The relative contribution of DNA methylation and genetic variants on protein biomarkers for human diseases

Animal and plant protein intake during infancy and childhood DNA methylation: a meta-analysis in the NutriPROGRAM consortium

BACKGROUND

Higher early-life animal protein intake is associated with a higher childhood obesity risk compared to plant protein intake. Differential DNA methylation may represent an underlying mechanism.

METHODS

We analysed associations of infant animal and plant protein intakes with DNA methylation in early (2-6 years, N = 579) and late (7̄-12 years, N = 604) childhood in two studies. Study-specific robust linear regression models adjusted for relevant confounders were run, and then meta-analysed using a fixed-effects model. We also performed sex-stratified meta-analyses. Follow-up analyses included pathway analysis and eQTM look-up.

RESULTS

Infant animal protein intake was not associated with DNA methylation in early childhood, but was associated with late-childhood DNA methylation at cg21300373 (P = 4.27 × 10¯8, MARCHF1) and cg10633363 (P = 1.09 × 10¯7, HOXB9) after FDR correction. Infant plant protein intake was associated with early-childhood DNA methylation at cg25973293 (P = 2.26 × 10-7, C1orf159) and cg15407373 (P = 2.13 × 10-7, MBP) after FDR correction. There was no overlap between the findings from the animal and plant protein analyses. We did not find enriched functional pathways at either time point using CpGs associated with animal and plant protein. These CpGs were not previously associated with childhood gene expression. Sex-stratified meta-analyses showed sex-specific DNA methylation associations for both animal and plant protein intake.

CONCLUSION

Infant animal protein intake was associated with DNA methylation at two CpGs in late childhood. Infant plant protein intake was associated with DNA methylation in early childhood at two CpGs. A potential mediating role of DNA methylation at these CpGs between infant protein intake and health outcomes requires further investigation.

New genetic and epigenetic insights into the chemokine system: the latest discoveries aiding progression toward precision medicine

Over the past thirty years, the importance of chemokines and their seven-transmembrane G protein-coupled receptors (GPCRs) has been increasingly recognized. Chemokine interactions with receptors trigger signaling pathway activity to form a network fundamental to diverse immune processes, including host homeostasis and responses to disease. Genetic and nongenetic regulation of both the expression and structure of chemokines and receptors conveys chemokine functional heterogeneity. Imbalances and defects in the system contribute to the pathogenesis of a variety of diseases, including cancer, immune and inflammatory diseases, and metabolic and neurological disorders, which render the system a focus of studies aiming to discover therapies and important biomarkers. The integrated view of chemokine biology underpinning divergence and plasticity has provided insights into immune dysfunction in disease states, including, among others, coronavirus disease 2019 (COVID-19). In this review, by reporting the latest advances in chemokine biology and results from analyses of a plethora of sequencing-based datasets, we outline recent advances in the understanding of the genetic variations and nongenetic heterogeneity of chemokines and receptors and provide an updated view of their contribution to the pathophysiological network, focusing on chemokine-mediated inflammation and cancer. Clarification of the molecular basis of dynamic chemokine-receptor interactions will help advance the understanding of chemokine biology to achieve precision medicine application in the clinic.

Integrating Common Risk Factors with Polygenic Scores Improves the Prediction of Type 2 Diabetes

We tested associations between 13 established genetic variants and type 2 diabetes (T2D) in 1371 study participants from the Volga-Ural region of the Eurasian continent, and evaluated the predictive ability of the model containing polygenic scores for the variants associated with T2D in our dataset, alone and in combination with other risk factors such as age and sex. Using logistic regression analysis, we found associations with T2D for the CCL20 rs6749704 (OR = 1.68, P_FDR = 3.40 × 10^-5), CCR5 rs333 (OR = 1.99, P_FDR = 0.033), ADIPOQ rs17366743 (OR = 3.17, P_FDR = 2.64 × 10^-4), TCF7L2 rs114758349 (OR = 1.77, P_FDR = 9.37 × 10^-5), and CCL2 rs1024611 (OR = 1.38, P_FDR = 0.033) polymorphisms. We showed that the most informative prognostic model included weighted polygenic scores for these five loci, and non-genetic factors such as age and sex (AUC 85.8%, 95%CI 83.7-87.8%). Compared to the model containing only non-genetic parameters, adding the polygenic score for the five T2D-associated loci showed improved net reclassification (NRI = 37.62%, 1.39 × 10^-6). Inclusion of all 13 tested SNPs to the model with age and sex did not improve the predictive ability compared to the model containing five T2D-associated variants (NRI = -17.86, p = 0.093). The five variants associated with T2D in people from the Volga-Ural region are linked to inflammation (CCR5, CCL2, CCL20) and glucose metabolism regulation (TCF7L, ADIPOQ2). Further studies in independent groups of T2D patients should validate the prognostic value of the model and elucidate the molecular mechanisms of the disease development.

Germline genetic variation and predicting immune checkpoint inhibitor induced toxicity

Immune checkpoint inhibitor (ICI) therapy has revolutionised the treatment of various cancer types. ICIs reinstate T-cell function to elicit an anti-cancer immune response. The resulting immune response can however have off-target effects which manifest as autoimmune type serious immune-related adverse events (irAE) in ~10-55% of patients treated. It is currently challenging to predict both who will experience irAEs and to what severity. Identification of patients at high risk of serious irAE would revolutionise patient care. While the pathogenesis driving irAE development is still unclear, host genetic factors are proposed to be key determinants of these events. This review presents current evidence supporting the role of the host genome in determining risk of irAE. We summarise the spectrum and timing of irAEs following treatment with ICIs and describe currently reported germline genetic variation associated with expression of immuno-modulatory factors within the cancer immunity cycle, development of autoimmune disease and irAE occurrence. We propose that germline genetic determinants of host immune function and autoimmune diseases could also explain risk of irAE development. We also endorse genome-wide association studies of patients being treated with ICIs to identify genetic variants that can be used in polygenic risk scores to predict risk of irAE.

Soluble CD14-associated DNA methylation sites predict mortality among men with HIV infection

OBJECTIVES

Elevated plasma levels of sCD14 predict all-cause mortality in people with HIV (PWH). Epigenetic regulation plays a key role in infection and inflammation. To reveal the epigenetic relationships between sCD14, immune function and disease progression among PWH, we conducted an epigenome-wide association study (EWAS) of sCD14 and investigated the relationship with mortality.

DESIGN AND METHODS

DNA methylation (DNAm) levels of peripheral blood samples from PWH in the Veterans Aging Cohort Study (VACS) were measured using the Illumina Infinium Methylation 450K (n = 549) and EPIC (850K) BeadChip (n = 526). Adjusted for covariates and multiple testing, we conducted an epigenome-wide discovery, replication, and meta-analysis to identify significant associations with sCD14. We then examined and replicated the relationship between the principal epigenetic sites and survival using Cox regression models.

FINDINGS

We identified 118 DNAm sites significantly associated with sCD14 in the meta-analysis of 1075 PWH. The principal associated DNAm sites mapped to genes (e.g. STAT1, PARP9, IFITM1, MX1, and IFIT1) related to inflammation and antiviral response. Adjusting for multiple testing, 10 of 118 sCD14-associated DNAm sites significantly predicted survival time conditional on sCD14 levels.

CONCLUSION

The identification of DNAm sites independently predicting survival may improve our understanding of prognosis and potential therapeutic targets among PWH.

Contribution of rare whole-genome sequencing variants to plasma protein levels and the missing heritability

Despite the success of genome-wide association studies, much of the genetic contribution to complex traits remains unexplained. Here, we analyse high coverage whole-genome sequencing data, to evaluate the contribution of rare genetic variants to 414 plasma proteins. The frequency distribution of genetic variants is skewed towards the rare spectrum, and damaging variants are more often rare. We estimate that less than 4.3% of the narrow-sense heritability is expected to be explained by rare variants in our cohort. Using a gene-based approach, we identify Cis-associations for 237 of the proteins, which is slightly more compared to a GWAS (N = 213), and we identify 34 associated loci in Trans. Several associations are driven by rare variants, which have larger effects, on average. We therefore conclude that rare variants could be of importance for precision medicine applications, but have a more limited contribution to the missing heritability of complex diseases.

Despite the success of genome-wide association studies, much of the genetic contribution to complex traits remains unexplained. Here, the authors identify effects by rare variants on plasma proteins, and estimate the contribution of rare variants to the heritability.

A Polynesian-specific copy number variant encompassing the MHC Class I Polypeptide-related Sequence A (MICA) gene associates with gout

Gout is of particularly high prevalence in the Māori and Pacific (Polynesian) populations of Aotearoa New Zealand (NZ). Here, we investigated the contribution of common population-specific copy number variation (CNV) to gout in the Aotearoa NZ Polynesian population. Microarray-generated genome-wide genotype data from Aotearoa NZ Polynesian individuals with (n = 1196) and without (n = 1249) gout were analyzed. Comparator population groups were 552 individuals of European ancestry and 1962 of Han Chinese ancestry. Levels of circulating major histocompatibility complex (MHC) class I polypeptide-related sequence A (MICA) were measured by enzyme-linked immunosorbent assay. Fifty-four CNV regions (CNVRs) appearing in at least 10 individuals were detected, of which seven common (>2%) CNVRs were specific to or amplified in Polynesian people. A burden test of these seven revealed associations of insertion/deletion with gout (odds ratio (OR) 95% confidence interval [CI] = 1.80 [1.01; 3.22], P = 0.046). Individually testing of the seven CNVRs for association with gout revealed nominal association of CNVR1 with gout in Western Polynesian (Chr6: 31.36–31.45 Mb, OR = 1.72 [1.03; 2.92], P = 0.04), CNVR6 in the meta-analyzed Polynesian sample sets (Chr1: 196.75–196.92 Mb, OR = 1.86 [1.16; 3.00], P = 0.01) and CNVR9 in Western Polynesian (Chr1: 189.35–189.54 Mb, OR = 2.75 [1.15; 7.13], P = 0.03). Analysis of European gout genetic association data demonstrated a signal of association at the CNVR1 locus that was an expression quantitative trait locus for MICA. The most common CNVR (CNVR1) includes deletion of the MICA gene, encoding an immunomodulatory protein. Expression of MICA was reduced in the serum of individuals with the deletion. In summary, we provide evidence for the association of CNVR1 containing MICA with gout in Polynesian people, implicating class I MHC-mediated antigen presentation in gout.

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

Introduction

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

Methods

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

Results

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

Discussion

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

Methylation-derived inflammatory measures and lung cancer risk and survival

BACKGROUND

Examining immunity-related DNA methylation alterations in blood could help elucidate the role of the immune response in lung cancer etiology and aid in discovering factors that are key to lung cancer development and progression. In a nested, matched case-control study, we estimated methylation-derived NLR (mdNLR) and quantified DNA methylation levels at loci previously linked with circulating concentrations of C-reactive protein (CRP). We examined associations between these measures and lung cancer risk and survival.

RESULTS

Using conditional logistic regression and further adjusting for BMI, batch effects, and a smoking-based methylation score, we observed a 47% increased risk of non-small cell lung cancer (NSCLC) for one standard deviation (SD) increase in mdNLR (n = 150 pairs; OR: 1.47, 95% CI 1.08, 2.02). Using a similar model, the estimated CRP Scores were inversely associated with risk of NSCLC (e.g., Score 1 OR: 0.57, 95% CI: 0.40, 0.81). Using Cox proportional hazards models adjusting for age, sex, smoking status, methylation-predicted pack-years, BMI, batch effect, and stage, we observed a 28% increased risk of dying from lung cancer (n = 145 deaths in 205 cases; HR: 1.28, 95% CI: 1.09, 1.50) for one SD increase in mdNLR.

CONCLUSIONS

Our study demonstrates that immunity status measured with DNA methylation markers is associated with lung cancer a decade or more prior to cancer diagnosis. A better understanding of immunity-associated methylation-based biomarkers in lung cancer development could provide insight into critical pathways.

Crosstalk Between Inflammatory Signaling and Methylation in Cancer

Inflammation is an intricate immune response against infection and tissue damage. While the initial immune response is important for preventing tumorigenesis, chronic inflammation is implicated in cancer pathogenesis. It has been linked to various stages of tumor development including transformation, proliferation, angiogenesis, and metastasis. Immune cells, through the production of inflammatory mediators such as cytokines, chemokines, transforming growth factors, and adhesion molecules contribute to the survival, growth, and progression of the tumor in its microenvironment. The aberrant expression and secretion of pro-inflammatory and growth factors by the tumor cells result in the recruitment of immune cells, thus creating a mutual crosstalk. The reciprocal signaling between the tumor cells and the immune cells creates and maintains a successful tumor niche. Many inflammatory factors are regulated by epigenetic mechanisms including DNA methylation and histone modifications. In particular, DNA and histone methylation are crucial forms of transcriptional regulation and aberrant methylation has been associated with deregulated gene expression in oncogenesis. Such deregulations have been reported in both solid tumors and hematological malignancies. With technological advancements to study genome-wide epigenetic landscapes, it is now possible to identify molecular mechanisms underlying altered inflammatory profiles in cancer. In this review, we discuss the role of DNA and histone methylation in regulation of inflammatory pathways in human cancers and review the merits and challenges of targeting inflammatory mediators as well as epigenetic regulators in cancer.

Causal effects of inflammatory protein biomarkers on inflammatory diseases

Many circulating proteins are associated with the presence or severity of disease. However, whether these protein biomarkers are causal for disease development is usually unknown. We investigated the causal effect of 21 well-known or exploratory protein biomarkers of inflammation on 18 inflammatory diseases using two-sample Mendelian randomization. We identified six proteins to have causal effects on any of 11 inflammatory diseases (FDR < 0.05, corresponding to P < 1.4 × 10^–3). IL-12B protects against psoriasis and psoriatic arthropathy, LAP-TGF-β-1 protects against osteoarthritis, TWEAK protects against asthma, VEGF-A protects against ulcerative colitis, and LT-α protects against both type 1 diabetes and rheumatoid arthritis. In contrast, IL-18R1 increases the risk of developing allergy, hay fever, and eczema. Most proteins showed protective effects against development of disease rather than increasing disease risk, which indicates that many disease-related biomarkers are expressed to protect from tissue damage. These proteins represent potential intervention points for disease prevention and treatment.

Insilico Functional Analysis of Genome-Wide Dataset From 17,000 Individuals Identifies Candidate Malaria Resistance Genes Enriched in Malaria Pathogenic Pathways

Recent genome-wide association studies (GWASs) of severe malaria have identified several association variants. However, much about the underlying biological functions are yet to be discovered. Here, we systematically predicted plausible candidate genes and pathways from functional analysis of severe malaria resistance GWAS summary statistics (N = 17,000) meta-analysed across 11 populations in malaria endemic regions. We applied positional mapping, expression quantitative trait locus (eQTL), chromatin interaction mapping, and gene-based association analyses to identify candidate severe malaria resistance genes. We further applied rare variant analysis to raw GWAS datasets (N = 11,000) of three malaria endemic populations including Kenya, Malawi, and Gambia and performed various population genetic structures of the identified genes in the three populations and global populations. We performed network and pathway analyses to investigate their shared biological functions. Our functional mapping analysis identified 57 genes located in the known malaria genomic loci, while our gene-based GWAS analysis identified additional 125 genes across the genome. The identified genes were significantly enriched in malaria pathogenic pathways including multiple overlapping pathways in erythrocyte-related functions, blood coagulations, ion channels, adhesion molecules, membrane signalling elements, and neuronal systems. Our population genetic analysis revealed that the minor allele frequencies (MAF) of the single nucleotide polymorphisms (SNPs) residing in the identified genes are generally higher in the three malaria endemic populations compared to global populations. Overall, our results suggest that severe malaria resistance trait is attributed to multiple genes, highlighting the possibility of harnessing new malaria therapeutics that can simultaneously target multiple malaria protective host molecular pathways.

Characterization of the human ABO genotypes and their association to common inflammatory and cardiovascular diseases in the UK Biobank

The ABO gene contains three major alleles that encodes different antigens; A, B, and O, which determine an individual's blood group. Previous studies have primarily focused on identifying associations between ABO blood groups and diseases risk. Here, we sought to test for association between ABO genotypes (OO, OA, AA; OB, BB, and AB) and a large set of common inflammatory and cardiovascular diseases in UK Biobank as well as disease-related protein biomarkers in NSPHS. We first tested for association by conducting a likelihood ratio test, testing whether ABO contributed significantly to the risk for 24 diseases, and 438 plasma proteins. For phenotypes with FDR < 0.05, we tested for pair-wise differences between genetically determined ABO genotypes using logistic or linear regression. Our study confirmed previous findings of a strong association between ABO and cardiovascular disease, identified associations for both type 1 and type 2 diabetes, and provide additional evidence of significant differences between heterozygous and homozygous allele carriers for pulmonary embolism, deep vein thrombosis, but also for von Willebrand factor levels. Furthermore, the results indicated an additive effect between genotypes, even between the two most common A subgroups, A1 and A2. Additionally, we found that ABO contributed significantly to 39 plasma proteins, of which 23 have never been linked to the ABO locus before. These results show the need of incorporating ABO genotype information in the consultation and management of patients at risk, rather than classifying patients into blood groups.

DNA methylation signatures of incident coronary heart disease: findings from epigenome-wide association studies

Coronary heart disease (CHD) is a type of cardiovascular disease (CVD) that affects the coronary arteries, which provide oxygenated blood to the heart. It is a major cause of mortality worldwide. Various prediction methods have been developed to assess the likelihood of developing CHD, including those based on clinical features and genetic variation. Recent epigenome-wide studies have identified DNA methylation signatures associated with the development of CHD, indicating that DNA methylation may play a role in predicting future CHD. This narrative review summarises recent findings from DNA methylation studies of incident CHD (iCHD) events from epigenome-wide association studies (EWASs). The results suggest that DNA methylation signatures may identify new mechanisms involved in CHD progression and could prove a useful adjunct for the prediction of future CHD.

Genome-wide association study of occupational attainment as a proxy for cognitive reserve

Occupational attainment, which represents middle-age cognitive activities, is a known proxy marker of cognitive reserve for Alzheimer's disease. Previous genome-wide association studies (GWAS) have identified numerous genetic variants and revealed the genetic architecture of educational attainment, another marker of cognitive reserve. However, the genetic architecture and heritability for occupational attainment remain elusive. We performed a large-scale GWAS of occupational attainment with 248,847 European individuals from the UK Biobank using the proportional odds logistic mixed model method. In this analysis, we defined occupational attainment using the classified job levels formulated in the UK Standard Occupational Classification system considering the individual professional skill and academic level. We identified 30 significant loci (P < 5 × 10-8); 12 were novel variants, unassociated with other traits. Among them, four lead variants were associated with genes expressed in brain tissues by expression quantitative trait loci mapping from 10 brain regions: rs13002946, rs3741368, rs11654986, and rs1627527. The single nucleotide polymorphism (SNP)-based heritability was estimated to be 8.5% (s.e. = 0.004) and partitioned heritability was enriched in the central nervous system and brain tissues. Genetic correlation analysis showed shared genetic backgrounds between occupational attainment and multiple traits, including education, intelligence, leisure activities, life satisfaction, and neuropsychiatric disorders. In two-sample Mendelian randomization (MR) analysis, we demonstrated that high occupation levels were associated with reduced risk for Alzheimer's disease (OR = 0.78, 95% CI = 0.65-0.92 in inverse variance weighted (IVW) method; OR = 0.73, 95% CI = 0.57-0.92 in the weighted median (WM) method). This causal relationship between occupational attainment and Alzheimer's disease was robust in additional sensitivity analysis that excluded potentially pleiotropic SNPs (OR = 0.72, 95% CI = 0.57-0.91 in the IVW method; OR = 0.72, 95% CI = 0.53-0.97 in the WM method). Multivariable MR confirmed that occupational attainment had an independent effect on the risk for Alzheimer's disease even after taking educational attainment into account (OR = 0.72, 95% CI = 0.54-0.95 in the IVW method; OR = 0.68, 95% CI = 0.48-0.97 in the WM method). Overall, our analyses provide insights into the genetic architecture of occupational attainment and demonstrate that occupational attainment is a potential causal protective factor for Alzheimer's disease as a proxy marker of cognitive reserve.

Ten Years of EWAS

Epigenome-wide association study (EWAS) has been applied to analyze DNA methylation variation in complex diseases for a decade, and epigenome as a research target has gradually become a hot topic of current studies. The DNA methylation microarrays, next-generation, and third-generation sequencing technologies have prepared a high-quality platform for EWAS. Here, the progress of EWAS research is reviewed, its contributions to clinical applications, and mainly describe the achievements of four typical diseases. Finally, the challenges encountered by EWAS and make bold predictions for its future development are presented.

Connecting the epigenome, metabolome and proteome for a deeper understanding of disease

Epigenome-wide association studies (EWAS) identify genes that are dysregulated by the studied clinical endpoints, thereby indicating potential new diagnostic biomarkers, drug targets and therapy options. Combining EWAS with deep molecular phenotyping, such as approaches enabled by metabolomics and proteomics, allows further probing of the underlying disease-associated pathways. For instance, methylation of the TXNIP gene is associated robustly with prevalent type 2 diabetes and further with metabolites that are short-term markers of glycaemic control. These associations reflect TXNIP's function as a glucose uptake regulator by interaction with the major glucose transporter GLUT1 and suggest that TXNIP methylation can be used as a read-out for the organism's exposure to glucose stress. Another case is the association between DNA methylation of the AHRR and F2RL3 genes with smoking and a protein that is involved in the reprogramming of the bronchial epithelium. These examples show that associations between DNA methylation and intermediate molecular traits can open new windows into how the body copes with physiological challenges. This knowledge, if carefully interpreted, may indicate novel therapy options and, together with monitoring of the methylation state of specific methylation sites, may in the future allow the early diagnosis of impending disease. It is essential for medical practitioners to recognize the potential that this field holds in translating basic research findings to clinical practice. In this review, we present recent advances in the field of EWAS with metabolomics and proteomics and discuss both the potential and the challenges of translating epigenetic associations, with deep molecular phenotypes, to biomedical applications.

Associations of age, sex, sexual abuse, and genotype with monoamine oxidase a gene methylation

Epigenome-wide studies report higher methylation among women than men with decreasing levels with age. Little is known about associations of sex and age with methylation of monoamine oxidase A (MAOA). Methylation of the first exonic and partial first intronic region of MAOA has been shown to strengthen associations of interactions of MAOA-uVNTR genotypes and adversity with aggression and substance misuse. Our study examined associations of sex and age with MAOA first exon and intron methylation levels in 252 women and 157 men aged 14–73 years. Participants included adolescents recruited at a substance misuse clinic, their siblings and parents, and healthy women. Women showed ~ 50% higher levels of exonic, and ~ 15% higher intronic, methylation than men. Methylation levels were similar between younger (M = 22.7 years) and older (M = 46.1 years) participants, and stable across age. Age modified few associations of methylation levels with sex. MAOA genotypes modified few associations of methylation with sex and age. Higher methylation levels among women were not explained by genotype, nor interaction of genotype and sexual abuse. Findings were similar after adjusting for lifetime diagnoses of substance dependence (women = 24.3%; men = 34.2%). Methylation levels were higher among women who experienced sexual abuse than women who did not. Results extend on prior studies by showing that women display higher levels of methylation than men within first intronic/exonic regions of MAOA, which did not decrease with age in either sex. Findings were not conditioned by genotype nor interactions of genotype and trauma, and indicate X-chromosome inactivation.

Association of IL1R1 Coding Variant With Plasma-Level Soluble ST2 and Risk of Aortic Dissection

Objective: Aortic dissection (AD) is characterized by an acute onset, rapid progress, and high mortality. Levels of soluble ST2 (sST2) on presentation are elevated in patients with acute AD, which can be used to discriminate AD patients from patients with chest pain. sST2 concentrations were found to be highly heritable in the general population. The aim of this study was to investigate the associations of variations in ST2-related gene expression with sST2 concentrations and AD risk. Methods: This case-control study involving a total of 2,277 participants were conducted, including 435 AD patients and age- and sex-matched 435 controls in the discovery stage, and 464 patients and 943 controls in the validation stage. Eight ST2-related genes were selected by systematic review. Tag single-nucleotide polymorphisms (SNPs) were screened out from the Chinese population of the 1,000 Genomes Database. Twenty-one ST2-related SNPs were genotyped, and plasma sST2 concentrations were measured. Results: In the discovery stage, rs13019803 located in IL1R1 was significantly associated with AD after Bonferroni correction (p = 0.0009) and was correlated with circulating sST2 levels in patients with type A AD(AAD) [log-sST2 per C allele increased by 0.180 (95%) CI: 0.002 - 0.357] but not in type B. Combining the two stages together, rs13019803C was associated with plasma sST2 level in AAD patients [log-sST2 increased by 0.141 (95% CI: 0.055-0.227) for per C allele]. Odds ratio of rs13019803 on the risk of AAD is 1.67 (95% CI: 1.33-2.09). Conclusions: The IL1R1 SNP rs13019803C is associated with higher sST2 levels and increased risk of AAD.

Functional Interplay between Methyltransferases and Inflammasomes in Inflammatory Responses and Diseases

An inflammasome is an intracellular protein complex that is activated in response to a pathogenic infection and cellular damage. It triggers inflammatory responses by promoting inflammatory cell death (called pyroptosis) and the secretion of pro-inflammatory cytokines, interleukin (IL)-1β and IL-18. Many types of inflammasomes have been identified and demonstrated to play a central role in inducing inflammatory responses, leading to the onset and progression of numerous inflammatory diseases. Methylation is a biological process by which methyl groups are transferred from methyl donors to proteins, nucleic acids, and other cellular molecules. Methylation plays critical roles in various biological functions by modulating gene expression, protein activity, protein localization, and molecular stability, and aberrant regulation of methylation causes deleterious outcomes in various human diseases. Methylation is a key determinant of inflammatory responses and diseases. This review highlights the current understanding of the functional relationship between inflammasome regulation and methylation of cellular molecules in inflammatory responses and diseases.

Elevated methylation of the vault RNA2-1 promoter in maternal blood is associated with preterm birth

Background

Preterm birth, defined as parturition before 37 completed weeks of gestation, is associated with an increased risk of neonatal complications and death, as well as poor health and disease later in life. Epigenetics could contribute to the mechanism underlying preterm birth.

Results

Genome-wide DNA methylation analysis of whole blood cells from 10 women (5 term and 5 preterm deliveries) was performed using an Illumina Infinium HumanMethylation450 BeadChips array. We identified 1,581 differentially methylated CpG sites in promoter regions between term and preterm birth. Although the differences were not significant after correcting for multiple tests, seven CpGs on the genomically imprinted vault RNA2-1 (VTRNA2-1; also known as non-coding RNA, nc886 or miR-886) showed the largest differences (range: 26–39 %). Pyrosequencing verification was performed with blood samples from pregnant women recruited additionally (39 term and 43 preterm deliveries). In total, 28 (34.1 %) samples showed hypomethylation of the VTRNA2-1 promoter (< 13 % methylation), while 54 (65.9 %) samples showed elevated methylation levels between 30 and 60 %. Elevated methylation of VTRNA2-1 promoter was associated with an increased risk of preterm birth after adjusting for maternal age, season of delivery, parity and white blood cell count. The mRNA expression of VTRNA2-1 was 0.51-fold lower in women with preterm deliveries (n = 20) compared with women with term deliveries (n = 20).

Conclusions

VTRNA2-1 is a noncoding transcript to environmentally responsive epialleles. Our results suggest that elevated methylation of the VTRNA2-1 promoter may result in increased risk of PTB caused by the pro-inflammatory cytokines. Further studies are needed to confirm the association of VTRNA2-1 methylation with preterm birth in a large population, and to elucidate the underlying mechanism.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07865-y.

Epigenome-wide scan identifies differentially methylated regions for lung cancer using pre-diagnostic peripheral blood

BACKGROUND

DNA methylation markers have been associated with lung cancer risk and may identify aetiologically relevant genomic regions, or alternatively, be markers of disease risk factors or biological processes associated with disease development.

METHODS

In a nested case-control study, we measured blood leukocyte DNA methylation levels in pre-diagnostic samples collected from 430 participants (208 cases; 222 controls) in the 1989 CLUE II cohort. We compared DNA methylation levels with case/control status to identify novel genomic regions, both single CpG sites and differentially methylated regions (DMRs), while controlling for known DNA methylation changes associated with smoking using a previously described pack-years-based smoking methylation score. Stratification analyses were conducted over time from blood draw to diagnosis, histology, and smoking status.

RESULTS

We identified 16 single CpG sites and 40 DMRs significantly associated with lung cancer risk (q < 0.05). The identified genomic regions were associated with genes including H19, HOXA3/HOXA4, RUNX3, BRICD5, PLXNB2, and RP13. For the single CpG sites, the strongest association was noted for cg09736286 in the DIABLO gene (OR [for 1 SD] = 2.99, 95% CI: 1.95-4.59, P-value = 4.81 × 10-7). We found that CpG sites in the HOXA3/HOXA4 region were hypermethylated in cases compared to controls.

CONCLUSION

The single CpG sites and DMRs that we identified represented significant measurable differences in lung cancer risk, providing potential biomarkers for lung cancer risk stratification. Future studies will need to examine whether these regions are causally related to lung cancer.

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.

Exploring epigenetic biomarkers of universal specificities and commonalities among pan-cancer cohorts in The Cancer Genome Atlas

Aim: To explore the mechanism of cancer by employing a comprehensive analysis of DNA methylation patterns and variations among pan-cancer cohorts. Materials & methods: This research focused on the discovery of universally specific or common biomarkers by mathematical statistics and machine learning methods in The Cancer Genome Atlas. Results: We found 138 differently methylated CpGs (DMCs) with a common methylation trend and eight common differently methylated regions in different cancer cohorts. Additionally, we found 99 DMCs to distinguish 32 different cancer cohorts in random forest analysis because of the specificity mechanism, but each DMC still had high instability. Conclusion: Our results could facilitate the development of biomarkers that are universally specific and common features across pan-cancer cohorts.

Cigarette smoke-induced alterations in blood: A review of research on DNA methylation and gene expression

Worldwide, smoking remains a threat to public health, causing preventable diseases and premature mortality. Cigarette smoke is a powerful inducer of DNA methylation and gene expression alterations, which have been associated with negative health consequences. Here, we review the current knowledge on smoking-related changes in DNA methylation and gene expression in human blood samples. We identified 30 studies focused on the association between active smoking, DNA methylation modifications, and gene expression alterations. Overall, we identified 1,758 genes with differentially methylated sites (DMS) and differentially expressed genes (DEG) between smokers and nonsmokers, of which 261 were detected in multiple studies (≥4). The most frequently (≥10 studies) reported genes were AHRR, GPR15, GFI1, and RARA. Functional enrichment analysis of the 261 genes identified the aryl hydrocarbon receptor repressor and T cell pathways (T helpers 1 and 2) as influenced by smoking status. These results highlight specific genes for future mechanistic and translational research that may be associated with cigarette smoke exposure and smoking-related diseases. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Proteome-wide Systems Genetics to Identify Functional Regulators of Complex Traits

Proteomic technologies now enable the rapid quantification of thousands of proteins across genetically diverse samples. Integration of these data with systems-genetics analyses is a powerful approach to identify new regulators of economically important or disease-relevant phenotypes in various populations. In this review, we summarize the latest proteomic technologies and discuss technical challenges for their use in population studies. We demonstrate how the analysis of correlation structure and loci mapping can be used to identify genetic factors regulating functional protein networks and complex traits. Finally, we provide an extensive summary of the use of proteome-wide systems genetics throughout fungi, plant, and animal kingdoms and discuss the power of this approach to identify candidate regulators and drug targets in large human consortium studies.

Biocompatibilidade do gel de quitosana associado ao glicerol fosfato na reparação de defeitos ósseos induzidos experimentalmente no rádio de coelhos (Oryctolagus cuniculus)

RESUMO A engenharia de tecidos caracteriza-se como ciência interdisciplinar, a qual vem desenvolvendo biomateriais para a regeneração do tecido ósseo no âmbito das medicinas humana e veterinária. O objetivo desta pesquisa foi avaliar a regeneração óssea obtida da aplicação do hidrogel de quitosana associado ao glicerol fosfato em falha óssea experimentalmente induzida no rádio de coelhos. Foram utilizados 15 coelhos adultos, distribuídos aleatoriamente em dois grupos, representados por cada um dos rádios de cada animal, sendo um grupo tratado com hidrogel de quitosana associado ao glicerol fosfato (grupo biomaterial - GB) e um grupo que não recebeu tratamento com o biomaterial (grupo controle - GC). Os animais foram avaliados radiograficamente, por densitometria óptica e análise histológica, nos períodos 30, 60 e 90 dias pós-operatórios. Houve superioridade estatística na média geral das avaliações radiográficas do GB (2,33±0,48) sobre o GC (1,77±0,06). As médias gerais de avaliação densitométrica do GB foram superiores às do GC, sendo 6,207±1,374 e 5,71±1,512, respectivamente. A avaliação histopatológica do GB foi superior à do GC nos períodos de 30, 60 e 90 dias. Assim, é possível afirmar que o hidrogel de quitosana constitui biomaterial de características desejáveis, promovendo consolidação óssea mais rápida e eficiente, sem causar reações adversas.

Genetics meets proteomics: perspectives for large population-based studies

Proteomic analysis of cells, tissues and body fluids has generated valuable insights into the complex processes influencing human biology. Proteins represent intermediate phenotypes for disease and provide insight into how genetic and non-genetic risk factors are mechanistically linked to clinical outcomes. Associations between protein levels and DNA sequence variants that colocalize with risk alleles for common diseases can expose disease-associated pathways, revealing novel drug targets and translational biomarkers. However, genome-wide, population-scale analyses of proteomic data are only now emerging. Here, we review current findings from studies of the plasma proteome and discuss their potential for advancing biomedical translation through the interpretation of genome-wide association analyses. We highlight the challenges faced by currently available technologies and provide perspectives relevant to their future application in large-scale biobank studies.

Multi-method genome- and epigenome-wide studies of inflammatory protein levels in healthy older adults

BACKGROUND

The molecular factors which control circulating levels of inflammatory proteins are not well understood. Furthermore, association studies between molecular probes and human traits are often performed by linear model-based methods which may fail to account for complex structure and interrelationships within molecular datasets.

METHODS

In this study, we perform genome- and epigenome-wide association studies (GWAS/EWAS) on the levels of 70 plasma-derived inflammatory protein biomarkers in healthy older adults (Lothian Birth Cohort 1936; n = 876; Olink® inflammation panel). We employ a Bayesian framework (BayesR+) which can account for issues pertaining to data structure and unknown confounding variables (with sensitivity analyses using ordinary least squares- (OLS) and mixed model-based approaches).

RESULTS

We identified 13 SNPs associated with 13 proteins (n = 1 SNP each) concordant across OLS and Bayesian methods. We identified 3 CpG sites spread across 3 proteins (n = 1 CpG each) that were concordant across OLS, mixed-model and Bayesian analyses. Tagged genetic variants accounted for up to 45% of variance in protein levels (for MCP2, 36% of variance alone attributable to 1 polymorphism). Methylation data accounted for up to 46% of variation in protein levels (for CXCL10). Up to 66% of variation in protein levels (for VEGFA) was explained using genetic and epigenetic data combined. We demonstrated putative causal relationships between CD6 and IL18R1 with inflammatory bowel disease and between IL12B and Crohn's disease.

CONCLUSIONS

Our data may aid understanding of the molecular regulation of the circulating inflammatory proteome as well as causal relationships between inflammatory mediators and disease.

CSF1R methylation is a key regulatory mechanism of tumor-associated macrophages in hepatocellular carcinoma

Tumor-associated macrophages (TAMs) are important in tumor microenvironments and are closely associated with cancer occurrence, metastasis and progression. Colony stimulating factor 1 receptor (CSF1R) serves a crucial role in TAM formation. Whether CSF1R expression is regulated by DNA methylation in hepatocellular carcinoma (HCC) has not been fully elucidated. In the current study, HCC and adjacent non-cancerous tissue (ANT) samples were collected from 160 patients with HCC. CSF1R methylation levels were analyzed using a Mass ARRAY Analyzer to establish the potential impact of CSF1R methylation alternations on HCC clinicopathological characteristics. The mean methylation level of the CSF1R promoter (chr 5:149492491-149492958) was demonstrated to be significantly higher in ANTs compared with HCC tissues (65.3±7.5% vs. 57.3±14.4%, respectively; P<0.0001). CSF1R also exhibited decreased expression in HCC tissues compared with ANTs (P=0.0026). However, CSF1R expression was negatively correlated with CSF1R methylation levels in ANTs (r>0.4; P<0.0001). Further analysis indicated that patients with diabetes exhibited lower methylation levels in ANTs compared with HCC tissues (P=0.0062). Furthermore, CSF1R hypomethylation in ANTs was associated with a larger number of tumors (P=0.0332), larger tumor size (P=0.0494) and higher tumor grade (P=0.0244). Therefore, methylation alternation of the CSF1R promoter region analyzed in the present study was a key regulatory mechanism on CSF1R expression and ANT hypomethylation indicated poor clinicopathological characteristics of HCC. CSF1R may be a potential immunological therapeutic target for HCC.

DNA Methylation-Derived Immune Cell Profiles, CpG Markers of Inflammation, and Pancreatic Cancer Risk

BACKGROUND

Pancreatic cancer is projected to become the second most common cause of cancer-related death over the next 5 years. Because inflammation is thought to be a common trajectory for disease initiation, we sought to prospectively characterize immune profiles using DNA methylation markers and examine DNA methylation levels previously linked to inflammation biomarkers to evaluate whether these immune markers play a key role in pancreatic cancer.

METHODS

In a nested case-control study pooling three U.S. prospective cohort studies, DNA methylation was measured in prediagnostic leukocytes of incident pancreatic cancer cases and matched controls using the Illumina MethylationEPIC array. Differentially methylated regions were used to predict immune cell types, and CpGs previously associated with inflammatory biomarkers were selected for the analysis. DNA methylation data from a retrospective case-control study conducted in Spain (PanGenEU) was used for independent replication.

RESULTS

Immune cell proportions and ratio of cell proportions were not associated with pancreatic cancer risk in the nested case-control study. Methylation extent of CpGs residing in or near gene MNDA was significantly associated with pancreatic cancer risk in the nested case-control study and replicated in PanGenEU. Methylation level of a promoter CpG of gene PIM-1 was associated with survival in both studies.

CONCLUSIONS

Using a targeted approach, we identified several CpGs that may play a role in pancreatic carcinogenesis in two large, independent studies with distinct study designs.

IMPACT

These findings could provide insight into critical pathways that may help identify new markers of early disease and survival.

Epigenetics meets proteomics in an epigenome-wide association study with circulating blood plasma protein traits

DNA methylation and blood circulating proteins have been associated with many complex disorders, but the underlying disease-causing mechanisms often remain unclear. Here, we report an epigenome-wide association study of 1123 proteins from 944 participants of the KORA population study and replication in a multi-ethnic cohort of 344 individuals. We identify 98 CpG-protein associations (pQTMs) at a stringent Bonferroni level of significance. Overlapping associations with transcriptomics, metabolomics, and clinical endpoints suggest implication of processes related to chronic low-grade inflammation, including a network involving methylation of NLRC5, a regulator of the inflammasome, and associated pQTMs implicating key proteins of the immune system, such as CD48, CD163, CXCL10, CXCL11, LAG3, FCGR3B, and B2M. Our study links DNA methylation to disease endpoints via intermediate proteomics phenotypes and identifies correlative networks that may eventually be targeted in a personalized approach of chronic low-grade inflammation.

Molecular mechanisms of epigenetic inheritance: Possible evolutionary implications

Recently interest in multi-generational epigenetic phenomena have been fuelled by highly reproducible intergenerational and transgenerational inheritance paradigms in several model organisms. Such paradigms are essential in order to begin to use genetics to unpick the mechanistic bases of how epigenetic information may be transmitted between generations; indeed great strides have been made towards understanding these mechanisms. Far less well understood is the relationship between epigenetic inheritance, ecology and evolution. In this review I focus on potential connections between laboratory studies of transgenerational epigenetic inheritance phenomena and evolutionary processes that occur in natural populations. In the first section, I consider whether transgenerational epigenetic inheritance might provide an advantage to organisms over the short term in adapting to their environment. Second, I consider whether epigenetic changes can contribute to the evolution of species by contributing to stable phenotypic variation within a population. Finally I discuss whether epigenetic changes could influence evolution by either directly or indirectly promoting DNA sequence changes that could impact phenotypic divergence. Additionally, I will discuss how epigenetic changes could influence the evolution of human cancer and thus be directly relevant for the development of this disease.

Improved power and precision with whole genome sequencing data in genome-wide association studies of inflammatory biomarkers

Genome-wide association studies (GWAS) have identified associations between thousands of common genetic variants and human traits. However, common variants usually explain a limited fraction of the heritability of a trait. A powerful resource for identifying trait-associated variants is whole genome sequencing (WGS) data in cohorts comprised of families or individuals from a limited geographical area. To evaluate the power of WGS compared to imputations, we performed GWAS on WGS data for 72 inflammatory biomarkers, in a kinship-structured cohort. When using WGS data, we identified 18 novel associations that were not detected when analyzing the same biomarkers with genotyped or imputed SNPs. Five of the novel top variants were low frequency variants with a minor allele frequency (MAF) of <5%. Our results suggest that, even when applying a GWAS approach, we gain power and precision using WGS data, presumably due to more accurate determination of genotypes. The lack of a comparable dataset for replication of our results is a limitation in our study. However, this further highlights that there is a need for more genetic epidemiological studies based on WGS data.

A phenotypic and genomics approach in a multi-ethnic cohort to subtype systemic lupus erythematosus

Systemic lupus erythematous (SLE) is a heterogeneous autoimmune disease in which outcomes vary among different racial groups. Here, we aim to identify SLE subgroups within a multiethnic cohort using an unsupervised clustering approach based on the American College of Rheumatology (ACR) classification criteria. We identify three patient clusters that vary according to disease severity. Methylation association analysis identifies a set of 256 differentially methylated CpGs across clusters, including 101 CpGs in genes in the Type I Interferon pathway, and we validate these associations in an external cohort. A cis-methylation quantitative trait loci analysis identifies 744 significant CpG-SNP pairs. The methylation signature is enriched for ethnic-associated CpGs suggesting that genetic and non-genetic factors may drive outcomes and ethnic-associated methylation differences. Our computational approach highlights molecular differences associated with clusters rather than single outcome measures. This work demonstrates the utility of applying integrative methods to address clinical heterogeneity in multifactorial multi-ethnic disease settings.

Genome and epigenome wide studies of neurological protein biomarkers in the Lothian Birth Cohort 1936

Although plasma proteins may serve as markers of neurological disease risk, the molecular mechanisms responsible for inter-individual variation in plasma protein levels are poorly understood. Therefore, we conduct genome- and epigenome-wide association studies on the levels of 92 neurological proteins to identify genetic and epigenetic loci associated with their plasma concentrations (n = 750 healthy older adults). We identify 41 independent genome-wide significant (P < 5.4 × 10^-10) loci for 33 proteins and 26 epigenome-wide significant (P < 3.9 × 10^-10) sites associated with the levels of 9 proteins. Using this information, we identify biological pathways in which putative neurological biomarkers are implicated (neurological, immunological and extracellular matrix metabolic pathways). We also observe causal relationships (by Mendelian randomisation analysis) between changes in gene expression (DRAXIN, MDGA1 and KYNU), or DNA methylation profiles (MATN3, MDGA1 and NEP), and altered plasma protein levels. Together, this may help inform causal relationships between biomarkers and neurological diseases.

Epigenetics and Inflammatory Markers: A Systematic Review of the Current Evidence

Epigenetic mechanisms have been suggested to play a role in the genetic regulation of pathways related to inflammation. Therefore, we aimed to systematically review studies investigating the association between DNA methylation and histone modifications with circulatory inflammation markers in blood. Five bibliographic databases were screened until 21 November of 2017. We included studies conducted on humans that examined the association between epigenetic marks (DNA methylation and/or histone modifications) and a comprehensive list of inflammatory markers. Of the 3,759 identified references, 24 articles were included, involving, 17,399 individuals. There was suggestive evidence for global hypomethylation but better-quality studies in the future have to confirm this. Epigenome-wide association studies (EWAS) (n=7) reported most of the identified differentially methylated genes to be hypomethylated in inflammatory processes. Candidate genes studies reported 18 differentially methylated genes related to several circulatory inflammation markers. There was no overlap in the methylated sites investigated in candidate gene studies and EWAS, except for TMEM49, which was found to be hypomethylated with higher inflammatory markers in both types of studies. The relation between histone modifications and inflammatory markers was assessed by one study only. This review supports an association between epigenetic marks and inflammation, suggesting hypomethylation of the genome. Important gaps in the quality of studies were reported such as inadequate sample size, lack of adjustment for relevant confounders, and failure to replicate the findings. While most of the studies have been focused on C-reactive protein, further efforts should investigate other inflammatory markers.

Circulating levels of inflammatory markers and DNA methylation, an analysis of repeated samples from a population based cohort

DNA methylation in blood may adapt to conditions affecting our health, such as inflammation, and multiple studies have identified differential DNA methylation related to smoking, obesity and various diseases. The purpose of this study was to evaluate previously reported, and explore possible new, associations between levels of inflammatory markers and DNA methylation in blood. We used a well-characterized study population consisting of 127 individuals, all of whom were participants in the population-based Västerbotten Intervention Programme cohort and had provided two blood samples, ten years apart. Levels of CRP and 160 other proteins were measured in plasma, and DNA methylation levels (assessed using the 850K Illumina Infinium MethylationEPIC BeadChip) were measured in white blood cell DNA. Associations between CpG methylation and protein levels were estimated using linear mixed models. In the study we were able to confirm the direction for 85 of 102 previously reported protein-methylation associations. Depicting associations in a network allowed us to identify CpG sites with associations to multiple proteins, and ten CpG sites were each associated with three or more inflammatory markers. Furthermore, two genetic regions included nine additional unreported CpG sites that may represent trans-acting methylation sites. Our study supports a complex interaction between DNA methylation and circulating proteins involved in the inflammatory response. The notion of trans-acting methylation sites affecting, or being affected by, the expression of genes on completely different chromosomes should be taken into account when interpreting results from epigenome-wide association studies.

Improved filtering of DNA methylation microarray data by detection p values and its impact on downstream analyses

Background

DNA methylation microarrays are popular for epigenome-wide association studies (EWAS), but spurious values complicate downstream analysis and threaten replication. Conventional cut-offs for detection p values for filtering out undetected probes were demonstrated in a single previous study as insufficient leading to many apparent methylation calls in samples from females in probes targeting the Y-chromosome. We present an alternative approach to calculate more accurate detection p values utilizing non-specific background fluorescence. We evaluate and compare our proposed approach of filtering observations with conventional ones by assessing the detection of Y-chromosome probes among males and females in 2755 samples from 17 studies on the 450K microarray and masking of large outliers between technical replicates and their impact downstream via an EWAS reanalysis.

Results

In contrast to conventional approaches, ours marks most Y-chromosome probes in females as undetected while removing a median of only 0.14% of the data per sample, catches more (30% vs. 6%) of large outliers (more than 20 percentage point difference between technical replicates), and helps to identify strong associations previously obfuscated by outliers between whole blood DNA methylation and chronological age in a well-powered EWAS (n = 729).

Conclusions

We provide guidance for filtering both 450K and EPIC microarrays as an essential preprocessing step to reduce spurious values. An implementation (including a function compatible with objects from the popular minfi package) was added to ewastools, an R package for comprehensive quality control of DNA methylation microarrays. Scripts to reproduce all analyses are available at doi.org/10.5281/zenodo.1443561.

Occupational Exposure to Pesticides in Tobacco Fields: The Integrated Evaluation of Nutritional Intake and Susceptibility on Genomic and Epigenetic Instability

Pesticides used at tobacco fields are associated with genomic instability, which is proposed to be sensitive to nutritional intake and may also induce epigenetic changes. We evaluated the effect of dietary intake and genetic susceptibility polymorphisms in MTHFR (rs1801133) and TERT (rs2736100) genes on genomic and epigenetic instability in tobacco farmers. Farmers, when compared to a nonexposed group, showed increased levels of different parameters of DNA damage (micronuclei, nucleoplasmic bridges, and nuclear buds), evaluated by cytokinesis-block micronucleus cytome assay. Telomere length (TL) measured by quantitative PCR was shorter in exposed individuals. Global DNA methylation was significantly decreased in tobacco farmers. The exposed group had lower dietary intake of fiber, but an increase in cholesterol; vitamins such as B6, B12, and C; β-carotene; and α-retinol. Several trace and ultratrace elements were found higher in farmers than in nonfarmers. The MTHFR CT/TT genotype influenced nucleoplasmic bridges, nuclear buds, and TL in the exposed group, whereas TERT GT/TT only affected micronucleus frequency. We observed a positive correlation of TL and lipids and an inverse correlation of TL and fibers. The present data suggest an important role of dietary intake and subjects' genetic susceptibility to xenobiotics-induced damages and epigenetic alterations in tobacco farmers occupationally exposed to mixtures of pesticides.