-STRs) are essential in understanding genetic structure and diversity of human populations and, most importantly, in identification of male perpetrators in criminal investigations. DNA methylation differences have been reported in human populations and methylation pattern at the CpG sites found within or flanking the Y-STR sites could also aid in human identification. Studies based on DNA methylation (DNAm) at Y-STRs are currently limited. The current study aimed to analyze the Y-STR diversity in South African Black and Indian individuals living in KwaZulu-Natal, Durban, South Africa, with the Yfiler™ Plus Kit and to analyze DNAm patterns in Y-STR markers CpG sites. DNA from 247 stored saliva samples were isolated and quantified. Across the 27 Y-STR loci in the Yfiler™ Plus Kit, 253 alleles were observed in 113 South African Black and Indian males, 112 unique haplotypes were observed, and one haplotype appeared twice (two Black individuals). No statistically significant differences were observed in the genetic diversity between the two population groups (Fst = 0.028, p-value ≥ 0.05). The kit showed a high discrimination capacity (DC) of 0.9912 and an overall haplotype diversity (HD) = 0.9995 among the sampled population groups. DYS438 and DYS448 markers displayed 2 and 3 CpG sites, respectively. Based on the two-tailed Fisher's Exact test, there were no statistically significant differences in the DNAm levels at DYS438 CpGs of Black and Indian males (p > 0.05). The Yfiler™ Plus Kit can be considered highly discriminatory among South African Black and Indian males. Studies on the South African population using Yfiler™ Plus Kit are scarce. Hence, accumulating Y-STR data on the diverse South African population will enhance the representation of South Africa in STR databases. Knowing which Y-STR markers are significantly informative for South Africa is essential for developing Y-STR kits better suited for the different ethnic groups. And to the best of our knowledge, DNA methylation analysis in Y-STR for different ethnic groups has never been done before. Complementing Y-STR data with methylation knowledge could provide population-specific information for forensic identification.

Maternal Immune Activation Induces Adolescent Cognitive Deficits Preceded by Developmental Perturbations in Cortical Reelin Signalling

Exposure to maternal immune activation (MIA) in utero significantly elevates the risk of developing schizophrenia and other neurodevelopmental disorders. To understand the biological mechanisms underlying the link between MIA and increased risk, preclinical animal models have focussed on specific signalling pathways in the brain that mediate symptoms associated with neurodevelopmental disorders such as cognitive dysfunction. Reelin signalling in multiple brain regions is involved in neuronal migration, synaptic plasticity and long-term potentiation, and has been implicated in cognitive deficits. However, how regulation of Reelin expression is affected by MIA across cortical development and associated cognitive functions remains largely unclear. Using a MIA rat model, here we demonstrate cognitive deficits in adolescent object-location memory in MIA offspring and reductions in Reln expression prenatally and in the adult prefrontal cortex. Further, developmental disturbances in gene/protein expression and DNA methylation of downstream signalling components occurred subsequent to MIA-induced Reelin dysregulation and prior to cognitive deficits. We propose that MIA-induced dysregulation of Reelin signalling contributes to the emergence of prefrontal cortex-mediated cognitive deficits through altered NMDA receptor function, resulting in inefficient long-term potentiation. Our data suggest a developmental window during which attenuation of Reelin signalling may provide a possible therapeutic target.

Aging Hallmarks and the Role of Oxidative Stress

Aging is a complex biological process accompanied by a progressive decline in the physical function of the organism and an increased risk of age-related chronic diseases such as cardiovascular diseases, cancer, and neurodegenerative diseases. Studies have established that there exist nine hallmarks of the aging process, including (i) telomere shortening, (ii) genomic instability, (iii) epigenetic modifications, (iv) mitochondrial dysfunction, (v) loss of proteostasis, (vi) dysregulated nutrient sensing, (vii) stem cell exhaustion, (viii) cellular senescence, and (ix) altered cellular communication. All these alterations have been linked to sustained systemic inflammation, and these mechanisms contribute to the aging process in timing not clearly determined yet. Nevertheless, mitochondrial dysfunction is one of the most important mechanisms contributing to the aging process. Mitochondria is the primary endogenous source of reactive oxygen species (ROS). During the aging process, there is a decline in ATP production and elevated ROS production together with a decline in the antioxidant defense. Elevated ROS levels can cause oxidative stress and severe damage to the cell, organelle membranes, DNA, lipids, and proteins. This damage contributes to the aging phenotype. In this review, we summarize recent advances in the mechanisms of aging with an emphasis on mitochondrial dysfunction and ROS production.

Maternal obesity and gestational diabetes reprogram the methylome of offspring beyond birth by inducing epigenetic signatures in metabolic and developmental pathways

BACKGROUND

Obesity is a negative chronic metabolic health condition that represents an additional risk for the development of multiple pathologies. Epidemiological studies have shown how maternal obesity or gestational diabetes mellitus during pregnancy constitute serious risk factors in relation to the appearance of cardiometabolic diseases in the offspring. Furthermore, epigenetic remodelling may help explain the molecular mechanisms that underlie these epidemiological findings. Thus, in this study we explored the DNA methylation landscape of children born to mothers with obesity and gestational diabetes during their first year of life.

METHODS

We used Illumina Infinium MethylationEPIC BeadChip arrays to profile more than 770,000 genome-wide CpG sites in blood samples from a paediatric longitudinal cohort consisting of 26 children born to mothers who suffered from obesity or obesity with gestational diabetes mellitus during pregnancy and 13 healthy controls (measurements taken at 0, 6 and 12 month; total N = 90). We carried out cross-sectional and longitudinal analyses to derive DNA methylation alterations associated with developmental and pathology-related epigenomics.

RESULTS

We identified abundant DNA methylation changes during child development from birth to 6 months and, to a lesser extent, up to 12 months of age. Using cross-sectional analyses, we discovered DNA methylation biomarkers maintained across the first year of life that could discriminate children born to mothers who suffered from obesity or obesity with gestational diabetes. Importantly, enrichment analyses suggested that these alterations constitute epigenetic signatures that affect genes and pathways involved in the metabolism of fatty acids, postnatal developmental processes and mitochondrial bioenergetics, such as CPT1B, SLC38A4, SLC35F3 and FN3K. Finally, we observed evidence of an interaction between developmental DNA methylation changes and maternal metabolic condition alterations.

CONCLUSIONS

Our observations highlight the first six months of development as being the most crucial for epigenetic remodelling. Furthermore, our results support the existence of systemic intrauterine foetal programming linked to obesity and gestational diabetes that affects the childhood methylome beyond birth, which involves alterations related to metabolic pathways, and which may interact with ordinary postnatal development programmes.

Cross-Ancestry DNA Methylation Marks of Insulin Resistance in Pregnancy: An Integrative Epigenome-Wide Association Study

Although there are some epigenome-wide association studies (EWAS) of insulin resistance, for most of them authors did not replicate their findings, and most are focused on populations of European ancestry, limiting the generalizability. In the Epigenetics in Pregnancy (EPIPREG; n = 294 Europeans and 162 South Asians) study, we conducted an EWAS of insulin resistance in maternal peripheral blood leukocytes, with replication in the Born in Bradford (n = 879; n = 430 Europeans and 449 South Asians), Methyl Epigenome Network Association (MENA) (n = 320), and Botnia (n = 56) cohorts. In EPIPREG, we identified six CpG sites inversely associated with insulin resistance across ancestry, of which five were replicated in independent cohorts (cg02988288, cg19693031, and cg26974062 in TXNIP; cg06690548 in SLC7A11; and cg04861640 in ZSCAN26). From methylation quantitative trait loci analysis in EPIPREG, we identified gene variants related to all five replicated cross-ancestry CpG sites, which were associated with several cardiometabolic phenotypes. Mediation analyses suggested that the gene variants regulate insulin resistance through DNA methylation. To conclude, our cross-ancestry EWAS identified five CpG sites related to lower insulin resistance.

DNMT3B rs2424913 as a Risk Factor for Congenital Heart Defects in Down Syndrome

Impairments of the genes that encode enzymes that are involved in one-carbon metabolism because of the presence of gene polymorphisms can affect the methylation pattern. The altered methylation profiles of the genes involved in cardiogenesis may result in congenital heart defects (CHDs). The aim of this study was to investigate the association between the MTHFR rs1801133, MTHFR rs1801131, MTRR rs1801394, DNMT1 rs2228611, DNMT3A rs1550117, DNMT3B rs1569686, and DNMT3B rs2424913 gene polymorphisms and congenital heart defects in Down syndrome (DS) individuals. The study was conducted on 350 participants, including 134 DS individuals with CHDs (DSCHD+), 124 DS individuals without CHDs (DSCHD−), and 92 individuals with non-syndromic CHD. The genotyping was performed using the PCR–RFLP method. A statistically significant higher frequency of the DNMT3B rs2424913 TT in the DSCHD+ individuals was observed. The DNMT3B rs2424913 TT genotype, as well as the T allele, had significantly higher frequencies in the individuals with DS and atrial septal defects (ASDs) in comparison with the individuals with DS and other CHDs. Furthermore, our results indicate a statistically significant effect of the DNMT3B rs1569686 TT genotype in individuals with non-syndromic CHDs. The results of the study suggest that the DNMT3B rs2424913 TT genotypes may be a possible predisposing factor for CHDs in DS individuals, and especially those with ASDs.

Decoding the genetic and epigenetic basis of asthma

Asthma is a complex and heterogeneous chronic inflammatory disease of the airways. Alongside environmental factors, asthma susceptibility is strongly influenced by genetics. Given its high prevalence and our incomplete understanding of the mechanisms underlying disease susceptibility, asthma is frequently studied in genome-wide association studies (GWAS), which have identified thousands of genetic variants associated with asthma development. Virtually all these genetic variants reside in non-coding genomic regions, which has obscured the functional impact of asthma-associated variants and their translation into disease-relevant mechanisms. Recent advances in genomics technology and epigenetics now offer methods to link genetic variants to gene regulatory elements embedded within non-coding regions, which have started to unravel the molecular mechanisms underlying the complex (epi)genetics of asthma. Here, we provide an integrated overview of (epi)genetic variants associated with asthma, focusing on efforts to link these disease associations to biological insight into asthma pathophysiology using state-of-the-art genomics methodology. Finally, we provide a perspective as to how decoding the genetic and epigenetic basis of asthma has the potential to transform clinical management of asthma and to predict the risk of asthma development.

Beadchip technology to detect DNA methylation in mouse faithfully recapitulates whole-genome bisulfite sequencing

Aim: To facilitate wide-scale implementation of Illumina Mouse Methylation BeadChip (MMB) technology, array-based measurement of cytosine methylation was compared with the gold-standard assessment of DNA methylation by whole-genome bisulfite sequencing (WGBS). Methods: DNA methylation across two mouse strains (C57B6 and C3H) and both sexes was assessed using the MMB and compared with previously existing deep-coverage WGBS of mice of the same strain and sex. Results & conclusion: The findings demonstrated that 93.3-99.2% of sites had similar measurements of methylation across technologies and that differentially methylated cytosines and regions identified by each technology overlap and enrich for similar biological functions, suggesting that the MMB faithfully recapitulates the findings of WGBS.

Genome-wide evaluation of the effect of short tandem repeat variation on local DNA methylation

Short tandem repeats (STRs) contribute significantly to genetic diversity in humans, including disease-causing variation. Although the effect of STR variation on gene expression has been extensively assessed, their impact on epigenetics has been poorly studied and limited to specific genomic regions. Here, we investigated the hypothesis that some STRs act as independent regulators of local DNA methylation in the human genome and modify risk of common human traits. To address these questions, we first analyzed two independent data sets comprising PCR-free whole-genome sequencing (WGS) and genome-wide DNA methylation levels derived from whole-blood samples in 245 (discovery cohort) and 484 individuals (replication cohort). Using genotypes for 131,635 polymorphic STRs derived from WGS using HipSTR, we identified 11,870 STRs that associated with DNA methylation levels (mSTRs) of 11,774 CpGs (Bonferroni P < 0.001) in our discovery cohort, with 90% successfully replicating in our second cohort. Subsequently, through fine-mapping using CAVIAR we defined 585 of these mSTRs as the likely causal variants underlying the observed associations (fm-mSTRs) and linked a fraction of these to previously reported genome-wide association study signals, providing insights into the mechanisms underlying complex human traits. Furthermore, by integrating gene expression data, we observed that 12.5% of the tested fm-mSTRs also modulate expression levels of nearby genes, reinforcing their regulatory potential. Overall, our findings expand the catalog of functional sequence variants that affect genome regulation, highlighting the importance of incorporating STRs in future genetic association analysis and epigenetics data for the interpretation of trait-associated variants.

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

BACKGROUND

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

RESULTS

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

CONCLUSIONS

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

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

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

Perinatal Fat-Diets Increased Angiotensin II-Mediated Ca2+ through PKC-L-Type Calcium Channel Axis in Resistance Arteries via Agtr1a-Prkcb Gene Methylation

Perinatal malnutrition affects vascular functions, and calcium is important in vascular regulations. It is unknown whether and how perinatal maternal high-fat diets (MHF)-mediated vascular dysfunction occurs via the angiotensin-PKC-L-type-calcium-channels (LTCC) axis. This study determined angiotensin II (AII) roles in the PKC-LTCC axis in controlling calcium influx in the arteries of offspring after perinatal MHF. Mesenteric arteries (MA) and smooth muscle cells (SMCs) from 5-month-old offspring rats were studied using physiological, ion channel, molecular, and epigenetic analysis. Pressor responses to AII were significantly increased in the free-moving MHF offspring rats. In cell experiments, MA-SMC proliferation was enhanced, and associated with thicker vascular wall in the obese offspring. Imaging analysis showed increase of fluorescence Ca²⁺ intensity in the SMCs of the MHF group. Angiotensin II receptor (AT1R)-mediated PKC-LTCC axis in vasoconstrictions was altered by perinatal MHF via reduced DNA methylation at specific CpG sites of Agtr1a and Prkcb gene promoters at the transcription level. Accordingly, mRNA and protein expression of AT1R and PKCβ in the offspring MA were increased, contributing to enhanced Ca²⁺ currents and vascular tone. The results showed that DNA methylation resulted in perinatal MHF-induced vascular disorders via altered AT1-PKC-LTCC pathway in resistance arteries of the offspring, providing new insights into the pathogenesis and early prevention/treatments for hypertension in developmental origins.

Long-term Temporal Stability of Peripheral Blood DNA Methylation Profiles in Patients With Inflammatory Bowel Disease

BACKGROUND & AIMS

There is great current interest in the potential application of DNA methylation alterations in peripheral blood leukocytes (PBLs) as biomarkers of susceptibility, progression, and treatment response in inflammatory bowel disease (IBD). However, the intra-individual stability of PBL methylation in IBD has not been characterized. Here, we studied the long-term stability of all probes located on the Illumina HumanMethylation EPIC BeadChip array.

METHODS

We followed a cohort of 46 adult patients with IBD (36 Crohn's disease [CD], 10 ulcerative colitis [UC]; median age, 44 years; interquartile range [IQR] 27-56 years; 50% female) that received standard care follow-up at the Amsterdam University Medical Centers. Paired PBL samples were collected at 2 time points with a median of 7 years (range, 2-9 years) in between. Differential methylation and intra-class correlation (ICC) analyses were used to identify time-associated differences and temporally stable CpGs, respectively.

RESULTS

Around 60% of all EPIC array loci presented poor intra-individual stability (ICC <0.50); 78.114 (≈9%) showed good (ICC, 0.75-0.89), and 41.274 (≈5%) showed excellent (ICC ≥0.90) stability, between both measured time points. Focusing on previously identified consistently differentially methylated positions indicated that 22 CD-, 11 UC-, and 24 IBD-associated loci demonstrated high stability (ICC ≥0.75) over time; of these, we observed a marked stability of CpG loci associated to the HLA genes.

CONCLUSIONS

Our data provide insight into the long-term stability of the PBL DNA methylome within an IBD context, facilitating the selection of biologically relevant and robust IBD-associated epigenetic biomarkers with increased potential for independent validation. These data also have potential implications in understanding disease pathogenesis.

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.

Monitoring EGFR-lung cancer evolution: a possible beginning of a "methylation era" in TKI resistance prediction

The advances in scientific knowledge on biological therapies of the last two decades have impressively oriented the clinical management of non-small-cell lung cancer (NSCLC) patients. The treatment with tyrosine kinase inhibitors (TKIs) in patients harboring Epidermal Growth Factor Receptor (EGFR)-activating mutations is dramatically associated with an improvement in disease control. Anyhow, the prognosis for this selected group of patients remains unfavorable, due to the innate and/or acquired resistance to biological therapies. The methylome analysis of many tumors revealed multiple patterns of methylation at single/multiple cytosine-phosphate-guanine (CpG) sites that are linked to the modulation of several cellular pathways involved in cancer onset and progression. In lung cancer patients, ever increasing evidences also suggest that the association between DNA methylation changes at promoter/intergenic regions and the consequent alteration of gene-expression signatures could be related to the acquisition of resistance to biological therapies. Despite this intriguing hypothesis, large confirmatory studies are demanded to consolidate and finalize many preliminary observations made in this field. In this review, we will summarize the available knowledge about the dynamic role of DNA methylation in EGFR-mutated NSCLC patients.

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.

DNA methylation signature aberration as potential biomarkers in treatment-resistant schizophrenia: Constructing a methylation risk score using a machine learning method

Treatment-resistant schizophrenia (TRS) is defined as a non-response to at least two trials of antipsychotic medication with an adequate dose and duration. We aimed to evaluate the discriminant abilities of DNA methylation probes and methylation risk score between treatment-resistant schizophrenia and non-treatment-resistant schizophrenia. This study recruited 96 schizophrenia patients (TRS and non-TRS) and 56 healthy controls (HC). Participants were divided into a discovery set and a validation set. In the discovery set, we conducted genome-wide methylation analysis (human MethylationEPIC 850K BeadChip) on the subject's blood DNA and discriminated significant methylation signatures, then verified these methylation signatures in the validation set. Based on genome-wide scans of TRS versus non-TRS, thirteen differentially methylated probes were identified at FDR <0.05 and >20% differences in DNA methylation β-values. Next, we selected six probes within gene coding regions (LOC404266, LOXL2, CERK, CHMP7, and SLC17A9) to conduct verification in the validation set using quantitative methylation-specific PCR (qMSP). These six methylation probes showed satisfactory discrimination between TRS patients and non-TRS patients, with an AUC ranging from 0.83 to 0.92, accuracy ranging from 77.8% to 87.3%, sensitivity ranging from 80% to 90%, and specificity ranging from 65.6% to 85%. This methylation risk score model showed satisfactory discrimination between TRS patients and non-TRS patients, with an accuracy of 88.3%. These findings support that methylation signatures may be used as an indicator of TRS vulnerability and provide a model for the clinical use of methylation to identify TRS.

The immune factors driving DNA methylation variation in human blood

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

Dynamics of Methylation of CpG Sites Associated With Systemic Lupus Erythematosus Subtypes in a Longitudinal Cohort

OBJECTIVE

Findings from cross-sectional studies have revealed associations between DNA methylation and systemic lupus erythematosus (SLE) outcomes. This study was undertaken to investigate the dynamics of DNA methylation by examining participants from an SLE longitudinal cohort using samples collected at 2 time points.

METHODS

A total of 101 participants from the California Lupus Epidemiology Study were included in our analysis. DNA was extracted from blood samples collected at the time of enrolment in the cohort and samples collected after 2 years and was analyzed using Illumina EPIC BeadChip kit. Paired t-tests were used to identify genome-wide changes which included 256 CpG sites previously found to be associated with SLE subtypes. Linear mixed models were developed to understand the relationship between DNA methylation and disease activity, medication use, and sample cell-type proportions, adjusted for age, sex, and genetic principal components.

RESULTS

The majority of CpGs that were previously determined to be associated with SLE subtypes remained stable over 2 years (185 CpGs [72.3%]; t-test false discovery rate >0.05). Compared to background genome-wide methylation, there was an enrichment of SLE subtype-associated CpGs that changed over time (27.7% versus 0.34%). Changes in cell-type proportions were associated with changes at 67 CpGs (P < 2.70 × 10^-5 ), and 15 CpGs had at least 1 significant association with immunosuppressant use.

CONCLUSION

In this longitudinal SLE cohort, we identified a subset of SLE subtype-associated CpGs that remained stable over time and may be useful as biomarkers of disease subtypes. Another subset of SLE subtype-associated CpGs changed at a higher proportion compared to the genome-wide methylome. Additional studies are needed to understand the etiology and impact of these changes on methylation of SLE-associated CpGs.

Conditional GWAS of non-CG transposon methylation in Arabidopsis thaliana reveals major polymorphisms in five genes

Genome-wide association studies (GWAS) have revealed that the striking natural variation for DNA CHH-methylation (mCHH; H is A, T, or C) of transposons has oligogenic architecture involving major alleles at a handful of known methylation regulators. Here we use a conditional GWAS approach to show that CHG-methylation (mCHG) has a similar genetic architecture—once mCHH is statistically controlled for. We identify five key trans-regulators that appear to modulate mCHG levels, and show that they interact with a previously identified modifier of mCHH in regulating natural transposon mobilization.

DNA methylation is an epigenetic mark common across eukaryotes. It is associated with transcriptional silencing, in particular of transposable elements. Multiple elements, including epigenetic inheritance, shape DNA methylation patterns, and the complexity makes it challenging to dissect the regulation. Our work on the 1001 Arabidopsis Epigenomes project led to the unexpected discovery that much of the natural variation for CHH methylation (mCHH; H is A, T, or C) on transposable elements could be attributed to allelic variation in three genes known to be involved in epigenetic regulation. However, our analysis of methylation in other sequence contexts (mCHG and mCG) revealed no genetic regulator.

Here we show that if mCHG variation is analyzed while taking mCHH into account, mCHG is also strongly influenced by allelic variation in a small number of genes with known or highly plausible direct roles in epigenetic regulation. The presence of common allelic variation of large effect is suggestive of some form of local adaptation. The nature of this adaptation remains obscure, but we present further evidence that allelic variation regulating DNA methylation influences transposon mobilization.

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

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

Look-alike humans identified by facial recognition algorithms show genetic similarities

The human face is one of the most visible features of our unique identity as individuals. Interestingly, monozygotic twins share almost identical facial traits and the same DNA sequence but could exhibit differences in other biometrical parameters. The expansion of the world wide web and the possibility to exchange pictures of humans across the planet has increased the number of people identified online as virtual twins or doubles that are not family related. Herein, we have characterized in detail a set of "look-alike" humans, defined by facial recognition algorithms, for their multiomics landscape. We report that these individuals share similar genotypes and differ in their DNA methylation and microbiome landscape. These results not only provide insights about the genetics that determine our face but also might have implications for the establishment of other human anthropometric properties and even personality characteristics.

DNA methylation as a mediator of genetic and environmental influences on Parkinson's disease susceptibility: Impacts of alpha-Synuclein, physical activity, and pesticide exposure on the epigenome

Parkinson's disease (PD) is a neurodegenerative disorder with a complex etiology and increasing prevalence worldwide. As PD is influenced by a combination of genetic and environment/lifestyle factors in approximately 90% of cases, there is increasing interest in identification of the interindividual mechanisms underlying the development of PD as well as actionable lifestyle factors that can influence risk. This narrative review presents an outline of the genetic and environmental factors contributing to PD risk and explores the possible roles of cytosine methylation and hydroxymethylation in the etiology and/or as early-stage biomarkers of PD, with an emphasis on epigenome-wide association studies (EWAS) of PD conducted over the past decade. Specifically, we focused on variants in the SNCA gene, exposure to pesticides, and physical activity as key contributors to PD risk. Current research indicates that these factors individually impact the epigenome, particularly at the level of CpG methylation. There is also emerging evidence for interaction effects between genetic and environmental contributions to PD risk, possibly acting across multiple omics layers. We speculated that this may be one reason for the poor replicability of the results of EWAS for PD reported to date. Our goal is to provide direction for future epigenetics studies of PD to build upon existing foundations and leverage large datasets, new technologies, and relevant statistical approaches to further elucidate the etiology of this disease.

Identification of TMEM129, encoding a ubiquitin-protein ligase, as an effector gene of osteoarthritis genetic risk

BACKGROUND

Osteoarthritis is highly heritable and genome-wide studies have identified single nucleotide polymorphisms (SNPs) associated with the disease. One such locus is marked by SNP rs11732213 (T > C). Genotype at rs11732213 correlates with the methylation levels of nearby CpG dinucleotides (CpGs), forming a methylation quantitative trait locus (mQTL). This study investigated the regulatory activity of the CpGs to identify a target gene of the locus.

METHODS

Nucleic acids were extracted from the articular cartilage of osteoarthritis patients. Samples were genotyped, and DNA methylation was quantified by pyrosequencing at 14 CpGs within a 259-bp interval. CpGs were tested for enhancer effects in immortalised chondrocytes using a reporter gene assay. DNA methylation at the locus was altered using targeted epigenome editing, with the impact on gene expression determined using quantitative polymerase chain reaction.

RESULTS

rs11732213 genotype correlated with DNA methylation at nine CpGs, which formed a differentially methylated region (DMR), with the osteoarthritis risk allele T corresponding to reduced levels of methylation. The DMR acted as an enhancer and demethylation of the CpGs altered expression of TMEM129. Allelic imbalance in TMEM129 expression was identified in cartilage, with under-expression of the risk allele.

CONCLUSIONS

TMEM129 is a target of osteoarthritis genetic risk at this locus. Genotype at rs11732213 impacts DNA methylation at the enhancer, which, in turn, modulates TMEM129 expression. TMEM129 encodes an enzyme involved in protein degradation within the endoplasmic reticulum, a process previously implicated in osteoarthritis. TMEM129 is a compelling osteoarthritis susceptibility target.

Methylation and expression quantitative trait locus rs6296 in the HTR1B gene is associated with susceptibility to opioid use disorder

Serotonin (5-HT) is implicated in the reward processes underlying substance use disorder. Epigenetic and transcriptional mechanisms contribute to the development of addictive states. To examine the potential mechanisms of 5-HT receptor genes in opioid use disorder, we first determined the associations between several single-nucleotide polymorphism (SNPs) in three representative 5-HT receptor genes (HTR1B, HTR2A, and HTR3B) and susceptibility to heroin use disorder in 1731 participants. Gene-gene interactions among these genes were analyzed. After identifying the susceptibility genes and SNPs for heroin use disorder, DNA methylation in the promoter region of these susceptibility genes was compared between 111 healthy controls and 120 patients with heroin use disorder. In addition, associations between the susceptibility SNPs and methylation of the CpG sites and gene promoters with differential methylation between groups were examined. Finally, the function of the susceptibility SNPs in the expression of the corresponding genes was screened. Our results demonstrated that rs6296 in the HTR1B gene was correlated with susceptibility to heroin use disorder. Gene-gene interactions between the HTR1B and HTR2A genes were identified. The CpG sites HTR1B_07 and HTR1B_26 and the promoter region of the HTR1B gene were hypermethylated in patients with heroin use disorder compared with healthy controls. Notably, rs6296 correlated in an allele-specific manner with methylation in the HTR1B gene promoter in the blood and gene expression of the HTR1B gene in the frontal cortex and hypothalamus. SNP rs6296 was associated with opioid use disorder by involving mechanisms of DNA methylation and expression of the HTR1B gene.

Functional correlation of genome-wide DNA methylation profiles in genetic neurodevelopmental disorders

An expanding range of genetic syndromes are characterized by genome-wide disruptions in DNA methylation profiles referred to as episignatures. Episignatures are distinct, highly sensitive and specific biomarkers that have recently been applied in clinical diagnosis of genetic syndromes. Episignatures are contained within the broader disorder-specific genome-wide DNA methylation changes which can share significant overlap amongst different conditions. In this study we performed functional genomic assessment and comparison of disorder-specific and overlapping genome-wide DNA methylation changes related to 65 genetic syndromes with previously described episignatures. We demonstrate evidence of disorder-specific and recurring genome-wide differentially methylated probes (DMPs) and regions (DMRs). The overall distribution of DMPs and DMRs across the majority of the neurodevelopmental genetic syndromes analyzed showed substantial enrichment in gene promoters and CpG islands, and under-representation of the more variable intergenic regions. Analysis showed significant enrichment of the DMPs and DMRs in gene pathways and processes related to neurodevelopment, including neurogenesis, synaptic signaling and synaptic transmission. This study expands beyond the diagnostic utility of DNA methylation episignatures by demonstrating correlation between the function of the mutated genes and the consequent genomic DNA methylation profiles as a key functional element in the molecular etiology of genetic neurodevelopmental disorders. This article is protected by copyright. All rights reserved.

In-Silico Study of Brassinosteroid Signaling Genes in Rice Provides Insight Into Mechanisms Which Regulate Their Expression

Brassinosteroids (BRs) regulate a diverse spectrum of processes during plant growth and development and modulate plant physiology in response to environmental fluctuations and stress factors. Thus, the BR signaling regulators have the potential to be targeted for gene editing to optimize the architecture of plants and make them more resilient to environmental stress. Our understanding of the BR signaling mechanism in monocot crop species is limited compared to our knowledge of this process accumulated in the model dicot species - Arabidopsis thaliana. A deeper understanding of the BR signaling and response during plant growth and adaptation to continually changing environmental conditions will provide insight into mechanisms that govern the coordinated expression of the BR signaling genes in rice (Oryza sativa) which is a model for cereal crops. Therefore, in this study a comprehensive and detailed in silico analysis of promoter sequences of rice BR signaling genes was performed. Moreover, expression profiles of these genes during various developmental stages and reactions to several stress conditions were analyzed. Additionally, a model of interactions between the encoded proteins was also established. The obtained results revealed that promoters of the 39 BR signaling genes are involved in various regulatory mechanisms and interdependent processes that influence growth, development, and stress response in rice. Different transcription factor-binding sites and cis-regulatory elements in the gene promoters were identified which are involved in regulation of the genes’ expression during plant development and reactions to stress conditions. The in-silico analysis of BR signaling genes in O. sativa provides information about mechanisms which regulate the coordinated expression of these genes during rice development and in response to other phytohormones and environmental factors. Since rice is both an important crop and the model species for other cereals, this information may be important for understanding the regulatory mechanisms that modulate the BR signaling in monocot species. It can also provide new ways for the plant genetic engineering technology by providing novel potential targets, either cis-elements or transcriptional factors, to create elite genotypes with desirable traits.

InterpolatedXY: a two-step strategy to normalize DNA methylation microarray data avoiding sex bias

MOTIVATION

Data normalization is an essential step to reduce technical variation within and between arrays. Due to the different karyotypes and the effects of X chromosome inactivation, females and males exhibit distinct methylation patterns on sex chromosomes; thus, it poses a significant challenge to normalize sex chromosome data without introducing bias. Currently, existing methods do not provide unbiased solutions to normalize sex chromosome data, usually, they just process autosomal and sex chromosomes indiscriminately.

RESULTS

Here, we demonstrate that ignoring this sex difference will lead to introducing artificial sex bias, especially for thousands of autosomal CpGs. We present a novel two-step strategy (interpolatedXY) to address this issue, which is applicable to all quantile-based normalization methods. By this new strategy, the autosomal CpGs are first normalized independently by conventional methods, such as funnorm or dasen; then the corrected methylation values of sex chromosome-linked CpGs are estimated as the weighted average of their nearest neighbors on autosomes. The proposed two-step strategy can also be applied to other non-quantile-based normalization methods, as well as other array-based data types. Moreover, we propose a useful concept: the sex explained fraction of variance, to quantitatively measure the normalization effect.

AVAILABILITY AND IMPLEMENTATION

The proposed methods are available by calling the function 'adjustedDasen' or 'adjustedFunnorm' in the latest wateRmelon package (https://github.com/schalkwyk/wateRmelon), with methods compatible with all the major workflows, including minfi.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

PTBP2 - a gene with relevance for both Anorexia nervosa and body weight regulation

Genetic factors are relevant for both eating disorders and body weight regulation. A recent genome-wide association study (GWAS) for anorexia nervosa (AN) detected eight genome-wide significant chromosomal loci. One of these loci, rs10747478, was also genome-wide and significantly associated with body mass index (BMI). The nearest coding gene is the Polypyrimidine Tract Binding Protein 2 gene (PTBP2). To detect mutations in PTBP2, Sanger sequencing of the coding region was performed in 192 female patients with AN (acute or recovered) and 191 children or adolescents with (extreme) obesity. Twenty-five variants were identified. Twenty-three of these were predicted to be pathogenic or functionally relevant in at least one in silico tool. Two novel synonymous variants (p.Ala77Ala and p.Asp195Asp), one intronic SNP (rs188987764), and the intronic deletion (rs561340981) located in the highly conserved region of PTBP2 may have functional consequences. Ten of 20 genes interacting with PTBP2 were studied for their impact on body weight regulation based on either previous functional studies or GWAS hits for body weight or BMI. In a GWAS for BMI (Pulit et al. 2018), the number of genome-wide significant associations at the PTBP2 locus was different between males (60 variants) and females (two variants, one of these also significant in males). More than 65% of these 61 variants showed differences in the effect size pertaining to BMI between sexes (absolute value of Z-score >2, two-sided p < 0.05). One LD block overlapping 5'UTR and all coding regions of PTBP2 comprises 56 significant variants in males. The analysis based on sex-stratified BMI GWAS summary statistics implies that PTBP2 may have a more pronounced effect on body weight regulation in males than in females.

Additive and Interactive Genetically Contextual Effects of HbA1c on cg19693031 Methylation in Type 2 Diabetes

Type 2 diabetes mellitus (T2D) has a complex genetic and environmental architecture that underlies its development and clinical presentation. Despite the identification of well over a hundred genetic variants and CpG sites that associate with T2D, a robust biosignature that could be used to prevent or forestall clinical disease has not been developed. Based on the premise that underlying genetic variation influences DNA methylation (DNAm) independently of or in combination with environmental exposures, we assessed the ability of local and distal gene x methylation (GxMeth) interactive effects to improve cg19693031 models for predicting T2D status in an African American cohort. Using genome-wide genetic data from 506 subjects, we identified a total of 1476 GxMeth terms associated with HbA1c values. The GxMeth SNPs map to biological pathways associated with the development and complications of T2D, with genetically contextual differences in methylation observed only in diabetic subjects for two GxMeth SNPs (rs2390998 AG vs. GG, p = 4.63 × 10−11, Δβ = 13%, effect size = 0.16 [95% CI = 0.05, 0.32]; rs1074390 AA vs. GG, p = 3.93 × 10−4, Δβ = 9%, effect size = 0.38 [95% CI = 0.12, 0.56]. Using a repeated stratified k-fold cross-validation approach, a series of balanced random forest classifiers with random under-sampling were built to evaluate the addition of GxMeth terms to cg19693031 models to discriminate between normoglycemic controls versus T2D subjects. The results were compared to those obtained from models incorporating only the covariates (age, sex and BMI) and the addition of cg19693031. We found a post-pruned classifier incorporating 10 GxMeth SNPs and cg19693031 adjusted for covariates predicted the T2D status, with the AUC, sensitivity, specificity and precision of the positive target class being 0.76, 0.81, 0.70 and 0.63, respectively. Comparatively, the AUC, sensitivity, specificity and precision using the covariates and cg19693031 were only 0.71, 0.74, 0.67 and 0.59, respectively. Collectively, we demonstrate correcting for genetic confounding of cg19693031 improves its ability to detect type 2 diabetes. We conclude that an integrated genetic–epigenetic approach could inform personalized medicine programming for more effective prevention and treatment of T2D.

Genetic regulation of THBS1 methylation in diabetic retinopathy

BACKGROUND

Diabetic retinopathy (DR) is a common and serious microvascular complication of diabetes mellitus (DM), but its pathological mechanism, especially the formation mechanism of new blood vessels remains unclear. Thrombospondin-1 (THBS1) is a potent endogenous inhibitor of angiogenesis and it was found over expressed in DR in our previous study. Our study aimed to determine whether overexpression of THBS1 is associated with its promoter methylation level, and whether methylation of THBS1 is regulated by genetic variants in DR.

METHODS

Patients diagnosed with DR and DM patients without retinal problems were included in the case-control study. DNA methylation detection of THBS1 by bisulfite sequencing and genotyping of specific SNPs by MassARRAY analysis were performed in the patients recruited from 2019-2020. Real time quantitative PCR was performed to obtain mRNA expression of THBS1 in the patients recruited from August to October 2022. The differentially methylated CpG loci of THBS1 were identified by logistic regression, and associations between 13 SNPs and methylation levels of CpG loci were tested by methylation quantitative trait loci (meQTLs) analysis. Mediation analysis was applied to determine whether CpG loci were intermediate factors between meQTLs and DR.

RESULTS

150 patients diagnosed with DR and 150 DM patients without retinal complications were enrolled in the first recruitment, seven DR patients and seven DM patients were enrolled in the second recruitment. The patients with DR showed promoter hypomethylation of THBS1 (P value = 0.002), and six out of thirty-nine CpG sites within two CpG islands (CGIs) showed hypomethylation(P value < 0.05). THBS1 mRNA expression in peripheral blood was significantly higher in DR patients than in DM patients. Five out of thirteen cis-meQTLs were identified to be associated with CpG sites: rs13329154, rs34973764 and rs5812091 were associated with cis-meQTLs of CpG-4 (P value=0.0145, 0.0095, 0.0158), rs11070177 and rs1847663 were associated with cis-meQTLs of CpG-2 and CpG-3 respectively (P value=0.0201, 0.0275). CpG-4 methylation significantly mediated the effect of the polymorphism rs34973764 on DR (B=0.0535, Boot 95%CI: 0.004~0.1336).

CONCLUSION

THBS1 overexpression is related to THBS1 hypomethylation in patients with DR. DNA methylation may be genetically controlled in DR.

Genetics, epigenetics and transgenerational transmission of obesity in children

Sedentary lifestyle and consumption of high-calorie foods have caused a relentless increase of overweight and obesity prevalence at all ages. Its presently epidemic proportion is disquieting due to the tight relationship of obesity with metabolic syndrome and several other comorbidities which do call for urgent workarounds. The usual ineffectiveness of present therapies and failure of prevention campaigns triggered overtime a number of research studies which have unveiled some relevant aspects of obesity genetic and epigenetic inheritable profiles. These findings are revealing extremely precious mainly to serve as a likely extra arrow to allow the clinician's bow to achieve still hitherto unmet preventive goals. Evidence now exists that maternal obesity/overnutrition during pregnancy and lactation convincingly appears associated with several disorders in the offspring independently of the transmission of a purely genetic predisposition. Even the pre-conception direct exposure of either father or mother gametes to environmental factors can reprogram the epigenetic architecture of cells. Such phenomena lie behind the transfer of the obesity susceptibility to future generations through a mechanism of epigenetic inheritance. Moreover, a growing number of studies suggests that several environmental factors such as maternal malnutrition, hypoxia, and exposure to excess hormones and endocrine disruptors during pregnancy and the early postnatal period may play critical roles in programming childhood adipose tissue and obesity. A deeper understanding of how inherited genetics and epigenetics may generate an obesogenic environment at pediatric age might strengthen our knowledge about pathogenetic mechanisms and improve the clinical management of patients. Therefore, in this narrative review, we attempt to provide a general overview of the contribution of heritable genetic and epigenetic patterns to the obesity susceptibility in children, placing a particular emphasis on the mother-child dyad.

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.

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.

Skeletal muscle methylome and transcriptome integration reveals profound sex differences related to muscle function and substrate metabolism

Nearly all human complex traits and diseases exhibit some degree of sex differences, with epigenetics being one of the main contributing factors. Various tissues display sex differences in DNA methylation; however, this has not yet been explored in skeletal muscle, despite skeletal muscle being among the tissues with the most transcriptomic sex differences. For the first time, we investigated the effect of sex on autosomal DNA methylation in human skeletal muscle across three independent cohorts (Gene SMART, FUSION, and GSE38291) using a meta-analysis approach, totalling 369 human muscle samples (222 males and 147 females), and integrated this with known sex-biased transcriptomics. We found 10,240 differentially methylated regions (DMRs) at FDR < 0.005, 94% of which were hypomethylated in males, and gene set enrichment analysis revealed that differentially methylated genes were involved in muscle contraction and substrate metabolism. We then investigated biological factors underlying DNA methylation sex differences and found that circulating hormones were not associated with differential methylation at sex-biased DNA methylation loci; however, these sex-specific loci were enriched for binding sites of hormone-related transcription factors (with top TFs including androgen (AR), estrogen (ESR1), and glucocorticoid (NR3C1) receptors). Fibre type proportions were associated with differential methylation across the genome, as well as across 16% of sex-biased DNA methylation loci (FDR < 0.005). Integration of DNA methylomic results with transcriptomic data from the GTEx database and the FUSION cohort revealed 326 autosomal genes that display sex differences at both the epigenome and transcriptome levels. Importantly, transcriptional sex-biased genes were overrepresented among epigenetic sex-biased genes (p value = 4.6e−13), suggesting differential DNA methylation and gene expression between male and female muscle are functionally linked. Finally, we validated expression of three genes with large effect sizes (FOXO3A, ALDH1A1, and GGT7) in the Gene SMART cohort with qPCR. GGT7, involved in antioxidant metabolism, displays male-biased expression as well as lower methylation in males across the three cohorts. In conclusion, we uncovered 8420 genes that exhibit DNA methylation differences between males and females in human skeletal muscle that may modulate mechanisms controlling muscle metabolism and health.

GWAS loci associated with Chagas cardiomyopathy influences DNA methylation levels

A recent genome-wide association study (GWAS) identified a locus in chromosome 11 associated with the chronic cardiac form of Chagas disease. Here we aimed to elucidate the potential functional mechanism underlying this genetic association by analyzing the correlation among single nucleotide polymorphisms (SNPs) and DNA methylation (DNAm) levels as cis methylation quantitative trait loci (cis-mQTL) within this region. A total of 2,611 SNPs were tested against 2,647 DNAm sites, in a subset of 37 chronic Chagas cardiomyopathy patients and 20 asymptomatic individuals from the GWAS. We identified 6,958 significant cis-mQTLs (False Discovery Rate [FDR]<0.05) at 1 Mb each side of the GWAS leading variant, where six of them potentially modulate the expression of the SAC3D1 gene, the reported gene in the previous GWAS. In addition, a total of 268 cis-mQTLs showed differential methylation between chronic Chagas cardiomyopathy patients and asymptomatic individuals. The most significant cis-mQTLs mapped in the gene bodies of POLA2 (FDR = 1.04x10^-11), PLAAT3 (FDR = 7.22x10^-03), and CCDC88B (FDR = 1.89x10^-02) that have been associated with cardiovascular and hematological traits in previous studies. One of the most relevant interactions correlated with hypermethylation of CCDC88B. This gene is involved in the inflammatory response, and its methylation and expression levels have been previously reported in Chagas cardiomyopathy. Our findings support the functional relevance of the previously associated genomic region, highlighting the regulation of novel genes that could play a role in the chronic cardiac form of the disease.

Genome-wide association studies (GWAS) have provided extensive information regarding the genetic component of complex traits, including parasitic diseases such as Chagas disease. However, these associations mapped in regulatory regions of the genome and assigning them a functional consequence have been cumbersome. In this study we aimed to evaluate the functional mechanism underlying the previously reported genomic association with chronic Chagas cardiomyopathy, by assessing the correlation between methylation changes and the underlying genetic variations within the region. These methylation quantitative trait loci (mQTLs) may be involved in gene expression regulation. We identified mQTLs in three genes that have been associated with cardiovascular diseases in previous studies. Interestingly, one of these genes was previously identified as differentially methylated and expressed in heart biopsies of chronic Chagas cardiomyopathy patients. Our results suggest novel genes that could play a role in the chronic Chagas cardiomyopathy, evidencing the functional relevance of the previously associated loci.

Identification of tissue-specific and common methylation quantitative trait loci in healthy individuals using MAGAR

Background

Understanding the influence of genetic variants on DNA methylation is fundamental for the interpretation of epigenomic data in the context of disease. There is a need for systematic approaches not only for determining methylation quantitative trait loci (methQTL), but also for discriminating general from cell type-specific effects.

Results

Here, we present a two-step computational framework MAGAR (https://bioconductor.org/packages/MAGAR), which fully supports the identification of methQTLs from matched genotyping and DNA methylation data, and additionally allows for illuminating cell type-specific methQTL effects. In a pilot analysis, we apply MAGAR on data in four tissues (ileum, rectum, T cells, B cells) from healthy individuals and demonstrate the discrimination of common from cell type-specific methQTLs. We experimentally validate both types of methQTLs in an independent data set comprising additional cell types and tissues. Finally, we validate selected methQTLs located in the PON1, ZNF155, and NRG2 genes by ultra-deep local sequencing. In line with previous reports, we find cell type-specific methQTLs to be preferentially located in enhancer elements.

Conclusions

Our analysis demonstrates that a systematic analysis of methQTLs provides important new insights on the influences of genetic variants to cell type-specific epigenomic variation.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13072-021-00415-6.